Rotman Management Fall 2023: Work in Progress

MANAGEMENT

The City of Toronto has been working with the local Indigenous community to create the Indigenous Centre for Innovation and Entrepreneurship (ICIE)—a 22,500 square foot space committed to empowering Indigenous entrepreneurs and innovators in pursuing their goals by providing business programming, advisory services, mentorship supports, shared co-workspace, community event space and connections to business networks. Set to open in late 2024, the ICIE will be managed and governed by an Indigenous-led organization or consortium of organizations. For more on the burgeoning Indigenous economy, turn to page 12 for our interview with Carol Anne Hilton.

Features

6 10 Shifts Making Waves Across Industries

by Patrick Simon, Dana Maor and Patrick Guggenberger

Leaders must embrace and address 10 organizational shifts that have significant implications for structures, processes and people.

18

Is AI an Existential Threat?

by S. Paikin, G. Hadfield, P. Domingo and J. Harris Many people were caught off guard by the request for a moratorium on AI development. Three thought leaders debate whether or not AI is an existential threat to humanity.

24

ChatGPT: What Leaders Need to Know

by Curt Nickisch and Ethan Mollick

Wharton Professor Ethan Mollick says ChatGPT is as big a deal for leaders as COVID-19 was — and that it is likely to make everyone more productive.

30

15 Reasons You Should Read this Article! The Pros and Cons of Over-Arguing

by Rhia Catapano

In the realm of persuasion, people generally believe that more is better. But that isn’t always true: Over-arguing can trigger a negative response.

36

The Microstress Effect: How Small Stressors Pile Up— and What to Do About It

by Rob Cross and Karen Dillon

We are in the midst of a widespread crisis of well-being. But there is a powerful antidote: identify and eliminate some of the ‘microstresses’ in your life.

42

Corporate Fraud: Just How Prevalent Is It?

by Alexander Dyck

Fraudulent behaviour in organizations is much more common than you might think. Indeed, the stories in the media are just the tip of the iceberg.

48

What Are Your Management Operating Principles?

by Claire Hughes Johnson

Identifying and understanding the personal ‘guardrails’ that influence your work and management style can make you a better leader.

54

Creating Value From Data: A Monetization Framework

by Barbara H. Wixom, Cynthia M. Beath and Leslie Owens

Three approaches to data monetization can help every organization ensure that its investments in data pay off.

60

AI Adoption in American Business: Who Is Doing What,

and Where?

by Kristina McElheran

A lack of comprehensive data on AI use by businesses has left its adoption and implications poorly understood. New findings fill in some of the blanks.

66

The Tech Trends Every Leader Needs to Understand

by Amy Webb

By understanding the changes shaping the technology landscape, executives can make informed decisions and capitalize on new opportunities.

74

Digital Crown Jewels: How to Protect Your Data Assets

by

Michael Parent, Greg Murray and Glen Whyte

Protecting your organization’s precious digital assets is no longer a choice. The price you could pay by failing to act is far too great.

80

Six Mindsets to Help You Change the World

by John Mullins

If there is one thing all of the best entrepreneurs do well, it’s breaking the conventional rules of business. Equipped with the right mindsets, so can you.

In Every

by Karen Christensen

Rotman Management Fall 2023

Published in January, May and September by the Rotman School of Management at the University of Toronto, Rotman Management explores themes of interest to leaders, innovators and entrepreneurs, featuring thought-provoking insights and problem-solving tools from leading global researchers and management practitioners. The magazine reflects Rotman’s role as a catalyst for transformative thinking that creates value for business and society.

ISSN 2293-7684 (Print)

ISSN 2293-7722 (Digital)

Editor-in-Chief Karen Christensen

Contributors

Rhia Catapano, Alexander Dyck, Gillian Hadfield, Tanjim Hossain, Eric Kirzner, Hai Lu, Kristina McElheran, Jee-Eun Shin, Dilip Soman, Glen Whyte

Marketing & Communications Officer

Mona Barr

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“If you can embrace the fact that you are probably wrong half the time, it will open you up to ideas that can transform your organization.”

–Ed Catmull, p. 124

Carol Anne Hilton

FROM THE EDITOR Karen Christensen

Work in Progress

WHETHER YOU ARE A CEO guiding a global corporation, a team leader in a small start-up or an influential figure in your community, the path of leadership is marked by constant evolution and self-improvement. Great leaders understand that their growth is intertwined with that of their teams and the world around them. They strive to stay ahead of the curve, adapting their strategies and approaches to meet the ever-changing demands and challenges of their stakeholders.

Put simply, leadership is not a destination, it is an ongoing journey. In this issue of Rotman Management we explore the multifaceted dimensions of great leadership as a work in progress.

We kick the issue off on page 6 with 10 Shifts That Are Making Waves Across Industries, where McKinsey & Co.’s Patrick Simon and his co-authors describe 10 transformational changes that have significant implications for leaders everywhere.

Is AI an Existential Threat? There are definitely conflicting opinions. Three experts, including the University of Toronto’s Schwartz Reisman Chair in Technology and Society and Rotman Professor of Strategy Gillian Hadfield, debate the issue on page 18.

Elsewhere in this issue, in our Thought Leader Interview on page 12 we speak with Carol Anne Hilton, founder of the Indigenomics Institute, about the progress being made in Canada’s Indigenous economy; MIT’s Barbara Wixom and colleagues present a framework for monetizing organizational data on page 54; and Rotman Professor Glen Whyte and his co-authors describe how to protect your digital assets on page 74.

In our Idea Exchange, Alex Osterwalder (#4 on the Thinkers50) describes how to become an invincible organization on page 86; Harvard’s Alison Wood Brooks breaks down the science of great conversations on page 96; Oxford’s Paulo Savaget describes four ‘workarounds’ for innovative outcomes on page 107; Pixar co-founder Ed Catmull shares insights for building a creative culture on page 124; and Rotman faculty Eric Kirzner, Hai Lu, Jee-Eun Shin, Dilip Soman and Tanjim Hossain share their latest ideas.

With so much work to be done in the world, this is a daunting time to be a leader. By embracing the mindsets and principles presented in this issue, we feel certain you will be able to navigate challenges more effectively and have a positive impact. But make no mistake: having an impact over time demands constant evolution. Just remember: we are all works in progress.

EDITOR’S NOTE: This letter was co-written by ChatGPT. For more about this groundbreaking technology, head to page 24.

Karen Christensen, Editor-in-Chief editor@rotman.utoronto.ca Twitter: @RotmanMgmtMag

10 SHIFTS MAKING WAVES ACROSS INDUSTRIES

by Patrick Simon, Dana Maor and Patrick Guggenberger

LEADERSHIP TEAMS AROUND THE WORLD have been operating in a highly volatile and uncertain environment — first having to cope with the COVID-19 pandemic and then with the ensuing economic slowdown, soaring inflation and geopolitical disruption. In such an unsettled period, it is no surprise that efforts to strengthen short-term resilience have dominated the agenda at many companies.

Less obviously — but no less importantly — business leaders are having to address a range of organizational shifts that have significant implications for organizational structures, processes and people. Depending on how organizations address them, these shifts are both challenging and harbingers of opportunity.

With this in mind, we have launched McKinsey’s “The State of Organizations Report,” an ongoing research initiative that both pinpoints the most important people, procedural and structural shifts that organizations are grappling with and seeks to provide some guidance about how to approach them.

In our inaugural report, we go into depth on 10 of the most important shifts. In this article, we will summarize them. For those interested, the complete report is available online.

SHIFT 1: Increasing Speed While Strengthening Resilience Business shocks requiring quick responses have become the new norm for organizations. Companies need to focus on being prepared and ready to act at all times — and quickly. Yet our research suggests that while some organizations do emphasize preparation, many focus only on one singular aspect of it (anticipating and then addressing an acute challenge, for instance). They forgo the holistic approach of routinely reviewing and transforming structures, processes and people so that they don’t just bounce out of crises but bounce forward — landing on their feet relatively unscathed and charging ahead with new energy.

Most people understand the importance of organizational resilience: More than 60 per cent of respondents in our survey reported that it will only become more important in the future. Yet many said they don’t feel that they are well prepared for the external shocks that may emerge over the next few years — or the further disruption those shocks might bring.

In our experience, companies with capabilities in both adaptability and resilience are better able than others to absorb

Leaders must embrace and address 10 waves of change that have significant implications for organizational structures, processes and people.

shocks and turn them into opportunities for capturing sustainable growth. Leaders and teams in adaptable organizations are better prepared than others to assess the situation at hand, reorient themselves, double down on what is working and walk away from what is not — and do it all quickly. With each bounce forward, they become increasingly resilient. Achieving this requires organizing for speed of response, giving power to your people and developing a culture of continuous learning.

SHIFT 2: Balancing In-Person and Remote Work

Before the onset of COVID-19, most organizations expected employees to spend more than 80 per cent of their time in an office. Now only about 10 per cent do, while the remaining 90 per cent have embraced a range of hybrid work models that allow employees to work virtually from off-site locations (including home) for some or much of the time. Employees generally like this development: More than four of five who have worked in a hybrid model over the past two years want to retain it, largely because of the flexibility and balance it affords them.

Only 14 per cent of respondents to our survey believe that remote work will become less common in the future; more than half believe it will become even more common. Leaders, managers and employees are still grappling with the effects of this broad behavioural upheaval.

To succeed, each organization must determine how best to combine remote and in-person work in ways that suit the specific needs of its workforce. This is the world of ‘true hybrid.’ True-hybrid organizations create policies, workflows and documentation that help employees understand which activities are best done in person and whether those activities are best carried out in real time or asynchronously (that is, with all team members being online when it is most convenient for them rather than simultaneously.)

True-hybrid organizations also consistently address the shortcomings that occur with conducting activities in the less optimal format. By looking beyond the static definition of hybrid work models and remaining open to the entire universe of options for how, when and where employees work, true-hybrid organizations can distinguish themselves as destination workplaces.

SHIFT 3: Making Way for Applied AI

The application of AI for building better organizations holds promise, particularly when companies manage AI with practical, ethical and risk-related concerns in mind. Our research shows a strong impact of AI on efficiency. Companies that have seen the biggest bottom-line returns from applied AI — those that attribute at least 20 per cent of EBIT to their use of AI — are more likely to have set themselves up for success by aligning AI and business strategies.

AI can amplify talent, helping leaders improve the speed and efficiency of everything from candidate hiring to making their resource deployment more effective, increasing the personalization of capability development and improving employee experience and engagement. In line with that, our research shows that organizations with strong use of people analytics see an 80 per cent increase in recruiting efficiency, a 25 per cent rise in business productivity and a 50 per cent decrease in attrition rates.

Applied AI — machine learning, in particular — can help organizations perform with speed and precision, thereby improving resilience. With it, individual and team decision-making can be pushed to the edges of the organization, removing obstacles to action and enabling faster responses to market needs while accounting for factors such as human bias. All tolled, this translates into quantifiable impact.

SHIFT 4: Embracing New Rules of Attraction, Retention and Attrition

Is there anybody out there? It’s a question senior leaders around the world are asking as they try to fill open positions while keeping existing employees on board and engaged. In the wake of the pandemic and the accompanying ‘Great Attrition,’ human capital is scarcer than it’s ever been.

McKinsey research conducted between 2021 and 2022 revealed something shocking: 33 per cent of employees across nine countries in Europe, 40 per cent of employees in the U.S., 45 per cent of employees in the Middle East and 60 per cent of employees in India were planning to leave their jobs. But we found that most surveyed employers in those countries erroneously believed that less than 20 per cent of their workforce was planning to leave. And relatively few employers have acknowledged or found ways to re-engage ‘quiet quitters’ — the spectrum of

What employees want from their work varies significantly depending on age group, life stage, work experience and other factors.

employees who are doing less than they had done previously, ranging from those who fulfill their defined job descriptions but don’t do anything more to those actively destroying value by doing nothing.

Many employees are redrawing the boundaries between their work and personal lives. Some have left jobs to take on very different roles while others are leaving the workforce entirely. We found that what employees want from work — for instance, flexible hours, opportunities to advance, tasks that have purpose and meaning and adequate compensation — varies significantly, depending on age group, life stage, work experience and other factors. In this changed environment, the question for senior leaders to ask is, ‘What do we need to do differently to attract and retain top talent?’

SHIFT 5: Closing the Capability Chasm

With the growing deployment of new technologies in the workplace, from automation to AI, the skills that are needed to drive growth and value over the next decade are changing, and companies everywhere are looking to fill capability gaps. In our experience, companies across sectors often announce technological or digital elements in their strategies without having the right capabilities already in place. To plug those gaps and achieve a competitive advantage, they need to build institutional capabilities.

Put simply, institutional capabilities are the key elements that make up a company’s superpower — that is, an integrated set of people, processes and technology that creates value by enabling an organization to do something consistently better than its competitors do. Institutional capabilities stem from a company’s strategy and need to involve work that is integral to the company and its industry.

When well executed, such capabilities become a lasting edge, leading to consistent outperformance and growth over time. But organizations today find themselves lagging behind in their core activities, often as a result of insufficient resources or consistent commitment to institutional capability building. Filling these gaps is a big agenda, but one that is increasingly significant. In our survey, 90 per cent of respondents asked about capability building deemed it to be something that their organizations need to act on ‘now’ or ‘soon’; while only five per cent felt that their capabilities were already set.

SHIFT 6: Walking the Talent Tightrope

Business leaders have long had to walk a talent tightrope — carefully balancing budgets while retaining their key people. That walk is more complicated than ever in a tight labour market affected by industry churn and post-pandemic corrections. As organizations look to protect the business in the near term at the same time as setting it up for success in the long term, one important focus is on ways to match top talent to the highestvalue roles.

This idea isn’t new, but it is timely when the value contribution of certain roles is increasingly shifting to tech specialists. In our survey, 40 per cent of respondants cited a lack of digital analytics capabilities, 32 per cent cited lacking software development capabilities and 26 per cent cited lacking capabilities in generating customer insights.

Mastering the talent tightrope pays off: Our research shows that companies that reallocate high performers to the most critical roles on a quarterly basis are 2.2 times more likely to outperform direct competitors than are those that revisit roles less frequently. These high performers can influence the overall productivity of projects and business units, which, in turn, affects financial outcomes. Yet many organizations are uncertain about exactly which roles are the most critical, where the high performers are in their organizations and how to bring these two sides of the equation together.

Indeed, 46 per cent of survey respondents asked about the roles that are most critical to creating value in their organizations said they had ‘no,’ ‘little’ or only ‘some’ clarity on the topic. Aggravating the matter is that about 20 per cent of the critical roles that organizations need either don’t exist yet or have greatly evolved in scope. And even when organizations do put people in the right roles, 40 per cent of those employees will require skill development or other interventions to be successful.

SHIFT 7: Leadership That is Self-aware and Inspiring Leaders may be tempted to stick with the approaches that have worked for them in the past — regardless of whether they are still fit for those purposes — rather than rethinking the way they lead. But the costs of remaining in the ‘familiar zone’ can be high. Those who do so run the risk of alienating key stakeholders

who now expect organizations to be accountable for both profit and sustainability objectives, as well as employees who may feel demotivated, overwhelmed or otherwise unable to bring their best self to the workplace.

The essential task for leaders comes in three layers: They need to be able to lead themselves; they need to be able to lead a team; and they need to exhibit the skills and mindsets required to lead at scale, coordinating and inspiring networks of teams and ensuring that their organization functions as a cohesive whole. That’s a big ask of any single human. For every leader, it requires building a keen awareness both of themselves and of the operating environment around them.

SHIFT 8: Making Meaningful Progress on Diversity, Equity and Inclusion (DEI)

Over the past several years, more and more organizations have prioritized DEI, including it in their product, process and investment decisions as well as how they hire, retain and develop talent. And despite recent economic challenges and resource constraints, most remain committed to these efforts. Almost half of survey respondents told us their organizations have focused on strengthening their leadership DEI efforts and holding leaders accountable for delivering on DEI goals. Forty-three per cent said their organizations have focused on creating more transparency in promotions and pay processes and 43 per cent said their organizations have taken measures to tackle bias and discrimination in the workplace.

In many cases, however, these initiatives are not translating into meaningful progress. Our results reveal a gap between what organizations say they want to do with DEI and what they are actually doing. While there has been some progress on diversity initiatives, equity and inclusion efforts continue to lag behind. Even relatively diverse companies face significant challenges in creating inclusive and equitable work environments. More than 20 per cent of respondents could not confirm that there is a sense of community and inclusion in their organizations.

SHIFT 9: Investing in a Portfolio of Mental Health Interventions

In the McKinsey Health Institute’s Global Survey on Mental Health and Well-being, almost 60 per cent of respondents said they had experienced at least one mental-health challenge at

some point in their lives — a figure consistent with other research. This trend holds true regardless of country, industry, age group, role or gender. The message is clear: Most employees are directly or indirectly affected by mental-health-related challenges, so they cannot be treated in isolation from the workforce.

Four of five HR leaders report that mental health and wellbeing are now top priorities for their organizations. And despite concerns by some about a potential rise in ‘well-being washing,’ estimates show that nine of 10 organizations are offering some form of structured wellness programs to employees, incorporating benefits such as yoga classes, mindfulness and time management workshops, paid subscriptions to meditation apps, and extra days off work for mental healthcare.

Despite these efforts, many workers continue to feel overwhelmed. Our research and experience in the field suggest that this may be because their organizations — with the best of intentions — have focused on launching interventions that remediate symptoms of mental distress rather than on addressing the root causes of poor mental health and well-being. Since this problem is system-wide, we encourage employers to invest in systemic interventions that are developed and managed with the same rigour and strategic thinking applied to other corporate initiatives.

SHIFT 10: Efficiency Reloaded

The mismatch between existing operating models and market realities is more visible than ever. With profitability levels often being challenged over the past three years, the room for tolerance and the margin for error have become slimmer. Companies are therefore refocusing their attention on efficiency measures. More than one-third of leaders who participated in our survey listed efficiency as one of their top three priorities for the coming years.

Much work lies ahead. In many cases, more than half of all direct reports to a CEO don’t have profit-and-loss responsibility, and there can be as many as 12 layers between the CEO and the front line. Many organizations have become bloated, with endless meetings and incessant e-mails among the unnecessary interactions. Getting efficiency right is about fixing the foundations of how work gets done while taking a leap ahead by placing decision rights in employees’ hands.

40 per cent of respondants cited a lack of digital analytics capabilities and 26 per cent cited a lack of capability in generating customer insights.

The Path Forward

Any one of the shifts we have highlighted is a complex undertaking in its own right. All 10 together amount to a supreme challenge for leaders and their teams, especially in our uncertain times. Following are four steps to get started.

1. SET THE DIRECTION AND CALIBRATE THE AMBITION. The critical first step is to develop a clear perspective on exactly what changes are required for your organization to compete more effectively. This calibration will set the course for what follows. As part of this process, CEOs must identify the value that may be trapped in their organizations because of certain elements of the operating model. Functional groups that isolate themselves from others, computing systems that are incompatible, overly complicated procurement and other administrative processes — all of these can prevent organizations from capturing productivity gains and financial outcomes that could create more value.

2. CULTIVATE TALENT. Without the right talent, any new organizational model likely won’t work. Long before the pandemic, digitization and globalization were already changing how organizations operated and the skill sets that they needed to compete. As indicated herein, finding, developing and retaining talent now and for the future have become key challenges — but not insurmountable ones.

3. INVEST IN LEADERSHIP. If talent is the lifeblood of organizations, leaders are the heartbeat, keeping ideas, people and workstreams moving and enabling breakthrough performance. Leaders are a heterogeneous bunch, working at different levels and affecting different areas of the organization. But their collective influence matters. Our research shows that an organization is 2.4 times more likely to achieve performance targets if it has a focus on developing leaders and that transformations are more than five times more likely to succeed if leaders model desired behavioural changes.

4. CHANGE BEHAVIOUR AT SCALE. At-scale change can be difficult to accomplish and even harder to sustain, especially now. Leaders’ messages don’t always break through to employees who may be working outside of an office, thinking differently

about the nature of workplace relationships and already feeling overwhelmed by the idea of yet another business transformation. Change becomes more manageable when CEOs adopt a human-focused approach and break it down to its essentials. If organizations need different behaviours, they need to encourage different mindsets — what employees feel, think and value. And to foster these new mindsets, leaders need to change the system — the set of the experiences that influence employee mindsets. To achieve this, they must engage employees’ hearts as well as their hands and heads.

In closing

Of the approximately eight billion humans on this planet, about 3.3 billion worked in an organization last year. At a time when the very definition of ‘being at work’ is in a state of flux, these billions of global citizens are being shaped every single day — both directly and indirectly — by what goes on at work. Getting organizations right is thus not just about the success of individual companies and institutions; it’s about the broader wellbeing of society.

Four of five HR leaders report that mental health and well-being are now top priorities for their organizations.

Thought Leader Interview: Carol

Anne Hilton

As the founding CEO of the Indigenomics Institute, how do you define ‘Indigenomics’?

Indigenomics draws on the ancient principles that have supported Indigenous economies for thousands of years and works to implement them as modern business practices. Collectively, it is a response to the systemic exclusion of Indigenous peoples from the economic table over time and a platform from which we can work together to design economic reconciliation for Indigenous peoples.

The goal is to address the Indigenous socio-economic gap by moving away from a narrative of ‘happened to us’ and towards a ‘designed by us’ approach. Many Canadians still perceive Indigenous peoples as being on the cost side of the economic equation. But going forward we will be focused on creating ‘own source revenue’ — revenue that our nations raise by generating business income and collecting taxes and resource revenues.

This new paradigm facilitates the widespread acknowledgement of a new narrative: Indigenous peoples are economic powerhouses. With the right investment and growth, the Indigenous economy has the potential to exceed $100 billion.

You believe Indigenomics will help provide a sustainable pathway forward for the Canadian economy. How so?

Given the state of our environment, the path forward must include key elements of the Indigenous worldview. I am Nuu chah nulth from the west coast of Vancouver Island, and we have a concept, hishuk’ish tsawalk, meaning ‘everything is one and interconnected.’

There is growing recognition that Indigenous knowledge systems are critical to developing solutions to the climate crisis and achieving climate justice. In the realm of business, it is important to align decisions from this worldview. Our knowledge

Interview by Karen Christensen

The founder of the Indigenomics Institute describes how the Indigenous worldview is critical to our collective future.

systems offer a foundation for adaptation and mitigation actions that work to sustain the resilience of social-ecological systems locally, regionally and globally. In the words of Jonathan Wilkinson, Canada’s former Minister of Environment and Climate Change, a country cannot have a comprehensive economic plan without a comprehensive climate plan. It is here — at the intersection of Canada’s climate and economic planning — where vast opportunity lives.

Tell us more about the Indigenous worldview. A ‘worldview’ is a collective set of beliefs and values that make up a way of seeing the world, and there are important differences between the Indigenous worldview and the mainstream Western worldview. In the Indigenous worldview, as indicated, first and foremost is our relationship to the land. There is an embedded understanding of the connection of the ‘whole’ that has supported our existence, culture and survival across time, and this approach helps to frame some of the most important questions of our time: How are we interacting with our environment today, and how do we need to interact with it going forward?

Long-term thinking is another key element of our worldview. The decisions we make today will impact future generations — which brings me to our concept of the seventh generation. Put simply, we believe that decisions being made about our energy, water and natural resources must be sustainable for seven generations into the future. More than ever, we need thinking that focuses on economic progress in parallel to responsibility for our lands and resources.

While the mainstream economy is geared towards monetary transactions as the source of exchange, the Indigenous economy is based on relationships. Our economy is the original sharing economy, the original green economy and the original circular economy. Today there is increased recognition of how critical these concepts are.

Our concept of wealth is much more community focused. It is less about revenue generation and more about our continuation as people in terms of economic development that supports our ways of being and upholds our Elders’ wisdom. These distinctions establish very different operating principles, and the implications for Canadian businesses are clear: All future re-

source projects, if they are to succeed, must have Indigenous voices onboard.

Describe the ‘push/pull dynamic’ that has long existed between Canada and its Indigenous Peoples.

At the centre of Indigenous economic progress and development has been our constant ‘pushing’ of Canada toward the activation of legal recognition as it is entrenched within the constitution of this country. The ‘pull’ dynamic has taken the form of years of government policies and practices that have created our systemic invisibility, as expressed through the continued denial, resistance and rejection of our rights.

Our ongoing push for recognition has taken the form of over 300 court cases, many in the resource sector, all of which the government has lost. With these legal victories, Indigenous communities have been literally redrawing the map of Canada, one ruling at a time. This country’s land base covers 998,500 hectares; and in a power shift that no one saw coming, today, over 20 per cent of that land is controlled directly by our peoples. This demonstrates a shifting sphere of influence and the foundation for Indigenous economic empowerment.

How do you define ‘environmental justice’?

Environmental justice refers to the impacts of both historical and current inequitable distribution of the costs and benefits of environmental degradation, including the consequences of climate change. Indigenous Peoples live the long-term cumulative effects of climate change from within an inherent sense of place that is directly connected to our identity. These effects include rising sea levels, leading to increased salination of freshwater, which results in needing to adapt to the effects of a significant decrease in food security and access to traditional medicines, amongst other impacts.

Another important term in Indigenomics is ‘collaborative consent.’ Please describe it.

Collaborative consent describes an ongoing process of committed engagement between Indigenous and non-Indigenous governments to secure mutual consent. As a young leader in the Nuu chah nulth region, I witnessed high-conflict clashes

Given the state of our environment, the path forward must include key elements of the Indigenous worldview.

around clearcut logging between Indigenous nations, the forestry sector and the government. Amidst all the chaos, I was deeply influenced by what I saw: The establishment of processes for the inclusion of Indigenous wisdom as a way to establish world-class forestry practices. This integration established that not only can upholding Indigenous wisdom support economic outcomes from a management perspective, it also works from a risk perspective and a financial perspective.

BC was the first province to implement the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) into law — even prior to a national response. Canada has since moved forward on this, and I believe we’re going to see a significant increase in the acknowledgment of decision-making frameworks and processes that include the structures of collaborative consent outlined in the UNDRIP.

Progress has begun. In early 2023, the Tahltan Nation of northern BC signed a first-of-its-kind agreement with the province that moved forward the Nation’s approach to lands management and established principles of consent based on UNDRIP. Through legal advancements, BC was a first mover in terms of embedding collaborative consent within the system.

Last summer you accepted a role on TELUS’s Indigenous Advisory Council. What is TELUS doing that other large corporations should consider doing?

I have much respect for the work TELUS is doing. It was the first telecommunications corporation to launch an Indigenous Reconciliation Action Plan. That is significant in itself, but it is also ensuring accountability by being transparent about meeting the goals of that plan, which has a strong focus on Internet connectivity. TELUS recognizes that connectivity is intricately linked to positive economic, social and health outcomes. It has committed to the advancement of broadband and mobility networks to Indigenous communities by leveraging publicprivate partnerships.

In 2022, TELUS enabled 12 Indigenous lands with advanced broadband connectivity, and it is on track to meet its targets. At the time the plan was released, it had already connected close to 85,000 Indigenous homes to pure fiber across 240 communities. It also has a five-year, million-dollar Indigenous Communities

Fund that provides grants to Indigenous-led organizations such as IndigeSTEAM, which aims to excite Indigenous youth about science, technology, engineering, art and mathematics in culturally relevant ways.

TELUS has also launched a Truth and Reconciliation Elearning Program for all of its employees. To have connectivity, social outcomes and economic reconciliation outcomes reported on regularly by one of this country’s largest and most successful corporations speaks to how much the company values the Indigenous relationship. TELUS is a leader in the journey to economic reconciliation and it is time for other corporations to find their leadership space, as well.

Describe some of the key business opportunities within the Indigenous economy.

Some of the hot spots include clean energy, procurement, trade, capital and equity ownership. As investment in these areas continues, value creation will follow. Within our communities, learning and expertise are being built up around sustainable energy. Indigenous clean energy projects are increasing rapidly, and with that we are also seeing financial knowledge and capacity increasing, as well as increased equity ownership in largescale infrastructure.

A prime example is First Nations Power Authority. FNPA was established in 2011 as North America’s only not-for-profit clean energy organization that is Indigenous-owned and led. It facilitates the development of partnerships between First Nations and industry players to develop, build, own, operate and maintain cleaner energy in Canada. The ultimate goal is energy sovereignty in all parts of Canada for Indigenous nations.

Among FNPA’s achievements to date is the establishment of a Master of Sustainability (MSs) in Energy Security at the University of Saskatchewan School of Environment and Sustainability. This program is empowering a network of northern, Indigenous, remote professionals to lead sustainable community energy development in communities across Canada — and globally. It’s the only program of its kind in North America.

Indigenous technology-focused companies are also increasing. OneFeather Mobile Technologies, for example, is an innovative technology company that is enabling dedicated

Indigenous banking solutions, a centre for digital Indigenous sovereign identity and data, community engagement and innovative election and voting services and products.

Is the idea to have an Indigenous economy operating alongside the traditional economy or do you want to see the two integrated?

They absolutely have to be integrated — and projects of national importance such as the Ring of Fire initiative shows why. This is one of the most promising development opportunities for critical minerals in Ontario. Located 500 kilometres northeast of Thunder Bay, it covers about 5,000 square kilometres and has generated very high estimates of the value of its critical resources to the global market to supply the emerging low carbon economy. But the other side of this story is that there are Indigenous nations in the Ring of Fire region who still do not have access to clean drinking water.

How do you define ‘economic reconciliation’?

I define it as the space between the lived realities of Indigenous People, the need to build understanding of the importance of the Indigenous relationship, and the demand for progressive action towards economic inclusion. Unless and until every business supports that, we will not have economic reconciliation. Economic reconciliation also entails recognizing how minimal the level of Indigenous content is in Canadian education. To build progress into the system going forward, that must change.

How will we know when economic reconciliation is achieved?

I am currenlty completing the Institute of Corporate Directors Designation at the Rotman School, which has established a focused program for Indigenous peoples and companies that want to work with our communities. This is a demonstration of excellent focused leadership to bring Indigenous people to the decision-making table in the corporate sector and the investment realm. That is a key way to create a strong trajectory of Indigenous economic strength.

For individual Canadians, the pathway towards economic reconciliation entails three things: becoming educated about Indigenous issues, demonstrating positive leadership in the face of racism and promoting systemic equality. Until there is

The Indigenous Worldview

PRINCIPLE 1: Everything is connected. This concept serves as a platform for ecological, generational and relational decision-making.

PRINCIPLE 2: Story. The role of stories is a core means of transmitting teachings, history and relationships over time, relaying protocol and speaking to consequences of action.

PRINCIPLE 3: Animate life force. This concept draws the physical and the spiritual realms together, weaving the Indigenous nature of reality.

PRINCIPLE 4: Transformation. The changing of form and the recognition of the ability to shape-shift is upheld as sacred and serves to challenge our existing and limited understanding of reality.

PRINCIPLE 5: The teachings. Teachings exist to tell us how to be human and form the basis of the ‘original instructions’ or the responsibilities and ethics at the heart of Indigenous identity.

PRINCIPLE 6: Creation story. Connection to origin and Creation is foundational to an Indigenous worldview. Within the Creation story comes a right to be in a place and belonging.

PRINCIPLE 7: Protocol. The highest form of expression of recognition, this is the responsibility of remembering, acknowledging and witnessing. It is a means for recognition of connection and making things right.

PRINCIPLE 8: To witness. This is the sacred responsibility of remembering — a practice that serves to validate experience, events, external relationships, ownership, recognition and ceremony across time.

PRINCIPLE 9: To make visible. What we experience on Earth is only a part of the whole dimension, with the opposite being spiritual. Much of Indigenous ceremonial design reflects this concept of ‘as above, so below.’

PRINCIPLE 10: Renewal. The shedding of the old, of being newborn, of a new time and a focus on transitioning from one state to another — this is both the physical and spiritual domain of an Indigenous worldview, centred in ceremony.

TELUS recognizes that connectivity is intricately linked to positive economic, social and health outcomes.

an increased focus on Indigenous investment rather than social programs, we will see the continued perception of Indigenous People as an economic burden on Canada’s system.

You are holding an event in November called Indigenomics On Bay Street [November 21-23; details online.] What is your message for financial services leaders?

In 2019 we identified that a $100-billion Indigenous economy is not only possible, but essential for Canada’s economic future. In November, Indigenous Nations, economic development corporations, businesses, organizations, educational institutions, governments and investment and pension firms will gather to activate value creation in this emerging economy. By hosting this event on Bay Street, we are calling attention to the vast opportunities for partnering and investing in Indigenous businesses.

As you look ahead, do you feel optimistic?

Absolutely. As with the future of our planet, our Indigenous future is all about young people seeing themselves in their own future. We need to understand young Indigenous perspectives and foster workforce development that meets the needs of the growing number of self-sufficient Indigenous communities. This is about designing our collective future for Indigenous economic success.

There are bright spots emerging across the country. One example is the establishment of the first Indigenous Centre for Innovation and Entrepreneurship in Toronto. [Editor’s Note: see page 1 of this issue for details.] The city has one of the largest Indigenous populations — over 75,000. The Centre will serve as a space where independent businesses can come to work together, establish visibility and flourish.

Elsewhere, Suncor is working with Indigenous communities across the country to increase their participation in energy development. It has worked with more than 150 communities, including the Regional Municipality of Wood Buffalo — home to Suncor’s oil sands operations — and other locations through Petro-Canada branded products and services. There are 26 Petro-Canada branded gas stations owned by First Nations, one wind project where a First Nation is an equity partner, and Suncor is an equity partner in PetroNor, a James Bay Cree

The Indigenomics Economic Mix: 12 Levers for Growth

1. Equity ownership

2. Capital

3. Entrepreneurship

4. Trade

5. Philanthropy

6. Procurement

7. Clean energy

8. Technology

9. Social finance

10. Investment

11. Commerce

12. Infrastructure

wholesale distributor.

The First Nations Major Projects Coalition is leading the charge for increased equity ownership in major projects across the country. The loan-guarantees process will allow Indigenous communities to buy equity stakes in major projects. This is one of the most exciting and important developments in Indigenous business in decades.

Overall, we are witnessing a powerful explosion of Indigenous entrepreneurship taking place across Canada. The capitalization of the growth and design of the Indigenous economy needs to brought into visibility to achieve widespread awareness.

Carol Anne Hilton is Founder and CEO of the Indigenomics Institute and author of Indigenomics: Taking a Seat at the Economic Table (New Society Publishers, 2021). She holds an international MBA from the University of Hertfordshire, England. Carol Anne is of Nuu chah nulth descent from the Hesquiaht First Nation on Vancouver Island.

IS AI AN EXISTENTIAL THREAT?

Many people were surprised by the March 2023 open letter from tech leaders requesting a moratorium on AI development. Three thought leaders debate whether or not AI is an existential threat to humanity.

Steve Paikin: In March of 2023, an open letter was released by technology leaders calling for a six-month pause on AI development. Elon Musk signed it, as did Apple co-founder Steve Wozniak. It said, in part:

AI systems with human-competitive intelligence can pose profound risks to society and humanity…recent months have seen AI labs locked in an out-of-control race to develop and deploy ever-more powerful digital minds that no one — not even their creators — can understand, predict or reliably control.

Soon after, Geoffrey Hinton, known as the Godfather of AI, announced his resignation from Google, saying: “Look at how it was five years ago and how it is now. Take the difference. Propagate it forwards. That’s scary.” Gillian, how would you characterize this moment in history for AI?

Gillian Hadfield: I think we are at a real inflection point in thinking about AI. As you pointed out, we are seeing tremendous advances. What we saw in the fall of 2022 with ChatGPT was exciting and new, and I think people are now saying, ‘Hey

folks, maybe we’re going a bit too fast. Maybe there’s a lot more happening here than we’ve understood.’ I think that’s what the pause letter is about.

SP: Pedro, what is your view on this?

Pedro Domingos: I don’t think we’re going too fast at all. In fact, I don’t think we’re going fast enough. If AI is going to do things like cure cancer, do we want to have the cure years from now or yesterday? What is the point of a six-month moratorium? To me, that letter is a piece of hysteria. The bigger worry for me — and most AI researchers — is not that AI will exterminate us, it’s that a lot of harm will be done by putting in restrictions, regulations and moratoria that are not needed.

SP: Jérémie, what’s your take?

Jérémie Harris: It’s clear that we’ve taken some significant steps towards human-level AI — in the last three years in particular. So much so that we have many of the world’s top AI

Gillian Hadfield, Pedro Domingos and Jérémie Harris speak to Steve Paikin

researchers, including two out of three of its earliest pioneers, wondering aloud about it. I might not go that far, personally, but this is being talked about through that lens. By throwing more data and processing power at these techniques, we might be able to achieve something like human-level or even superhuman AI. If that is even a ballpark possibility, we need to contemplate some fairly radical shifts in the risk landscape that society is exposed to by this technology.

There are many dimensions to consider, but a key one is malicious use. As these systems become more powerful, the destructive footprint of malicious actors that use them will only grow. We’ve already seen, for example, China using powerful AI systems to interfere in Taiwan’s electoral process. We’ve seen cybersecurity breaches and malware being generated by people who don’t even know how to code. Then, of course, there’s the risk of catastrophic AI accidents, which folks like Geoff Hinton are flagging. Those two broad categories of risk are very significant.

SP: Gillian, let’s circle back to Pedro’s initial comment, that if you want a cure for cancer, you don’t move slower, you move faster. What do you say to that?

GH: I actually agree. There are lots of potential benefits to be had and we absolutely want them to materialize. We want to continue doing our research and building the system. That’s a really important point. But if you think about medical research, it takes place within a regulated structure. We have ways of testing it and there are clinical trials. We have ways of deciding which pharmaceuticals, medical devices and treatments to put out there. With AI, we’re seeing such a leap in capability that the ways in which it transforms research and work have basically outstripped our existing regulatory environments — and we haven’t yet built a system that ensures AI is working the way we want it to.

SP: Pedro, on the topic of searching for a cure for cancer, what about the notion that patient-protection regulations don’t yet exist for AI, and therefore we ought to be careful?

PD: I think the analogy between AI, medicine and drug approval is mistaken. Each area faces problems of its own. The drug approval mechanisms that we have in place are costing lives, and even the Food and Drug Administration in the U.S. under-

stands that it needs to change. So that is hardly a good model. Regulating AI is not like regulating drugs. It’s more like regulating Quantum Mechanics or Mechanical Engineering. You can regulate the nuclear industry, cars or planes; you can regulate — and should and do regulate — specific applications of AI. But regulating AI itself doesn’t make sense.

I think we definitely need to ‘ask questions before we shoot,’ make sure we understand the technology and figure out what needs to be regulated and what doesn’t. I think what OpenAI has been doing is great. The best way to make AI safe is to put it in the hands of everybody, so everybody can find the bugs. We know this from Computer Science: The more complex the system, the more people need to look at it. What we don’t need is to put this in the hands of a committee of regulators or experts to figure out what’s wrong with AI. I think that’s the wrong approach.

SP: Jérémie, do you think AI poses an existential risk to humanity?

JH: I think the argument that it does is backed by a lot more evidence than most people realize. It’s not a coincidence that Geoff Hinton is on board here. It’s not a coincidence that when you talk to folks at the worlds’ leading AI labs — the ones that are building the world’s most powerful AI systems, the GPT4s — you hear people talking about the probability that this will amount to an existential risk.

One of the things these people are discussing is the concept of ‘power-seeking’ in sufficiently advanced systems. That’s one concern that Geoff Hinton put on the table, and it’s been written up and studied empirically. I think it’s something we should take seriously. Nothing is guaranteed. That’s part of the unique challenge of this moment. We’ve never before made intelligence systems smarter than us. We’ve never lived in a world where those systems exist. So we have to deal with that uncertainty in the best way we can. Part of that entails consulting with folks that actually understand these systems and who are experts in technological safety.

SP: Gillian, what was your reaction when you heard Geoffrey Hinton’s comments?

GH: I think Geoff was truly surprised by the advances he’d seen in the previous six months. Obviously, he’s been tremendously

As these systems become more powerful, the destructive footprint of malicious actors that use them will only grow.

close to this. I think a number of people didn’t realize that scaling up large language models and generative models would produce the kind of capabilities we’re seeing. I’ve had lots of discussions with Geoff — he’s on my Advisory Board at the Schwartz Reisman Institute — and this was an important moment for him as to the nature of the risk. If you listen to what he has to say, it’s not ‘I know for certain that there is an existential risk,’ it’s ‘There is so much uncertainty about the way these things behave that we should be studying that problem and not getting ahead of it.’ That is an important clarification.

SP: Pedro, when someone like Geoffrey Hinton rings the existential bell, does it not give you pause?

PD: I’ve known Geoff for a long time. He’s a great researcher; but he’s also an anarchist from way back and a bit other-worldly, and I think we need to be careful about overinterpreting what he says. People need to know that most AI researchers do not think AI poses an existential threat. But of course, it’s interesting to try to understand why some do people believe that.

There are many researchers who don’t think we’ll ever get to human-level AI, which is quite possible. I do happen to think we’ll get there, but it won’t happen tomorrow. People need to understand that, number one, we are still very far from humanlevel intelligence AI. Geoff has said things like, “What if an AI wants to take over?” To which Meta’s Head of AI Yann LeCun responded, “But AIs don’t want anything.” It’s an algorithm; it’s not something that we can’t control.

When you use machine learning, the AI does something you can’t predict. But it is being done to optimize the functions that you have determined. That’s where the debate needs to be, is how to optimize that. AI is for solving problems that are intractable, meaning it would take exponential time to solve them. That’s the technical definition of AI. But it’s easy to check the solution.

GH: I want to put the existential threat question in a broader lens, as well. It’s true that malicious use is something to be concerned about, but I don’t think the risks are around a ‘rogue AI’ that develops its own goals and, Terminator-style, sets out to kill us all.

The thing I worry about is our complex systems — our financial systems, economic systems and social systems. I worry

about the capacity for autonomous agents — which are out there already, by the way, trading on our financial markets and participating in our labour markets, reviewing candidates for jobs. When we start introducing more and more autonomous agents into the world, how do we make sure they don’t wreak havoc on our systems?

SP: Jérémie, do you worry that we are entering Terminator territory?

JH: A couple things. First off, on the question of ‘These are just algorithms, what do they really want?’ and so on, this is where the entire domain of power-seeking comes up. As I indicated, this is an entire subfield in AI safety that is well researched. These objections are very robustly addressed, at least in my opinion. This is a real thing. And the closer you get to the centres of expertise at the world’s top labs — the Google DeepMinds, OpenAIs, the very labs building ChatGPT and the next generation systems — the more you see the emphasis on this risk class.

A poll from a few months ago showed that 48 per cent of general AI researchers estimate a 10 per cent or greater probability of catastrophic risk from AI. Imagine if you were looking to get on a plane and 50 per cent of the engineers that built it said, ‘There is a 10 per cent chance that this plane is going to crash.’

SP: Yann LeCun recently tweeted the following: “We can design AI systems to be both super-intelligent and submissive to humans. I always wonder why people assume that intelligent entities will necessarily want to dominate. That’s just plain false, even with the human species.” Jérémie, why do you assume that if AI does become more intelligent than us, it will automatically want to conquer us?

JH: This is actually not an assumption, it’s an inference based on a body of evidence in the domain of power-seeking. Pioneering work at frontier labs suggests that the default path for these systems is to look for situations to occupy and position themselves in. Basically, the systems seek high optionality, because that is useful for whatever objective they might be trained or programmed to pursue. As AI systems get more Intelligent, the concern is that they will start to recognize and act more and more on these incentives.

SP: While you were speaking, Pedro had a big smile on his face. What’s behind that smile, Pedro?

PD: I just have a hard time taking all of this seriously. The people who tend to be most hysterical about AI are the ones who are furthest from actually using it in practice. There’s room for a few of these people in academia; the world needs that. But once you start making important societal decisions based on them, you need to think twice.

I agree with Gillian that these Terminator concerns are taking attention away from the real risk we need to be talking about, which is the risk of malicious use. We are going to need something like ‘AI cops’ to deal with AI criminals. We have to face the problem of AI in the hands of totalitarian regimes and democracies need to start making better use of the technology.

The biggest problem with AI today, not tomorrow, is that of incompetent, stupid AI making consequential decisions that hurt people. The mantra of the people trying to control AI is that we need to restrict it and slow it down, but it’s the opposite: Stupid AI is unsafe AI. The way to make AI safer is by making it smarter, which is precisely the opposite of what the moratorium letter is calling for.

GH: As indicated earlier, I signed that letter, and I signed it so that we would have these very conversations — not because I think it’s essential that we stop progressing. I don’t believe we’re on a precipice; but I do think it’s critical to think carefully about all this. These systems are being built almost exclusively inside private technology labs. I work with folks at OpenAI, so I know there is a lot of concern there about safety. They’re making decisions internally about how to train AI so it ‘speaks better’ to people, when to release it, to whom and what limits and guardrails should be put in place. These are things we should be deciding publicly and democratically, with expertise outside of the engineering expertise that is currently dominating this arena. As a social scientist, an economist and a legal scholar, I think about the legal and regulatory infrastructure that we need to build, and I don’t see us paying enough attention to that set of questions.

SP: When the printing press was invented, we didn’t know what impact it would have. We had to use it for a while in order to understand that. Same goes for the Internet, the cotton gin and the steam engine. Why is this technological moment any different from previous discoveries?

JH: Because we are currently on a trajectory to build something potentially smarter than ourselves. That may or may not happen, but if it does, we’re going to find ourselves in a place where we just can’t predict anything important around how the future is going to unfold.

Throughout history, human intellectual capacity has been the one constant. We’re all born with biological thinking hardware, and that’s all we’ve had to work with. But we just don’t have a point of reference here, which is why it’s so important to track this and think deeply about where it might go.

PD: It’s true that AI introduces uncertainty because it is powerful and can be used for lots of different things, and we can’t possibly predict them all. But that is good! The best technology is like the examples you gave earlier. Most of the best applications are things no one could have anticipated. What happens is, we all work to optimize good applications and to contain bad ones. AI is still subject to the laws of physics and the laws of computation, and to the sociology of sociotechnical systems. We’re actually going to have a lot of control over it, even if there are aspects of it that we don’t yet understand.

A good analogy here is a car. As a user, you don’t feel an urgent need to understand exactly how the engine works just because it could blow up one day. That’s for the mechanic. What you do need to know is where the steering wheel and pedals are, so you can drive it. And AI does have a ‘steering wheel’ — it’s called the objective function, and we need to understand how to ‘drive’ that.

I very much agree that we need more than just the technologists thinking about this. The limiting factor in the progress of AI is actually not on the technical side, it’s around the human ability to use it and come to terms with it. That’s what’s going to set the right limits.

SP: Gillian, Do you think this technological moment is different from previous ones?

GH: I do. What is critical here is the speed with which AI transforms entire markets. For example, in the legal domain, I’ve seen how, in just a few minutes, tools like ChatGPT can do what it would usually take a week for a lawyer to do. That is going to be very disruptive, and the potential scale is massive. Because it’s a general purpose technology, it can and will show up everywhere.

The people who tend to be most hysterical about AI are the ones who are furthest away from using it in practice.

To return to the analogy of the automobile, what I am concerned about is that we live in a world with copius regulation around how to build and drive automobiles. It took 50 years before we built all that regulatory structure. There was basically nothing in the beginning. And that’s just one part of our economy. I don’t think we can approach AI as we have with previous technologies and say, ‘Let’s just put it out there, find out how it works and then figure out how to regulate it.’ I think we have to be much more proactive about it.

SP: There appears to be consensus that AI must be developed in a responsible way. How do we do that?

PD: We don’t even know what a real AI is going to look like, because we don’t have one yet. So trying to regulate in advance is almost guaranteed to be a mistake. What needs to happen is, the government and the regulatory organizations need to have their own AI, whose job it is to deal with the AIs of the Googles and the Amazons and so on.

There is no fixed, old-fashioned set of regulations that will work with AI. We need something as adaptive on the government side as it is on the corporate side, so AIs can talk to each other. This is already starting to happen in the financial markets, because there is no choice. There’s a lot of bad activity going on and you’ve got to have the AI in place to deal with it.

GH: There are two things I want to pick up on. First, I agree that we’re going to need AI to regulate AI. I actually think we need to build that as a competitive sector unto itself. But it’s important to recognize that there are some building blocks that we don’t have in place currently that allow us to regulate other parts of the economy. For example, one thing we can do right now is create a national registration body — a registry system so that we have eyes on where AIs are, how they’ve been trained and what they look like.

I think this should be a government function. Every corporation in the country has to register with a government agency. They have an address on record; they have the name of someone who is responsible. The government can say, ‘Okay, we know you’re out there.’ We register our cars so we know where all the cars are. Right now we don’t have that kind of visibility into AIs. So that’s the starting point.

People would have to disclose basic pieces of information about the models to government — not publicly, not on the

Internet. That would give us visibility into this as a collective. It would also provide us with the tools needed if a dangerous method of training or a dangerous capability emerges. We don’t even have that basic infrastructure in place yet.

SP: Last word goes to Jérémie. How do we need to proceed?

JH: I think it’s worth noting that the most advanced AI capabilities require giant processing-power budgets — on the order of hundreds of millions of dollars. OpenAI’s latest model cost is in the hundreds of millions. And we’re seeing that cost rise and rise. That immediately implies a bunch of counter-proliferation levers. And OpenAI has really led by example by inviting third parties to audit their AI models for behaviours like power-seeking and malicious capability. It would be great to see a lot more of that in the AI community.

Gillian Hadfield is a Professor of Law at the University of Toronto and Professor of Strategic Management at the Rotman School of Management. She is Director of the Schwartz Reisman Institute for Technology and Society at the UofT as well as AI Chair of the Canadian Institute for Advanced Research (CIFAR). Pedro Domingos is a Professor Emeritus of Computer Science and Engineering at the University of Washington and author of The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (Basic Books, 2018). Jérémie Harris is Co-founder of Gladstone AI and the author of Quantum Physics Made Me Do It: A Simple Guide to the Fundamental Nature of Everything (Viking, 2023).

This article is a condensed version of an interview from TVO’s The Agenda, hosted by Steve Paikin. Video of the entire conversation is available on the TVO website: www.tvo.org/theagenda

ChatGPT: What Leaders Need to Know

Wharton Professor Ethan Mollick believes ChatGPT

by Curt Nickisch and Ethan Mollick

Curt Nickisch: In late 2022, people started talking about how ChatGPT was poised to change work as we know it. What is so special about this technology?

Ethan Mollick: ChatGPT-3, which is the base generation of this technology, was around for about a year, and it was okay. It worked at or near the level of a D-minus student. But we have since crossed a threshold of ability that has made ChatGPT incredibly useful. It can now achieve the output of a B-minus student. And if you use a more advanced model like the one on Microsoft’s Bing search engine, you can achieve the level of an A-minus student. This represents radical progress in a very short period of time.

We have some early results on how these tools affect productivity. One was a controlled experiment on people doing business writing, and the other looked at website coders. The results were amazing: In both cases the researchers found a 30 to 50 per cent improvement in productivity. And these were people who hadn’t even been trained on the system. Clearly, this is major. We have never seen productivity improvements like that.

To provide some context, the productivity improvement we saw when the first American plant added steam power to its operations in the 1800s was about 25 per cent.

CN: What kind of opportunities does this open up for companies?

EM: There is no rulebook or manual to work from, so you have to explore for opportunities yourself. As indicated, this AI is really good at writing computer code and common documents like memos or reports. If you need to write a letter of recommendation or a performance review, it will do an amazing job. But when you start to incorporate the Bing version or some of the other new AIs coming our way, you’ll be able to get it to do complex, multi-layered tasks. For example, you’ll be able to say, ‘Look up everything about the precision agriculture industry and give me a table showing the growth rates for each company along with their strengths and weaknesses, using the perspective of Michael Porter’s Five Forces Model.’ This type of request could save someone up to 12 hours of work

is as big a deal for leaders as COVID-19 was — and that it is likely to make everyone more productive.

and provide a document that they can build on — because as good as it is, you do still have to check AI’s work.

CN: The applications you mention seem to be for individuals within a company setting, rather than organization-wide applications. Is that the case?

EM: Yes, and that’s part of what makes it so interesting. This technology has already been released to 100 million users, making it the fastest product rollout in history. But right now, the only people who can use it are individuals. There is no real benefit to large-scale corporate use at this point. You can’t call up a consulting company and ask them how to implement ChatGPT across your company, like you would with Salesforce or some other system application. Over time, there will be more organizational applications, but so far, the main story is at the individual level.

And people are using it. I guarantee you, there are secret users of ChatGPT in every organization who have cut their workload by two thirds and don’t want to tell anyone about it. I’m hearing examples all the time. It’s easy to get started; you just need to spend an hour or two learning how it works and what it’s good and bad at.

I’ve talked to tons of people who are big fans. First of all, virtually everyone in programming is using it to help with coding. They’ve switched over from Stack Exchange to ChatGPT. But increasingly I’m talking to managers who have just automated tasks like performance reviews, grant applications or regulatory compliance. This is a general-purpose technology, as its name suggests.

CN: What do leaders need to do in terms of putting rules and policies in place?

EM: A number of organizations, including JP Morgan, have outright banned the use of ChatGPT by its employees. But I am willing to bet lots of their employees are conducting the chat on their phones and e-mailing it to themselves to get around the rule. When people find a technology that cuts their work time by such a considerable margin — particularly some of the most boring aspects of it — they are going to figure out a way to use it.

At the same time, this technology is evolving so quickly and the potential performance improvements are so significant that leaders need to figure something out now. You can’t just wait and see what happens in your industry. You should be asking

questions like: ‘Who in our organization is likely experimenting with this?’ Maybe leaders can have all their employees spend three or four hours on a prescribed day hacking away at it, to see how they can use ChatGPT to automate their job. They could even give a cash prize to the workers who come up with the best ideas. This is a company-by-company thing.

CN: Should some organizations be in triage mode? Will this bring back the need for a ‘war room,’ like we saw during the pandemic?

EM: I do believe this is as big a deal as the pandemic, in the medium term. I absolutely think leaders need to be on it. Pick a topic like idea generation or writing, and stay current on what’s happening out there. You could even take a ‘red team’ approach and ask, ‘How could external people use this tool to attack our business model?’ This is definitely a war room situation because of how quickly it’s evolving.

CN: Should some workers have to use ChatGPT, if they haven’t already started?

EM: I don’t know about forcing people to use it, especially if there’s no corporate-use case in place. The policy will come from the use cases, and in cases where high levels of accuracy are required, the current versions of ChatGPT are probably not going to be what you need. But already, some of the fine-tuned models like Google’s medical model are giving advice about common illnesses that is equal to that of doctors. And doctors are actually rating the answers from the medical AI as being less dangerous than the answers from other doctors! We are going to see ‘specialized disruption’ coming next, which is partly why ChatGPT needs to be understood by every leader.

CN: Can you give an example of a common-use case?

EM: Any creative endeavour that is undertaken today should include a seat for ChatGPT at the table. It adds a huge amount to the innovative process because it can generate tons of ideas and find novel combinations. Let’s say you are a marketing consulting company that does market research, provides creative services and helps clients increase their search engine optimization (SEO.) What I would do is ask my people in each area to start using ChatGPT and documenting use cases. Then, over time, you can start to build policy around that.

Today, any creative endeavour that is undertaken should include a seat at the table for ChatGPT.

The key is to figure out how much human oversight is required. To what degree can you let ChatGPT do your writing and to what degree should it be a combination of ChatGPT and humans? When you use Bing AI for research, how often is it right and how often is it wrong? To a certain degree, you have to turn everyone in your organization into a quasi research scientist and say to them, ‘Let’s experiment. Let’s see what works and what doesn’t.’

CN: Could ChatGPT lead to happier, more engaged employees?

EM: It definitely could. People who used ChatGPT in the preliminary studies were happier because they were able to offload the worst parts of their job and get to focus on more interesting stuff. All of the more creative and interesting tasks can stay in human hands. The one caveat is that today’s technology is improving so rapidly that it’s not clear where (or if) humans will always be needed in the loop. And that is both exciting and super worrying.

CN: What kind of implications does this have for HR and hiring?

EM: One of the questions for HR leaders is, ‘What does this mean for skill requirements going forward?’ That is going to depend on the organization and the setting, but in general there are four scenarios. The first is that ‘ChatGPT makes everyone more productive.’ As indicated, we have early evidence that this is the case, and if it is true, great. But that will affect how much high level human capital you need to hire, because these people may be able to run chatbots to do most of their work.

The second scenario is, ‘ChatGPT makes your best workers even more productive.’ The people who are already good at what they do tend to be the best at using this tool in a hybrid way, which would mean you will want to hire even more superstars because they will accomplish more than ever. In scenario three, ‘ChatGPT levels out work.’ The worst performers start to do just as well as the strong performers because these tools help them solve problems. Of course that, too, has implications for who you hire.

The fourth scenario is that ‘ChatGPT creates a new role in every organization.’ Some people will become really good

‘AI whisperers,’ and if you can find and hire them, they will be many times more productive even if they’re not the best traditional workers. Every organization is going to have to figure out which scenario applies to them.

CN: If I’m a manager leading a team, what should I be doing right away?

EM: The next time you open up your laptop to get some work done, open a ChatGPT window and try to do as much of your work with it as you can for the rest of the day. As I said earlier, you’ll find that it’s incredible at writing memos and other information. It’s great at helping run meetings. You can say to it, ‘I need to set up a meeting with these four people about this topic: Do the research on the science of meetings and give me the steps I should follow,’ and it will give you the steps. Or you can say, ‘Create an agenda’ or ‘Compose the e-mails I need to send to each invitee.’ It will do that. Then during the meeting, you can do a text-to-speech transcript and paste it in afterwards and say, ‘Summarize the meeting notes and give me action points; then write an e-mail to each participant assigning them one action point.’ It will actually do a pretty good job at all of this. The bottom line is that you have to try it out to see how it can change your job.

CN: What do you say to anyone who is intimidated by this technology?

EM: Anyone who is afraid of ChatGPT shouldn’t be. There is no advantage to being an expert coder here, or in understanding how large language models (LLMs) work. These are tools that anyone can program using the English language. You literally give it instructions. ‘Hey, write a four-page market research report for me using the following major bullet points. Write it in an academic-but-authoritative style and use clear metaphors,’ and it will do that. There’s no reason not to dive in.

In terms of long-term career impact, I don’t think we know the answer to that. In general, new technologies tend to both disrupt jobs and also create new ones. I’m hopeful that that will be the case here — but we have never seen a leap in technology like this one. I advise people to proactively figure out how much of their own job they can automate — not only to make their life easier but also to give them a sense of their exposure to job-loss.

When people first use ChatGPT they often stop using it very quickly because the first thing they ask it to do doesn’t turn out well. Lots of people try to use it like a Google search and they find out quickly that it doesn’t ‘know’ anything and it’s not connected to the Internet. So they get frustrated. Or, they try to treat it like Alexa or Siri and ask it fun questions, and they find it doesn’t have a fun personality. Maybe they ask it a factual question about something like, ‘What is my biography?’, and it makes stuff up, and they’re like, ‘This is awful. Why would anyone use this?’

That’s not how to use this tool. The way to approach it is, start to explore with it, and you will realize it can automate huge amounts of your writing and other tasks. You can paste a résumé into it and then say, ‘Write a letter of recommendation that makes these three points.’ On Bing, you could say, ‘Go out and summarize the research on topic X.’ Or you can say, ‘Come up with a hundred ideas for a marketing slogan for my company; here’s the company description.’ The use cases can be transformative, but it takes a new approach to have it work well.

CN: Are there any dangers to warn people of? Any disadvantages?

EM: There are tons of risks. One thing I mentioned earlier is the risk of ‘hallucination.’ In its attempt to make you happy, ChatGPT will often make things up. And that’s why the first rule is, you have to be accountable for the content you create using it.

The second set of issues is around morality and ethics. These systems are trained using the entire Internet. Does that mean they’re plagiarizing? Not directly; they’re not using someone else’s exact words, but what does that mean? I was able to use AI to create a very credible deep fake video of myself giving a speech I never gave—in my voice—and it took about four minutes to do that. Chatbots can be very convincing. How will we deal with that?

Then there are the larger-scale implications for work. What does it mean if you automate many of your organization’s tasks? Who benefits from that? The workers or the company? Then there are the even larger implications: What do we do in a world where machines can perform tasks intelligently, without being sentient? How do we deal with their growing ability over time? There are a lot of concerns that we need to consider very carefully.

CN: What is coming down the pipe that leaders should know about?

EM: Most people are aware that the ChatGPT-4 release is coming soon, and that it’s much more comprehensive than the model we’ve been using. If the capability increases remain at the scale they’ve been so far, it is going to be a game changer.

Google has, by far, the largest AI research team and they’ve been cautiously rolling out specialized products in different industries. There are other companies like Anthropic, which has Claude, which users can get access to. There will be a lot of LLMs out there soon. There are also diffusion-based models, which can be used to create images. DALL-E for example, lets you easily create images from text, and video is next. You’ll be able to describe the video you want to see and quickly receive a copy of it. Eventually, you’ll be able to do that with user interfaces.

A lot of specialized tools will be coming out for organizations. Some will be designed as companions for meetings; others will do particular kinds of writing. Obviously, I advise readers not to use ChatGPT in cases where danger is involved. For instance, doctors should not be using it to write notes to patients or specialists. That would be unethical. Wherever there is federal compliance in place, you should not be using ChatGPT. But apart from that, holding off on experimenting with it is a big mistake.

This article began its life as a podcast from that series. Ethan Mollick is the Ralph Roberts Distinguished Faculty Scholar, Associate Professor of Management and Academic Director of Wharton Interactive at the Wharton School of the University of Pennsylvania.

Curt Nickisch is a Senior Editor at Harvard Business Review and hosts the HBR Ideacast

This means all of the more creative and interesting tasks can stay in human hands.

Powerful Leadership Lessons from Former IBM CEO Ginni Romet ty

One of the world’s most respected leaders, former IBM CEO Ginni Rometty overcame childhood and financial stru les to embark on a groundbreaking career that took her from entry-level engineer to eight years as the first woman CEO of an iconic global company. Rometty delivers a powerful combination of memoir, leadership lessons, and big ideas on how we can all drive meaningful change. This is her story—with lessons for us all.

15 Reasons You Should Read This Article! The Pros and Cons of Over-Arguing

In the realm of persuasion, people generally believe that more is better. But that isn’t always true: Over-arguing can also trigger a negative response.

by Rhia Catapano

WHETHER RECOMMENDING A RESTAURANT, endorsing a brand or promoting a policy, it seems reasonable to think that the more arguments you can provide, the more persuaded your audience will be. Indeed, past research suggests that, assuming one has compelling points, providing many rather than few arguments generally promotes greater persuasion.

Laypeople share this belief. When I asked 249 online participants whether giving a low or high number of arguments would be more persuasive, 59 per cent indicated that using a high number of arguments would be the better strategy.

In contrast to this view, in recent research with Mohamed Hussein and Zakary Tormala of Stanford University’s Graduate School of Business, we posited that a high rather than low

number of arguments might have conflicting effects on persuasion. And further, these competing effects might actually cancel each other out, resulting in minimal or no overall benefit to persuasion from using more arguments. In this article I will summarize our research and the key takeaways.

Less Can Be More

Past research suggests that the more arguments one provides for a position, the more persuasive one tends to be. In one notable study, participants were asked to imagine being trial jurors and read arguments for both the prosecution and the defence. Then, they rated how guilty the defendant was. The researchers varied the number of arguments given by the prosecution and the

defence to be one, four or seven. Results indicated that the more arguments provided by the prosecution, the more guilty participants found the defendant to be — and the same went for the defence. In other words, more arguments led to more persuasion.

In another example, undergraduates read an editorial promoting a campus policy. The researchers varied argument quantity (three versus nine), argument strength (weak versus strong) and participants’ involvement (low versus high). They found that the effect of argument quantity depended on involvement. Under low involvement, nine arguments led to more persuasion than three, regardless of argument strength. This effect was thought to be driven by a simple ‘more-is-better’ heuristic. Under high involvement, the argument quantity effect depended on argument strength. Because high-involvement participants processed more carefully, nine (versus three) arguments promoted persuasion when arguments were strong, but undermined persuasion when arguments were weak. These results suggest that as long as one’s arguments are strong, providing more of them fosters more persuasion.

In our research, we hypothesized that people actually draw competing inferences about sources who provide many arguments. On the one hand, they might come across as more expert on the topic, which boosts persuasion; on the other, they might come across as more biased, undermining persuasion. These inferences, we felt, could suppress each other, producing minimal or no overall benefit to providing many arguments.

It seems reasonable to suspect that a source who provides many arguments might be seen as having more expertise on the topic at hand. ‘Source expertise’ refers to the extent to which a source is knowledgeable, competent and capable of making accurate claims. Compared to someone who offers few compelling arguments (e.g. one or two), a source who provides many (e.g. nine or 10) might seem to possess greater knowledge and competence and, thus, more expertise. As indicated, prior work suggests that experts are more persuasive than nonexperts. Thus, to the extent that using more arguments increases perceived expertise, we expected it to enhance persuasion.

At the same time, however, we felt that a source who uses many arguments might come across as more biased on the issue at hand. ‘Source bias’ refers to the extent to which a source has a slanted or skewed perspective on an issue or a vested interest in a specific outcome. Compared to someone who provides few arguments, a source who provides many might elicit questions such as, ‘Why is she providing so many arguments? Does she have a vested interest?’ or ‘Does he have a hidden agenda here?’ In other words, message recipients might question whether sources providing many arguments are biased.

Although there is not a wealth of research on source bias, the nascent literature suggests that perceived bias undermines persuasion. For example, one researcher found that under-justifying one’s position (e.g. providing weak arguments) can lead to perceptions of greater bias, which reduces persuasion.

My colleagues and I felt that just as under-justifying one’s position with weak arguments could trigger perceived bias, overjustifying one’s position with too many arguments could, as well. Specifically, we predicted that providing more arguments than is typical in a given setting increases perceived bias. For example, if the norm on a customer review platform such as Yelp is to provide three reasons for your positive review, providing 10 might lead people to infer that you are biased. If this proved to be true, we hypothesized that providing many arguments might undermine persuasion, as well.

Our Research

We tested our hypotheses across three experiments, using different topics and settings, including brand endorsements on social media and restaurant reviews. In our first experiment, participants viewed a social media post containing either three or nine arguments. We predicted that providing more arguments would increase perceived expertise and perceived bias, and that these perceptions would have a ‘cancelling out’ effect on persuasion.

Four hundred one participants completed our study, and 369 were included in the final analysis. Participants imagined

As predicted, there was both a positive effect of over-arguing (through perceived expertise) and a negative effect (through perceived bias).

that they were browsing Instagram when they came across a story from someone they followed. Next, they viewed an Instagram story that appeared over two pages. On the first page, they saw a picture of cold-brew iced coffee. The picture contained text that endorsed the brand of cold-brew (‘Love this cold-brew coffee!’ and ‘Highly recommend that you give it a try!’). We made an effort to mimic a typical Instagram story, but did not specify the brand.

The second page differed by condition. Participants in the three-arguments condition saw three arguments advocating for the coffee brand (e.g. ‘In terms of flavour, this one definitely stands out. Not too sweet and has a smooth and creamy texture.’) In both conditions, the arguments were randomly selected from a larger list of 10 and all appeared on the same page. Participants indicated their overall attitude towards the brand using a star-rating similar to those commonly employed online. They could report any star-rating between .5 and 5, with half-star increments (e.g. .5, 1, 1.5), making this a 10-point scale. They reported their interest in trying the brand of coffee on a 7-point scale (1 = not at all interested, 7 = very interested). Then they completed a three-item ‘bias index’:

1. How much do you believe that this user has a biased perspective on this brand of cold-brew coffee?

2. How one-sided does this user seem on the subject of this coffee brand?

3. To what extent do you believe this user has a vested interest or a hidden agenda in promoting this brand?

Responses, provided on scales ranging from 1 (not at all) to 7 (extremely), were averaged. Participants also completed a two-item ‘expertise index’:

1. How knowledgeable do you think this user is about this brand of coffee?

2. How much of an expert on this brand of coffee do you think this user is?

Responses, provided on scales ranging from 1 (not at all) to 7 (extremely) and once again, were averaged.

RESULTS: Participants perceived the source as ‘more expert’ in the nine-argument rather than three-argument setting and more biased in the nine-argument rather than three-argument setting. In terms of persuasion, attitudes were slightly more favourable in the nine-argument condition, but there was no difference in interest in trying the brand between the two settings.

While there was no overall effect of the number of arguments on interest, we did find evidence for suppression: As predicted, there was a positive indirect effect through perceived expertise and a negative indirect effect through perceived bias.

For attitudes, we found a slight-but-significant positive effect of number of arguments. Importantly, though, a negative indirect effect through bias attenuated what would have been a stronger overall effect. Indeed, we found a positive indirect effect through perceived expertise and a negative indirect effect through perceived bias.

In short, our first study had conflicting effects on persuasion. Offering nine rather than three arguments increased perceived expertise, which promoted persuasion, but also increased perceived bias, which undermined persuasion. Combined, these effects produced no or minimal benefit to increased argument quantity.

Our second experiment was similar to the first but used a different context. Participants read either one or 10 positive reviews of a restaurant, all written by the same reviewer and ostensibly taken from Yelp.com. We predicted that participants would perceive the source as more expert and more biased in the 10- compared to one-review condition. Furthermore, we predicted that these perceptions would have countervailing effects on downstream consequences, including participants’ attitudes towards the restaurant and interest in trying it. We also measured an additional consequence — interest in receiving future information from the source — to assess whether the suppression effect would generalize to outcomes beyond the attitude object.

Four hundred and four participants completed our study on Prolific Academic , and 374 were included in the final analysis. All participants read reviews of a restaurant called HappyGreens. Participants in the first condition saw one positive review, whereas those in the second condition saw 10 positive reviews, all written by the same source. They then answered questions about their attitudes, interest in trying the restaurant, desire to receive future information from it, and perceived source bias and source expertise.

RESULTS: Participants perceived the source as more expert in the 10-review rather than one-review condition; and also, more biased in the 10-review rather than one-review condition. There was no difference in any of the persuasion outcomes. Attitudes did not differ following 10 versus one review; interest in trying the restaurant did not differ following 10 versus one review; and interest in receiving future information from the source did not differ. For all three persuasion outcomes (attitudes, interest in the restaurant, interest in receiving further information), we found evidence for suppression. That is, we found a null overall effect of number of arguments on these persuasion outcomes. In addition, there was a positive indirect effect through perceived expertise and a negative indirect effect through perceived bias.

Experiment 2 replicated the ‘dual effect’ of argument quantity. First, compared to one positive review, providing 10 increased perceived expertise, which had a positive impact on persuasion. However, 10 positive reviews also triggered perceived bias, which had a negative effect on persuasion. These two competing effects suppressed each other, producing no overall benefit to offering many arguments compared to just one.

Together, Experiments 1 and 2 showed that increasing argument quantity can have conflicting effects on persuasion. Using many rather than few arguments increased perceived expertise and bias, and these perceptions had a cancelling effect on persuasion-relevant outcomes.

Our outstanding question was this: At what point does adding more arguments introduce perceived bias and offset the benefit of conveying expertise? Our third experiment addressed this question. In an online review context, we presented

participants with anywhere from one to 10 reviews and tracked perceptions of expertise and bias across all ten conditions. We also assessed participants’ perceptions of norms around posting online reviews — specifically, how many reviews are typical and how many reviews would be too many. We explored the possibility that when argument quantity exceeds the norm in a given context, the countervailing effects of source bias and expertise emerge.

One thousand and twelve participants completed our study, and 969 were included in the final analysis. Similar to Experiment 2, participants read positive reviews of a restaurant called HappyGreens. Here, the number of reviews varied from one to 10. Following the review(s), participants reported attitudes, interest in trying the restaurant, and perceived bias and expertise.

Finally, we assessed perceived norms. First, participants reported the number of reviews people generally leave on Yelp (‘In general, when someone reviews a restaurant on Yelp, how many reviews on the restaurant’s page do they leave?’). Second, they reported how many reviews would be too many (‘Sometimes people leave more than one review of the same restaurant on Yelp. How many reviews from the same reviewer seem like too many? For example, how many reviews from the same reviewer would make you feel doubt or suspicion?’). These questions, we reasoned, could help us identify the point at which adding arguments might trigger perceived bias and suppress the expertise effect on persuasion.

RESULTS: Participants perceived the source as more expert in the 10-review rather than the one-review condition, and as more biased in the 10-review condition. In terms of persuasion, there was no difference in attitudes between the ten-review and onereview condition, nor in interest in trying the restaurant.

For attitudes, while there was no overall effect of number of arguments, we did find a positive indirect effect through perceived expertise and a negative indirect effect through perceived bias. For interest in trying the restaurant, there was no overall effect of number of arguments, but there was a positive indirect effect through perceived expertise and a negative indirect effect through perceived bias

Next, we examined perceived norms to pinpoint when we

might expect the countervailing forces of bias and expertise to produce suppression. Most participants (84 per cent) reported that they would expect to see only one review from the same reviewer on a restaurant’s Yelp page. The average number of reviews that would seem like ‘too many’ was 3.32. Together, these results suggest that as the number of reviews from the same reviewer passes one and approaches three, we start to observe suppression. Thus, we conducted the same analyses described above, but instead of comparing one- and 10-review conditions, we compared one- and two-review conditions.

Here, we observed an immediate rise in both perceived expertise and perceived bias when comparing one to two reviews. Consistent with this finding, there was no difference in attitudes or interest in trying the restaurant between the one- and two-review conditions, and we found suppression effects for both outcomes. For attitudes, there was a positive indirect effect through perceived expertise and a negative indirect effect through perceived bias. For interest too, there was a positive indirect effect through perceived and a negative indirect effect through perceived bias.

Our third experiment replicated the earlier studies. Most notably, it provided a simple norms-based approach to detect the point at which adding arguments might be perceived as over-arguing. It helps establish the role of norms in shaping the inferences people draw from argument quantity. Practically, it helps persuaders gauge norms and modify their messages to avoid over-arguing their positions.

Of course, argument-quantity norms will vary across contexts. With online reviews in Experiment 3, the perceived norm was one review; providing more triggered perceived bias. In other contexts, such as writing an editorial or pitching a new idea in a meeting, norms might be higher. Normative differences should influence when increasing argument quantity no longer boosts persuasion.

Key Takeaways: Our three experiments show that providing a high rather than low number of arguments can have conflicting effects on persuasion. Presenting many arguments boosts perceived expertise, which has a positive effect on persuasion; but at the same time it builds perceived bias, which has a negative

effect on persuasion. These forces can cancel each other out, providing minimal or no benefit to offering many arguments to support one’s position.

We observed these effects in the context of online endorsements of products and restaurants, but we suspect that the same phenomenon occurs in other settings as well (e.g. when a colleague speaks up at a team meeting). Put simply, including additional arguments — even cogent ones — often yields no benefit.

In closing

Although it can be tempting to add arguments to your message to increase persuasion, as indicated herein, additional arguments can introduce perceived bias. Adding arguments comes with costs, both in terms of time (e.g. the time it takes to generate arguments) and money (e.g. adding words in a print ad can be expensive).

Our findings act as a reminder to think twice before including additional arguments in any message, even if the arguments are compelling. The trade-offs between expertise and bias can actually undo any persuasive advantage of further argumentation.

Rhia Catapano is an Assistant Professor of Marketing at the Rotman School of Management. This article has been adapted from her working paper, “15 Reasons You Should Read This Paper: How over-Arguing Increases Perceptions of Both Expertise and Bias.”

Put simply, including additional arguments — even cogent ones — often yields no benefit.

THE MICROSTRESS EFFECT: How Small Stressors Pile Up— and What to Do About It

There is a palpable crisis of well-being today. But there is also a powerful antidote: identify and eliminate some of the ‘microstresses’ in your life.

by Rob Cross and Karen Dillon

ABOUT A YEAR BEFORE THE PANDEMIC SET IN, we began to notice something about the high performers we were studying for our ongoing research. For many, their lives felt out of control or had been pushed in directions not aligned with who they set out to be. After decades of research on teamwork and collaboration, we were familiar with the kinds of stress that high performers typically endure. This, though, was completely different.

What we were hearing about was stress, yes, but in a form that neither they — nor we — had the language to articulate. As people fumbled to describe it, patterns emerged. It was never one big thing that led them to feel overwhelmed. Rather, it was the relentless accumulation of small events — in passing moments — that was drastically affecting their well-being.

We call these small pressures microstresses. But being ‘micro’ doesn’t mean they don’t take an enormous toll. We wanted to understand their impact, so between 2019 and 2021, we interviewed 300 people from 30 global companies, evenly split between women and men. Many of these high performers were powder kegs of stress, and to our surprise, most didn’t realize it. But gradually, they began to acknowledge that they were struggling to keep up, with both work and in their personal lives.

Through this research we were able to identify 14 sources of microstress that fall into three broad categories.

CATEGORY 1: Microstresses that drain your capacity to get things done.

These are why so many of us feel that we’re failing at work and in our personal lives: We can barely get through our daily responsibilities. The key sources are:

1. Uncertainty about others’ reliability

2. Unpredictable behaviour from a person in a position of authority

3. Collaborative demands that are diverse and high in volume

4. Surges in responsibilities at work or home

5. Misalignment between collaborators on roles or priorities

CATEGORY 2: Microstresses that deplete your emotional reserves.

These are disruptions to the internal ‘well’ of peace, fortitude and resilience that helps us focus, prioritize and manage conflict. The key sources are:

6. Managing and feeling responsible for the success and wellbeing of others

7. Confrontational conversations

8. Lack of trust in your network

9. People who spread stress

10. Political manoeuvering

CATEGORY 3: Microstresses that challenge your identity. These trigger the uncomfortable feeling that you’re not the person you really want to be, which can chip away at your motivation and sense of purpose. Key sources are:

11. Pressure to pursue goals out of sync with your personal values

12. Attacks on your sense of self-confidence, worth or control

13. Draining or otherwise negative interactions with family or friends

14.Disruptions to your network

Most of us experience several of these events in our day-to-day lives. We discuss each microstressor in detail in our book [The Microstress Effect: How Little Things Pile Up and Create Big Problems — And What to Do About It]. In this article we will focus on one of the most common microstresses: surges in responsibility at work and/or at home.

The High Toll of Added Responsibility

The more things you are responsible for, the more microstresses will emerge and cascade throughout discrete parts of your life in unexpected ways: having a child, moving, settling into a new job, taking on a significant volunteer project and so on.

Most of us recognize the toll these responsibilities take on our lives, and when these big transitions happen, our friends and family step up to support us. But surges in responsibility come in smaller doses, too. Unlike a major life transition, with microstress surges, we just throw the extra responsibility onto our already-full plate without thinking about the cumulative load we are carrying.

Microstresses that increase our responsibilities at work are often exacerbated by the amount of time we need to collaborate with others. At a time when we are expected to be agile, juggle multiple tasks, be part of numerous cross-functional teams and respond to real-time demands from management and customers alike, surges in work often come from seemingly simple requests that don’t factor in their complexity.

Two projects can look identical in terms of the work required, but if one involves three functional areas across two time zones, two leaders who don’t like each other and the need for resources from a unit with different priorities, that’s a very different story. Such a project entails a far greater workload than does a project with the same number of people in only one unit. Surges in responsibility create stress not only because of

the actual work but also because of the collaborative footprint of the task.

Surges also occur in our personal lives, and they don’t always come from immediate family responsibilities. Microstress can also occur when we feel the burden of responsibility for extended family members. We might need to care for aging parents, and the stress can be exacerbated when relatives who aren’t involved in your parents’ day-to-day life freely weigh in with opinions but offer no help. Of course, surges never land on an empty plate, so they cause some amount of stress purely because of the effort required to address them.

One interviewee described the burden of what she called ‘parent homework’ — the assignments children bring home from school that are far beyond their capacity to complete independently. These tasks take planning and preparation and often force parents to run out and buy last-minute supplies. And these assignments always seem to creep up on you.

For example, your child might tell you Friday night that they have a big report due Monday. But your weekend is already crammed with plans. Adding even one extra project like that onto an already full to-do list can ripple stress throughout your whole family: Your child feels stress from your impatience or frustration with the project; your spouse feels stress as you struggle to get the project done or ask them to step up to take care of it. You may cut corners at work because you’re distracted and frustrated by this parent homework that suddenly appears. And the stress continues to generate ripples.

The secondary effects of surges in responsibilities can be particularly damaging. Surges at work are bad enough, but perhaps even more painful is how they bleed into stress at home. When you’re consumed with microstress from work, you aren’t your best self at home. You may stay late at the office or bow out of family obligations, disappointing everyone in the process.

But even simply failing to give your family your full attention when you are home can profoundly affect your family’s everyday happiness. Everyone feels it. And surges at home inevitably create stress at work — either because you have to work harder or because you need to manage disparate demands of work and home life. Working late at night and very early in the morning is bad for your brain; cortisol levels increase and you’re exhausted. It’s hard to be present in ways you should be at work and at home when you’re constantly hanging on by a thread. These stresses have become so commonplace that many people live their lives as one long string of microsurges.

Surges in work stress often come from seemingly simple requests that don’t factor in their complexity.

The Ripple Effects of One Capacity-Draining Microstressor

TERTIARY RIPPLE

MICROSTRESSOR

Rita receives a late-day e-mail request from a new manager.

IMMEDIATE RIPPLE

Rita’s commute turns stressfull because of the e-mail.

Rita spends two hours of her early evening alerting her team and working on the request.

SECOND RIPPLE

Rita’s team must coordinate with each other to respond to the request.

Rita’s team logs 20 hours after work to have materials ready the next morning. Rita fields complaints from the team about the new boss.

Rita is short with her husband after the stressful commute.

To fulfill the request, Rita skips dinner with her son.

Worried about shirking her family and pressuring her team, Rita doesn’t sleep well.

Other team members endure similar microstresses.

Strategies for Pushing Back

You can’t always control what you’re asked to do, but you can control how you respond. You don’t have to default to yes: you can respond in ways that help you prevent a surge from taking over your day, your week and your life. Here are some ideas.

PUSH BACK ON UNREASONABLE DEMANDS. Before people even ask, set expectations by clarifying the unique value that you add. This way, you ensure that they don’t ask you to tackle something outside your areas of expertise. When possible, look to redirect work to someone who is in a better position to deliver on it. Be more confident in pushing back when others’ demands are unreasonable. Finally, tap into your network for authoritative opinions to support you through a surge, or into data and the backing of experts to legitimize your point of view when shifting unreasonable demands off your plate.

BE HELD ACCOUNTABLE. Have people in your life who hold you accountable for not just saying yes to every request. Even wellmeaning colleagues will take as much as you’re willing to give. Happier people tend to have others around who help them make

conscious decisions about what to give time to and what’s not worth it. The important people in your life, like your partner or other respected family members, can provide you with a kind of counterbalance when you are considering whether to jump into a major new commitment. They can help reinforce the importance of personal and family time to correct for the tendency to allow work to fill all available time.

RENEGOTIATE YOUR WORK PORTFOLIO. The moment you’re asked to handle a major surge of work, renegotiate other work demands. Instead of adding more to your workload without thinking, use that inflection point to get agreement on what can be taken off your plate or what resources you can receive to make the new request feasible.

The Top 10 Per Cent

In our research, however, we found some bright spots. A small subset of our high performers were not beaten down; harboured few regrets; were physically healthy; and had a rich life beyond work and family. The contrast between these people and the microstressed was striking. We have come to call these people

‘the 10 percenters,’ and we wanted to understand what they do differently.

While they have little in common on the surface, we observed some recurring patterns. Each 10 percenter had made deliberate choices to shape the relationships in their lives. They defined success for themselves in a broad and multidimensional way, and they held themselves accountable to it. Achieving that involves being connected to a wide variety of people, both in and out of work. And these connections, in turn, help them fend off crushing microstresses. It’s a virtuous cycle.

During our research, both of us began to adopt some of the 10 percenters practices. We can report that these efforts have made a meaningful difference to both of us. Here’s what we can all learn from these microstress masters.

• IDENTIFY OPPORTUNITIES TO PUSH BACK. Identify a few microstresses that are affecting you and come up with concrete strategies for pushing back on them. ‘Stop responding to notifications in real time’ is probably not achievable; but ‘Turn off notifications between 6 p.m. and 8 a.m.’ is both more concrete and actionable.

• CHANGE HOW YOU INTERACT WITH THE MICROSTRESS. Consider whether you are contributing to the problem in some way, perhaps without even knowing it. Even small shifts in dialogue make a difference: “What I thought of as an innocent remark,” one midlevel manager told us, “my boss heard as me questioning his ability. I changed the first word of the sentence so instead of making a statement, I was asking a question. And it altered the entire dynamics of relationship.” For this manager, ‘You don’t want us to do a quality control round?’ became ‘Do you want us to do a quality control round?’ Such subtle changes can soften an entire interaction.

• LOOK FOR OPPORTUNITIES TO RESET RELATIONSHIPS. One executive found herself paired with a difficult colleague during a training session on recognizing implicit bias. Neither thought they had any implicit bias, but the training helped both of them realize that they had subtly staked out what they thought was a moral high ground. This became an opportunity to better understand one another, taking some of the heat out of their interactions when they might disagree. Take the time to understand what might be driving rifts in relationships to overcome them. One strategy is to pivot to what another person is passionate about

in their lives— personal or professional. This often helps uncover common ground you might not have been aware of.

• DISCONNECT FROM THE STRESS. You won’t be able to push back or rise above some microstresses. So, consider distancing yourself or separating from the source of the stress entirely. That doesn’t mean you have to cut people out of your life completely. A distancing strategy can be temporary. You can decline social commitments that pull you into behaviour you don’t want, or you might recommend different non-stress-triggering ways to get together with those same friends. Meet for dinner before heading to the baseball game rather than spilling out into a local bar afterward, when alcohol-fuelled tensions inevitably lead to an argument. When you can’t see another path to minimizing or eliminating a microstress that’s taking a heavy toll, consider disconnecting.

Well-Being Is Other People

One of the most important insights we have gained from the happiest people in our research was that other people are not only critical to helping you keep microstresses in perspective, they are also essential to helping you build a full, rich life. Very few people find happiness in isolation.

Every model of happiness we’ve found makes clear that personal well-being depends on authentic personal relationships. One of the longest-running studies of adult life, what’s known as the Grant Study, followed Harvard alumni for nearly 80 years, collecting data on their physical and mental health. The study’s most significant conclusion was that the single biggest determinant of happiness and well-being over a lifetime was not fame or fortune but high quality personal relationships. Taking care of your body is always important, but tending to your relationships is a form of self-care too.

There’s an old saying that ‘if you find one true friend in your lifetime, then you have been truly blessed.’ But our research suggests that a single friend is not enough. You need a variety of relationships (not just close friends) to help you get through the reality of living in a cauldron of microstress.

Achieving well-being involves developing strategies to combat microstress and live a fulfilling life in three key areas: resilience, physical well-being and purpose. In each area, your connections with others play a critical role. The key lies with both the authenticity and the diversity of the relationships. The most significant impact comes from being connected with people

Done right, your relationships with others can become a kind of force field against the inevitable barrage of microstress.

Sample Personal Microstresses Chart

STEP 1: DEFINE YOUR SURGE:

STEP 2 : List the relationships involved in the surge

ROTATION TO NEW BUSINESS UNIT AS PART OF HIGH-POTENTIAL DEVELOPMENT PATH

• New boss

• New team

• Spouse (absorbing more responsibilities because you’re overloaded)

• Children (because you are less present for them)

CHILD SUDDENLY STRUGGLING IN SCHOOL

• Child

• Spouse

• Teacher

• Child’s siblings

STEP 3: Consider how these touch points create microstress

• Investing more time to understand role and build trust

• Spending time to understand capabilities and aspirations to learn

• Diverting any time you would spend on yourself to make up for shortfall with family

• Time spent understanding struggle with child (and discussing with spouse)

• Interactions with teacher to assess concerns and plot path forward

• Time taken from child’s siblings

STEP 4: Figure out ways to mitigate

• Tactically focus on behaviours that build competence and benevolent trust

• Leverage former leader’s expertise to understand team

• Secure extra help at home (e.g. cleaner and grocery service) to create time for surge

• Engage in discussions as a full family to diagnose problems and create a supportive environment

• Ask teacher to provide more timely feedback

• Secure tutor for support and to separate this role from parenting role FIGURE

who unite around some interests — religion, singing, tennis or activism, for example — but who come from different career, socio-economic, educational or age groups. The shared interests tend to create authentic and trusted interactions, and the diversity of perspectives helps expand the way we see the world and our place in it. And yet in spite of how important relationships are to our happiness, too many of us let them slip as the years roll by.

People who told us positive life stories invariably described authentic connections with two, three or four groups outside of work: athletic pursuits, volunteer work, civic or religious communities, book or dinner clubs and so on. Often, one of the groups supported physical health — through nutrition, mindfulness or exercise practices. They were sometimes surprising relationships that might seem improbable; but they provided something meaningful.

The 10 percenters we met consciously build meaningful connections with other people into their day-to-day lives in ways that helps them rise above much of the noise of microstress and focus on what matters most to them. To be clear, this group wasn’t necessarily extroverts who found time to keep up with a wide range of friends and social connections. The common thread was dimensionality — building and maintaining connections with a variety of people, often in small ways.

Done right, your relationships with others can become a kind of force field against the inevitable barrage of microstress.

But meaningful relationships require you to take deliberate actions daily. What’s more, at critical transition periods in your life, you need to maintain these relationships even more, so you don’t default into a defensive posture, become one-dimensional and simply absorb all the stress coming at you.

In closing

Social science research shows that a negative interaction has up to five times more impact on us than a positive one. All of us are flooded daily with microstresses that we don’t even recognize. Think of the impact you can have by identifying and correcting even one or two of the microstresses in your everyday life. Better still, think of the effect of creating some new, positive interactions with people who will add purpose and growth to your life. The reality is, in today’s interconnected world, we’ve never had more opportunities to shape what we do and whom we do it with.

Rob Cross is the Edward A. Madden Professor of Global Leadership at Babson College and the Co-founder and Director of the Connected Commons. Karen Dillon is a former editor of Harvard Business Review. They are co-authors of The Microstress Effect: How Little Things Pile Up and Create Big Problems — and What to Do About It (Harvard Business Review Press, 2023).

CORPORATE FRAUD: IT’S MORE PREVALENT THAN YOU THINK

by Alexander Dyck

IT’S A TALE AS OLD AS TIME — or at least, as old as the history of public companies. Shareholders want and expect companies to maximize shareholder value. But the risks involved in public ownership are many, and one of the most widely recognized is ‘agency costs.’

In any relationship between a ‘principal’ and an ‘agent’, the agent is given powers to make decisions on behalf of the principal. Examples include shareholders (principal) vs. management (agent); voters (principal) vs. politicians (agent); and financial institutions (principal) vs. rating agencies (agent).

The root of principle-agent problems is the fact that the two parties often have different incentives and generally, the agent has more information. In most cases, the principal cannot directly ensure that its agent is always acting in its best interests, and this potential divergence in interests is what gives rise to agency costs.

While copious research has documented the agency costs of public ownership, one of the less studied of these costs has been corporate fraud. Fraud occurs whenever management makes decisions that are not in the best interests of shareholders but instead, benefit themselves. To enrich themselves, some individuals are willing to break the law for their own financial gain via asset misappropriation, financial statement fraud or bribery and corruption.

The question is, how widespread is fraudulent behaviour? Is it a major or minor component of the agency costs of public ownership? The frauds we observe, where firms settle cases with securities regulators or private plaintiffs, provide on indication of the scope of the problem. But are these publicly observable frauds the entire iceberg — or just its visible tip? In a recent paper published in the Review of Accounting Studies, Adair Morse (University of California/Berkeley), Luigi Zingales (University

Fraudulent behaviour by corporations is much more common than you might think. Indeed, the stories in the media are just the tip of the iceberg.

of Chicago) and I set out to answer these questions by studying what is widely believed to be the biggest audit failure in U.S. history. On October 22, 2001, Enron acknowledged an inquiry by the Securities and Exchange Commission (SEC) concerning possible conflicts of interest in various partnerships. Things went downhill very quickly: On December 2nd, Enron declared bankruptcy, and one month later, a criminal investigation into its accounting practices began. Former executives Kenneth Lay and Jeffrey Skilling were eventually convicted of conspiracy to commit securities and wire fraud. The verdict put the blame for the demise of what was once the nation’s seventhlargest company squarely on its top two executives.

But who was supposed to be keeping an eye on Enron’s books throughout this period? Arthur Andersen (AA). In addition to Enron, AA was the auditor of record for roughly one-fifth of all large publicly-traded firms at the time. To the surprise of no one, its own demise was swift: Details of its questionable accounting practices for Enron (and soon after, telecom giant Worldcom) were revealed and in August of 2002, AA collapsed.

Naturally, an extreme cloud of suspicion would surround former AA clients. What might they be getting away with? Auditing firms who took on these clients had strong incentives to uncover any fraud being committed — and these incentives were shared by many, including bystanders, the media and investors worldwide. All told, this period in business history provided an ideal scenario for us to analyze the prevalence of corporate fraud. In this article I will share our key findings.

Our Research

We adopted the definition of fraud in Securities Law, where fraud requires the presence of three elements: misrepresentation, materiality and intent. All of the frauds we focused on were examples of misrepresentation and they were material as they involved multi-million dollar settlements. There was enough indication of intent such that the cases were not dismissed, but intent can only be proven in court. And all these alleged fraud cases are settled before they reach the final verdict, since directors’ and officers’ insurance does not indemnify executives if they are convicted in court. As a result, all the corporate fraud I discuss here is alleged fraud that was settled out of court. Specifically, we allow the reader to choose among four fraud definitions, and used the Arthur Anderson demise to shine light on

how much more fraud is lying beneath the surface for each of these definitions.

AUDITOR-EXPOSED FINANCIAL MISREPRESENTATION. To detect this we started with the SEC’s dataset of class actions suits. To ensure comprehensiveness, the DMZ dataset focuses on large firms (those with over US$750 million in assets) so that a potential payoff from a suit would be sufficiently attractive to mobilize monitoring by legal actors.

FINANCIAL MISREPRESENTATION THAT LED TO ENFORCEMENT BY THE SEC. Since 1982, the SEC has issued Accounting and Auditing Enforcement Releases (AAERs) during or at the conclusion of an investigation against a company, an auditor or an officer for alleged accounting or auditing misconduct.

RESTATEMENTS OF FINANCIAL RESULTS. To obtain this information we started from the most widely employed data on restatements: the Audit Analytics database. We then used the Audit Analytics classification to separate clerical errors from intentional implementation of misstatements.

SEC SECURITIES FRAUD CASES. While all these cases arise from some material misstatements or omissions in providing material information, they also include non-auditing-related misrepresentations.

The data for our research were monthly and spanned from 1997 (four years pre-Enron) to 2005 (four years post-Enron.) We defined a company as having AA as an auditor if AA had signed a financial report anytime in the calendar year 2001, irrespective of the firm’s fiscal year. All companies without AA as auditor during this period were ‘non-AA clients’. We considered that a fraud was revealed during the detection period if the fraud started before the watershed date of November 30, 2001, and came to light between the watershed date and the end of 2003 (the detection period).

Not surprisingly, the prevalence of detected fraud depends upon its definition. Over the business cycle, at any point in time, an average of 13 per cent of public firms will issue a restatement, three to four per cent of firms per year will have an AAER or class action case with a multi-million dollar settlement (SCAC), and zero to one per cent of firms per year will have an auditor-

A substantial amount of corporate fraud goes undetected.

detected fraud. If this was all there was to fraud, it is likely you would not view the situation as alarming.

What the Andersen demise showed us is that detected fraud measures significantly undercount fraud. Auditor scrutiny was clearly affected by the demise of Andersen. In former AA clients we found three times as many auditor-detected frauds and three times as many restatements as in firms that were not forced to change their auditor. We found similarly significant increases in fraud in former Andersen clients when we looked at AAERs and SCACs — although somewhat less in magnitude, which is not surprising as the Andersen demise didn’t change SEC budgets. Our takeaway is that detection likelihood in ‘normal times’ averages 33 per cent, with frauds below the surface being twice as large as those we ordinarily detect.

Having come up with an estimate of detection likelihood, we were in a position to provide an estimate of how much fraud there is in U.S. capital markets. As the baseline level of detected fraud, we used the approximately 3.3 per cent of firms per year that had detected securities fraud (SCACs). To this we added the undetected fraud — which is twice the level of detected fraud, or 6.7 per cent of firms per year. Thus, we concluded that 10 per cent of large corporations were committing a misrepresentation, information omission or other misconduct that could lead to an alleged securities fraud claim.

By using the AAER measure, we arrived at a similar estimate: 8 per cent of fraud pervasiveness. This magnitude was similar to the SCAC estimate, even though AAERs have lower observed frequencies because their existence requires the SEC to act. Recall that the SEC failed to act on Madoff despite six substantive complaints.

Accounting violations — less severe than alleged securities fraud — were far more prevalent, with an average annual pervasiveness of 41 per cent. We do not want to conclude from this estimate that each year, 41 per cent of large corporations commit a severe misreporting. To reach this conclusion we would need some more substantive filters to eliminate inconsequential misreporting. Nevertheless, this estimate does not bode well for the U.S. auditing system.

The High Cost of Fraud

The finding that 10 per cent of large corporations are committing fraud at any one time does not necessarily imply that the economic cost of fraud is large. To draw that conclusion, we

needed to estimate the cost of these corporate frauds. As in the prior literature, we focused on the cost of fraud borne by equity holders of the firms involved, ignoring other potential losses (e.g. loss in debt value, loss of employee pensions and jobs, loss of customer prepayments, loss of taxes owed) and spillover costs borne by competitors.

Prior research has estimated the ‘reputational loss’ of detected fraud at 25 per cent of the equity value of the fraudulent firm. This cost, which is almost entirely due to a loss in reputation, represents the present value of the decline in expected cash flows as firms’ investors, suppliers and customers change the terms by which they interact with a fraudulent firm.

Notably, KLM’s cost estimates are for detected fraud and do not necessarily apply to undetected fraud. But even when a fraud is not yet in the public domain, the firm incurs costs for two reasons. First, the fraud is unlikely to remain a secret for customers and employees, who will seek business relationships or employment elsewhere, demand a premium to remain — or take advantage of the fraud themselves. For example, Bernie Madoff employees like Frank Di Pasquale were lavishly paid to ensure their silence. In addition, they stole money for themselves.

Second, the biggest cost is often in the cover-up. For 20 years, the Japanese company Olympus was able to hide a $730 million financial loss from 1990 with a series of bad acquisitions and accounting tricks. Those bad acquisitions alone cost $300 million. It is hard to put a number on these costs. But if we assume that, at least in the medium term, the stock market is strong-form efficient, the abnormal low returns of companies that are likely to have committed a fraud but were never exposed can provide an estimate of these hidden costs.

In one study, researchers did this. They compared the annual buy-and-hold return of firms with a high probM score with that of firms with a low probM score. After controlling for a four-factor model, they estimated an annual 10.9 per cent difference in returns.

We took this underperformance as an estimate of the costs of undetected fraud, and were now in a position to compute the total cost of fraud. As indicated, our estimates suggested that 10 per cent of firms were committing fraud at any one time. If the detected fraud costs 10.9 per cent, the cost of an average fraud was 15.6 per cent of a firms’ market capitalization.

Thus, the cost of fraud is 1.6 per cent of a firm’s equity

value per year: fraud pervasiveness (10%) multiplied by the loss of market capitalization for an average firm in case of fraud (15.6%).

In 2004, the total capitalization of the U.S. equity market was $16 trillion. Since, on average, 10 per cent of firms were engaged in fraud at the time, the annual cost was $254 billion a year. If we repeat the calculation at the end of 2021, the expected annual cost would have been $830 billion.

In closing

The sudden demise of one of the world’s most successful auditing firms allowed my colleagues and I to determine the frac-

tion of corporate fraud that goes undetected. The news was not good: We found that two out of three corporate frauds go undetected, implying that prior to the 2002 implementation of Sarbanes Oxley (SOX), 41 per cent of large public firms were misreporting their financial accounts in a material way and 10 per cent were committing securities fraud, imposing an annual cost of $254 billion on investors.

These figures project a dismal picture of the effectiveness of financial auditing pre-SOX. Whether that federal act has succeeded in reducing the problem was beyond the scope of our research. Yet, the magnitude of the problem we identified suggests that strong action was indeed warranted. Based on our

The Rise of External Fraud by Jennie Chan and Edward Matley

On the global stage, and right here in Canada, rising environmental, geopolitical, financial and social pressures are creating a risk landscape that is more volatile than ever. Even as organizations act quickly to navigate change, bad actors look to exploit the potentially widening cracks in fraud defences.

As a business leader, you must ask yourself: Are sufficient controls in place for the myriad new business processes and digital technologies being deployed?

This year’s Global Economic Crime and Fraud Survey conducted by PwC shows that organizations’ perimeters are increasingly vulnerable, and external fraudsters are emerging as an even bigger threat. Our survey examined organizations’ attitudes toward fraud and financial and economic crime in the current environment, with polls being conducted at two different times (May and June 2022), in total surveying 2,319 people in 68 countries.

Our key finding: New risks have emerged related to supply chain disruptions and ESG. On a global scale, just 51 per cent of the organizations that we surveyed reported experiencing some form of fraud or other economic crime within the last 24 months. But in Canada, that number was higher, at 60 per cent. And although many Canadian organizations have invested large amounts of resources to fight financial crimes and prevent and detect fraud, new threats and perpetrators continue to emerge.

Organizations, however, are getting better at detection: In Canada, the rate of fraud detected through advanced data analytics is nine per cent higher than the global average; the ‘suspicious activity’ monitoring detection rate is seven per cent higher than the global average; and external audits are six per cent higher than the global average.

So what’s ahead for Canadian business leaders? These are the three main areas to focus on.

1. Fraud-prevention measures work. Despite the rising risks on the global stage — from the pandemic, supply chain issues, environmental and geopolitical instability, an uncertain economy and a talent shortage — no significant increase has appeared

in fraud, corruption and economic crime rates since 2018. In Canada, however, the rates of fraud have risen, and it’s important for business leaders to remember that fraud is expensive. It hits the bottom line, leaving less money to redistribute to stakeholders, improve employee conditions or invest in innovation. In the future, it will be wise for organizations not to underestimate the cost of fraud versus the cost of investing in better controls to prevent and detect fraud.

2. Threats are changing, so protecting the perimeter has to change. Our survey identified an unsettling threat profile emerging. Dangerous new predators — external entities, including cyber threat actors and organized crime rings — that can’t be controlled or easily influenced are quickly growing in strength and effectiveness. Nearly 70 per cent of organizations surveyed around the world that reported experiencing fraud also reported that the most disruptive incident came via an external attack or collusion between external and internal sources. This is because external fraudsters (e.g. cyber threat actors) are immune to traditional fraud prevention tools such as codes of conduct, training and investigations.

3. ESG reporting, supply chain disruptions and the rise of more connected enterprise-wide digital systems increase fraud risks. In general, Canadian organizations reported slightly fewer concerns about ESG challenges, as compared with global respondents, but they all face similar challenges in this area. Canadian organizations’ greatest concerns involved three issues:

• 49 per cent of respondents reported concern about their inability to prevent or detect misconduct related to ESG risk (compared with 37 per cent globally.)

• 48 per cent reported concern about their inability to accurately monitor or report ESG metrics of third-party business partners (compared with 42 per cent globally.)

estimates, if the new regulation reduced the probability of starting a fraud by 10 per cent, its cost — estimated at $3.8 million per firm, on average — would be fully justified.

• 42 per cent reported concern about their inability to accurately monitor or report ESG metrics within their organization (compared with 40 per cent globally.)

When it comes to the future of fraud, we expect to see more risks coming from the enterprise-wide digital systems (i.e. platforms) that organizations rely on today. The rise of digital platforms such as social media, e-commerce or services (for example, ride-sharing or lodging), opens the door to myriad fraud and other economic crime risks that most companies are just beginning to understand.

Here are three considerations to help you build resiliency for the future:

Understand the end-to-end life cycle of customer-facing products. Identify where opportunities exist for a fraudster to exploit customer-facing products and cause financial, legal or reputational damage.

Strike the proper balance between user experience and fraud controls. Through the right combination of fraud technology, strategy and processes, both a good user experience and effective fraud controls are achievable.

Orchestrate data. Consolidate data from disparate, disconnected systems into a centralized platform that can track the end-to-end life cycle of users, including fraudsters, and generate meaningful alerts.

Looking ahead, business leaders will need to prioritize humanled, tech-powered solutions when it comes to fraud prevention and detection. Putting people at the heart of decision-making is a critical way to build trust and create culture change, thereby adding value across the organization and driving better business outcomes.

Alexander Dyck is a Professor of Finance and Economic Analysis and Policy at the Rotman School of Management, where he holds the Manulife Financial Chair in Financial Services.

Jennie Chan and Edward Matley represent PwC’s Crisis Team in Canada.

What Are Your Management Operating Principles?

WHETHER YOU’VE HEARD THE TERM OR NOT, you’ve probably already formed many of your own ‘management operating principles’ — the guidelines you use to make decisions and get work done. Knowing and understanding how these ‘guardrails’ influence your work can make you a better leader.

Over time, I have refined the backbone of how I lead into four key principles, and I believe they form the foundation of my success:

1. Build self-awareness to build mutual awareness.

2. Say the thing you think you cannot say.

3. Distinguish between management and leadership.

4. Come back to the operating system.

These principles are about one thing: building trust. If you’re not self-aware, how can others trust your feedback about their own abilities and behaviour? If you’re not direct with your opinions and judgments, how will people know where

they stand? If you’re not clear on whether you’re managing to a defined goal or charting an entirely new vision, how will your team trust that you’re leading them to success? And if you don’t maintain a foundation of consistency, how will those around you know what to expect? Let’s take a deeper dive into each of the four principles.

PRINCIPLE 1: Build self-awareness to build mutual awareness

Self-awareness is the key to great management. The other three operating principles are much more about functioning in the moment, but this is the one that underpins them all. Self-awareness has three components:

UNDERSTAND YOUR VALUES. At Google, I worked with a manager whom I’ll call Eli. His reports liked working for him, his teams delivered results and he cared a lot about the company. Eli was a good manager. But we had a problem: He told his team everything.

Identifying and understanding the personal ‘guardrails’ that influence your work and management style can make you a better leader.

by Claire Hughes Johnson

What do you do reallywell? Which skills do you already have, and which do you need to build?

When we were planning a divisional change that would affect many teams, he informed his reports early, making other managers look uncommunicative. When we were working on a new compensation process, he told his reports and introduced uncertainty into the team’s dynamic, letting his fears guide his language with announcements like “It’s a mess and we don’t know our compensation plan yet, so I’m totally stressed.” His reports started to feel anxious about the process and rejected it before they’d had an opportunity to learn how it might benefit them.

Eli and I had a couple of difficult sessions to discuss his behaviour. In each meeting, he agreed with my assessment of his behaviour, but as soon as he left the room he would revert to his habits. I felt stuck.

Not long after one of these frustrating conversations, my HR partner helped me organize a training session for my division with Stan Slap, the author of Bury My Heart at Conference Room B. Stan led us through a session on values in which he asked all of us to reflect on the values that were important to us and where we thought they came from. He invited participants to come on stage, in front of hundreds of other managers, to share one of those core values.

Eli raised his hand. This was the story he told: When he was around seven or eight, his mom fell very ill. Later, he would learn that she had breast cancer, but at the time, no one in his family told him what was going on. They wanted to keep things as normal as possible. Of course, things were far from normal, and Eli noticed that his mother was not herself, physically or emotionally. Her condition deteriorated, and she eventually had to go to the hospital. Eli was not allowed to visit her. One day, Eli’s stepdad came to pick him up from school. They drove to his favourite diner and ordered pancakes. While Eli poked at his pancakes, his stepdad told him that his mom had died.

Eli’s core value was transparency. That story has stuck with me for a long time, particularly the two lessons I took from it. First, you never know someone else’s story. When you’re finding a direct report difficult to work with, there’s almost always a deeper reason for their behaviour that’s worth trying to understand. Second, some people don’t necessarily understand why they act the way they do. If you don’t understand how your

actions are driven by your underlying beliefs, you’ll never be able to adapt them, no matter how hard you try.

Eli knew that his lack of discretion was making it harder for his team to operate and also sometimes harmed the division. He wanted to do better, but at the same time, withholding information from them felt like betraying his commitment to transparency.

Once Eli became aware of this value and was able to share it with others, we were able to talk about every situation at a meta level. We could negotiate what felt right and appropriate for him to share with his team and his division. By building selfawareness, he was able to contribute to the dynamic of mutual awareness that makes managers — and their reports, teams and divisions — work successfully. Ultimately, Eli realized that he needed to consult his peers and his manager before he shared critical decisions, and that being thoughtful about communication was a way of caring in and of itself.

Understanding what is most important to you will help you make sense of how you work, what gives you energy (and what saps it) and what might trigger an outsized reaction. With these insights, you’ll be able to express your values and understand when they are at odds with someone else’s. When you get frustrated, you’ll be more open to the possibility that your own values are making you a ‘blocker.’ Then, you can develop a path forward, as Eli did.

IDENTIFY YOUR WORKSTYLE PREFERENCES. If you spend even just a few weeks writing down the moments when you feel most energized and when you feel drained, you’ll start to see patterns. Most workstyle assessments plot you and your team on a continuum from ‘introverted’ to ‘extroverted’ and from ‘taskoriented’ to ‘people-oriented.’ Common ones include DiSC (which stands for dominance, influence, steadiness and conscientiousness) and the widely used Myers-Briggs Type Indicator (MBTI), which helps identify 16 different personality types and is based on the work of Carl Jung.

My personal favourite assessment is Insights Discovery, which quickly builds a strong vocabulary for certain behaviours within a team. The assessment puts you into one of four coloured quadrants of a circle: red, yellow, green or blue

The Insights Discovery® Framework

cautious precise deliberate questioning formal caring encouraging sharing patient relaxed

competitive demanding determined strong-willed purposeful sociable dynamic demonstrative enthusiastic persuasive

COOLBLUE FIERYRED EARTHGREEN SUNSHINEYELLOW

The order and strength of the four colour energies in each participant generates eight types:

Director | Extraverted Thinking | Results focus, decisive, assertive

Motivator | Extraverted Intuition | Drive, enthusiasm, positive thinking

Inspirer | Extraverted Feeling | Persuasive, creative, people skills

Helper | Introverted Intuition with Extraverted Sensing | Flexible and helps others, shares ideas

Supporter | Introverted Feelings | Listens, loyal, team approach

Coordinator | Introverted Sensing | Planning, organizing, time management

Observer | Introverted Thinking | Sets standards, product knowledge, analysis

Reformer | Extroverted Sensing with Introverted Intuition | Determination, monitoring performance

Courtesy of The Insights Group

(see Figure One.) Your placement with respect to the centre of the circle depends on the strength of your preference. The results also indicate how much you dial your behaviours up or down at home versus at work.

For me, the biggest insight was that my preferred style (green, near the border with yellow, in the ‘supporter’ category) is closely followed by the opposite style on the wheel (red, or ‘director’), which is apparently somewhat unusual. These insights gave me the language to articulate what I think is (largely) a strength of mine: I love to get things done, but I do so via process and people, whereas other leaders who have a lot of red in their charts do so more via assigning tasks or just doing the work themselves.

ANALYZE YOUR SKILLS AND CAPABILITIES. Once you can articulate your core values and workstyle preferences, you can get down

to the more tactical version of self-awareness by asking yourself two sets of questions:

1. What do you do really well? Which skills do you already have, and which ones do you need to build?

2. What are your capabilities? What are you naturally good at, and which capabilities have you acquired over time?

Skills are quite tactical: whether you can use HTML, build a financial model in a spreadsheet or create a detailed marketing campaign. At a slightly higher level, they also encompass abilities, like whether you can break down a business problem and write a strategy. But they’re all fairly binary: ‘Yes, I have done this’ or ‘No, I haven’t done that.’ Take inventory of what skills you need for your role, what you know how to do and what you need to learn in order to identify any gaps and make a plan to fill them.

Capabilities (also called competencies) are a step above a pure skill. They’re more about an innate ability to use a particular set of skills in a given situation. For example, my tactical analytical skills are not particularly strong. Although I learned how to build a financial model in business school, I wouldn’t trust myself to build a good enough one to base a decision on. But my analytical capabilities are strong. I’ve been told that I can absorb a lot of data and opinions and quite quickly synthesize all the elements to identify the decision that needs to be made.

Consider managing internal and external communications for a company in a crisis. This takes skill, yes, but also instincts and pattern-matching to past events, both of which allow you to handle any issue that might arise, even if it’s a new one. Your skills might include project management and writing talking points for a leader. Your capabilities might include the ability to manage stakeholders, assess risk and make sound judgments on communication strategy in high-pressure situations.

Your strengths are the sum of your skills and capabilities — which is why both skills and capabilities come up in conversations about strengths and weaknesses. For example, when asked about an area for development, one of my reports might say, ‘I want to write better e-mails.’ When I ask why, they might answer that their team has grown to a size that requires them to have stronger communication skills. Because e-mail is the primary method of communication for them, they’re all working on that skill. But as they do that, they’re also building leadership communication capabilities. Both are important, but it’s the capability that really fosters growth, because it can be translated and repurposed into other forms of communication.

PRINCIPLE 2: Say the thing you think you cannot say

How often have you sat in a meeting and mused, ‘It really feels like there’s something that isn’t being talked about right now’? Or had a conversation with a report and thought, ‘I think they’re getting upset about what I’m saying’? These questions prompt a bigger one: ‘Why don’t managers say what is actually on their minds?’

People often think good management is about having a lot of filters, and for good reason. There’s a lot that might feel risky to say, or that feels like a personal judgment. But be wary

of over-filtering. Following are three tactics I’ve found useful in this regard.

SHARE YOUR FEELINGS. Everyone has emotions, which makes them a powerful management tool. We all know what it feels like to be worried or overloaded. Sharing a feeling with your team can quickly contextualize the importance of your statement. If you say, ‘We didn’t hit our target,’ you haven’t offered any comment on the gravity of the situation. On the other hand, if you say, ‘We didn’t hit our target, and I’m worried about the impact this will have on our team and on the business,’ the team will immediately understand that there is a problem that demands attention.

BE MEASURED. On the other hand, imagine how your team would react if you said, ‘I’m freaking out because we didn’t hit our target.’ People might start to feel panicked, which would impede your ability to move necessary work forward. In the example I shared earlier, Eli was honest about what was going on in the division and how it made him feel (“It’s a mess; I’m totally stressed”), but he failed to deliver the information and feelings in a measured way, which destabilized his team.

SEPARATE THE PERSON FROM THE IDEA OR TASK. Always make the distinction between who someone is and what they did. I once had a coach who observed that criticism and risky observations often feel oppositional — when in fact it’s very powerful to stand next to someone and look at the same thing and make observations together. Think about the difference between saying ‘That presentation was terrible,’ prompting the other person to feel defensive about whatever role they played in it, versus ‘What did you think of the presentation? I was disappointed in aspects of it and would love to hear what you thought.’

I understand why a lot of managers don’t say what they think. Sometimes management can feel like a balancing act in a gymnastics competition: Take one step to the right and you’ve shared too much; take one to the left and you’re unapproachable. But learning to constructively express the closest thing to your truth helps you keep your balance. It feels highstakes, because it is; but honing this ability will help you land the dismount: building trust.

Understanding the distinction between management and leadership has proved invaluable in my career.

The payoff will be enormous, because it will strengthen your whole team. Teams where people can say what’s on their minds will raise and resolve problems much more quickly. They’ll also be happier, since they won’t be suppressing thoughts and feelings about their work. More importantly, being more open and direct, yet always constructive, will earn you the one-to-one trust that is critical to an effective relationship with direct reports.

PRINCIPLE 3: Distinguish between management and leadership

Great leaders put forth a vision and set lofty goals that inspire others to forge ahead. Even when the path isn’t always clear, the clarity of their vision keeps everyone focused on the big picture and sustains participation and motivation. Leaders don’t have to be managers, but if they aren’t, they need to know how to work with and hire managers to build the right teams to execute the vision.

Management is all about human-centric execution. Great managers know how to define goals and set operational cadences, all while helping each report have a clear view of their current performance and future career aspirations. Teams with great managers have a high level of trust, experience the challenge and reward of hard work, and feel like they’re making progress both as individuals and as a team. Great managers don’t initially have to be great leaders, but the more senior they become, the more important it is that they also develop leadership skills. Eventually, managers need to be able to set a vision and direction for their team — and potentially make the team uncomfortable with a bit of heat — or they’ll hit a ceiling in their careers.

Understanding the distinction between management and leadership has proved invaluable in my career. It has helped me retain high performers I might have been tempted to promote into management but who I recognized could be much more effective as leaders in non-manager roles. It has also helped me push myself and others to develop beyond technical problem management and into the adaptive leadership zone.

I recently coached a talented up-and-coming product marketing leader at Stripe who kept running up against the challenge of syncing her team’s work with the company’s everchanging product roadmap. We spent a whole one-on-one talking about solutions, at the end of which I observed that there would never be a one-and-done fix for the issue. Instead, she would need to continually adapt her approach and push the product team to adapt theirs. The realization that this situation called for leadership via influence and careful communication, rather than building the perfect process, freed her from seeking the perfect answer.

Experienced employees mostly need a leader and just a bit of a manager. If they’ve made it to a certain point in their careers, they’re probably good at getting their work done. But they’ll look to a leader to lay out the overarching vision and the milestones they should be working towards, and to pave the way for progress within the systems that operate outside of the team.

PRINCIPLE 4: Come back to your operating system

It was only recently that I was able to articulate this as an actual guiding principle. In 2018, I was leaving a conference in Colorado when bad weather prompted a huge number of flight cancellations. I ended up problem-solving a trip home with a venture capitalist and a banker who were seated nearby, forming what we jokingly called our ‘escape syndicate.’ Our solution involved chartering a small plane (luckily for me, paid for mostly by the other syndicate members) to get back to the Bay Area. Trapped as we were for hours in the airport, and then on the flight, we traded stories.

The banker, who has worked with many successful companies as they’ve gone public, said that he has a favourite question he asks the CEOs and leaders he gets to know: What is your secret power? I thought for a minute and realized what my own secret power is: The ability to build a repeatable operating system for every team I manage. They each have the same components: a clear mission, stated goals, metrics that matter, similar meeting structures, and weekly and quarterly cadences. That means that as a leader, I can switch contexts seamlessly.

When I started managing multiple teams at Google, I felt overwhelmed by the constant context-switching. Creating a common ‘user interface’ for all of them made things much easier. Just as it did for me, a common operating approach with the same core elements across all of your teams will give you a ‘management shortcut’ of sorts.

Your system, like mine, will be based on the rhythms of how you operate: quarterly goals, metrics review meetings on Mondays, team meetings on Tuesdays, weekly one-to-ones, offsites for big-picture thinking and so on. Teams and companies vary, but these fundamental approaches create stability.

In closing

Building self-awareness, saying the thing you think you cannot say and knowing when to be a manager versus a leader are all fundamental principles of great management. But none of them describe how you will drive results. It is the combination of your team environment and the team’s execution that will produce great results. But for that to happen, in my experience, you need to operate within a framework of core principles.

Claire Hughes Johnson is a Corporate Officer and Advisor at Stripe. Previously, she was its Chief Operating Officer, helping the company grow from fewer than 200 employees to more than 8,000. She spent 10 years at Google, overseeing aspects of Gmail, Google Apps and consumer operations, as well as serving as a vice president for AdWords, Google Offers and Google’s selfdriving car project. She serves on the boards of Ameresco, The Atlantic, Aurora Innovation and HubSpot.

Creating Value From Data: A MONETIZATION FRAMEWORK

Three approaches to data monetization can help every organization ensure that its data investments pay off.

by Barbara H. Wixom, Cynthia M. Beath and Leslie Owens

AS A BASIC BUSINESS PRINCIPLE, every organization should generate more money from its data than it invests in producing and managing it. Yet the idea of turning data into money is often associated with sneaky tactics or ‘going too far’ with unacceptable exploitation of data. As a result, some organizations, especially noncommercial ones, have little appetite for the term ‘data monetization.’ We believe in neutralizing the heat around the term. It helps to have clear, shared language that more people can use in discourse and debate.

We use the term ‘data monetization’ to convey the concept of generating financial returns from data. Most people immediately think of selling data as the only viable approach, but in fact, there are two additional approaches that your organization may already engage in but not consider within the rubric of data monetization: improving work and wrapping products with datafuelled features and experiences.

Each approach uses data differently and has an ideal ‘owner,’ a particular set of risks to mitigate unique outcomes. Orga-

nizations can use one, two or all three approaches to make sure data contributes to their bottom line:

IMPROVING uses data to create efficiencies in work for cheaper or faster operations;

WRAPPING uses data to enhance products such that customers want to buy more or are willing to pay more; and

SELLING is the exchange of an information solution for some form of money.

Recognizing what makes the three approaches different is crucially important; trying to run a selling initiative as if it were an improving initiative can be disastrous. It would be like fixing a kitchen appliance with the tools, talent and expertise needed for landscaping the yard. Organizations that understand the distinct requirements of each data monetization approach can make the right investments, set realistic expectations and generate optimal returns. Let’s take a closer look at each approach.

STRATEGY 1: Improving. This is the most common way for organizations to monetize data, and examples abound. The United Parcel Service (UPS) used vehicle route data to optimize delivery routes to save US$400 million annually. Columbia Sportswear used historical package-tracking data to eliminate root cause issues in their supply chain. This decreased both outof-stock and overstocking problems, saving more than US$27 million in inventory costs. Trinity Health used data from smart hospital beds to speed up nurse response time by 57 per cent. Leaders at Trinity Health associated the nurse response time improvement with a reduction in patient falls, likely decreasing the cost of patient care.

Most organizations have experience using data to improve business processes and work tasks. Many were inspired by the Business Process Reengineering (BPR) movement in the 1990s that encouraged organizations to analyze and design efficient workflows and business processes. To execute BPR, organizations applied technology to clean data and boost its availability. The data was then used to analyze the root cause of process slowdowns, to measure the benefits of moving from an old way of work to a new, more radical way and to monitor and manage critical process metrics.

The BPR movement convinced many organizations of the benefits of data-driven process or task improvements. But a negative result of this movement was that many organizations got in the habit of assuming that the benefits of process improvement would make their way to their bottom lines. In fact, it takes organizational attention, resources and discipline for financial value to materialize from efforts like those at UPS, Columbia Sportswear and Trinity Health.

Quantifying the outcome from improving takes two steps. First, organizations need to measure the uplift in efficiencies or quality that result from improving with data. Second, they must remove or redirect the slack created by those efficiencies or productivity improvements.

Some complications make the value of efficiencies hard to turn into money: sometimes, an improvement in one process creates efficiencies in downstream processes; or slack created by an improvement is used to relieve overworked or stressed employees; or efficiencies gained in a process show up in increased production or reduced inventory rather than slack. But if an improvement is supposed to reduce costs or budgets and they don’t change, data is not being monetized.

STRATEGY 2 : Wrapping. Wrapping initiatives create datafuelled features and experiences to increase the customer value proposition of a product. When we say ‘product,’ we are referring to the thing an organization delivers to a customer that satisfies their needs. This might be a good or a service, it might be virtual or physical, or some combination of all of these.

To realize some of the value created by an enhanced product, the organization must raise the product’s price or sell more of it. ‘Selling more’ could mean selling more units of the same offering to an existing customer, selling more related offerings, selling to additional customers or sustaining sales of a product whose sales are eroding.

Opportunities to ‘wrap’ products are everywhere; just look around at the surge in connected devices and the new personalized ways organizations engage with customers. Examples include adding information to offerings in the form of reports, alerts, scores, visualizations or dashboards that complement or enhance the offering and make it more appealing to customers.

The wrapping approach to data monetization creates distinctive offerings in the marketplace. Consider Schindler, an elevator maker. The company complements its elevators with an equipment performance dashboard to help building managers monitor elevator performance. Intergovernmental organizations like the World Bank provide portals for contributing governments to show them that their donations are achieving their desired philanthropic goals. Healthcare insurers add

‘Wrapping’ initiatives create data-fuelled features that increase the customer value proposition.

Three Approaches to Data Monetization

Improving

Wrapping

Selling

VALUE-CREATION PROCESS:

Data creates efficiencies (and thus ‘slack’) by making operational processes or tasks better, faster and cheaper

Data enhances the customer value proposition of products

Data is commercialized and sold in the form of information solutions

VALUE-REALIZATION PROCESS:

MEASURE VALUE REALIZATION VIA:

WHO IS ACCOUNTABLE FOR OUTCOMES:

KEY RISKS:

Slack is elimated or redirected

Impact on the bottom line

Process owner

Lack of action-taking and value creation

Customers pay more or buy more

Impact on the bottom line

Product owner

Negative impact on customer value proposition when a wrap falls short

New revenue streams are generated

Impact on the bottom line

Information solution owner

Inability to create or sustain competitive advantage

visualizations for health plan administrators to help them manage their healthcare costs. In each case, an offering — an elevator, a philanthropic initiative, an insurance plan — is wrapped with data or insights to make them even more attractive to customers or other constituents.

Virtually any offering can be wrapped — even diapers. Pampers is one of several diaper companies that developed sensors to attach to diapers that send a mobile alert via an app to parents when the diaper is wet. The app also tracks information about the baby’s sleep and wake times. It’s hard to imagine a product that could not be wrapped.

In the digital era, organizations are expected to wrap their offerings using data-fuelled features and experiences that delight customers. But too often, they assume that they are realizing value from those efforts — without verifying whether and how much money is hitting their books. As it does with improving, data monetization by wrapping takes organizational attention, resources and discipline. It requires that organizations first gauge the extent to which customers regard the product more positively because of the wrap.

For example, do customer loyalty scores go up? Do customers recommend the product more enthusiastically? Second, organizations need to cash in on this positive regard by extracting revenues from customers, for instance, by raising the price of the offering.

There are also complications with data monetization by wrapping. Sometimes an enhanced offering has already been paid for, and the opportunity to raise prices will only arise in the

future. Sometimes wrapping staves off competitive pressure on prices or increases switching costs, thus retaining customers who might otherwise have been lost. In those cases, there might not be an immediate lift in sales but instead a future lift in sales or dampened sales erosion. However, none of these complications are reasons to ignore the step of value realization. Wrapping must make financial sense, or the associated investments might have been made more profitably elsewhere.

STRATEGY 3: Selling. Companies have been monetizing data by selling information for decades. Consider the retail industry: retailers have sold their point-of-sale (POS) transaction data to companies like IRI since the late 1970s. IRI, in turn, sold aggregated data and analytics back to retailers (and other organizations) that wanted to better understand their product sales compared to those of their competitors. POS data is an important raw material for the aggregator because they can generate a substantial revenue stream from it.

Instead of purchasing reports or metrics from the aggregators, some retailers exchanged their POS data for these solutions. This is bartering, which is a financial transaction. In fact, both retailers and aggregators must regularly assess whether the tender they receive for their POS data and analytic reports justifies the expense or risk of the exchange.

To distinguish it from other kinds of products, we refer to a data product as an ‘information solution.’ Information solutions are standalone offerings that solve compelling customer problems. Customers might buy an information solution because it

includes scarce data that they need, because it will help them get their own products to market faster, because of its sophisticated algorithms or because the interface is user-friendly, to name just a few reasons. A subscription to Bloomberg news, data and trading tools is an example of an information solution. Another example is IBM’s Weather Company data application programming interfaces (APIs), which serve climate, environment and forecast data from a cloud-based platform. Note that selling is one of three approaches to data monetization, yet too many organizations may naively view selling their data as the only way to monetize it. When organizations limit what they view as a data monetization opportunity, they end up leaving money on the table. Often, a lot of money.

The Improve-Wrap-Sell Framework

Together, the three approaches to data monetization make up the Improve-Wrap-Sell Framework. Regardless of industry,

business model, size, geographic location or strategic intent, your organization can monetize data using some combination of the three.

The success of improving depends on the leadership of process owners who define needed changes, recognize the opportunity for applying data, and ensure the adoption of changes. Wrapping demands engaged product owners who can envision the value offered by data to their products. They must be willing to engage with other parts of the company — like IT and customer service — in ways that were not necessary when developing and selling the core product. Finally, selling requires the identification of an entrepreneurial leader who can envision and launch a new information solution for new customers.

As indicated, the three approaches introduce distinctly different risks. The risk with improving is that value will not be created. Process owners are ideally suited to manage this risk by carefully tracking likely value creation and making course

Fintech applications have long aimed to give consumers more control over their finances. Yet, many banks have failed to deliver seamless applications—and some offer multiple applications for different functions. Now is the time for leaders to go beyond thinking in terms of monetary transactions — and instead develop the idea of payments as embedded in every facet of the customer journey.

frog recently partnered with J.P. Morgan to develop a payments ecosystem and unlock opportunities in the wearable devices space. Together we have been imagining and developing ecosystems across multiple industries. Eventually, every brand will seamlessly integrate financial services into its offerings to remove friction across all stages of the guest experience.

Payment-device-as-accessory is on its way to becoming an emerging genre of smart devices. The frog/J.P. Morgan team have been exploring prototypes of thoughtfully designed rings, bracelets, necklaces and more that will service multiple sets of needs compared to current smartwatches and smartphones. The first industry we focused on was resorts, gaming and entertainment (RGE). In the fan -

tastical world of RGE, the magic of the physical experience is central. But that magic can fade if guests remain constantly connected to (and disrupted by) the outside world. An ever-expanding number of establishments are working to rapidly adopt cashless experiences on the casino floor — furthering the removal of any barriers between guests enjoying themselves on-site. What if people could leave their smartphone in their pocket—or better yet, in their room—yet maintain full access to all of the resort’s services and experiences?

Drawing on our dual understanding of wearables and invisible banking, we have devised a three-part creativity blueprint. Leaders in banking, entertainment, fashion and beyond can take inspiration from these high-level principles as they prepare for their own forthcoming seismic shifts:

Form follows emotion. Forget the phrase ‘form follows function.’ In their work together, frog founder Hartmut Esslinger and Steve Jobs shared a vision that innovation was rooted not in functionality, but in the emotions consumers have with a brand’s products, services and experiences. The physical incarnation of a digital wallet

The Dawn of Invisible Banking by Sean Rhodes

When you limit what you view as data monetization opportunities, you leave money on the table. Often, a lot of money.

corrections. The risk associated with wrapping is already familiar to product owners: that the product enhancement adversely affects the value the customer enjoys from the core offering. Product owners, fortunately, already know how to track customer satisfaction; they will need to follow similar protocols when implementing wraps.

Finally, the risk associated with selling is the risk that accompanies any new business venture: business failure due to the inability to create or sustain competitive advantage. Information solution owners must remain highly sensitive to competitive pressures from substitutes and new entrants.

In closing

By actively engaging in data monetization, you will learn and you will help your organization learn. Your engagement will create momentum that initiates a positive reinforcing cycle: more data use, leading to more value, leading to more data use

— and so on. Imagine this happening across your organization, as people everywhere make it their business to monetize data. This is why data is everybody’s business.

Dr. Barbara H. Wixom is Principal Research Scientist at the MIT Sloan Center for Information Systems Research (MIT CISR) and founder of its Data Research Advisory Board. Cynthia M. Beath is Professor Emerita in the Department of Information, Risk and Operations Management at the University of Texas at Austin’s McCombs School of Business. Leslie Owens is a former Senior Lecturer at MIT and the former Executive Director of MIT CISR. They are the co-authors of Data is Everybody’s Business: The Fundamentals of Data Monetization (MIT Press, 2023).

or beautifully designed wearables can give users something tangible to connect with. These desirable yet subtle accessories — embedded with near-field communication (NFC), finger-print scanners and cashless technology providers — could deliver familiar, yet entirely new payment experiences, enabling consumers to pay directly and securely across resort landscapes.

Solve for experience. There are cultural indicators that ‘staying present’ has become the new luxury. Consumers are always connected, consistently distracted and reminded of their status at every turn. Resort guests expect high-end experiences and are willing to invest time, money and energy while on property. Resort operators must create new, unexpected experiences that unlock new behaviours, deliver greater and more trackable loyalty benefits and ultimately differentiate in order to keep guests returning and recommending.

Predict the curve, then follow it. Co-innovating with partners can help to identify areas of unknown need and opportunity, deliver a shared vision and the courage to pursue, industry-changing

initiatives together. Woven into the growing RGE culture of ‘being present’ is the consumer desire to retain the benefits brought by a connected experience. As with any new technology that changes consumer behaviour and creates business value, early adopters cross the business value chasm by serving the needs of small, highly influential segments — like high rollers at casinos — paving the way for mass adoption.

As indicated, RGE is just one industry that will be impacted by the invisible banking revolution. Broader applications including healthcare, construction and virtual goods are already being explored as emerging technology continues to beget brave clients.

Sean Rhodes is Executive Creative Director at frog and an Adjuct Professor of Design Strategy at NYU’s Tandon School of Engineering.

AI ADOPTION IN AMERICAN BUSINESS: WHO IS DOING WHAT, AND WHERE?

Kristina McElheran

EXCITEMENT ABOUT ARTIFICIAL INTELLIGENCE (AI) is on the rise among business leaders and investors, and for good reason: AI has the potential to transform business and the economy. But are businesses embracing it yet? If so, to what extent?

Very little evidence exists about which technologies have actually been adopted thus far, who the adopters are or where they are located — which has made it difficult to understand AI’s true economic and managerial implications. In a recent paper, I and my colleagues Erik Brynjolfsson (Stanford University), J. Frank Li (UBC) and Zachary Kroff, Emin Dinlersoz, Lucia Foster and Nikolas Zolas of the U.S. Census Bureau set out to fill in some of the blanks.

Our study sheds light on the rate and direction of AI diffusion and the influences that will shape its ultimate impact on workers, firms and society. In this article I will summarize our key findings.

Why Study AI Adoption?

Throughout the history of big technological shifts, firms have required time to adjust and achieve new productivity gains. Changing processes, restructuring the organization, hiring the right talent and learning how to integrate new technology into products and services is difficult. So difficult, in fact, that adjustment often unfolds unevenly across firms.

AI represents an important new input into the production

of novel ideas. If AI provides an antidote to purported declines in innovation or a pathway to new or better jobs, this could be cause for optimism. Understanding the firm context shaping this innovative activity is essential. At the same time, however, concern is growing that many industries are becoming more concentrated — and changing technology is increasingly taking the blame. In recent years we have seen the rise of ‘superstar firms’ like Amazon and Tesla that may benefit even more from technologies like AI.

One key issue for leaders is this: If AI goes hand-in-hand with rising inequality between firms and workers, we must think carefully about its broader competitive and socio-economic implications. Yet little guidance exists for decision-makers at this critical time.

A new nationally representative survey, the Annual Business Survey (ABS), conducted jointly between the U.S. Census Bureau and the National Center for Science and Engineering Statistics (NCSES) addresses this gap. The ABS began collecting information on the adoption and use of several advanced technologies — including AI — as of 2017. We sent our survey to 850,000 firms, and obtained a representative sample of 573,000.

In our work, we matched firms in the first year of the ABS to the Census Bureau’s Longitudinal Business Database (LBD), which provides administrative data on outcomes such as

A lack of comprehensive data on AI use by firms has left its adoption and implications poorly understood. My colleagues and I recently set out to fill in some of the blanks.

by

employment and revenue across the firm lifecycle for a nearuniverse of firms in the economy.

Our study progressed in stages. First, we uncovered broad patterns of AI use across the entire U.S. economy. AI use showed up primarily in firms that also had high reliance on digital information and cloud computing, suggesting key interdependencies among recent technology trends. We found that firms that rely on robotics also typically use AI in production, pointing to the importance of embodied technology that can spread through tangible inputs. In other words, the ‘recipe’ for using AI effectively is not simple and requires attention to other types of investments and practices. Thus, we next drilled down into a large sample of 75,000 younger and arguably more dynamic firms for which we had unusually detailed organizational data. Following are the firm characteristics we analyzed in this subset:

OWNER CHARACTERISTICS. In previous research, high-growth entrepreneurship has been linked to a number of founder characteristics and motivations. The founder’s experience and identity are influential in early decision-making, when objective data is sparse, and often entail difficult-to-reverse commitments that affect the trajectory of the firm. Owner characteristics matter for performance throughout the lifecycle, as well.

We expected that several features of the founder would play a role in AI adoption and/or firm growth. Intuitively, founders with advanced degrees are likely to lead firms that are more technology-focused, equipping them with the objective data inputs required for advanced analytics, including AI. They are also more likely to be familiar with advanced technologies and their applications as a result of their advanced formal training.

Informal training is often important, as well. Prior entrepreneurial experience has been identified as one of the key predictors of firm survival and performance. In particular, ‘serial entrepreneurship’ may be correlated with a better assessment and exploitation of the opportunities advanced technologies offer. We also expected that the goals and motivations of entrepreneurs would be critical to the trajectory of the firm. For instance, smaller, older firms lagging in advanced technology may have been set up to pursue objectives other than growth, potentially lacking the inputs and scale that would justify AI adoption. In this vein, the entrepreneurship literature has noted a clear delineation between ‘lifestyle’ and ‘high-growth’ entrepreneurship.

We anticipated that lifestyle-focused business owners would be less likely to make the technology and organizational investments required to deploy AI in a meaningful way, if at

all. We further anticipated that founder motivations may have farther-reaching influence on how AI is deployed, in practice. For instance, recent work points to the important distinction between founders motivated by pro-social aspirations and those motivated by earning potential. The connection between founder motivations and the use of advanced technology remains poorly understood.

START-UP CONDITIONS. A firm’s growth potential is not exclusively determined by its owners. ‘Insiders’ such as venture capitalists may have an information advantage about firm quality. Indeed, firms funded via venture capital (VC) or other outside investors have been associated with greater growth potential than firms funded through the owners’ capital. The funding amount has also been interpreted as an early signal of venture quality.

While higher initial capitalization may reflect firm quality, care in interpretation is in order. Higher capital intensity within industries may reflect production strategy as much as firm quality and is positively associated with the presence of advanced technologies that tend to increase a firm’s capital-to-labour ratio. Detailed industry controls only partially address this; thus, we leveraged additional information on firm strategy and positioning that is rarely observable at this scale.

INNOVATION AND BUSINESS STRATEGIES. Innovation and related activities geared to exploiting innovation outcomes — in particular, formal intellectual property use — have been correlated with a firm’s growth potential. Recent research suggests that firms that apply for trademarks exhibit higher growth after application. But harder-to-measure complementarities between AI and innovation may also exist, particularly if new applications are difficult to patent or protect by other means.

The survey we leveraged directly queries firms about their recent innovations in new products or services, as well as processes. These innovations, in turn, can be linked to different business strategies. In particular, we can distinguish ‘cost-reducing objectives’ from ‘growth-oriented goals.’ These different strategies may lead, in turn, to distinct AI adoption patterns and outcomes.

GEOGRAPHY. AI is still in a relatively early stage of its geographic diffusion, and its future diffusion path will likely depend on where it is concentrated now, as geographic spillovers in AI use may determine the spread of utilization from current hubs to nearby locations. Therefore, uncovering the current state of geographic disparity in AI adoption was a key objective of our analysis.

Uncovering the current state of geographic disparity in AI adoption was a key objective of our analysis.

Our Research

The 2018 ABS was sent to 850,000 firms nation-wide based on a sampling method that classifies firms by state, industry and a range of ownership characteristics. Approximately 590,000 firms responded to the survey — a relatively high response rate (over 69 per cent). Roughly 573,000 were linked to the Longitudinal Business Database (LBD).

The vast majority of firms in the U.S. are very small, and this was reflected in our sample. In fact, the ABS sample differs dramatically from standard data sets (like Compustat) that primarily represent large, public firms. While the average firm in the raw sample had roughly 90 employees, this fell to 26 with weighting, and nearly 70 per cent had fewer than 10 employees. Thus, care is required to disentangle young, high-potential ‘gazelles’ from mom-and-pop firms that contribute to the economy in broader, less eye-catching ways.

The technology module in the 2018 ABS contained three novel and connected questions. The first queried firms’ reliance on digital information (data), widely regarded as a key input and even a prerequisite to more advanced uses of digital technologies. A second enabler is sufficient computing power to manage and exploit massive quantities of data. Thus, the second question explored the extent to which firms rely on cloud services for their IT functions, as this has shifted the cost structure and speed of access to IT resources for most firms.

The third question — and the primary focus of our research — asked directly about the use of advanced business technologies in producing goods or services. The specific technology definitions include five commonly associated with AI: machine learning, machine vision, natural language processing, voice recognition software and automated guided vehicles.

Our key takeaways can be summarized as follows.

DIFFUSION OF AI IS LOW, YET IT IS CONCENTRATED IN IMPORTANT SEGMENTS OF THE ECONOMY. Overall, we found AI adoption to be low and concentrated in a smaller number of relatively larger firms. We found that under six per cent of firms actually used an AIrelated technology in their production operations. However, importantly, the majority of very large firms (>5,000 employees) used at least some AI, and the intensity of AI use was higher in these firms.

Readers may note that the level of AI diffusion we found is significantly lower than that reported in the European Commission’s survey of AI and other surveys by McKinsey, Deloitte and PwC. However, those surveys do not claim to be

representative of the underlying economy; instead, they focus on larger, publicly traded companies. In contrast, the ABS sample included many small firms for which AI adoption is quite limited, but whose inclusion allows us to estimate the correct ‘denominator’ for country-wide use rates.

The low adoption rate does not make AI irrelevant for the aggregate economy. In fact, the potential exposure to AI by workers was much higher than its usage rate among firms, a difference we estimated using detailed employment data at the firm level. AI use showed up primarily in firms that also had high reliance on digital information and cloud computing, suggesting key interdependencies among recent technology trends. Firms that relied on robotics also typically used AI in production, a relationship that is often missed when one or the other is studied in isolation.

Several impediments to AI adoption appear to limit its diffusion. These include scale effects (many businesses may not possess the vast amounts of data to utilize AI applications), as well as a potential hierarchy of technology adoption needed for proper deployment of AI applications. A possible interpretation of these relationships is that information digitization is a key prerequisite for AI adoption, as is infrastructure such as the cloud or other advanced IT systems.

To the extent that it takes time, resources and potentially economies of scale to accumulate technology complements, considerable frictions to AI adoption and use likely remain. Moreover, a large fraction of firms may also not yet benefit from AI until new applications arise.

The disparity in adoption rates across firm types suggests an early ‘AI divide’ among businesses in the U.S.: A small set of firms with the special characteristics we uncovered lead the diffusion curve, with a large number of laggards that are yet to overcome the impediments to AI adoption or to benefit from AI. Yet, the prevalence of AI among innovating start-ups with high growth potential indicates that we might expect significant dynamism in these patterns in the years to come. Delving into our subsample of start-up firms is instructive:

FIRM-LEADERSHIP CHARACTERISTICS PREDICT AI USE. More educated, more experienced and younger founders are more likely to adopt AI. Education may be a proxy for the complexity of products and services offered by the firm, which may require a higher degree of education — and, at the same time, advanced technology like AI — to be produced.

Serial entrepreneurship, which has been linked to firm performance in prior work, also predicts AI use, suggesting a novel

explanation for performance gains in the digital age. Likewise, our finding that firms with owners younger than 35 are more likely to adopt AI is consistent with research that finds younger cohorts of entrepreneurs tend to be more sophisticated users of advanced technology and may be more open to adopting these technologies in their businesses.

High-growth and innovative firms are not only led by individuals motivated by bringing new ideas to market, but also by those who report prosocial values such as helping society. In turn, such motivations are highly correlated with AI use. Other motivations for founding or owning firms matter, but there is a clear distinction between markers of growth-oriented and socalled ‘lifestyle entrepreneurship’ when it comes to AI use.

FIRMS WITH MARKERS OF ‘HIGH-GROWTH’ ENTREPRENEURSHIP ADOPT AI.

Higher initial capital levels at start-up and VC funding are associated with higher likelihood of AI use. For instance, the presence of venture capital was associated with a 3.6 per cent increase in AI adoption likelihood, holding everything else constant. Recall that such markers often provide early signals of start-up quality and growth potential.

Being a high-growth firm in the first few years of life is positively and significantly associated with the adoption of AI at some point in the firm’s lifecycle — a firm trait that is directly observable in the rich Census of Bureau. Yet, when all of these observable factors were included together, revenue growth had a far weaker relationship with AI adoption. Firms with patents were more likely to adopt AI (by 3.5 per cent), and firms that identified IP protection as ‘very important’ had a 6.1 per cent higher likelihood of being AI users.

Importantly, once we controlled for early growth, we found that late growth is still robustly correlated with AI use. While our study lacked the ability to establish a causal relationship between AI use and growth, this finding establishes that not only is AI use prevalent among fast-growing firms early in their lifecycle, but that higher revenues later in life are also linked to AI, even when many of the other well-known drivers of growth are removed from the picture.

FIRM STRATEGY MATTERS FOR AI ADOPTION. Our results suggest that a firm’s innovative activity and innovation strategy matter significantly for AI adoption. Both product and process innovations are positively correlated with AI adoption, but the latter has a much higher correlation. Firms with process innovation are 5.4

per cent more likely to adopt AI — a magnitude that is equivalent to the overall adoption rate of AI for the firms. Similarly, firms that possess patents and those that identify IP protection as ‘very important’ are more likely to adopt AI.

GEOGRAPHIC DISPARITY IN THE ADOPTION OF AI IS PRONOUNCED. We found substantial geographic disparity in the adoption and use of AI. Our data are most informative for start-ups, which tend to be single-unit firms and hence easy to situate geographically. In particular, the rate of AI adoption tends to be higher in the southern and western parts of the country. Technology hubs such as Silicon Valley, the Research Triangle and Provo-Orem, as well as large metro areas such as the Capital Region, Los Angeles, Houston and San Francisco stand out in AI adoption. Once we weighted by share of local start-up employment, Riverside, San Francisco and San Jose stood out in California; while Louisville, Columbus, Austin, Atlanta and Nashville also showed concentrated AI use. This has the potential to fuel an AI-based ‘digital divide’ if initial patterns persist.

In closing

The complementarities between AI use and measures of firm quality and growth potential suggest that while the diffusion of AI is low — and may remain low for some time — AI’s impact on the economy will be disproportionately large because it is concentrated both among large firms and in a niche of start-ups that are innovative, highly capitalized and fast-growing — the type of firms that contribute significantly to aggregate growth and productivity.

While AI adoption is still in its very early stages, its concentration among innovative, high-growth firms and in certain geographies portends not only an opportunity for transformative economic effects, but also ongoing challenges for creating broadly shared prosperity.

Kristina McElheran is an Assistant Professor of Strategy at the University of Toronto Scarborough and the Rotman School of Management. She is also a Faculty Affiliate at the Schwartz Reisman Institute for Technology and Society at UofT; a Digital Fellow in the Digital Economy Lab at Stanford; a Digital Fellow of the Initiative on the Digital Economy at MIT and a Lab Economist at the Rotman School-based Creative Destruction Lab.

The majority of very large firms (>5,000 employees) used at least some AI.

The Tech Trends Every Leader Needs to Understand

by Amy Webb

LATELY, it’s as if we’ve been living through the aftermath of cataclysmic explosions: the release of generative artificial intelligence systems like ChatGPT and Midjourney, a fusion breakthrough that could someday generate zero-carbon energy, and AlphaFold’s protein-folding algorithms that predicted structures for nearly all catalogued proteins known to science, to name a few. These and other forces of change are colliding, resulting in an unfathomable amount of new signals — bits of change that, over time, will result in the trends that shape society.

In this increasingly complex world, leaders who focus on the trends that matter and adapt to changing circumstances will make better decisions and see improved outcomes.

Some of the trends featured in the Future Today Institute’s 2023 Tech Trends Report are new advancements on mature technologies, while others represent frontier technologies and areas of science. When we look at the trends collectively, new centres of gravity come into focus, and we can glimpse the impacts they will have on every sector.

In this article I will share a sampling from three categories of trends with you. For those interested, the complete report can be downloaded on our website (www.futuretodayinstitute.com).

CATEGORY 1: ARTIFICIAL INTELLIGENCE (AI)

If the 2010s were known for ‘perception AI’ — systems that sensed signals such as images, the 2020s will be known for ‘generative AI’. These systems not only sense and understand the world but can also generate new content, concepts and ideas while communicating with us. As a result, AI is emerging as an assistant for all knowledge workers. Within the next 18 months, we will see assistive technology developed for a variety of professions. Think GitHub’s Copilot for financial analysts, commercial real estate developers and lawyers.

Generative AI will also be incorporated into consumer applications. Already, Canva, the popular online graphic design tool, has integrated Stable Diffusion in its platform; Microsoft has incorporated OpenAI’s DALL-E 2 image-generating system into its Designer and Image Creator applications, which is a big upgrade to clip art; and Google’s Bard includes an application programming interface (API) to encourage developers to start building new products.

The first players to succeed in this space will likely be creative apps, all of which will have large language models (LLMs) as a backbone to inspire and augment human creativity. Some

Trends, on their own, cannot predict the future. But by understanding the changes shaping the technology landscape, executives can make informed decisions and capitalize on new opportunities.

companies will win by providing a refined/value-added LLM product to the end consumer and meeting the customer in desired distribution channels, such as LLMs for healthcare, legal, finance and architecture.

Publicly available LLMs are often the foundation for AI start-ups, but some researchers and technologists question their defensibility when it comes to capturing value. The moat is in data. Techniques and models will largely get commoditized and served via the infrastructure layer, where real value will be realized.

Longer term, we expect to see niche LLMs owned by a select few players, while general-purpose LLMs become commoditized. At the infrastructure layer, we anticipate a variety of generative AI services built to better serve a variety of applications. In addition to OpenAI, specialized players entering the market include AI21, Cohere and Scale AI. Following are a few things to look out for:

WE WILL SEE INCREASED ENTERPRISE ADOPTION OF AI. Top talent will start breaking away from the largest players to form their own start-ups, which will include conversational agents, artificial general intelligence programs and AI-first biotech companies. Consolidation will continue to be a driving theme. Microsoft plans to increase its investment in and leverage OpenAI for Bing to pull market share away from Google search.

More and more leaders see AI as necessary for growth in the current macroeconomic environment, even as new developments make some job categories obsolete. In nearly every industry, AI will serve as a force multiplier for growth, bringing efficiencies, better tracking, business intelligence and assistance with decision-making. As training costs decline, more applications will be built. Spending on AI systems and hardware is likely to explode this decade, creating significant enterprise value.

AI CODING ASSISTANTS WILL GROW IN POPULARITY. OpenAI’s Codex, introduced in 2021, evolved from research to open commercialization by the middle of 2022; GitHubs Copilot is now available as a subscription ($10 per month); and Amazon’s CodeWhisperer is now available free for individual use. Internally, Google is using a machine language–powered code completion tool—and it may soon be made available to everyday users.

AI WILL BE MORE DEEPLY INTEGRATED INTO HEALTHCARE AND LIFE SCIENCES. Generative AI will yield new proteins, antibodies and drugs, while biology- and chemistry-specific models will result in faster discovery, further providing practical use cases and leading to increased investment. Could 2023 mark the beginning of the end of human radiologists? Lithuania-based Oxipit, an AI-first medical imaging start-up, built an autonomous system that reports on chest X-rays that show no abnormalities. The technology is good enough that it received state-level certification to operate independently, without a radiologist in the loop.

HOW TO PREPARE: We recommend that chief strategy officers in every field develop a solid understanding of AI to engage more closely with the C-suite to develop a cohesive point of view on digitalization, augmentation and automation—and develop strategic plans. Importantly, businesses should keep abreast of emerging regulations that could restrict the use of consumer data, algorithms or generative AI systems. Risk models should be developed to determine plausible near-futures, so that leaders can adjust their strategies accordingly.

The need for highly skilled people in this arena is fast outpacing university graduation rates, which might lead to a shift in higher education: It is plausible that companies in search of AI specialists might opt for ‘modular certifications,’ which can be earned faster than traditional four-year degrees. Talent sourcing and retention will continue to pose challenges for tech companies—and for organizations in other industries that need a trained workforce but may not be able to provide the same perks as the hottest AI players.

CATEGORY 2: FINANCIAL SERVICES

Multi-year efforts to digitize financial services are finally coming to fruition, enabling the explosion of financial technologies that underpin the movement to open banking. Open banking can lead to open finance, which can accelerate open data and fundamentally change how scarce resources are distributed and allocated.

Customer-centric and socially responsible approaches are increasingly table stakes in the design of financial services products. We expect increasing commoditization of financial services infrastructures. During the next 18 months, decentralized finance (DeFi) will mature, sparking new investment, growth and adoption.

In nearly every industry, AI will serve as a force multiplier for growth.

My colleagues and I expect mainstream financial services and decentralized financial services to run in parallel for some time. As DeFi continues to mature, organizations will gain hardfought insights around structural and customer protection systems. We anticipate legacy finance will evolve while trying to build connective tissue to decentralized systems, with the explicit goal of absorbing enough functionality to avoid total disintermediation.

Look for large non-financial players with significant centralized market power, such as platform providers and regulators, to play increasingly active roles in setting rules and guiding the evolution of financial services. As back-office infrastructure has opened up and become standardized, banking-as-a-service providers are growing increasingly popular. We anticipate growth in the space during the next 24 months.

New forms of data modeling and credit scoring will expand access to financial systems. Responsible innovation will be crucial to the future of alternative credit scoring, especially as machine learning techniques and generative artificial intelligence systems are applied at scale.

Macro opportunities ripe for accelerated change include:

• Using financial data accessed through open banking;

• Converting existing money movement to real-time and near real-time frequency;

• Efforts to make DeFi mainstream (regulation, on and off ramps, governance);

• Orchestration of back-office intermediaries for invisible customer and business experiences;

• Commoditization of financial services;

• Financial inclusion to increase the global market for financial services;

• Platforms reinforcing their walled gardens; and

• Social responsibility becoming table stakes.

HOW TO PREPARE: To prepare for all of the above, corporate innovators should:

• Prepare to ‘fast follow’ as waves of start-ups reach maturity and demonstrate viability of new markets and business model.

• Look to start-ups with new business models and local product market fit that seek to expand regionally or globally.

• Build the corporate muscles to make strategic decisions in uncertain environments by creating clear guidance across the organization.

• Develop intentionality around acting, watching or ignoring.

We recommend that DeFi builders:

• Prepare for potential regulation.

• Adopt a global mindset with local implementation.

• Support parallel development to legacy financial services, while establishing sufficient rules and guardrails for the industry to mature.

• Prepare for DeFi and legacy financial services to become increasingly interlinked.

We recommend that VC investors:

• Seek out companies with break-even strategies and healthy unit economics.

• Prepare for internal rounds and decreasing valuations.

• Help failing companies shut down quickly, and with dignity.

And finally, we advise retail investors to:

• Expect story stocks and meme stocks to revert to more standard valuations.

• Prepare for new asset classes, like NFTs and fractional investments, to become a part of a well-diversified portfolio.

• Keep an eye out for financial advice from non-traditional sources.

CATEGORY 3: CLIMATE, GREEN TECH AND ENERGY

Next-generation solar cells are thin, flexible and printable, and they expand the spectrum of wavelengths from which they can extract energy, dramatically growing the application opportunities for the technology. Wind is moving offshore. New types of turbines — vertical or bladeless, for example — might provide more efficient alternatives to horizontal ones, or can be used side-by-side to catch winds at different altitudes. Start-ups are aiming to tap into geothermal energy 20 kilometers beneath the earth’s surface. If successful and scalable, this could provide the majority of energy needed in the world. Hydrogen can now be made from sewer gas (hydrogen sulfide) using nothing but visible light, making the production

much more affordable. Biofuels from hemp and algae could be more efficient to produce than from traditional biomass, bringing down the fuel’s price and making it more likely that governments implement blending requirements. Former landfills and mining sites can be repurposed for renewable energy development. They often have existing infrastructure and permitting advantages compared to other swaths of real estate.

The Lawrence Livermore National Laboratory’s National Ignition Facility produced a nuclear fusion reaction that resulted in a net energy gain. Decades in the making, the breakthrough potentially paves the way for emissions-free energy — though realistically that won’t happen for decades more. Many challenges remain, including devising the supporting infrastructure and storage for fusion energy.

New methods of harvesting energy can supplement or replace more traditional carbon-emitting energy sources. Waves, tides and currents in bodies of water could provide more reliable sources of energy than wind or solar. Even sweat can provide a way to power small electronics and medical devices, producing no toxic by-products. Rare earths can be found in mining waste, opening the door to diversifying the world’s supply. Of note: China currently controls 80 per centof the global market in rare earths. Following are some innovations to look out for.

ENERGY INFRASTRUCTURE. The costs associated with renewable energy have decreased significantly, but other barriers still limit the scale of these energy sources. More efficient and fastercharging batteries and novel methods of energy storage at the grid level are leading the way to affordable, environmentally friendly, lasting, flexible and scalable solutions.

New technologies are making it possible to move and harvest energy in groundbreaking ways. Ultra-high-voltage power lines, power-beaming microwaves and space-based solar power are among the solutions that will allow energy to be transferred to undersupplied regions or moved to areas experiencing energy shortages. Grids are becoming more resilient and dynamic. This will be of supreme importance as more intense storms and forest fires increase as climate change worsens.

EMISSIONS REMOVAL. Volcanic sand and genetically edited crops could be significant natural carbon capture and storage (CCS) opportunities, in addition to expensive mechanical CCS installations at plants. Companies are developing ways to use carbon dioxide captured from smokestacks or simply the air. A suite of new products ranging from fashion accessories to imitation meat can be made from the captured gas. The most viable products will combat environmental challenges by not only taking excess carbon out of the atmosphere, but also minimizing processes that emit extra carbon dioxide. Tracking technologies are enabling both consumers and manufacturers to take control of their carbon footprints. Companies can develop competitive advantages by being more transparent with their value chains, appealing to environmentally conscious consumers.

EMISSIONS REDUCTIONS. Carbon-neutral or carbon-negative cement, 3D printing and AI-aided project planning, and the use of alternative materials such as recycled plastic all have the potential to significantly reduce the construction sector’s emissions. By using computer vision to better identify materials, recycling programs can boost their accuracy and profitability and thereby increase opportunities to bring new life to old products. New materials are radically changing the built environment and bringing new life to the construction industry.

A suite of biomaterials and advanced materials science will reduce carbon emissions and even result in carbon being stored within these new materials. Consumer and industrial products are being equipped with solar and electric capabilities to reduce carbon emissions and provide reliable solutions for unstable energy grids. They are also being equipped with capabilities for reducing microplastics in the ocean. The transportation sector is minimizing emissions through a series of innovations that improve vehicle aerodynamics, optimize charging and even enable vehicles to be charged while moving. These innovations will be necessary for a critical mass of users to adopt electric alternatives. Behavioural changes such as shifting to plant-based diets or using renewable energy for heating, cooling and cooking will have measurable effects on reducing carbon emissions.

Waves, tides and currents in bodies of water could provide more reliable sources of energy than wind or solar.

Impact of Trends on Your Industry

Automotive

Aviation and Travel

Construction and Engineering

Consumer Packaged Goods

Education

Financial Services

Government and Policy

Healthcare Systems and Services

Hospitality

Media (Entertainment)

Media (News)

Pharmaceutical and Medical Products

Public and Social Sectors

Real Estate

Restaurants

Retail

Space and Aerospace Defence

Supply Chain and Logistics

Telecommunications

FIGURE ONE

ENVIRONMENTAL MANIPULATION. Rewilding projects are growing and are getting a lot of public support, as healthy and balanced ecosystems also help combat climate change. Cloud manipulation — brightening or seeding — might help reduce Earth’s temperature or increase the amount of rain. Overall implications to the world’s ecosystem are not clear. The oceans could be our best bet for removing CO2 from the air, if humans ‘help’ them by, for example, adjusting their alkalinity or encouraging the growth of phytoplankton. However, the effects of these experiments on the wider maritime ecosystem have not been explored.

EFFECTS OF CLIMATE CHANGE. Using AI, satellites and drones to monitor the effects of climate change reveal data and new discoveries that otherwise would remain unknowable. New types of city projects have garnered attention as climate change forces humanity to rethink where and how we live. Examples include domed, floating and underground cities — all of which completely upend life as we know it.

HOW TO PREPARE: As is usually the case, there are a range of opportunities and threats ahead for organizations. Here are some key things to consider.

AI: Key Questions For Your Team

How do these trends change our perspective on our current AI investment and capabilities?

Is our organization positioned to leverage AI for growth, in addition to realizing new efficiencies?

When we engage in longterm strategic planning, how does the evolution of AI factor in?

Are we adequately preparing our workforce to succeed in a world in which their knowledge tasks might be augmented or fully automated by AI?

What is our process to vet, verify and monitor our vendors?

Is the AI we’re using explainable?

If not, does that open us up to additional risk?

Does our team have an expansive enough viewpoint on emerging threats and attack surfaces?

What parts of our business make us vulnerable as AI evolves?

What is our point of view on using generative AI systems?

If proposed antitrust legislation passes in the U.S. and EU that further regulates Big Tech companies, how does this create a strategic opportunity for our organization?

Or, what might our organization lose?

How might we develop the knowledge, experience and talent to leverage AI trends?

INTERIM SOLUTIONS. It takes time — decades — to implement green processes and methods such as carbon capture and storage technologies or infrastructure upgrades to accommodate renewable energies and distributed grids. Long interim periods come with their own specific subsets of pain points. Are there developments in your industry that would benefit from products that address these transient states?

THE ENERGY OPPORTUNITY. The energy sector is experiencing a shift in the power dynamics of stakeholders as customers demand and search for environmentally friendly products and services. Decentralization of the grid and non-dispatchable energy sources such as wind and solar are not only introducing new players to the energy market, but demands on the grid itself are fundamentally changing to accommodate frequent energy transformations and changes in energy direction. How can your company rethink energy, be it as a possible additional product or an alternative form of production?

ENVIRONMENTAL JUSTICE. Discussion about wealthy countries paying reparations to smaller, poorer countries that are disproportionately affected by climate change has gained momentum. Wealthy nations pledged payments during the COP27 last year. How can your company go beyond introducing green practices and help alleviate the damage done?

GO LOCAL. By reconfiguring supply chains, manufacturers can source materials closer to production lines, minimizing the need to transport goods and products over long distances. Through innovations such as using repurposed carbon to make products, organizations can have more control over where products are made, allowing them to incorporate more instances of near shoring.

GET AHEAD OF REGULATION. As more emphasis continues to be placed on ESG, the onus will be on organizations to provide transparency into their inner workings and environmental

FIGURE TWO

impacts. It will behoove organizations to get ahead of these new expectations. Aside from the adoption of more stringent ESGs from shareholders and investors, swift regulatory changes will catch many organizations off guard and have significant bottom-line ramifications.

CYBERSECURITY. Technology enables and facilitates the shift to environmentally friendly processes in many of our most important industries — energy, food, industrial processes. However, this also makes those industries vulnerable to cyberattacks. As you upgrade your company’s digital infrastructure, are you making sure that your systems are adequately protected? And how are you preparing for outages caused by cyberattacks?

UNEXPECTED IMPACTS. Disrupted supply chains have caused balloon flights from the National Weather Service’s Storm Prediction Center to be canceled, reducing data collection and compromising forecasts. The number of cities across Europe declaring clean air zones is expected to rise exponentially by 2025, forcing polluting vehicles off the road and possibly affecting last-mile delivery. Most leaders are aware of the direct impacts of climate change and environmental regulations on their businesses — shortages of raw materials, for instance, or a fragile supply chain. But are you aware of the second- and third-order impacts on your business of shifts in consumer behaviour and an evolving regulatory landscape?

A SHORTAGE OF QUALIFIED WORKERS. Although many tech workers have left the industry to find climate-related roles, the world will still face a dearth of talent dedicated to ensuring a climate-resilient future. Roles will become increasingly specialized, as the need for new technologies will also create the need for careful operation and maintenance. Universities can be slow to adjust to such changes, so climate-conscious organizations will have to source and train much of the available talent on their own.

PLANNING FOR CLIMATE MIGRATION. Climate migration will become an existential threat sooner and to a greater degree than many are anticipating. As climate migration increases, businesses will have to adjust their operations, supply chains and skilled talent. Many will face decisions to uphold human rights and equality.

THE END OF GREENWASHING. Are you prepared for complete transparency? As the ability to track CO2 emissions increases and industries can account for and track emissions throughout the entire value chain and lifecycle of a product, it will be easy to determine who greenwashes and who is implementing truly environmentally friendly practices.

In closing Trends, on their own, cannot predict the future. Rather, futurefocused organizations can use them to deeply reflect on the tension between long-term and short-term goals and to reduce uncertainty. By understanding the trends and changes shaping the technology landscape, executives can make informed decisions and capitalize on new opportunities in the year ahead. We invite you to join us in observing how the stardust settles.

Amy Webb is the Founder and CEO of the Future Today Institute and a Professor of Strategic Foresight at New York University’s Stern School of Business. Her latest book, The Genesis Machine (PublicAffairs/Hachette, 2022) examines the futures of gene editing, biotech and synthetic biology.

DIGITAL CROWN JEWELS: How to Protect Your Data Assets

by Michael Parent, Greg Murray and Glen Whyte

IN THE REALM OF CYBERSECURITY, an important concept is that of ‘digital crown jewels’ (DCJs). These are your organization’s most precious digital assets, and the analogy to priceless national ceremonial objects such as the Crown Jewels of the United Kingdom is apt: These assets must be protected at all costs from nefarious interference.

DCJs consist of, in part, an organization’s data, and more specifically the data that a firm possesses, processes and passes on that allows it to operate and deliver on its strategy. These data might include customer records, purchasing histories, employee records, finances and intellectual property information about proprietary products and services.

Such data are extremely valuable, and even more so when they contain personally identifiable information (PII) and personal health information (PHI). Data, however, are not the only valuables in need of protection. An organization’s DCJs also include its data processing environment (DPE). This consists of both how data flows through the organization and the processes by which the firm and its agents access and manipulate these data. Failing to protect the DPE has and will continue to lead to notorious and costly digital breaches.

Consider the case of the 2020 SolarWinds breach. SolarWinds is a large U.S.-based software company specializing in information systems management tools like Orion, its IT monitoring system. More than 30,000 public (local, state and federal) agencies and private organizations like Microsoft, Intel

and Cisco were using Orion to manage their information systems when computer hackers gained access to SolarWinds’ system in September 2019. The hackers corrupted Orion’s source code with malware that enabled them to access clients’ data and information systems. The hackers also infected Orion’s automated software updating process, such that when customers attempted the update (an automatic process much like software updates on a laptop computer), the malware would be automatically downloaded.

More than 18,000 unsuspecting SolarWinds customers installed the malicious update, causing the malware to propagate undetected. In turn, this allowed the hackers to install even more malware to spy on and steal from these victims. The insurance costs of this breach alone were estimated at US$90 million, not to mention the costs of reputational and brand damage and further unexpected cyber risk exposure for SolarWinds and its infected clients. In October 2022, SolarWinds agreed to pay shareholders $26 million to settle claims against the company and its directors. In addition, the Securities and Exchange Commission issued an enforcement notice that will have longlasting effects.

Another cautionary example occurred in 2021 when remote management software provider Kaseya’s update system was infected with malware. The virus was implanted by the Russian criminal collective REvil into 60 of Kaseya’s managed service providers (MSPs), resulting in over 1,500 unsuspecting

Protecting your organization’s precious digital assets is no longer a choice. The price you could pay by failing to act is far too great.

customers downloading ransomware. MSPs are firms that provide and maintain information systems for end-user client organizations. REvil claimed to have infected over one million systems in this way and demanded a one-time payment of $70 million from Kaseya to provide a decryption key. Kaseya chose not to pay, instead deciding to rebuild its entire system at considerable cost in terms of time and money.

In both examples, these companies failed to properly protect their DCJs. Worse, as suppliers to many large corporations, they neglected to protect something that mattered just as much as their data: their software upgrading process. They consequently transferred supplier-induced cyber risk to their clients, resulting in a digital train wreck that was eminently preventable.

Elsewhere, Colonial Pipeline, a major supplier of fuel oil to the American Eastern Seaboard, was confronted in 2021 with a ransomware attack and a ransom demand of $4.4 million. As a vital part of American energy infrastructure (Colonial provides 45 per cent of the fuel for the East Coast), many assumed the company would be hardened and protected against such attacks. Yet, the attackers got into Colonial’s network merely by using credentials from an employee who had left the company three years previously! To state the obvious, Colonial customers would have been severely impacted had they run out of fuel in the dead of winter.

Like many organizations that have recently experienced cyber breaches, Colonial appears not to have considered user credentials (and the associated security processes required to keep them safe) as part of their DCJs. If they had, Colonial would have deleted them. That they did not is, unfortunately, not surprising based on existing cyber risk frameworks and models.

Too often, the DPE is not fully considered in DCJ assessments. Usually, the DPE is considered from a ‘controls’ perspective — and threat actors are continually searching for and unfortunately finding new ways to bypass controls. The result is a game of ‘whack-a-mole,’ where digital risk analysis is continually being assessed against the total number of controls on the DPE. Threat actors therefore look for alternate or unexpected paths to breach the perimeter of the DPEs that may not be protected as diligently as they should be, like unexpired access credentials. If effective cyber risk protection is to be achieved, the historic view of DCJs and their relationship to the must evolve.

According to KnowBe4, a cybercrime defense firm, the global cost of ransomware in 2021 was $20 billion. Left unchecked, these costs are expected to grow to an astounding $265 billion by 2031. The need to ensure that appropriate structures and processes are in place to reduce the potential for infection or cyber breach and the damage they cause is obvious. Most ransomware infections, for example, are the result of human error, such as employees inadvertently clicking on a link or downloading an attachment in a phishing email. Ongoing training, a cybersecurity-conscious culture, behavioural reinforcement and simple mechanisms like warnings in e-mails (i.e. ‘Do not click on or open attachments from unknown senders’) are critical.

Beyond such first steps, executives and managers need to broaden their understanding of DCJs by including the critical flows and processes that surround their data and DPEs in their risk analyses. They further need to consider the access paths that threat actors may attempt to exploit that have not historically been included in their cyber risk analyses — whether these paths have been technically compromised, socially engineered or sourced from an insider. Too often, in protecting the obvious, we neglect the more subtle, ancillary components of an enterprise that are at greatest risk.

Guidelines for Leaders

The list of actors who pose a threat to the integrity of a firm’s data and DPE is long. It includes the freelancer working from home and ranges from there to petty criminals, organized crime, terrorists and state-sponsored hacking engaged in by nations who believe they are fighting a war on a non-traditional battlefield. Such actors pose various levels and types of risk, but they are all capable in their own way of inflicting severe harm on unsuspecting victims.

There is considerable evidence that the cybercrime industry is rapidly evolving, with actors specializing in various functions. For example, you will rarely be bargaining with the criminals that have ransomed you. These days, ransom negotiations are outsourced to specialists who work on commission and deal with multiple victims. Hackers are becoming as sophisticated as the organizations they prey on.

Cyber threats against an organization’s data as well as its DPE should be considered as part of any organization’s risk management system. These threats should be identified, assessed and managed according to such traditional risk management criteria as likelihood and impact. Threat actors, however,

The list of actors who pose a threat to the integrity of a firm’s processing environment is long.

do not as a rule follow standard enterprise risk protocols. It is thus important that a firm’s leaders ensure the enterprise’s risk management system reflects the complex and rapidly changing nature of the cyber risk landscape.

Cyber risk management therefore needs to reflect an understanding that cyber risk comes in not one but three primary forms: preventable, strategic and external. Let’s take a closer look at each.

PREVENTABLE CYBER RISKS. These risks reside within the organization itself and are thus entirely within an organization’s control. They include employees who click on unknown links or who fall prey to phishing scams, or who download and use apps that pose intrinsic information privacy and other risks. Many Canadian governments, for example, have recently developed criteria to ban downloading of these types of apps onto government-owned hardware.

Such actions make sense because there are no redeeming virtues to being exposed to these types of cyber risks. Leaders, therefore, should take steps to drive such risks to zero, or at least to minimize them cost effectively. One way to do this involves education across the entire organization about proper ‘IT hygiene’ with respect to the DPE, from the most junior employee up to and including the Board of Directors. Other approaches include the dissemination and enforcement of rules. In short, leaders need to create, nurture and sustain an internal culture of control and compliance to minimize preventable threats to the organization’s data and DPE.

Preventable cyber risks also include those posed by a firm’s customers or clients. For example, customers reusing credentials can lead to a breach when those credentials are stolen and used to gain entry at multiple sites. This is what happened to Canada Post in 2019 when it was victimized in a ‘cred stuffing’ attack. To mitigate such risks, firms first must be aware of them. Customers, for example, could then be required to use multi-factor authentication (MFA) before being allowed to access the firm’s website. MFA reduces cyber risk significantly, albeit at the cost of exposure to other risks, including increased friction at the customer interface and subsequent damage to firm revenues and profits.

STRATEGIC CYBER RISKS. This type of risk is taken to achieve the organization’s most important, value-creating objectives. These objectives, typically described in a firm’s strategic plan, might involve specific initiatives like market positioning and competitive

analyses, cost and pricing information, new product and client development, expansion plans and even intellectual property such as patents, unique processes, innovations and inventions. Equifax, for example, is in the credit rating and reporting business. To do what it does, Equifax needs to gather, manipulate and retain a massive amount of sensitive information. In 2017, Equifax was breached and over 150 million of its credit records were stolen. This was, simply, the result of a failure to patch the firm’s software in a timely manner, leaving the company’s entire database open to thieves. Equifax did not consider its software patching process to be a DCJ, trusting instead what turned out to be a flawed verification process. When executives asked if the system had been patched, they meant to ask if the software had been updated and the loophole closed. What IT management thought the executives were asking was whether the patch was queued and therefore in the process of being verified and authenticated before installation. The ensuing one-month gap between verification and installation led to theft of the sum total of Equifax’s strategic value — a breach that has cost the company billions, and the CEO, CIO, CISO, CMO and general counsel their jobs.

Very few strategic objectives entail exposure to zero risk. The pursuit of different objectives to create value and obtain competitive advantage inevitably entails exposure to distinct types and levels of risk. Some strategic initiatives intrinsically involve exposure to more digital risk than others. Generally, the greater the IT content in a business project, the greater the exposure to cyber risk as a by-product of pursuing that business project. For example, transitioning from a bricks-and-mortar to a web-based retail strategy entails more and different exposure to cyber risk than would the opposite transition.

It makes sense to seek out strategic objectives and exposure to the risks that the pursuit of such objectives entails, assuming one believes one will be compensated or rewarded for doing so. But such risks should, if possible, still be reduced, transferred or insured against. Cyber risks, despite being taken in the pursuit of superior returns, can still imperil even well-established organizations. Appropriate steps therefore need to be taken to ensure that, if this happens, the damage will be less than fatal. Strategic cyber risks have some desirable attributes, but it is often hard to distinguish such risks from others. The taking of cyber risks for strategic purposes places a premium on managers’ ability to have a constructive debate and even engage in something akin to an adult conversation about the nature and

value of such risks and how they can best be addressed. Such abilities are not likely to flourish unless leaders establish a culture of constructive confrontation within the top management team and the boardroom that provides an organization’s leadership with the opportunity to develop a realistic understanding of the cost, benefits and risks involved in any strategic IT initiative, and the measures needed to contain them.

EXTERNAL CYBER RISKS. The fact that a risk originates externally does not mean that it can’t be identified or that steps can’t be taken in advance to minimize the fallout that exposure to such risks entails. Sources of external cyber threats may include nation states such as China, Russia, Iran or North Korea. Other sources may not be as obvious, such as COVID-19, which induced organizations to either neglect cyber risk or accelerate their digital transformations without prioritizing security. The effective risk management of external threats to a firm’s DCJs places a premium on a firm’s leaders’ ability to imagine, identify and prioritize such risks. Such threats also challenge a firm’s ability to design effective responses as well as to stress test those responses before they are required.

For example, all firms need to formulate business continuity and disaster recovery plans (BC/DR) to help them respond effectively when they are breached. Imagine that your firm’s BC/DR plans had been obtained by hackers before a successful breach. This may sound far-fetched, but once these plans exist in electronic form, and are stored on your company’s servers, they become a target. Less difficult to imagine is the havoc a cybercriminal could wreak with advance complete knowledge of your firm’s response plans.

The purpose of risk management is not to induce paranoia and panic attacks but rather to allow leaders to manage the firm’s digital risk exposure to keep it within the organization’s risk appetite. So, important but frequently unasked questions for leaders are: How much cyber risk are we prepared to seek out or retain in quest of our business objectives? How much risk appetite do we have for exposure to digital risk by failing to practise proper cyber hygiene within our DPE?

Failure to ask these kinds of questions — or asking them without formulating an actionable and measurable response — can induce either excessive conservatism in managers paralyzed by the thought of something going wrong, or complacency and a propensity for the taking of severe and unjustifiable digital risks. Neither of these reactions is usually performance-

or career-enhancing. To encourage appropriate levels of cyber risk taking, managers need to understand whether the avoidance, mitigation, transference or embracing of all types of cyber risk is a core objective.

Other ways leaders can ensure their organizations’ cybersecurity policies, practices and procedures are gold standard with respect to the myriad threats to their DCJs involve the setting of specific and ambitious goals in this regard. Not only should such goals be set (i.e. ‘The organization will have attained state-of-theart cyber maturity within 12 months’), but also adequate funding for the attainment of such goals should be provided. Further, managers should be rewarded contingent on goal attainment. To ensure such goals are accepted by those expected to implement them, leaders should officially announce their and their organization’s commitment to such goals. Abundant evidence supports the view that specific and ambitious goals that are also widely accepted result in both strong motivation and high performance.

In closing

The widely understood notion of ‘loss aversion’ teaches us that losses are felt more intensely than comparable gains. As a result, getting managers to consider the consequences of failing to act on any initiative will be much more motivating than having them focus on the potential benefits if they do act.

To get started on protecting your digital crown jewels, begin by asking: ‘What are the possible consequences of failing to protect our most precious digital assets in the best conceivable way?’ As indicated herein, the potential cost of failing to act is far too great.

Michael Parent is a Professor of Management Information Systems at Simon Fraser University’s Beedie School of Business and Academic Director of the Rotman and Institute of Corporate Directors’ Directors Education Program in Vancouver and Montreal. Greg Murray serves as Cyber Security and Technology Director-in-Residence for Rotman’s ICD Directors Education Program. He is also Co-Chair of the Canadian Security Telecommunications Advisory Committee and a board member of the Canadian Institute for Cybersecurity. Glen Whyte is a Professor of Organizational Behaviour at the Rotman School of Management and Academic Director of the Rotman and Institute of Corporate Directors’ Directors Education Program in Toronto.

All firms need to formulate business continuity and disaster recovery plans.

September 29, 2023

Reunite at Rotman

Our largest alumni gathering of the year is back with fireside chats, faculty lectures, class reunions and more.

www.rotman.utoronto.ca/reunite

Six Mindsets to Help You Change the World

by John Mullins

WHAT DOES IT TAKE TO SUCCEED as an entrepreneur? I mean really succeed, like Elon Musk, Michael Dell and Phil Knight have. And do these wildly successful founders have attributes that set them apart from other successful business leaders?

I myself am a veteran of three entrepreneurial ventures — with one win, one loss and one draw to my name. I have studied entrepreneurs extensively and have taught and learned from close to 2,000 of them in executive programs at leading business schools and elsewhere. As a result, I’ve observed first-hand the differences between entrepreneurs and other successful businesspeople. It’s their mindsets, I’ve discovered.

A couple of years ago I set out to codify these mindsets to help people everywhere — not just start-up founders — become more entrepreneurial. The six mindsets I have identified break the conventional rules that are widely observed in large organizations, and they fly in the face of much of what we teach in business schools — about finance, target marketing, strategy and more. In this article, I will summarize them.

MINDSET 1: Yes, We Can!

When a customer asks an entrepreneur to do something that they are not currently doing for them, the answer isn’t, ‘Sorry, we don’t offer that’; instead they say, ‘Yes, we can!’ Then they figure out how to deliver on the promise.

Big companies almost never do this. Broadly speaking, leaders are advised to ‘stick to their knitting’: They are supposed to know what their organization’s core competencies are, nurture them and do what they can to make them more robust. If a customer asks for something outside the box, they say, ‘No, I’m sorry, we don’t offer that.’

Entrepreneurs like Brazil’s Arnold Correia personify the Yes We Can mindset. Back in college, Correia and a buddy started hosting fancy Sunday night parties for their fellow students, complete with light shows, music, dancing and more. When he finished college, his buddies started taking jobs in consulting and banking. But he wasn’t ready to give up on his passion for live events.

If there’s one thing the best entrepreneurs do well, it’s breaking the conventional rules of business. Equipped with the right mindsets, so can you.

He asked himself, ‘How can I transfer my skills for running events to the business world?’ He placed a small ad in the media, and almost right away, McDonald’s answered it. The company had a big event coming up and asked if he could manage it. All of a sudden, he found himself in the events business. And given his mindset, it grew quickly.

At an event for Walmart, he was told by the organizers that the person who was supposed to record the event had cancelled. Could he record it for them? Correia thought for a nanosecond and said, “Yes, I can!” He had neither shot nor edited a video in his life, but he got on the phone, worked his network and found someone who could handle the task. Overnight, he found himself in the video production business, as well.

As his business grew, Correia continued to wonder how he could offer his customers more. On a trip to the U.S. to see what Walmart was doing there, he discovered that the U.S. operations were producing ‘corporate TV.’ They had placed TVs in all the stores’ training rooms, and corporate executives could broadcast motivational events and sales meetings in real time to excite and motivate employees around the country.

Correia realized immediately that he should do the same in Brazil. So he prepared a plan to propose to Walmart; but first, he mentioned the idea to another one of his clients, a Brazilian company called Magazine Luiza, a chain of appliance stores. It loved the idea, and six months later, Correia’s concept was in all 200 Magazine Luiza stores.

To accomplish this, Correia had to develop an array of new competencies: satellite broadcasting (the Internet was insufficient at the time); the ability to install video gear across a vast country (to date, his team had only done events in São Paulo) and more, all requiring new skills and new talent. Yes, we can, yet again!

Fast forward to the global financial crisis of 2008-09. Correia realized that in tough economic times, companies cut their costs. He was on the cost side of his customers’ P&L, but he wanted to be on the revenue side. What could he do? He returned to the U.S. for inspiration and found that Walmart was doing something called Digital Out of Home Television. The idea was to place TV screens in the sales areas of the stores; customers walking down the detergent aisle would see a screen broadcasting an ad for, say, a Procter & Gamble detergent — paid for by P&G, of course.

Again, he went to his key customers and said, ‘I’d like to do something new for you.’ It wasn’t long before the Digital Out of Home Television: service at Walmart Brazil accounted for 10 per cent of its profits in a single year. The point is this: Correia transformed his business, now called Atmo Digital, again and again, without regard for his or his team’s current competencies. If a customer could benefit from something, he would figure out how to deliver it.

MINDSET 2: Problem-First, Not Product-First

Logic

Big companies are obsessed with their products, to a fault in some cases. Take for example, the laundry detergent category. My family and I have used Tide detergent for many years, and every time a new brand manager comes along, they tweak the product: They might add green speckles to the powder, change the scent slightly or add more water so the liquid soap pours easier. Does any of this count as innovation? I don’t think so.

Entrepreneurs like Jonathan Thorne, in contrast, start with a customer problem. Thorne, the founder of Silverglide Surgical Technologies, had developed a technology that stopped the surgical instruments used in medical procedures from sticking to human tissue. He asked himself, ‘What are the most common sticky-tissue problems?’ His first idea was plastic surgeons. If they’re doing a face lift for someone and the surgical instrument sticks to the tissue, the final outcome might be marred. That’s not what the patient — nor the plastic surgeon — has in mind!

That’s how Silverglide got started, but soon Thorne realized there were medical practitioners facing much bigger problems with human tissue: neurosurgeons. Working on delicate areas like the brain and spine, this work is very precise. The last thing a neurosurgeon wants is for a surgical instrument to stick to the healthy tissue around a tumor. The business took off, and Thorne sold it some years later, making him and his investors very happy. All because he focused on customer problems.

MINDSET 3: Think Narrowly, Not Broadly, About Your Markets

Big-company wisdom is straightforward: ‘If we’re going to try doing something new, it has to be for a big market.’ Any new product or service has to be big enough to ‘move the needle’ for the company. Otherwise, why bother? The best entrepreneurs, on the other hand, don’t worry about how big the target market is at

It’s easier to solve the problems of a narrowly-defined target market than to make one product that attempts to serve all.

the outset. They realize that if they build a foundation in a narrow market from which they can learn, good things will happen. They start out thinking narrowly, not broadly. After all, it’s far easier to solve the problems of a narrowly defined target market than to make one product that attempts to serve all.

Everyone is familiar with Nike, but perhaps not with its founding story. Back in the 1960s, Philip Knight and Bill Bowerman became concerned about a problem that elite distance runners like Knight were facing. Bowerman was Knight’s track coach at the time, and the shoes that long-distance runners were wearing were made for sprinters. This was problematic, because distance runners didn’t run around paved tracks. They trained on country roads and dirt paths that were littered with sticks and stones — and, as a result, they were plagued by sprained ankles and shin splints.

Knight and Bowerman realized that distance runners needed a better shoe — more lateral stability, more cushioning and lighter in weight, for faster race times, too. They started a company called Blue Ribbon Sports and began selling shoes out of the back of Knight’s station wagon. It took five years before Knight could quit his day job and devote himself full-time to the business. But once the world’s best distance runners started wearing his shoes to win Olympic medals, guess what happened? Other runners wanted to wear the shoes, too.

Along the way, Knight and Bowerman learned how to design athletic shoes; how to do sourcing in Asia; how to tap elite athletes to advise what they needed in a shoe — and, equally importantly, to endorse it. Before long they had John McEnroe on board for tennis shoes and Michael Jordan for basketball shoes.

The point is that you can start out with a very narrow target market. Knight and Bowerman’s initial target market — elite distance runners — were few and far between. If there was ever a prize for the smallest target market, they might win it; but we’ve all seen the astronomical growth that followed for Nike. The takeaway: Build a solid foundation in a narrowly defined target market, then grow from there.

MINDSET 4: Ask For the Cash and Ride the Float

Today’s big corporations are awash with cash. Many have too much actually, and don’t know what to do with it. So, they return it to shareholders via dividends or spend lots of money buying back their own stock, because they can’t figure out something

better to do with all that cash. Case in point: In 2018, Merck spent $18 billion on buybacks and dividends, but only $10 billion on R&D.

What do world-class entrepreneurs do? When Michael Dell started his computer company, his customers had to pay for their computers before they were even built. Dell used that up-front cash to assemble the computers and do all the other things required to run the business. I call this ‘riding the float,’ and Dell isn’t the only company to put it into practice.

In the beginning, Elon Musk and his Tesla co-founders had a plan: They would build a fancy sports car, then use the proceeds to build market awareness and a slightly cheaper car; and then they would do this again, over and over. In 2006 Musk and the team set out on a road show in California. Within three weeks, they had sold 100 Roadsters at $100,000 each, paid for up front, to people who were environmentally conscious, wealthy and thought it would be cool to have a Tesla Roadster parked in their driveway.

Let’s do the math: 100 Roadsters at $100,000 each provided Musk and team a cool $10 million, with which they set out to start building more cars. This principle of getting a deposit up front was, to the surprise of many, a key source of Tesla’s funding along its entire journey. Yes, Tesla raised venture capital, although much of it came from Musk himself; but the key thing they did was get deposits up front.

When Tesla introduced the Model 3, its lowest priced car yet, in 2016, nearly half a million people put down $1,000 deposits to get their hands on one. Let’s do that math: Half a million deposits at a $1,000 is half a billion dollars paid up front, before the first Model 3 had even gone into production. That money went a long way towards funding the engineering, building the tooling, fitting out the factory and much more.

The lesson: Best-of-breed entrepreneurs find a way to get the customer to pay up front and, riding the float, they then use that cash to do all the things they need to do to grow the business.

MINDSET 5: Beg or Borrow (But Please Don’t Steal) the Assets You Need

If you’re going to try something new, you have to invest in it. In the retailing industry, for example, if you want to try a new store concept, you’ve got to build out a prototype store and stock it with inventory. But before proceeding, you’ve got to forecast

the cash flows you expect to reap — and only if your figures meet some predetermined ROI hurdle rate will the project go ahead.

But why invest in assets if you can ‘borrow’ them — at least until you can prove your concept will work? Entrepreneurs Tristram and Rebecca Mayhew of Go Ape did just that. While on vacation in Europe, they came across an interesting tree-top adventure business located smack dab in the middle of a forest in France. Wouldn’t it be cool to bring something similar to the UK, they thought?

Once home and eager to move forward, they discovered that the most important landowner in the UK was the UK Forestry Commission, which had sites all over the UK, each equipped with a visitor centre, huge parking lot and washrooms. Tristram went to the Forestry Commission and said, ‘Look, we know you’re trying to grow visitor traffic to the forests. We’ve got an idea that might help you do that.’ They described how they’d like to build Go Ape ‘treetop adventure sites’ in the forests.

The foresters loved the idea and struck a deal; if Go Ape could build six sites within five years, the Commission would give them an exclusive for the rest of their sites that would last for 25 years. That would certainly be long enough to keep any competition at bay.

Go Ape ‘borrowed’ numerous resources: the trees (so they didn’t need to use telephone poles (like most zipline operators did), the parking lots, the visitor centres and the loos, paying rent in arrears. Sure, they still required some investment: They had to build the Tarzan swings, ziplines and other attractions within each forest. But it turned out that within two years, given the modest investment, a typical park would be able to pay back that investment in full. Today, Go Ape operates more than 30 locations throughout the UK — and has a growing portfolio in the U.S., too. The lesson? If you think you need to invest in your next project, think again — and find a way to borrow what you need, instead.

MINDSET 6: Don’t Ask for Permission (Beg Forgiveness Later).

In a big company, if you want to try something new, you need to ask for permission. Most big companies have armies of lawyers whose key job is to make sure nobody ends up in jail. Thus, it’s really hard to get permission to do something new, especially if the proposed project is something entirely new that lawyers and regulators don’t yet understand.

Entrepreneurs like Uber’s Travis Kalanick and Garrett Camp, don’t ask permission. They just get started. The Uber team knew that existing regulations applied to taxi companies. But they were not going to be a taxi company. Instead, they would be a marketplace. They would bring together people with cars with people who needed to get somewhere. Existing regulations didn’t apply to that, in their view. While I surely don’t applaud some of the ways in which Uber built its business — some of them unethical and perhaps illegal — the principle of acting boldly when the regulatory frameworks are ambiguous has given birth to the rapidly growing ‘gig economy,’ whether we like it or not.

Of course, we know what happened with Uber and Grab and all the others who took such bold action: By the time they had to deal with regulators, they already had a slew of customers on board who wanted their service to survive. They had become too big to shut down, and too valuable to consumers.

In closing

Do you embody one or more of these six mindsets already? Are there some that you could teach to your team, to help them become more entrepreneurial? I would be willing to bet that at least one of these mindsets could help you break through on a challenge you are currently facing. If there’s one thing that the best entrepreneurs do well, it’s change the world — or at least their small corner of it. And equipped with the right mindset, so can you.

John Mullins is an Associate Professor of Management Practice in Marketing and Entrepreneurship at London Business School. He is the author of Break the Rules! The Six CounterConventional Mindsets That Can Help Anyone Change the World (Wiley, 2023).

By the time it had to deal with regulators, Uber already had a slew of customers onboard who wanted their service to survive.

Q &A

You have noted a radical shift in the way value is being created today. Please describe it.

It used to be enough for an organization to focus on getting better at what it does. Today, that isn’t enough; you need to get better at what you do and explore ways to reinvent yourself at the same time. It’s the classic balance between exploitation and exploration. It’s not that one is better than the other; every organization needs both cultures under their roof. The challenge is that the logic of experimentation is completely different. You might invest in 10 projects and only one will actually work out.

As a result, you believe innovation needs to be measured in a whole new way. What needs to happen?

It’s very simple. In the world where you’re managing your existing business, you can continue to measure return on investment (ROI). You can still make projections and expect to achieve them within a certain time frame, at least in part. But when it comes to exploration, you can’t know ahead of time if a project is even going to work. So how can you measure that side of the business?

My advice is this: Rather than measuring ROI in your exploratory work, measure ROP — return on portfolio. Let’s say your company decides to invest in 100 ideas. Portfolio theory tells us that a small number of them are going to succeed — and that those successes will pay for all the other failures. If you look at venture capital, only one out of 250 ideas or early stage start-ups wins big. The implication for established companies is that they need to spread their bets. The CFO, the CEO and the Chief Marketing Officer all need to think about how these two completely different types of returns can coexist under the same roof.

What are some powerful approaches to exploration?

Interview by Karen Christensen

We call top-level explorers Visionaries, and they are usually entrepreneurs. They use their imagination to find huge market potential where others don’t and are able to satisfy unmet needs with new value propositions. Examples include Tesla cars, the iPhone and Nintendo Wii. Another approach is what we call the Repurposer. These companies find innovative ways to tap into proven market demand by

The Thinkers50’s fourthmost-influential management thinker explains how to be more innovative — invincible, even.

QUESTIONS FOR Alex Osterwalder, CEO, Strategyzer and Author, TheInvincibleCompany

repurposing existing technology and/or infrastructure that previously served other ends. AWS (Amazon Web Services) and M-Pesa (Africa’s leading payment method) are successful examples of this approach.

Should different people be running each side of the business?

It’s hard to find people who can do both. The famous example is Steve Jobs. In the early days of Apple, he failed. He wasn’t able to run an execution machine because he was an innovator. Later, when he returned to the company, he had become world class at hiring the right people to run the existing business. He understood that innovation was a separate endeavour and that he needed to hire the right people to create the future under the same roof as those executing the present. This mindset represents a new type of leader who is able to switch from one role to the other within milliseconds, and we call them ‘entrepreneurial CEOs.’

Another option is to have co-CEOs: one is the Chief Execution Officer and the other is the Chief Entrepreneur. This approach, in my opinion, is better, because you can have two people who are 100 per cent dedicated to completely different aspects of the business. However, they must get along well, because a project that grows out of exploration will eventually be handed over to the execution side. And the CEO who runs the current business needs to understand that the Chief Entrepreneur will need access to some of the resources of the exploitation side of the business.

You’ve become an expert on innovation risk. What key learnings can you share?

Innovation risk is the risk that a business idea is going to fail. Risk is high when there is little evidence beyond impressive slides and spreadsheets to support an idea, and it decreases with the amount of evidence supporting four things: desirability, feasibility, viability and adaptability.

The danger posed by desirability risk is that customers just aren’t interested. The market being targeted is too small, too few customers want the value proposition or the company can’t reach, acquire and retain targeted customers. With viability risk, the risk is that a business can’t generate successful revenue streams, that customers are unwilling to pay (enough) or that the costs are too high to make a sustainable profit.

Feasibility risk is the risk that a business can’t manage, scale or get access to key resources (technology, IP, brand etc.), key activities or key partners. And lastly, adaptability risk is the degree to which external factors are unfavourable — that a business won’t be able to adapt to the current competitive environment, technology, regulatory, social or market trends, or that the macro environment is not favorable (due to a lack of infrastructure, recession, etc.)

The way to manage these risks is by constantly exploring and only investing significantly in those few projects that show signs that there is something there — based on evidence. If there is such evidence, the team receives more funding; if not, the project is halted. But here’s the good news: the teams that don’t get follow-up investments can try again in a year or two. You don’t punish people for trying and failing. Everybody in a company should be allowed to prove they have a great idea by getting some time to explore, and you need a rigid process for that. It’s about saying ‘Here is some funding. Come back to us in three months with evidence that customers actually care about this.’ That’s how you find the best innovators — you let them emerge by creating the right system around them.

Talk a bit about the importance of being able to pivot while exploring.

The journey in the exploration portfolio is one of searching and pivoting until you have enough evidence that the new idea will work. The search for ideas, value propositions and business models that will work consists of two main activities that continuously nourish each other: business design and testing.

Business design is the activity of turning vague ideas, market insights and evidence from testing into concrete value propositions and solid business models. Good design involves the use of strong business model patterns to maximize returns and compete beyond product, price and technology. Testing is the activity of reducing the risk of pursuing ideas that look good in theory, but won’t work in reality. You test ideas by defining critical hypotheses, conducting rapid experiments and learning from the evidence. But be ready for the evidence to either support or refute the value propositions and business models you are exploring.

There is this myth that creative geniuses are just born that way. But the reality is that innovation is like medical

Everybody in a company should be allowed to prove they have a great idea by getting some time to explore.

The Art of Business Model Portfolio Management

Designing and maintaining a strong business model portfolio requires three main activities:

VISUALIZE

The starting point for any good discussion, meeting or workshop about your business model portfolio is a shared language to visualize it. You need a shared understanding of which business models you currently have and which ones you are exploring.

FIGURE ONE

school. Of course you have to learn all about anatomy and physiology; that’s the theory part. But then you also have to do an internship to learn how to put it all into practice. It’s the same with innovation. It demands a combination of business theory and practice.

Are there companies out there who are doing all of this really well?

One example is Bosch, whose R&D led to successes such as the diesel injection pump and the antilock brake system. In 2014, CEO Volkmar Denner sent out a communication to spur business model innovation. He told people that Bosch needed to maintain its technology and product focus but simultaneously turn more of its attention to new business models. In 2015, they created an actual Business Model Innovation Department. They saw a need to create an ecosystem dedicated to exploring, nurturing and facilitating growth innovation, moving beyond product innovation.

Next, that department created an Accelerator Program.

ANALYZE

A shared understanding of your business model portfolio allows you to identify if you are at risk of disruption and if you are doing enough against it. This includes analyzing which of your business models are most profitable, which ones are most at risk and which ones you are exploring to ensure your future growth.

MANAGE

This includes continuously growing and improving existing business models by shifting outdated ones to new business models and protecting those that are established. It also includes exploring completely new business models — of which many will fail, but some will produce outsized returns and ensure your future.

Teams going through the program explore either a new idea or explore a concept originating in an existing business. The program managers select an initial cohort of 20 to 25 teams from all over the world that work together for two to 10 months. Each team receives initial funding of $120,000 and gets two months to test whether their idea can scale. Depending on the results, they can then obtain an additional $300,000 or more during Phase 2 of the program, so they can test minimum viable products with customers and demonstrate the ability of the business model idea to scale profitably. Only the teams with the best evidence move on to Phase 3, the incubation phase.

Since 2017, Bosch has invested in more than 200 teams. Seventy per cent had to retire their projects after the first investment round and 75 per cent of the remaining teams stopped after the second. With this process, 15 teams have successfully transferred their projects to scale with followup funding. Bosch has succeeded at creating a global standard for validating new business ideas.

Potential Steps in The Exploration Journey

PROMISING CONCEPT

Large financial potential

+ weak-to-no evidence of success

NICHE OPPORTUNITY

Small financial potential

+ weak-to-no evidence of success

RISING STAR

Large financial potential + strong evidence of success

Small and large companies that constantly reinvent themselves have an enormously positive impact on society. They provide economic growth and potentially game-changing innovations. The best of them put environmental and societal impact at the centre of their endeavours to change the world for the better.

SAFE PLAY

Small financial potential + strong evidence of success

You need to understand which parts of your business have further potential to grow, which parts need renovation and which are at substantial risk of disruption. You also need to understand which initiatives have the potential to define tomorrow’s business.

Your most recent book is called The Invincible Company

How do you define that term?

We chose that title to be provocative. The reality is, the moment you start believing you’re invincible, you’re probably going to get disrupted. The most successful companies are those that recognize there is no such thing as invincibility, so instead, they constantly reinvent themselves. You can love or hate Amazon, but from the start Jeff Bezos always said to his teams, “We need to keep a mindset of Day One. When we lean back and adopt the mindset of Day Two, that will be the end of us.” Even in the midst of huge success, they were always trying new things. Likewise,

today’s leaders need a mindset that invincibility doesn’t exist. And as soon as they adopt that mindset, ironically, they actually do become invincible.

Alex Osterwalder is Founder and CEO of Strategyzer, a Visiting Professor at IMD Business School and creator of the Business Model Canvas. He is the co-author of The Invincible Company: How to Constantly Reinvent Your Organization with Inspiration From the World’s Best Business Models (Wiley, 2020). He is currently ranked No. 4 along with his business partner Yves Pigneur on the Thinkers50 list of the world’s most influential management thinkers.

FIGURE TWO

Sheena Iyengar, Professor, Columbia Business School and Author, ThinkBigger

Want to Solve a Big Problem? Start Small

I’LL START THIS ARTICLE OUT with some words to live by: If you want to solve a big problem, it’s often best to start out thinking small. That advice might sound backward, but it is informed by my decades of experience in this space. To illustrate, let’s take a really big problem: the elimination of segregation and racism in the United States.

Dr. Martin Luther King once said, “I have a dream that my four children will one day live in a nation where they will not be judged by the colour of their skin but by the content of their character.” Dr. King imagined a world where race no longer mattered. This was a lofty dream that, sadly, he did not achieve in his lifetime. But what he did achieve was leading a movement that forced Congress to pass the Civil Rights Act of 1964, making racial discrimination illegal. That was a remarkable achievement. How did he do it?

Dr. King started small, with the Montgomery bus boycott. Inspired by Gandhi’s campaign of non-violent disobedience in India, the Black residents of Montgomery, Alabama — most famously Rosa Parks — boycotted the

segregated bus system and went to jail for it. It worked, which inspired the Southern Christian Leadership Council to do it again and again across the south. In turn, that led to the Student Non-Violent Coordinating Committee, where thousands of college and high school students were arrested for sitting at white lunch counters and other segregated venues.

The result was a mass movement. And that’s how a quarter of a million people were there on the day of Dr. King’s unforgettable speech — the largest gathering in the history of the U.S. up to that time.

Now, in contrast, consider a seemingly mundane problem: how to make watching movies at home more convenient. Reed Hastings set out to answer that question. He had faced this issue directly when he had to pay $40 for returning a movie late to Blockbuster (the movie was Apollo 13). On the drive to Blockbuster he passed a gym and had a realization: nobody pays a late fee for gyms. They require a monthly fee. And with this fee, you’re allowed to go as many or as few times as you want. Why not do the same for videos?

Hastings had just sold his software company, so he had time and money to work on the problem. Online commerce was coming — Amazon was already big — so he wondered if he could cut costs by skipping physical stores. Why not use the mail instead? Keep in mind the technology of the day. This was just when the DVD appeared to rival videotape. So, Hastings bought a DVD and mailed it to himself. It came through fully intact. Like Henry Ford, Hastings drew on a new technology, not simply because it was there but because he could see the piece of his problem it solved: delivering movies safely to people’s homes.

Thus was born the Netflix empire, which would go on to command a US$82.5 million IPO and at last count, had a market cap of $160 billion. The important point here is not Netflix’s success; it is the methodical way in which Hastings approached problem-solving in structured steps. Only after solving the smaller late-fee problem did he move on to solve a bigger problem: how to make watching movies at home cheap and easy for everyone. Hastings would never even have dreamed of that bigger problem if he hadn’t solved the smaller one first.

The message here is not to lower your sights. Dr. King never gave up on his dream of a nation where race didn’t matter. But he found a way to make progress toward that goal by solving smaller problems first. In my latest book, Think Bigger: How Innovation Works, I outline a six-step method for taking advantage of lessons learned from neurological and cognitive science to generate our best ideas. Here, I will share the first and most important step: identifying the problem you want to solve.

The key is to identify a problem that is big enough to matter but small enough to be solved. It should also be a problem that everyone involved understands and wants to solve. This step is crucial and takes time, effort, revision and reflection to appropriately make a determination of the problem before you move on to solving it.

Once you pick out the problem from your longer list that you want to set out to solve, rewrite it as a question of ‘how.’

For example, say you want to grow your business by 10 per cent this year. Rewrite that as ‘How can I grow my business?’ That is what you need to figure out, whether your goal is nine per cent or 11 per cent, this year or next. Once you come up with a solution, you will have an idea of what is possible and when. At that point you can say, ‘By implementing this solution, I see how I can grow my business by 15 per cent over the next nine months.’ This kind of detail comes later, in your implementation plan. It is not part of solving the problem of how to get there.

Our initial problem phrasing is open-ended enough to permit many possible answers. A common mistake is to embed a single answer in the question. For example, ‘How do I create a mobile application to reduce food waste?’ This assumes that the answer is a mobile app. We rephrase that to say, ‘How do I reduce food waste?’ Even among my students, an average of 51 per cent jump to the idea that an app should be their solution — and while it very well might be part of the solution, the app doesn’t necessarily solve the problem they identified.

Always remember: closed questions reduce your chances of being creative by suggesting there is a single ‘correct’ solution to your problem. Open questions give you more choices for creative solutions. This is true even as you narrow down your question.

Once you’ve decided on your open-ended ‘how’ question, you can test whether it’s too broad or narrow. To do this, think of an upside-down pyramid. Up top, at the widest level, you have the huge problem. At the bottom, the narrowest level, you have a tiny problem, and in between are different gradations. You move up or down the pyramid, making your problem wider or narrower, until you find the right level.

I call this Step Analysis: ‘Step up’ to widen your problem. ‘Step down’ to narrow it. Step up and your solution makes a bigger impact, but it’s harder to solve; step down and your solution makes a smaller impact, but it’s easier to solve. Your motivation works both ways: you want to make a bigger impact, but if the problem is impossible to solve, it

Reed Hastings would never even have dreamed of solving that bigger problem if he hadn’t solved the smaller one first.

Sample Step Analyses

Step Up: Reduce all harm to the environment

Step Up: Reduce all polution

DRAFT PROBLEM: Reduce plastic pollution

Step Down: Reduce single-use plastic bags

Step Down: Reduce single-use bags in my neighbourhood

Step Up: Replace all non-biodegradable materials

Step Up: Replace plastic with biodegradable materials

DRAFT PROBLEM: Reduce plastic pollution

Step Down: Replace all non-biodegrable materials

Step Down: Reduce plastic pollution in my city

saps your desire to work on it. Move up and down the steps until you find the level where your motivation is the greatest. That’s the problem you want to solve — what I call your personal sweet spot.

Take a look at the sample Step Analyses above. Put your draft problem question in the middle tier. Then restate the problem, up and down, until you arrive at the sweet spot. If you’re in a group, do this first as individuals, then pool your charts to arrive at a single one for the group. You will find that people step up and down to very different problems.

For example, let’s say your question is, ‘How do we reduce world hunger?’ One person might ‘step down’ to ‘How do we reduce hunger in the poorest countries?’ Someone else might step down to ‘How do we reduce hunger among poor people in rich countries?’ You can see right away that these details matter. These two different questions will send you on the hunt for very different solutions. Each step up or down represents a crucial decision in defining your problem.

In the process of stepping up or stepping down your problem, you might find that you want to frame the problem in a completely different way. That is an important lesson to learn because it gives you the opportunity to explore and examine the different ways you can address your problem, until you find one that is just right.

If you skip this step and press on with your first problem statement, you’re in for some nasty surprises down the line. In a group, such surprises can lead to conflict or gridlock. So don’t be afraid to have a full and honest discussion up front, where each member of the group can talk about their own Step Analysis and explain the rationale behind it. When you’re working with a group, the group needs to find a sweet spot that keeps everyone motivated, interested and eager to solve the problem.

Once you arrive at the sweet spot, do a final check by asking two questions:

1. Can we feasibly solve this problem?

2. Are we motivated to solve this problem?

If the answer is yes, you are ready to proceed.

In closing

While you as an individual creator can’t predict the future, here’s what you can do: be clear about the problem you want to attempt to solve — and gain clarity about why you want to solve it. You can also work to understand why solving the problem is valuable and how the solution you have come up with works. If you can do all of that, I have good news for you: you are already thinking bigger.

Sheena Iyengar is the S.T. Lee Professor of Business in the Management Division at Columbia Business School and the author of Think Bigger: How to Innovate (Columbia Business School Publishing, 2023). She received the Financial Times and Goldman Sachs Business Book of the Year Award for her 2010 book, The Art of Choosing. Her TED Talks have received over four million views.

FACULTY FOCUS Eric Kirzner, Professor Emeritus of Finance, Rotman School of Management

Meme Stocks: A Cautionary Tale

MOB MENTALITY. Groupthink. Pack behaviour. General strikes. Sports events. All are forms of herd behaviour, which occurs whenever a large number of unconnected people act in the same way at the same time — sometimes with direction from others, sometimes not. Fuelled by fear, greed or a desire to be part of a particular group, individual judgment and opinion-forming processes shut down as people automatically follow the group’s behaviour.

Herd behavior can have both positive and negative effects, depending on the situation. For example, it can lead to increased efficiency and safety in a group. But it can also cause people to make irrational or dangerous decisions. In the realm of investing, herding results when investors copy the behaviour of other investors. And like many forms of herd behaviour, the results can be catastrophic.

This behavioural phenomenon underlies some of the biggest stock and property bubbles in history, including some very recent ones. The bubble metaphor stands for assets — real or financial — that are based on nothing but air and subject to sudden bubble bursts. A bubble is when specific asset prices (such as stocks, or real estate or

precious metals) far exceed their intrinsic value. Bubbles are often perpetrated by scoundrels exaggerating or lying about the real value of the investments, although sometimes the bubble is created through irrational exuberance of the crowd itself.

For those interested, you can read about some of the early bubbles, beautifully documented by Charles Mackay in Extraordinary Popular Delusions and the Madness of Crowds. In it, he describes the Dutch Tulip Mania of the 1640s, the South Sea Company bubble of 1711–1720, and John Law and the Mississippi Company of 1719–1720.

Modern-day financial bubbles include the 1982-1989 Japan stock and real asset crash, the 1999-2001 dot-com bubble, the 2007-08 teaser-mortgage-created global financial crisis and various cryptocurrency bubbles, including the one that occurred in May 2022. But a relatively new form of micro, isolated bubbles has emerged: meme stocks.

But first, a look at how this all began. The growth of the Internet has fostered a whole new wave of investing and disseminating investment advice — and hype. Online chat and discussion rooms developed in the 1990s, and a favourite topic was the dot.com stocks that were leading the 1990s disinflation market rally. The activity of chat room traders

was a contributing factor in fuelling the dot.com price explosion of the 1990-2001 period.

Chat rooms have since morphed into modern-day social network chat rooms. Users — many of whom are small, often inexperienced investors — post messages about their investment ideas and recent stock purchases and in some cases, exhort others to join them. It is very easy to trade small quantities today using online services, direct trading accounts (with $10 or less commissions,) and investing apps, some of which have ‘free’ trading accounts.

One of the most popular platforms is r/WallStreetBets (WSB) on Reddit, a social news network, where a large group of users, some organized and some independent, share stock tips, make predictions, engage in contests and share trading experiences. The WSB group isn’t new; it started about a decade ago and now has millions of users. If you go to the site you will see thousands of messages about purchases and trade opportunities — and plenty of bragging about trade successes. Some of the ideas are logical and some are pretty wild. It’s pretty much a Wild West trading show, although in in fairness they do have posted rules. Some of the rules and guidelines are (please excuse Reddit’s colourful language):

• Your gains and losses must be realized if you want to talk about them.

• Avoid pump and dumps, short squeezes and market manipulation.

• No bulls*!tting: only comment if you know what you’re talking about. Don’t make s*!t up, and be responsible when giving and taking advice. This includes talking about things you don’t know about. You should listen, not talk. Nobody wants an ill-informed opinion.

• Paper trades don’t count as real trades and are forbidden as standalone posts. Nobody gives a s*!t about your preschool’s trading competition, don’t ask us for help.

• No advertisements, self-promotion, fundraising or begging.

So-called ‘meme stocks’ are favourites of the chat room crowds. A meme stock refers to the shares of a company that have gained online attraction and popularity on social media platforms. These online communities can focus huge attention resources toward a particular stock. The meme

stock movement unofficially started in the summer of 2020 when most people were stuck at home during the first few months of the pandemic. Looking for something to do and a way to turn some of that extra free time into money, many people turned to the stock market and social media for ideas.

Last year in this publication, I wrote about what was then the poster child of meme stocks: GameStop. I explained how GameStop (GME) — the world’s largest video game seller, but an unprofitable company — went from $15 a share in 2020 to $483 a share in January 2021 due to a shortsqueeze perpetrated by chat room traders. WSB and others were not only buying GME, they were buying and talking up some other companies with large short positions, including AMC Entertainment and BlackBerry. GME traded as high as $483 a share at one point giving the company a market value about $24 billion — about 80 times greater than its closing 2019 value. In the short run, the WSB group won, hands down.

The hedge funds were caught in a classic ‘rising price short squeeze.’ For those who aren’t familiar with the term, this is an unusual condition that triggers rapidly rising prices in a stock or other tradeable security. It occurs when a security has a significant amount of short sellers, meaning lots of investors are betting on its price falling. The short squeeze begins when the price jumps higher unexpectedly and gains momentum as a significant measure of the short sellers decided to cut losses and exit their positions.

With enormous losses piling up, huge margin calls and no stock to deliver, sector leaders like Melvin Capital and Citron Capital (and possibly others) gave up, covered their shorts and took enormous losses (with Melvin shutting down in May 2022.) It all came to an end as the reality of the company’s real value finally took hold. The buying momentum ended with a whimper. With the shorts now out of the market, buying in GME dried up, the bubble burst and the stock sunk.

Today, GameStop stock is priced at $19, close to where it was when this all started, and it’s almost like nothing ever happened. But not quite: the mayhem is not forgotten. There is an entertaining TV series called Eat the Rich: The GameStop Saga and a movie coming out later this year titled Dumb Money, starring Seth Rogen as hedge fund manager Gabe Plotkin.

The meme stock movement unofficially started in the summer of 2020, when most people were stuck at home.

The latest chapter in the meme stock saga is Hong Kong-based fintech firm AMTD Digital, and it tops GameStop in sheer audacity. AMTD Digital (ticker: HKD) went public on the New York Stock Exchange in July 2022, priced at $7.80 a share. Based on the earnings per share, sales revenue, other metrics and current prospects, the IPO was probably fairly valued. Here is how the company described itself in its prospectus:

Our mission is to act as fusion reactor for the best entrepreneurs and innovative ideas fusing synergistically all elements within the AMTD Spidernet ecosystem using digital means, harnessing and magnifying the power from each partner to create a force with meaningful and influential social, technological and economic impact.

An ambitious vision, to say the least. So, what happened next? The IPO exploded out of the blocks in early August, and within a few weeks rose to $2,225 per share during the day on August 2. Undoubtedly this was some type of record for aftermarket trading for an IPO. Its $360 billion market cap made it at that time one of the most valuable companies in the world based on market capitalization: worth more than Coca-Cola, Shell, Facebook and Costco. The ticker HKD was the most popular mention on the WSB chat room, but WSB users denied being involved. CNBC called HKD “The $300 billion meme stock that makes GameStop look like child’s play.”

As is always the case, gravity quickly took hold and the stock came back to earth. It then fell steadily into 2023. But the meme traders didn’t forget about it. On January 5, it traded over 40 million shares and hit $37.72 after closing at $10 the day before. That petered out quickly and lo and behold, at press time it is back to $6.75 — very close to its IPO price. Thus concludes — at least for now — one of the great bubbles in stock history.

To date, no person or group has taken credit for the bubble. Certainly not the company. In August 2022 it stated: “To our knowledge, there are no material circumstances, events nor other matters relating to our company’s business and operating activities since the IPO date.”

Meme traders remain very active, gravitating to companies with large short positions. They seem to particularly like

companies that have announced bankruptcy such as Revlon and Bed Bath and Beyond. To top it off there is a meme stock exchange-traded fund (ETF.) The Roundhill Meme ETF tracks a meme index of companies that exhibit a combination of elevated social media activity and high short interest, both of which are indicators of market sentiment. Under normal circumstances, at least 80 per cent of the fund’s net assets will be invested in meme stocks and it will invest in all component securities of the index in approximately the same proportions as in the index.

All in all, meme stocks and meme bubble trades appear to be here to stay. And while they represent a tiny portion of the overall investment landscape, the ethical and regulatory challenges posed by both are formidable.

A final note. After he initially made some money, Sir Isaac Newton apparently lost virtually all of his life savings in 1720 by buying back into the South Sea Co. His famous quote at the time: “I can calculate the motion of heavenly bodies, but not the madness of people.”

Oh, the irony. Of all people, you would think that the discoverer of the law of gravity would have recognized that what goes up comes down — and usually faster.

Eric Kirzner is Professor Emeritus of Finance and the John H. Watson Chair Emeritus in Value Investing at the Rotman School of Management. He has served as director and Audit Committee Chair at Equitable Trust, a director of the Investment Industry Regulation Organization of Canada (IIROC), a director of Deutsche Bank Canada and an external advisor for the Healthcare of Ontario Pension Plan. Author or co-author of 13 books, he has written for The Globe and Mail, the Financial Post, Maclean’s, Investors Digest, The Canadian Investment Review, Benefits Canada and the Toronto Star

HKD was called “The $300 billion meme stock that makes GameStop look like child’s play.”

Q &A

Interview by Matt Abrahams

We’ve heard a lot about difficult conversations, but you believe all conversations are difficult. Please explain. In recent years we have heard a lot about so-called difficult conversations from the realm of academic research and in the public discourse. The focus has been on conversations like negotiations, delivering constructive feedback, giving hard advice or other things that we have come to think about as difficult. But what I’ve come to realize through my life, teaching and research is that even easy conversations are difficult.

That’s because every conversation we have involves uncertainty and a lack of control. We are co-constructing this interaction right now, Matt. I don’t know what you’re going to say next; I don’t know what you’re thinking — and I can’t possibly know. I can’t control how you react to what I say or what you think of me. That uncertainty is always there.

An expert on difficult conversations explains why all conversations are difficult—and what to do about it.

QUESTIONS FOR Alison Wood Brooks, Behavioural Scientist and Professor, Harvard Business School

Once you delve into the complexity and nuance that live and breathe within each conversation, you begin to see why conversations are so hard — even when our goals align and when our only goal is to have fun. We might say the wrong thing. We don’t know how other people are feeling or what they’re thinking about. If you can make each conversation just a little bit better, over your lifetime it will make a massive difference for you, your career and for the people you love.

Talk a bit about what you call the mechanics of conversations.

Few people ever think about these things, but they underlie every conversation you have. One aspect is turn-taking. I speak, then you speak, and then someone else speaks, then I speak again. Ideally, you try to avoid as much crosstalk and overlapping turns as possible. One thing you can start to think about is the time gap between turns. Research shows that shorter pauses between turns, or inter-turn silences, indicate that you’re closer with the other person or people, that the discourse is exciting and/or it’s going well. You’re clicking.

Another aspect I study is topics. Once we’re on a particular topic, how do we steer it ahead in a direction that serves my purposes and your purposes best? And how do we manage the boundaries between topics? What we don’t realize is that we are making these micro-decisions constantly. Literally every time you speak, you’re choosing whether to stay on topic or switch to something else.

Then, there’s the content of conversations, which is made up of three streams. The first is verbal, the words we say to each other. The second is nonverbal, with pertains to how your body is moving, your hand gesticulations, your facial expression, your eye gaze. Everything that you can perceive visually about other people.

Then there’s a third bucket, which people tend to know the least about, and that’s paralanguage. This consists of everything about how we’re talking to each other that is not words. Words are the carriers of meaning, but paralanguage can change the meaning of them. It can include the tone of my voice, how fast I’m talking, my pauses, whether I laugh when I say something. There are many aspects of paralanguage that can completely change a conversation.

Describe the difference between ‘supporting choices’ and ‘shifting choices’ within a conversation. Every time someone speaks, they are making a microdecision that you can imagine as, ‘I am either going to support the topic or I’m going to switch.’ That’s a good heuristic, but actually, there is some gray area in between those two poles. There is also, ‘I’m going to actively encourage us to stay on this topic’ by saying, ‘Oh my God, that’s amazing. Tell me more,’ which is very different from saying ‘Uh-huh.’

Sometimes there are really aggressive switches to new topics, where we’re talking about something and someone says, ‘Guys, let me tell you about my chicken salad sandwich. It was so yummy. Everyone should eat chicken salad.’ When we’re making choices about how to manage topics, there are degrees to which you can support the current topic or switch to something new.

What we find in our research is that people who assertively switch topics in those moments are great conversationalists. They can sense if there are long pauses, if there’s awkward laughter, if people start repeating things they’ve already said, and they recognize these as signals that it’s time to switch. Doing this assertively is something we can all aim to do a little bit better. The risks are quite low, because if either party feels like they actually have more to say, they can always come back to it. That’s the amazing thing about conversation. You can always go back and say, ‘Oh, wait.

People who assertively switch topics are great conversationalists.

There’s one more thing I wanted to mention, and this was the thing I meant to tell you all along.’ Or you can text or email this to them afterwards.

We have this instinct to be a bit afraid to switch topics because it feels rude or abrupt. We worry the other person has more to say, when in fact it’s much safer and usually a good idea to switch to something new, because boredom and stagnation are even bigger risks.

Small talk is a fact of adult life, but it can be really challenging for some people. What advice do you have for those who dread it?

Small talk gets a really bad rap. Its purpose is to help us coordinate around more important topics. Everything about conversation is this sort of coordination kerfuffle. We’re trying to coordinate with another human mind, ‘What should we be talking about? How should we be interacting here? What do I feel safe sharing with you? Small talk is really useful. It’s the predictable way that we open up this really crazy experience we’re about to have together.

There’s an amazing article from The Atlantic called “Ode to Small Talk” by James Parker. He has this amazing quote: “The merest morsel of speech can tip you headfirst into the blazing void of another person’s soul.” That’s pretty dramatic, but it captures the spirit of ‘we are preparing to discuss a topic that we are both excited to move on together.’ If you lean in to small talk, it can become less awkward.

What does it mean to be a good listener?

My colleagues and I have some exciting research about listening that’s just come out. What we realized is that the human mind is built to wander. It is not built to focus on one

person for long stretches of time, and yet that’s what conversation demands of it — to really pay attention to those three streams of content I mentioned earlier: verbal content, non-verbal cues and paralanguage.

It’s like drinking from a fire hydrant. We’re bombarded by information, and that information is very interesting. It often makes our minds make connections to random ideas, and then we want to elaborate and think about something else. For everyone, it takes tremendous work to stay focused on a conversation partner as the conversation unfolds. What we have found in our research is a key piece of this is, if you’re putting in the effort to listen attentively to someone, show it to them. Don’t just assume that they know.

There is extensive research on active listening, which focuses on things like eye contact, nodding and smiling, laughing at the right times and physically leaning toward your partner. These are all nonverbal cues that you’re listening to somebody, and they are great — but only as a basic starting point. What we are finding is that actually expressing your attentive listening with words is what makes someone a compelling communicator and listener.

I heard you mention earlier that you eat the same lunch every day. I could have asked a follow-up question like, ‘That is so interesting, Matt; why do you do that?’ Follow-up questions are undeniable cues that you have heard someone and processed what they were saying. That’s a sign of good listening. Too often, people put in the work to listen to someone, but they forget to show it. That’s a huge missed opportunity to build relationships and trust.

In addition to follow-up questions, you can do ‘callbacks’ to earlier topics, paraphrasing what someone has said, or if someone said something that’s confusing, revisiting it.

It’s okay to say, ‘I actually heard you say something that I didn’t quite understand. Can you explain that a bit more?’ All of these things show that you’re listening attentively and that you care.

To become a better communicator, you have to be engaged in the conversation and present in the moment, but at the same time, you need to observe the conversation from above to see what’s going on and what’s needed. Really effective communicators learn how to toggle between these two areas.

You have developed a simple approach to help people cope with public-speaking anxiety and all anxiety for that matter. Please describe it. We tested out a very simple coping strategy. The question we asked people was, Can you try to reframe your anxious feelings as excitement by telling yourself, ‘I am excited’? It’s such a simple idea, but it often works. By telling themselves this, the people in our study gave better public speeches, sang better in our karaoke lounge, and did better on a math test.

When we feel anxious, we have a powerful instinct that we should try to calm down. But that isn’t easy, because it requires mitigating the physiological signs of anxiety — a racing heart, sweaty palms and spiked cortisol in your body. You’re trying to suppress all of that, and at the same time, move from negative emotions into the positive zone of calmness. That two-step move is nearly impossible to achieve. Instead, reframing your feelings as excitement allows you to remain in the high-arousal zone. Rather than trying to combat automatic physiological processes, you’re just performing a mental reframe from negative to positive.

What is the best communication advice you have ever received?

I heard something a while back that sticks with me. Harvard Business School Executive Fellow Rachel Greenwald said: “Be more interested than interesting.” To me, conversation is the vehicle by which we express our humanity to each other and our caring for other people. So the idea of being more interested in others than trying to be interesting yourself is a good nudge to keep in mind. It’s not only about us. It’s also about the people that surround us.

Alison Wood Brooks is the O’Brien Associate Professor of Business Administration and Hellman Faculty Fellow in the Negotiation, Organizations & Markets Unit at Harvard Business School. This article began its life as a podcast: Author Matt Abrahams, a Lecturer in Strategic Communication at Stanford’s Graduate School of Business, hosts Think Fast, Talk Smart . His new book is Think Faster, Talk Smarter: How to Speak Successfully When You’re Put on the Spot (S&S/Simon Element, September 2023).

The human mind is not built to focus in on one person for long stretches of time.

FACULTY FOCUS Hai Lu and Jee-Eun Shin, Professors of Accounting, Rotman School of Management

Outsourcing ESG Responsibility: How and Why Companies Are Doing it

HEIGHTENED AWARENESS AROUND ENVIRONMENTAL , social and governance (ESG) issues has led to enhanced demand for ESG-related information from companies and resulted in the passage of mandatory disclosures in numerous countries. Whereas previous research has looked at how mandatory ESG disclosure impacts a firm’s valuation and profitability, we felt that it might also be creating incentives for firms to make particular operational decisions with respect to their supply chain.

Put simply, we felt that some firms might be changing suppliers based on the disclosure requirements in their own country and/or the rules in the supplier’s country. For decades, multinational corporations have adopted global outsourcing strategies to minimize production costs and optimize profit margins; sometimes at the expense of human rights. Nike, for example, was accused of unethical sourcing practices in the 1990s and 2000s when

it subcontracted production to Southeast Asian countries with poor working conditions to save on labour costs. Such pressures were fuelled by higher production costs in Korean and Taiwanese factories, where Nike’s supplier factories had previously been based.

Whereas rising prices constituted the main driver for Nike’s supply chain reconfiguration, we posited that reputational costs associated with the passage of mandatory ESG disclosure requirements might result in similar effects.

Disclosure of ESG-related information consists of published details on corporate strategy and internal business processes that can entail significant compliance costs for firms. Due to heightened awareness about ESG issues by the investment community, mandatory disclosure can induce reputational incentives to ‘compete’ on ESG performance. This is particularly the case in light of the documented positive capital market effects associated with the disclosure of voluntary ESG information.

Whereas the reputational benefits associated with mandatory disclosure may incentivize firms to make real

investments at existing supplier firms (to adhere with ESG standards), the benefits of doing so are only likely tomaterialize in the long-term. Adjusting the firm’s supply chain configuration comprises a more immediate strategy to meet the higher standards imposed by mandatory disclosure. We set out to test our hypotheses.

Our Research

We analyzed the supply chain data of 22,890 global firms from the FactSet database, spanning from 2003 to 2021. After identifying the year in which mandatory disclosure was introduced in different countries, we examined subsequent changes in firms’ global supply chain composition.

We distinguished between suppliers located in countries with or without mandatory disclosure. The intuition was that focal firms can more likely ‘hide’ their ESGobligations when suppliers are located in countries without mandatory disclosure. We felt that a poorer corporate information environment around ESG at supplier firms would allow for a higher likelihood of concealment of customer firms’ adverse ESG activities.

We were looking for two particular supply chain management practices. First, firms concealing their adverse ESG activities by expanding their supplier network and adding new suppliers from countries with weaker ESGrelated corporate information environments. Second, firms concealing their adverse ESG activities by switching from existing suppliers to new suppliers from such countries with weaker ESG-related corporate information environments.

As expected, the introduction of mandatory ESG disclosure in jurisdictions where the focal firm was located was indeed associated with adjustments to their supply chain composition to benefit from suppliers with more opaque ESG-related information environments. After the introduction of mandatory disclosure, firms notably reduced their existing relationship with suppliers in the same country and established new relationships with suppliers from countries without mandatory disclosure.

Collectively, our findings highlight a real effect of mandating ESG reporting in individual jurisdictions. Due to complex global supply chain configurations, firms located in areas with enhanced disclosure requirements are migrating their ESG responsibilities to suppliers whose activities are more likely to be concealed.

We also explored the role of external governance mechanisms that may mitigate firms’ incentives to adjust their supply chain composition following the introduction of mandatory disclosure. We considered three external factors that have been shown to influence firms’ practices.

REGULATORY ENFORCEMENT. To examine the role of enforcement strength, we used the rule-of-law index that captures the extent to which agents in a country have confidence in and abide by the rules of society. Prior research suggests that enforcement strength by regulatory bodies can significantly impact corporate governance oversight. Accordingly, we expected that firms’ propensity to evade and/ or hide ESG-related obligations to their suppliers would be more pronounced when firms are subject to stronger legal enforcement. FINDING: Supply chain migration activities are concentrated in firms in countries with a higher degree of law enforcement.

ANALYSTS. Research suggests that analyst following can serve as an effective external monitor, mitigating agency problems between firm insiders and outsiders. For example, higher analyst coverage is associated with fewer earnings-management activities and stock crash risks. We expected to find that firms’ propensity to evade and/ or outsource ESG-related obligations to their suppliers following mandatory disclosure would be less pronounced in firms with greater analyst coverage. FINDING: In response to the introduction of mandatory ESG disclosure in a country, firms with higher analyst coverage were indeed less likely to choose new suppliers from countries without mandatory ESG disclosure.

PRESENCE OF INSTITUTIONAL INVESTORS. Institutional ownership is positively associated with management conservatism, corporate governance and innovation. Recent years have seen an increasing demand for sustainability principles in asset management by institutional investors. For example, in 2020, the U.S. Forum for Sustainable and Responsible Investment (USSIF) reported US$16.6 trillion of assets under management according to sustainable and responsible investment principles with significant representation by institutional investors. This constitutes an increase of more than 8x since 2003, the beginning of our sample period.

Firms are establishing new relationships with suppliers from countries without mandatory ESG disclosure.

Accordingly, we expected that the likelihood for firms to engage in unethical supply chain activities in response to mandatory disclosure would be less pronounced for firms with higher institutional ownership. FINDING: Compared to firms with lower institutional ownership, firms with higher institutional ownership were indeed less likely to reduce the number of new suppliers from home countries in response to mandatory disclosure. Collectively, our results corroborate the role of financial intermediaries as external monitors.

Finally, we examined other possible effects following the introduction of mandatory ESG disclosure. First, we explored whether and how such disclosure is associated with reported ESG performance. Specifically, we looked at the number of reported ESG incidents and found that the introduction of mandatory disclosure is associated with an overall decline in the number of reported ESG incidents—that is, an improved ESG profile.

Moreover, we found that the effect of an improved ESG profile following the introduction of mandatory disclosure was primarily driven by firms that engaged in supply chain migration in the three years following the introduction of the mandate. This suggests that firms’ supply chain management strategies were successful in attaining an improved ESG profile.

Second, we explored whether and how mandatory disclosure is associated with changes in firms’ cost structure. A potential explanation for observing changes in the global supply chain composition may be that it is simply driven by rising production costs such that firms have incentives to relocate to relatively underdeveloped countries.

Whereas we found an overall increase in production costs following the introduction of mandatory disclosure, we did not find evidence that these increases led to significant differences between firms with and without engagement in supply chain migration activities in the three years following the introduction of mandated disclosure. This finding corroborates that the changes in supply chain composition in response to mandatory disclosure may not be entirely driven by cost-based motives, but also based on reputational incentives to conceal adverse ESG-related activities.

In closing

Following the introduction of mandatory ESG disclosure, a portion of firms evaded their ESG-related responsibilities by switching to suppliers where the corporate disclosure environment was weaker. In contrast, we found no evidence of a change to suppliers with stronger corporate information environments. These findings confirm that stronger standards at supplier firms may comprise a burden in light of elevated disclosure standards.

Our findings are consistent with mandatory ESG disclosures generating reputational costs for firms wanting to manage their ESG profile. That is, in order to evade and/or hide their ESG-related obligations following the implementation of mandatory disclosures, they decide to engage in supply chain migration strategies that transfer ESG-related risks to supplier firms located in countries with weaker corporate information environments. However, such supply chain migration strategies are mitigated by financial intermediaries such as analysts and institutional investors acting as external monitors.

Our evidence also indicates that the migration strategy of supply chains partially explains the reduction of reported ESG incidents following the introduction of mandatory disclosure. Overall, our findings suggest that mandatory disclosure policies can have long-lasting real effects on firms’ global outsourcing practices.

Hai Lu is the McCutcheon Professor in International Business and Professor of Accounting at the Rotman School of Management and Director of the School’s Guanghua-Rotman Centre for Information and Capital Market Research. Jee-Eun Shin is an Assistant Professor of Accounting at the Rotman School. This article summarizes their working paper, “Migration of Global Supply Chains: A Real Effect of Mandatory ESG Disclosure,” The complete paper is available online.

Some changes in supply chain composition are based on reputational incentives to conceal adverse ESG-related activities.

Q &A

A diversity, equity and inclusion expert shares lessons learned from her own path to belonging.

Interview by Karen Christensen

Why is belonging such a critical concept right now?

I think for many of us, the dramatic shift over the past few years in how we’re living, working and leading has given rise to all kinds of new insights. With the increased spotlight on inclusion and equity, we’ve done some deep soul searching around who we are, what we want out of life, and how we want to work and lead going forward. What has been revealed is that for a long time, we haven’t felt accepted for who we are. We’ve struggled to be seen and to bring our differences to bear in our interactions — both in our personal and professional lives.

And what we’ve ultimately realized is that we’re searching for belonging. We want to be honoured for who we are. We want to feel seen, valued and respected for who we are. And belonging gives us a path to living a life that we can love.

About 15 years ago, you realized that you hated the life you had created for yourself. Please describe the situation.

Like many people, I had been fed the corporate dream and I bought into it. As a young woman of colour born in Canada of Indian immigrant parents, I thought that getting a good education, becoming a lawyer on Bay Street, doing my MBA, and progressing to the leadership team of a preeminent

QUESTIONS FOR Ritu Bhasin (Rotman MBA ’10), Author, We’veGotThis:UnlockingtheBeautyofBelonging

Canadian law firm would unlock tremendous happiness for me. But it didn’t — especially since it was on the basis of conforming to a White male normative. What I realized is that by trying to fill my ‘joy cup’ with external forms of affirmation that weren’t in alignment with who I am at my core, I was experiencing momentary spikes in joy, but I wasn’t feeling joyful on a whole in how I was living.

Something deep within me kept saying, ‘No, Ritu; there is something more fulfilling for you out there. You deserve to be more joyful.’ And I decided to heed the call.

Let’s zoom back to well before that. Many people believe our childhood experience impacts our sense of belonging as a adults. Can you touch on that aspect of your journey?

I had a quintessential upbringing as a child of immigrants. My parents immigrated to Canada over 50 years ago from India. We are Punjabi by culture and Sikh by faith. My father wears a turban and my mom has long hair, and so do I. My parents came to the country with very little money. As members of the Sikh community, we stuck out, and I saw the oppression they experienced on a daily basis.

I also had my own experiences with racism. I am a survivor of relentless childhood bullying that was deeply traumatizing. Thankfully, I’ve done decades of therapy and self-healing work to help me tend to those wounds, but my healing journey hasn’t been easy. Plus, I experienced cultural confusion growing up struggling to reconcile Indian culture with white Canadian culture. I really grappled with my identities growing up. I learned how to shift cultural codes and ‘perform’ by putting out a curated image of who I am.

Sadly, this experience continued when I entered corporate Canada as a young woman of colour lawyer, where I found that the messages of cultural conformity were everywhere. No one said directly, ‘change who you are to get ahead,’ but it was understood through subtle, nuanced messaging.

For example, I felt pressure to Anglicize my name and accept not having it pronounced properly. I felt pressure to wear navy and grey and black as opposed to colours I prefer, like hot pink, red and yellow. And I felt pressure to be

more direct and assertive around what I needed and wanted to get ahead, even though that’s not how I prefer to behave. I just felt constant pressure to change myself, which was really stressful.

Over the years, you began to build up and lean on your ‘core wisdom.’ How do you define this term?

Core wisdom is the knowledge that we hold deep within us that helps us tune in to what our body and mind are telling us. We ask ourselves questions like: What are my body and mind signalling to me right now? Where am I holding tension inside me and why is this happening? What negative thoughts are swirling through my mind? What do I need to do to settle and release whatever it is I’m holding on to? What can I do to calm myself? What can I do to be to feel more resilient, so I’ll be less activated in a moment like this going forward?

Our core wisdom helps calm and soothe our body and mind so we can make better decisions, understand how we’re judging and impacting others, feel more empowered, practice greater empathy, use our voices to name inequities we’re experiencing and so much more. In a nutshell, our core wisdom will help us be more regulated and calm in the face of difficult situations.

If you asked me, ‘What is the number one thing I can do to live a better life, be a better leader, a better human being, a better parent and to feel greater joy?’— I would tell you it’s tapping into your core wisdom. How do you build it up? It essentially entails using body and mind-based practices that enable you to track, understand, release and settle sensations, feelings and thoughts inside of you.

In teaching about belonging, you talk a lot about the ‘Performing Self.’ Can you describe what this is?

I developed the Three Selves Framework™ as a way to help people bring their authentic self into how they live, work and lead. The Performing Self sits on one end of the continuum in the ‘Zone of Disempowerment’ and it’s the self you show up as when you feel like you don’t have a choice but to conform or hide who you are because otherwise you believe people will reject, hate or judge you. The goal is to

I learned how to shift cultural codes and ‘perform’ by putting out a curated image of who I am.

push yourself out of the Performing Self toward the Zone of Empowerment, which is where your Authentic Self and your Adapted Self are.

Your Authentic Self is who you would be if there were no negative consequences for your behaviour. This is how you’d express your emotions, how you’d speak, what you’d do with your body language, how you’d dress, etc. It’s the good, the bad and the ugly of who you are, but because it’s the truest reflection of your core self, it feels the best to put out. To experience belonging, you want to show up as your Authentic Self as much as possible.

This said, sometimes you need to show up as your Adapted Self, which is perfectly fine to do because it also lives in the Zone of Empowerment. Your Adapted Self is who you are when you willingly choose to adjust your behaviour from how your Authentic Self would show up, because the moment calls for it. It’s a choice, it feels good to do, it serves you and it serves others. But it’s important to pay attention to the following: when you keep adapting your behaviour, and it starts to feel like you’re now conforming or masking who you are, you’ll have slipped into the Zone of Disempowerment.

In using the Three Selves Framework to experience greater belonging, you’ll want to use your core wisdom to help make choices that enable you to show up as your Authentic Self and Adapted Self as much as possible, instead of living life as your Performing Self.

Talk a bit about the power of ‘cloud relationships.’

As a professional speaker, I travel a lot for engagements and I love to gaze out the airplane window to stare at the beautiful, poofy clouds. I often think to myself, ‘Wouldn’t it be amazing to fall into one of those clouds and float around?!’ It is that same sensation I picture when I think about the relationships in my life that are rooted in belonging — relationships with loving people with whom I have healthy, deep and meaningful ties, who we can rely on to lift us up and share joy.

These are our cloud relationships. With these people, we can just let go and be because we feel safe to be fully authentic. We feel cared for, loved, seen and supported. Everyone needs a few cloud relationships in their life.

You have said that the path to belonging is both beautiful and difficult. What are the first steps toward feeling like one belongs?

Many of us have been conditioned to believe that life is only supposed to be beautiful. I certainly was, and when I started to realize how hard life can be, I both railed against the difficulties coming my way and worked even harder to be ‘perfect.’ But through a lot of self-growth work, especially in my thirties, I realized that life is both beautiful and hard, and we can hold both truths at once.

I have the same sentiment about the journey to claim belonging — it is both beautiful and hard, but it’s so worth it. The first step is to learn to belong to yourself. When you belong to yourself — i.e. you accept and honour who you are for your own soul — you will feel empowered to claim belonging with others. But it’s more than that: you’ll accept that life can be hard but, because you have deep core wisdom, you will always feel anchored. This is an important goal — and it’s what the beauty of belonging is all about.

Your Authentic Self is who you would be if there were no negative consequences for your behaviour.

Ritu Bhasin (Rotman MBA ‘10) is an award-winning DEI and leadership expert, speaker, author and coach. Her latest bestselling book is We’ve Got This: Unlocking the Beauty of Belonging (Random House Canada, 2023).

Q &A

Interview by Karen Christensen

You have studied innovation that is the result of mild deviance. How do you define these ‘workarounds’?

A workaround is a flexible and creative problem-solving approach that defies the conventions around how problems are traditionally solved — and by whom they are solved. One of the analogies I make is the notorious Trojan horse story from mythology, where the Greeks seized the city of Troy. It represents the idea that there are ways to accomplish things that have never been thought of before. In this case, the Greek soldiers didn’t have to scale the walls of Troy or break through its gates to seize the city. They came up with an ingenious idea: they built a giant wooden horse that was presented as a gift to the goddess Athena celebrating the Trojans’ victory over Greece. What they didn’t know was that there were 38 Greek soldiers hiding inside it. They were able to sneak out after dark and win the battle. That’s the very essence of a workaround.

An innovation expert describes how to deviate from the status quo by embracing ‘workarounds.’

QUESTIONS FOR Paulo Savaget, Professor, Oxford University’s Saïd Business School

ColaLife started to literally piggyback on Coca-Cola’s distribution chain.

One of your favourite examples of a workaround involves crates of Coca-Cola bringing life-saving medicine to remote areas of the world. Please summarize how this was done.

In sub-Saharan countries, diarrheal disease is one of the biggest killers of children under the age of five, and it’s a very challenging problem to address due to infrastructure issues. The treatment as recommended by the World Health Organization is very affordable and is available over the counter in most places. It doesn’t require refrigeration, which means it could travel easily from a logistics perspective. Yet there are still many remote regions in low-income countries where this medicine could not be found.

Many large organizations, including governments, are focused on improving infrastructure, logistics or funding. These things are important, of course, but they’re costly and they take a long time. A small scrappy non-profit organization focused on delivering medication called ColaLife came up with an ingenious workaround. They realized that even in very remote regions of the world, Coca-Cola is sold. So, they started literally piggybacking on Coca-Cola’s distribution chain by placing diarrheal medicines in between bottles in the delivery crates to get the medicine to remote areas.

This is an example of the first kind of workaround, the Piggyback. I call it that because they got a free ride on something that already existed, and it shows us the power of finding unconventional pairings. Who would ever think you could address a health problem by leveraging the system for fast-moving consumer goods?

A second type of workaround is the ‘Loophole,’ which we usually think of as something negative. How can loopholes be positive?

Loopholes entail working around rules, and that’s why they can be controversial. People’s ethics and morals are

involved, so what one person might consider positive will be viewed as negative by others. One of the cases I cover in the book is from a group in the Netherlands that believed strongly that all women should be entitled to abortion services. Of course, the legislation in many countries doesn’t allow it, so they found a loophole: They sail their boat, Women on Waves, from the Netherlands to places where abortion is illegal. Women seeking an abortion can come onboard and sail with the group to international waters. Here’s the loophole part: in international waters, the law that applies is that of the country that owns the vessel. In other words, the legislation from the Netherlands applies in this context, so safe abortion services can be provided to these women before they are returned to their country.

You have said workarounds also saved lives during COVID-19. How so?

In high-stakes situations like the pandemic, we saw a lot of workarounds. One that caught my attention was a scenario from my home country, Brazil. Flávio Dino, then-governor of Maranhão, had worked previously as a federal judge, so he knew a lot about the rule of law. Early in the pandemic, like so many leaders, he wanted desperately to purchase ventilators for his constituents.

Maranhão is Brazil’s poorest state. You will probably remember that there was a rush to buy ventilators early in the pandemic. The supply could not meet the demand, so the first avenue the Maranhão team tried was to procure through the government. But the process would have taken far too long, and people would have paid with their lives. So instead, they changed their approach. They tried to purchase directly from a manufacturer in China through a Brazilian company that already had a procurement system in place to purchase from Chinese suppliers; this company could subsequently donate the ventilators to the government.

However, there is no direct flight from China to Brazil, because the distance is too long. So the plane had to stop somewhere to refuel. The first and the second time they tried this, they refuelled in Germany and the United States, and both times, the ventilators were confiscated by these countries due to the huge demand.

Then they tried something else: some of the local companies had representatives in China because they procured from there. Once they got their hands on the ventilators, they chartered a cargo flight, and instead of refuelling in Germany or the U.S., they stopped for fuel in Ethiopia because they assumed there would be less monitoring of the cargo and that the country wouldn’t have the resources to confiscate the ventilators.

Even once they passed this hurdle, they still had to go through São Paulo to get through customs. This would be a challenge because the Federal government could confiscate the ventilators and re-route them to other Brazilian states. So, once they landed in São Paulo, they quickly took a second flight to the state of Maranhão. Even in Maranhão, the federal government was the employer of the Revenue Customs officers, and they could still confiscate the cargo. But the team planned it in a way that once they landed, it would be after hours and customs officers had gone home for the day. A state secretary signed a document ensuring that he would return the following day to fulfil the legal requirements (which was, in fact, done), and state government employees took the equipment directly to hospitals to intubate patients.

If anyone claimed they were violating laws or administrative processes, they could honestly say they were not. Sure, they worked around the rules, but they didn’t necessarily violate them. That’s an example of a sequence of workarounds on top of workarounds that allowed life-saving equipment to make it to public hospitals in one of the poorest Brazilian states.

Tell us a bit about the third type of workaround, the Roundabout.

Roundabouts interrupt self-reinforcing behaviours and buy time to mobilize, negotiate and develop alternatives, alleviating an urgent problem while building momentum to pivot in a different direction.

An example is the social distancing we all endured during the pandemic. In March of 2020, the scientific community quickly underscored that in the midst of the worst public health emergency in 100 years, we simply couldn’t continue with our usual daily lives. Locking ourselves away in our homes might have seemed backward, but because COVID-19 spreads at an exponential rate, we needed a temporary stopgap measure to slow the rate of transmission. While they couldn’t end the pandemic on its own, social distancing lockdowns did save lives and bought time for vaccine and treatment development.

You have said Bitcoin and cryptocurrency are examples of another kind of workaround, Next Best. Please explain.

A Next Best workaround focuses on repurposing or recombining resources, which can range from the most high-tech to the most basic. One of the most famous workarounds ever pursued by tech enthusiasts emerged in 2008: Bitcoin. This cryptocurrency — and the blockchain technology it relies on — were created in the aftermath of the global financial crisis when distrust of financial institutions was high.

The geeks saw people in debt while governments bailed out big corporations. By inventing cryptocurrency, they found a way to bypass the centralized structures of the financial system, providing an alternative for anonymizing members and making transactions possible that left no detectable traces.

One of the most famous workarounds ever pursued by tech enthusiasts emerged in 2008: Bitcoin.

Identifying Opportunities for Workarounds

WHEN… USE...

There are other people or relationships a Piggyback that you can leverage

There is a set of formal or informal rules a Loophole that you dislike

There is a self-reinforcing behaviour a Roundabout that can be influenced

There are available resources that a Next-Best can be repurposed

Satoshi Nakamoto — a pseudonym that disguises the (still unknown) identity of a person or group of people — registered the domain bitcoin.org and authored a paper on peerto-peer electronic cash system, explaining how it works.

In 2009, the network came into existence, allowing everyone to ‘mine’ the digital coin through a lottery-based system and to transact Bitcoin digitally and untraceably. The idea was so promising — and the timing was so good — that Bitcoin quickly took off. For better or worse, cryptocurrency systems have opened up room for many others to creatively work around mainstream financial organizations (and law enforcement, in some cases.)

Does all of this come down to becoming comfortable with being deviant?

It does, yes. But I always distinguish between deviance and disobedience. These workarounds are not necessarily disobedience; they simply deviate from the status-quo in effective ways. I actually believe we don’t deviate enough in life. The problem is that the ‘social contract’ makes us believe that conformity is always preferable — that our unconditional compliance frees us from our harmful natural instincts.

A better way of looking at conformity and deviance is by contrasting ourselves with machines. Conformity means doing as we’re told, or as we’ve been programmed to do. It means we haven’t critically evaluated our options or acted based on reasoning. In this mindset, deviance is what humanizes us and makes us stand out.

If you think about it, some of the worst harm to humankind has been perpetrated and validated by people following a system of rules. When we blindly follow rules, we ignore that rules aren’t necessarily fair. We should never think of conformity as the only option.

How can we learn to recognize opportunities for workarounds?

When we analyze a problem, our instinct is usually to try to get a fuller, more detailed picture. We assume that a more detailed picture is better, just as we assume that more — and more specialized — resources will always help us deal better with our problems. What if, instead, we thought a little more like a hacker, working only with the materials we have immediately at hand?

If we embrace working with what we have rather than what we want, we can start addressing pressing challenges. I often make an analogy to the camera lens. Just as focus, aperture and shutter speed are components of capturing an image, rethinking our resources, focus and scope are all ways to shift our mind’s inner ‘lens’ to emphasize different aspects of a phenomenon. I encourage readers to use these workaround strategies as they would fiddle with the settings on a digital camera: curiously, playfully and frequently.

Paulo Savaget is the author of The Four Workarounds: Strategies from the World’s Scrappiest Organizations for Tackling Complex Problems (Flatiron Books, 2023). He holds a joint appointment at Oxford University between the Department of Engineering Science and Saïd Business School. He received his PhD from the University of Cambridge as a Gates Scholar.

Scaling Behavioural Insights: One Size Does Not Fit All

MORE THAN A DECADE after the publication of Nudge, the organizational relevance of insights from Behavioural Science is no longer questioned. But in terms of applying these insights, two challenges remain. The first relates to creating organizations that truly understand the science and embed it deeply within their structures and methods. The second challenge is one of scaling: How can we ensure that the results of experiments and pilots successfully scale into interventions that reliably improve consumer welfare? In this article, we will focus on the latter and identify three specific scaling challenges.

First, one of the biggest themes from the research is the notion of context dependence. We now know that numerous elements in a given context (e.g., the medium of the message, the time of day, information framing and ambient factors, to name a few) influence peoples’ choices. A rich literature of preference reversals has shown, for example, that consumer preferences can reverse with seemingly irrelevant changes to the context. For business leaders and policymakers, the implication is clear: the fact

that a particular intervention worked well in one particular context does not guarantee its success in a completely different context.

Second, the lack of diversity of pilot-study participants poses a real challenge. While it is important to understand the efficacy of an intervention among a representative group, it is equally important to understand the heterogeneity of the population. Small-scale studies may focus on the set of people for whom the treatment effects are believed to be the most significant, but a goal for largescale initiatives should be to figure out the effects for a wide array of segments of the population. The fact is, in some cases interventions may not scale well to the entire population, but can be very effective on a subgroup. After all, successful business models and policies don’t have to be one-size-fits-all.

Third, there is often a temptation to adopt a ‘kitchen sink’ approach, whereby multiple interventions that have been successfully tested independently are deployed simultaneously. Unfortunately, multiple-insight interventions can interact in complex and unpredictable ways, and can actually backfire. Following are three examples that illustrate the challenges of scaling behavioural interventions.

FACULTY FOCUS Dilip Soman and Tanjim Hossain, Professors of Marketing, Rotman School of Management

EXHIBIT A: Credit Card Reminders

Research shows that consumers tend to spend more when using a credit card rather than when paying with cash. One reason for this ‘credit card premium’ is the fact that continued use of the credit card weakens memory of past expenses. Consequently, giving people feedback (reminders) on how much they have spent on prior expenses should improve mental tracking and mitigate spending differences.

In response to growing concerns about credit card debt, in 2010 the government in South Korea mandated that credit card providers introduce a text messaging service to remind consumers about recent transactions. In addition to preventing the fraudulent use of credit cards, the policy was designed to improve rational spending behaviour. The expectation was that the text-alert system would help people control their spending and hence reduce credit card balances.

THE RESULT: The policy had the intended outcome for only about 12 per cent of the population—the heaviest spenders. For the remaining 88 per cent, it actually resulted in increased spending. This backfiring effect can be attributed to an important difference in the manner in which the reminder message was delivered. In the pilot studies, it was available on the same screen where spending decisions were being made, while in the scaled-up intervention, it appeared separately on the user’s mobile device. This created a degree of ‘digital dependency’ whereby consumers believed that they could easily access their past spending if they needed to, thereby reducing the motivation to track it.

EXHIBIT B: A Retirement Savings Intervention

Mexico is facing a poverty crisis among its elder citizens. All salaried employees in Mexico must make a 6.5 per cent mandatory contribution to their pensions, but projections show they need to make an additional five per cent voluntary contribution in order to retire comfortably. Unfortunately, the voluntary contribution rate in is abysmally low.

In working with the pension authority in Mexico CONSAR and ideas42, Rotman professors Avni Shah, Matthew Osborne and one of the authors (Dilip Soman) redesigned the quarterly statement that every salaried employee receives. Research shows that simplifying communication and making it more engaging increases the likelihood that recipients will consume the information and act on it. Accordingly, the redesigned statement was made significantly

more engaging than the original in two ways. First, it provided a simplified visual illustration (in the form of a categorical thermometer) showing whether the recipient’s current savings were adequate for retirement.

Second, the statement included one of several interventions that had been shown to be successful elsewhere: gain-versus-loss framing, a wallet cut-out to increase implementation intentions, an appeal that made the family’s welfare salient and a fresh-start intervention encouraging recipients to start saving after a particular temporal landmark.

THE RESULT: In a large-scale trial with members of two pension funds, the intervention was a success with one of the funds. It increased the contribution incidence, the contribution amounts and the contribution frequency. However, it backfired in the other fund. Why? Because of a specific design feature unique to the Mexican pension system. Mexicans need to first choose a pension fund and then make their contribution decisions. The quarterly pension statements displayed the performance of each fund in a tabular form. By making these statements more engaging, the researchers increased the attention that was paid to the table. If the fund was high performing, then the engaging statement ended up improving voluntary contributions because it increased the motivation to save. If, on the other hand, the recipient had chosen a low-performing fund, the intervention resulted in demotivation because it highlighted attention to the fund’s lower performance.

EXHIBIT C: Heterogeneity in Text Message Reminders

In ongoing work with Mexican pension contributors, the same group of researchers compared a control condition with one in which recipients received the redesigned quarterly statement. In previous research, text reminders have been shown to successfully convert intention into action. Thus in a third condition, subjects additionally received a text message with a variety of call-to-action messages.

THE RESULT: Compared to the control group, a condition in which recipients received a text message emphasizing their family’s financial security in addition to the redesigned statement increased contribution rates significantly. However, did both men and women care equally about their families? What about people who didn’t have children? Did age matter?

The fact that a particular intervention worked well in one context does not guarantee its success in a completely different context.

Using a machine learning technique, the researchers identified heterogeneous treatment effects across the scaled-up population. Their results were unsurprising, but worked to show exactly for which sub-segments in the population the intervention was particularly successful and where it was not. For instance, they found that the ‘family security text message’ intervention increased contribution rates for people who were aged between 28 and 42. It did not have a significant effect for those above the age of 43, and it had a backfiring effect for people under the age of 27.

Knowing exactly where the family-security text message (as well as each of the other messages tested) was most effective would allow the pension authority to effectively target sub-segments of the population. How might these scaling challenges have been at work for an intervention based on the most robust findings from Behavioural Science: the framing of monetary outcomes as either gains or losses?

In a field study in a high-tech manufacturing facility, one of us (Tanjim Hossain) manipulated the manner in which a productivity bonus was presented to workers. In particular, the same bonus was presented to a random subset of workers as a potential gain and to another subset as a potential loss. The author found that both the gain and loss framing increased productivity compared to a control condition in which there were no incentives. Incentives clearly worked; and more importantly, framing the incentive as a potential loss led to a small but significant increase in productivity over presenting it as a potential gain.

It is quite important that this small increase in productivity happened in a real-work setting. If this small gain in productivity could be scaled to large populations of workers, it would indeed have a significant impact on welfare. The question remains as to whether scaling-up happens at exactly the same rate or whether there would be a ‘voltage drop.’ Could the intervention actually backfire? In this study, the intervention was implemented for only about a month. While the impact was evident throughout the experiment, a negative framing of incentives might be less likely to be successful if the intervention is permanent or much longer in duration.

We believe that the effect of loss aversion on productivity depends on the interaction between the framing (gain vs. loss) and the underlying incentive scheme. Hence, one needs to be careful in choosing the economic part of the intervention while scaling up to ensure that it doesn’t back-

fire. Moreover, the effectiveness of loss framing may also depend on the size of the economic incentives. In the study mentioned, the size of the bonus was above 20 per cent of any of the workers’ base salaries. The treatment effect for smaller-sized incentives may be insignificant or opposite in direction.

Our views of why scaling challenges exist are grounded in organizational realities. In particular, we will highlight three reasons for this, as well as one to do with the nature of evidence. The first reason is solution-mindedness. Unlike scientists, governments and businesses are typically under enormous time pressure to solve problems.

Second, as applications of behavioural insights have spread, organizations are increasingly relying on non-specialists to design and deploy behavioural interventions. In an effort to help non-specialists, a number of heuristic frameworks have been developed. Frameworks are elegant in that they allow a non-specialist to try to design interventions based on the learnings of others. However, they can often be counterproductive because they change the process of intervention design from one that begins with a careful audit of the context to a checklist-based approach.

Third, most organizations we have worked with operate in silos of capability. Behavioural scientists are typically located in a different department from data scientists and design teams. Some of the scaling challenges described herein will be best addressed if we have large and diverse teams working on these projects. Perhaps most importantly, the cost of experimentation — collecting and analyzing data, time commitment and organizational buy-in, among others — is high; therefore, many organizations embrace off-theshelf results.

The nature of insights in the behavioural sciences is significantly different from evidence in other sciences. Consider fields such as Physics or Medicine. As an example, ‘objects released from a height will fall to the ground, irrespective of who releases them, the height of release, their colour and whether there are other objects being released at the same time.’ The theory of gravity has a large bracket of context surrounding it, and how the theory works in foreseeable but uncommon contexts is also well understood. For example, releasing the same object from earth or the surface of the moon will not result in the same sort of drop. Most people properly understand the difference between the two contexts.

Behavioural scientists are typically located in a different department from data scientists and design teams.

Unfortunately, the field of Behavioural Science has very narrow brackets of context. Therefore, it is important to emphasize that the documented robust demonstration of an effect in a particular context with a particular type of end user at a particular point in time does not guarantee that it will successfully replicate across contexts.

We therefore caution the practitioner to avoid the temptation of simply using an off-the-self solution from the proverbial Nudgestore, and recommend instead using a more customized and tailored approached based on the mantra popularized by the UK-based Behavioural Insights Team: Test, Learn and Adapt!

In particular, it is of utmost importance that pilots are done in the context in which the intervention is going to be scaled up. ‘In situ’ testing in South Korea could have flagged the potential backfiring effect of reminders at a stage where it could have been corrected. Finally, scaling up must be accompanied by continuous testing, learning and adapting in order to detect and respond to potential backfiring due to context changes, interactions between different interventions and heterogeneity.

In closing

We will end with a few proposals. First, rather than viewing researchers purely as producers and organizations purely as consumers of research, we should strive to cocreate evidence.

Second, researchers should be incentivized to articulate all of the dimensions of the context (or features of the situation) under which their documented effects hold. They should further be incentivized to test for the effect under different contexts.

Third, when in situ testing is not possible, we should document the dimensions of the context of the scaled-up situation that might be different from the testing phase and invite the original researcher to speculate on whether these differences might change the results.

Fourth, we should test for heterogeneous treatment effects of interventions and use a family of appropriately targeted interventions to scale solutions.

Finally, we should encourage researchers and organizations to create project teams of behavioural scientists, designers and data scientists to collectively design, test, scale and monitor interventions. And we should strive to reduce the cost of experimentation within organizations. All of these efforts will be worthwhile to bring the power of behavioural insights into organizations of all types.

Dilip Soman is the Canada Research Chair in Behavioural Science and Economics, Founding Director of the Behavioural Economics in Action Research Centre at Rotman [BEAR] and Professor of Marketing at the Rotman School of Management. He is the author of The Last Mile: Creating Social and Economic Value from Behavioural Insights (RotmanUTP Publishing, 2015). Tanjim Hossain is a Professor of Marketing in the Department of Management at the University of Toronto Mississauga, where he serves as the Chair of the Department, with a cross-appointment to the Marketing Area at the Rotman School. He also serves as a chief scientist at the BEAR centre.

ARTIST: IRIS DENG

Q &A

What is the Future Normal? Will we like it there?

When people talk about the future, it is often tinged with the fear that everything could go wrong. With this book, my coauthor Henry Coutinho-Mason and I wanted to present an alternative perspective — because we can only build the future we can imagine. We do this through sharing a collection of emerging trends that are both positive and based on reality. We want people to be inspired by the world-changing innovations (and the instigators behind them) that we discovered while writing this book.

I have been studying our shared culture to curate trends for more than a decade now, and I’ve learned how to anticipate the ‘likely.’ Henry and I often describe ourselves as reluctant futurists. We believe our work is better described as ‘near futurism’ — a quest to catalog and understand the implications of the biggest innovations on our lives today and over the next few years. The greatest question we found ourselves asking as we wrote the book was, ‘What if things go right?’

The fact is, the ideas and innovations that catch on and expand are all closely tied to human needs. If you look back through history, you will see that many of our fundamental motivations have barely changed over centuries. The need to feel secure. The desire to be loved and to appear successful to those around us. The quest to discover ourselves and develop as individuals. These are the deeply human needs and wants that are as present in the plays of Shakespeare as they are today. People’s fundamental needs evolve at a much slower pace than the innovations that cater to them, if they evolve at all.

Interview by Carolyn Drebin

Describe how business innovation fits into the picture. Understanding people’s core wants and needs can help any leader or innovator uncover the advancements that will become our future normal. If you think about it, every business innovation is really a bet on the future. Taken in isolation, each is a signal that a group of people believe their view of the future will be successful. When similar wagers are being made in a diverse range of markets and categories,

A renowned trend forecaster shares the secret to seizing emerging opportunities.

QUESTIONS FOR Rohit Bhargava, Trend Expert and Co-Author, The Future Normal

How We Will Connect, Get Healthy + Thrive

Multiversal Identity

What if we could all be our real and most authentic selves both online and offline?

Immersive Entertainment

What if you could be part of entertainment instead of watching it passively?

Certified Media

What if you could trust the authenticity of the media and content you consume?

Stealth Learning

What if you could educate yourself using the very videos and games that are typically written off as a waste of time?

Ending Loneliness

What if closing the generation gap could cut loneliness at any age?

Virtual Companionship

What if you could develop a meaningful relationship with an app or robot?

Psychedelic Wellness

What if mainstream medicine tuned into the mental health benefits of psychedlics?

Metabolic Monitoring

What if tracking your glucose level became as normal as counting your steps?

we can extract insights about where our ‘future normal’ is going. Anticipating a fast-moving future is difficult, but it is not impossible.

How did the pandemic affect the adoption of trends and behaviours ?

The pandemic was an interesting case study, because people had to find alternate ways to meet their core needs. Baking bread was less about the bread and more about the need for a sense of ritual and comfort during a time of disconnection. And Zoom happy hours were an attempt to satisfy our desire to connect safely. As we started to emerge from our homes, these behaviours were quickly abandoned as we shifted back to the ways we achieved these things before the pandemic.

Tell us about your Industry Playlists.

We are often asked, ‘What are the most important trends for my industry?’ We found that building ‘playlists’ by industry (see Figure One, page 117) was a way to make the

book more actionable. We have found that many readers start off on the path most relevant to them, but eventually they are intrigued by the more unexpected ideas they might discover in the rest of the book. This is where magic often happens and fresh insights and ideas come about.

Talk a bit about personal identity and how it will morph into a ‘multiversal identity.’

When we talk about multiversal identity, we are not only referring to the multiverse, where people can buy and sell virtual properties or live virtual lives. Instead, we’re writing about the digital identities we all create for ourselves online everyday that vary by platform. The profile photo we use on Linked-In is different than the one we might use on a dating website. Already, most of us have become accustomed to this idea that we can curate how we present ourselves to the world across each digital platform we choose to use.

In the early days of social media, we would only share the most flattering images or post about the most fabulous times we were having. Our online identity back then was crafted to present a highly curated and controlled version of ourselves. In hindsight, a backlash against the faux authenticity this ecosystem incentivized seemed inevitable. Life is not always great. Sometimes we lose a job or end a relationship. Over time, this created a simmering resentment of celebrities, influencers and anyone else who tried too hard to curate an enviable identity. Today, we are increasingly repelled by these people, which reflects our desire to surround ourselves with people who are unafraid to be their imperfect selves.

As time progresses, we will all find new ways to balance how we see ourselves with how we present ourselves through digital tools and media. One way we’ll do that is by shaping virtual avatar versions of ourselves.

These avatars will not capture all the nuances of our identity and personality. And yet the choices we make in creating them could have life-altering effects. If you create a virtual identity that presents you to the world as a musician, for example, it may inspire you to lean further into that passion in the real world as well. Research from the Stanford Virtual Human Interaction Lab famously called this the Proteus Effect — a term describing how an individual’s behaviour conforms to their digital self-representation, independent of how others perceive them. The hope is that these new and possibly improved versions of ourselves, our multiversal identities, will inspire us to actually become more of the person we aspire to be.

Industry Playlists: The Non-Obvious Trends That Will Influence...

One of the trends you identify asks, ‘What if companies aimed beyond going carbon neutral and toward being actively regenerative?’ What might that look like?

Some companies are already reinventing how they fight back against environmental degradation and climate change. For example, the shoe brand Vivobarefoot, a certified B Corporation, has made a commitment not just to reduce the biological resources it uses but to create a positive environmental and social impact. As the company’s 2021 impact report states, “Vivobarefoot isn’t just about doing less bad. Instead, we want our footwear and the way

we do business to do more good. Every time we make and sell our footwear, we want the world to step toward a better place.”

To that end, Vivobarefoot was the first of dozens of footwear brands to partner with algae technology startup Bloom to use its patented BLOOM foam, which takes harmful algae blooms out of waterways, reversing the effects of water pollution. The partnership is one way the brand is trying to go beyond the usual sustainability practice of sourcing recycled materials to reverse the impact of its products on the environment.

How Humanity Will Survive

New Collectivism

What if startup founders dreamed of more than venture capital and unicorns?

Good Governing

What if government policies were recognized for actually making citizens’ lives better?

The 15-Minute City

What if every journey in the city was kept to a max of 15 minutes?

Inhuman Delivery

What if you could get anything delivered to your doorstep within minutes?

Urban Forests

What if we invested in more green infrastructure to make cities more sustainable?

Nu-Agriculture

What if we could make clean, abundant food for everyone out of thin air?

Waste-Free Products

What if you could throw things away with a clean conscience?

Millions of Microgrids

What if you could generate your own energy—reliably and cheaply?

Making Weather

What if humanity could control the weather to fight the effects of global warming?

Beyond Net Zero

What if companies aimed beyond going carbon neutral and toward being actively regenerative ?

This push for carbon negative products can be seen in a growing range of industries. Numerous building materials, from bricks to wood, are now being manufactured with carbon negative processes. New York–based Air Company uses solar energy to heat and transform carbon dioxide into luxury goods. Its flagship product, a carbon negative vodka, is promoted as ‘the world’s cleanest, highest quality and most sustainable spirit.’ Soft knitwear brand Sheep Inc. calls itself the first carbon negative clothing brand and sends customers regular updates about the sheep that provided the wool for the products they purchased. These sort of efforts will — and must — continue.

You also believe there will come a time when humanity can control the weather to fight the effects of global warming. Please unpack this for us.

In some ways this time is already here… and it’s creating a lot of debate about what we should or could do. Scientists are actively testing weather modification technologies. For example, in early 2019, the renowned Association of Siamese Architects issued an unusual call for entries for its annual design competition. The theme of the contest was Uncanny Sustainability, and entrants were challenged to share fresh ideas that were so radical, unanticipated and transformative that they could earn the epithet ‘uncanny.’ One of the winning entries was a bold program for ‘re-iceberg-isation’ in the Arctic. Led by then 29-year-old Indonesian architect Faris Rajak Kotahatuhaha, the idea involved building a ship that could be submerged in ice-cold waters to produce 16-foot-thick, 82-foot-wide hexagonal icebergs. The hexagonal shape, according to Kotahatuhaha, might allow these ‘ice babies,’ as he called them, to interlock and eventually create new icebergs to replace those that are melting.

There are concerns about tampering with nature, of course. One form of geo-engineering is ‘ocean fertilization,’ the practice of dispersing iron into the world’s oceans as a way to create more carbon-dioxide-absorbing algae blooms. The concept offers the prospect of both reducing the concentration of atmospheric greenhouse gases with the aim of slowing climate change and at the same time increasing fish stocks via increasing primary production. However, it has inspired concerns about unintended consequences among some scientists — such as whether we may be introducing an imbalance in the ecosystem that we may not be able to measure until it becomes irreversible. Other weather modification innovations such as solar geoengineering or cloud seeding face similar debates. Yet the most compelling argument in favour of these experiments is also the most dire: at some point in the future, humanity may truly have no choice but to invest in these efforts.

What is your advice to those who want to embrace future normal opportunities?

The secret to seizing emerging opportunities has always been in bridging two dimensions: embracing the new, while grounding it in what will not change. Over the three years that we interviewed the instigators profiled in the book, we were regularly inspired by their positivity and belief that we can build a better future. This all starts with being able to imagine it.

Maintaining this sense of optimism can be hard. Every day we face new stories about the potentially dire consequences of AI or climate change or geopolitical tensions. Despite all the negativity, our shared future normal will not be driven by technology alone. And it will not be a disaster if we work together to imagine something better. If there is one thing that writing this book taught us, it is the lesson that human ingenuity and what we can accomplish when we work together is the one thing that should always give us hope.

How We Will Live, Work, and Consume

Augmented Creativity

What if artificial intelligence could make humans more creative?

Remote Work for All

What if even the most physical of jobs—from tattooist to truck drivers—could be done remotely?

Reflective Cultures

What if our organizations’ cultures reflected the societies in which they operate?

Big Brand Redemption

What if more of the world’s biggest businesses prioritized doing good over profits?

Impact Hubs

What if your office space could contribute to the local economy and community?

Unnaturally Better

What if “fake” was better?

Calculated Consumption

What if we started tracking our carbon footprints in the same way we track our calorie or salt intakes?

Guilt-Free Indulgence

What if you didn’t have to give up products and experiences that are not great for you or the planet?

Secondhand Status

What if buying pre-loved goods became a sign of saviness and a source of pride?

Rohit Bhargava is Founder and Chief Trend Curator of The NonObvious Company and an Adjunct Professor of Marketing and Storytelling at Georgetown University. The founder of Ideapress Publishing and the Wall Street Journal bestselling author of the Non-Obvious Trends series, his latest book is The Future Normal: How We Will Live, Work and Thrive in the Next Decade, co-authored with Henry Coutinho-Mason, one of the world’s leading authorities on consumer trends.

3D rendering of the Artic ice-making submarine concept. (Source:AssociationofSiameseArchitectsCompetition)

At some point in the future, humanity may truly have no choice but to invest in these efforts.

Dear Executives: Please Stop Performing ‘Culture Theatre’

DEAR EXECUTIVES, We have two requests for you. First, stop relegating your cultural change programs to HR. Start adding them to the top of your leadership agenda. And second, stop blaming others if your attempts at culture change don’t stick. Start shifting your focus to how you and your colleagues behave.

In our work with leading organizations, we are seeing a growing divide between the rhetoric of leaders and their actual behaviour. In their words, they are ‘eager to abandon the conventional, command-and-control model.’ They want to change the narrative. They use popular words like purpose, psychological safety, empowerment and tolerance for failure. But in practice, these buzzwords are frequently not reflected in their daily actions and attitudes.

Recently, an executive of a large utility company praised the importance of psychological safety during a half-day workshop we organized with his team. A couple of hours later, he was telling his team what needed to be done, leaving no room for discussion. Unfortunately, this happens more often than not. Too many executives aren’t walking the talk. And the more inconsistent their espoused val-

ues are with their actual behaviour, the harder it is to fight employee cynicism, disengagement and dissatisfaction. So, what should executives do to avoid perpetuating ‘culture theatre’?

Mixing our consulting experience with the research of Harvard Business School Professor Gary Pisano, we have developed a practical approach to help leaders lay the foundation for successful cultural transformations. At the heart of our ‘culture change recipe’ is what we call the Leadership Social Contract, a set of actionable behaviours that leaders must commit to either stop doing, start doing or keep doing. Our approach follows three main steps:

1. Measure concrete behaviours rather than abstract values;

2. Select specific behaviours to stop/start/keep doing; and

3. Live these behaviours in practice.

Let’s take a closer look at each.

STEP 1: Measure Concrete Behaviours Rather Than Abstract Values

Why shift the focus from abstract value statements to concrete behaviours? Simple: because they are observable and measurable. In 2021, we surveyed over 3,000 executives

POINT OF VIEW Elisa Farri and Gabriele Rosani, Capgemini Invent’s Management Lab

Survey Results: Benchmark

Our 30 questions were clustered into five main dimensions (each with two polarities)

Bars indicate respondants who ‘agree’ or ‘strongly agree’ with their company’s propensity for each element

from large industrial, life sciences and chemical companies in the U.S. and Europe. For each level of the organization, participants anonymously evaluated the behaviours of the leader they reported to. Some companies applied the evaluation to individual leaders (with their acceptance) rather than at a category level, which made the analysis more powerful, specific and actionable, reducing the typical dilution of general surveys.

The assessment covered 30 concrete behaviours organized around five main dimensions of innovative cultures: collaboration, psychological safety, empowerment, attitude toward failure and experimentation. With survey results, each leader could identify the key imbalances and improvement areas. They also looked at how demographics both within and across teams compared.

The survey allowed, for example, chemical manufacturer BASF to confront the challenge of a substantial lack of giving candid and frank feedback rather than muffled criticism. Comparison of scores in different areas, functions and layers helped the company identify areas of opportunity to focus on. “One of the key findings for us was the need for more candid and open discussions at gate meetings of the innovation funnel, in order to determine measures for providing further important insights,” recalls Helmut Winterling, a senior vice president at BASF. The company was able

to track real progress by quantifying its ‘leadership behaviour shift’ and launched further targeted actions. By pulling together the survey data, each participating company could also compare its own positioning against the benchmark, deriving common patterns or differences. For instance, candour was a common challenge across companies (see Figure One), with most leaders falling short on that dimension.

Some companies went further and applied the survey more granularly. Leaders were assessed anonymously by the people they manage or work with (not only direct reports but also other collaborators and peers). “To be honest, I was hesitant to participate,” declared the vice-president of operations of a European energy firm. “My specific behaviours were the subject of the analysis. The discussion on survey results was difficult and sometimes painful, but I must say, the gains were significant. We agreed on the importance of working on ourselves. It sealed our shared commitment for authentic change.”

STEP 2: Select Specific Behaviours to Stop/Start/Keep Doing

Change starts with an understanding of where gaps and unbalances exist and calls for an honest discussion about what leaders have learned and agree to address going forward.

Example From Vodafone Digital Networks’ Leadership Pact

CATEGORIES STOP KEEP/START

Tolerance for failure BUT no tolerance for incompetence

Willingness to experiment BUT highly disciplined

Psychologically safe BUT brutally candid Collaboration BUT with individual accountability

Empowerment BUT strong leadership

FIGURE TWO

• Being uncomfortable with poor/subperformance (‘I’ve tolerated incompetence for too long’; ‘I’ve defended failure assuming I was defending my team’)

• Hesitating to kill experiments if they are not progressing

• Making facial/body expressions of irritation when receiving bad news

• Encouraging conversations on failure, measuring learnings and embedding them into our ways of working

• Promoting a high-performing and competent culture, taking concrete actions when incompetence occurs

• Setting clear goals, criteria and rules for experimentation

• Challenging the status quo by exploring uncharted territories

• Ensure active listening and being present during meetings by setting clear meeting rules (e.g., ‘close laptop’/ ‘put mobile on airplane mode’)

• Clarify meeting expectations: who should join and why it makes sense for some to skip a meeting

• Making decisions based on consensus

• Marking own territory (‘us vs. them’)

• Acting as a top-down decision-maker, overriding decisions, wanting to be involved in all decisions

• Clarity on who decides and how decision-making should unfold (e.g., context setting)

• Communicating strategy clearly

• Being more explicit and/communicating expectations on what you expect other people to do — as well as what they should expect from you as a role model

To facilitate the discussion and alignment, we developed a set of 30 behavioural cards that mirror the survey questions. On the front of the card, a behaviour is labelled with three or four words. On the back, a few sentences make it more concrete, with an empty space that participants can customize to write specific actions related to their particular context. Half of the cards represent typically virtuous positive behaviours, while the other half comprise negative/toxic behaviours.

We applied the cards in dozens of workshops with leaders, helping them sort out positive behaviours they commit to start/keep doing and negative behaviours to stop. Nothing was hidden. The hard truth about what needed to change, and why, forced leaders to align on a shared path forward.

Simon Norton, head of Vodafone Digital Networks and OSS Europe recalled: “Alongside the usual priorities that typically eat up so much of our available time, we found the time to focus on our organizational culture. The card deck

lent structure and helped to make the discussion concrete. We went to the core of a number of challenges that have led to certain tensions on our team in the past.”

When the discussion was over, leaders signed their contract (see the sample in Figure Two), a one-page document with a list of three or four concrete behaviours to stop and three or four to start or keep doing from day to day. Being specific when choosing the behaviours that need to change is fundamental so leaders can remember them every day.

At Enel X WAY, the electric mobility division of Enel, the first two management lines defined their own Leadership Social Contract. Once finalized, each presented and discussed it with their team during a dedicated meeting. The goal was to nurture a diffused sense of ownership and commitment throughout the organization. The people and organization team and the communications function supported the dissemination and visibility of the contract. “Working

in a new sector like e-mobility means that you cannot leverage a traditional culture,” Elisabetta Ripa, CEO of ENEL X WAY, told us. “What you need is a strong pact with the team, a framework of solid trust and encouraging people to try new things without fearing mistakes. To define our #waymakers Social Contract, we openly shared reflections and visions about the team we want to become.”

To turn a Social Contract into daily practice, each person should customize it to their specific context, by identifying one concrete individual action for each behaviour included in the contract. All individual actions, written on cards, can be placed on a bulletin board in the office. Making all commitments transparent reminds people to give ongoing feedback — and to recognize people for living the social contract.

STEP 3: Live the Behaviours in Practice and Measure Progress

Respecting the behaviours listed in the Social Contract is hard work. Despite leaders’ best intentions, it is tempting to go back to familiar ways of being and managing. To help leaders live their contract, new routines, metrics and team practices should be introduced to support them. The CEO of an agrichemical company devised a structured approach to ‘force’ himself and his leadership team to behave consistently with the Social Contract. In the agenda of routine meetings, he started including a specific discussion item related to one of the challenging behaviours identified in the contract. By providing time and space for candid discussion and peer feedback, he keeps people focused on making the transition to a new behavioural framework.

At Vodafone Digital Networks and OSS Europe, the leadership team organizes ‘Social Contract circles’, which are remote periodical sessions to share stories and experiences on how leaders are making the transition. They also have candid debates about challenges and ways to overcome them.

Another essential element to help leaders pay more attention to behavioural change is measuring the evolution and progresses against the initial baseline survey. Ideally every year, the survey should be repeated to measure the improvement on the scores after implementing the corrective actions of the selected behaviours. For the most critical areas, it could be helpful to develop ad hoc indexes. For instance, one life sciences company addressed the gap discovered on ‘candor’ by measuring progress on a tool dubbed The Candor Index.

In closing

We have seen far too many culture-change programs built around vague value statements and cascaded down throughout companies. Before announcing that entire organization needs to change, executives have a duty to change their own behaviour first.

Starting from the hard truth depicted through a quantitative baseline of observable and measurable behaviours, leadership teams can construct a Social Contract and make it a habit to sustain the change every day. So, to be credible, dear executives, please look to your own behaviour — for the good of your organization.

Elisa Farri is Vice President and Co-Lead of Capgemini Invent’s Management Lab and a member of the Thinkers50 Radar Class of 2023. Previously, she was a researcher at the Harvard Business School Europe Research Center in France. Gabriele Rosani is Director of Content and Research at Capgemini Invent’s Management Lab.

Each team member should identify one concrete action to tackle for each behaviour in the contract.

Q &A

Interview by Jason Hreno

George Lucas hired you to start the computer division at Lucasfilm in 1979. Seven years later, that division was sold to Steve Jobs and became Pixar. The rest is history. What was it like running Pixar in the early days?

My leadership mindset actually started to form before that, at the University of Utah, where I studied computer graphics at the Graduate School of Computing. It was this totally open, sharing environment with a remarkably innovative, long-term vision that allowed me to combine my passions for animation and computers. We were on the frontier of an entirely new field, and those years had a profound effect on me. I knew I wanted to be in that kind of environment for the rest of my life.

At Lucasfilm and then at Pixar, I absolutely loved the technical problem-solving aspects of the work, but I also became fascinated by the way people interact in a creative environment. I recognized quickly that I wanted to create a culture where people felt like they were all peers and equally necessary. From the very beginning, we talked about how we treated each other and how we valued people. These became core values for the company — and for me.

A film industry pioneer explains the core elements of his leadership style—and why people are wrong about Steve Jobs.

QUESTIONS FOR Ed Catmull, Co-Founder, Pixar and Author, CreativityInc.

In a culture of innovation, experimentation and failure are critical. Describe how you built a ‘fearless’ environment. Pixar people have always loved high-risk ideas. When you do something new and original, by definition you’re doing something that has never been done before, which means you’re going to face problems. That’s certainly true with making films. However, we rarely used the terminology of failure. The mindset was more about constantly asking, ’Okay everyone, is this working?’ If the answer was no, then it was ‘Let’s try this’ — and so on. Think how easy it would have been for a movie about talking toys to feel sappy, or how off-putting a movie about rats preparing food could have been. We dared to attempt these stories, but we certainly didn’t get them right on the first pass — not by a long shot.

In meetings, if there were three people in the room with more power than the others, for the first 15 minutes, they knew they had to remain silent. If they spoke first, they would set the tone, and we didn’t want that. That’s part of creating a fearless environment. It tells people, ‘We support you and want to create a safe environment where we can all benefit from a sense of inclusion.’ Candour has been absolutely critical to our culture and success. You can’t address problems if people are afraid to say they exist.

Pixar has some unique practices that reflect these values, including Braintrust meetings. Please describe how they work.

That’s one of the ways we tried to institutionalize candour, and it has been our primary delivery mechanism for straight talk. The Braintrust meets after a screening of a film-inprogress to help solve problems. The premise is simple: put smart, passionate people in a room together, charge them with identifying and solving problems and encourage them to be candid with each other.

All of our storytellers are at these meetings: the directors, writers, problem-solvers and people from the story

department. The truth is, early on, all of our movies suck; our job is to make them go from suck to not-suck. Every director, no matter how talented, gets a bit lost somewhere along the way. So we screen the movie in its current form and the team picks away at it. We want people to be honest, but we also want them to get comfortable with candour. If I could distill a Braintrust meeting down to its essential ingredients, they would be frank talk, spirited debate, laughter and love. Over time, that’s a big part of how our culture was built.

Describe the ongoing struggle between what you call ‘the beast’ and ‘the baby’ at Pixar.

After all the success of Disney Animation in the 1990s, each new Disney film created a fierce hunger for more. And as the company’s infrastructure grew, the need for more product in the pipeline only expanded. That’s where the concept of ‘feeding the beast’ came from. The problem is that originality can be very fragile, and in its first moments, it’s often far from pretty. That’s why I came to call early mockups of films ‘ugly babies.’ They all needed nurturing, in the form of time and patience, in order to grow. But that meant they would have a hard time coexisting with the beast side of the organization.

After The Lion King was released in 1994, Disney Animation began a slow decline, and I believe that was the direct result of its leaders thinking their job was to keep feeding the beast. I knew if we weren’t careful at Pixar, the same thing would happen to us. Our job was to protect our ‘babies’ from being judged too quickly by people who didn’t understand that, in order for greatness to emerge, there must be phases of ‘not-so-greatness.’

After Disney acquired Pixar in 2006, our first task was to restore an understanding of the delicate needs and challenges of new ideas, without getting overwhelmed by the need to keep everyone else busy. We also felt that the studios needed be treated as separate groups, so the ownership for each movie was fully within each studio.

You can’t address problems if people are afraid to say they exist.

Ed’s Tips for Managing a Creative Culture

• Give a good idea to a mediocre team and they will screw it up. Give a mediocre idea to a great team and they will either fix it or come up with something better. If you get the team right, chances are that they’ll get the ideas right.

• When hiring people, give their potential to grow more weight than their current skill level. What they will be capable of tomorrow is much more important than what they can do today.

• Try to hire people who are smarter than you. Always take a chance on better, even if it seems like a potential threat.

• If there are people in your organization who feel they are not free to suggest ideas, you lose. Do not discount ideas from unexpected sources. Inspiration can, and does, come from anywhere.

• Engaging the collective brainpower of the people you work with is an active, ongoing process. As a manager, you must coax ideas out of your staff and constantly push them to contribute.

• There are many valid reasons why people aren’t candid with one another in a work environment. Your job is to search for those reasons and address them.

• Likewise, if someone disagrees with you, there is a reason. Your first job is to understand the reasoning behind their conclusion.

• If there is more truth in the hallway than in meetings, you have a problem.

• Sharing problems is an act of inclusion that makes employees feel invested in the larger enterprise.

• If you don’t always try to uncover what is unseen and understand its nature, you will be ill prepared to lead.

• It is not the manager’s job to eliminate risks. It is their job to make it safe to take them.

• A company’s communication structure should not mirror its organizational structure. Everybody should be able to talk to anybody.

• Imposing limits can encourage a creative response. Excellent work can emerge from uncomfortable or seemingly untenable circumstances.

• Does the least powerful person in the room feel safe speaking up? If the answer is no, you’ve got a problem.

Writing about your personal leadership style, you say, “Be patient, be authentic and be consistent. The trust will come.” Can you elaborate?

I’ve spent my career thinking hard about how to help smart, ambitious people work effectively with one another. The way I see it, my job is to create a fertile environment, keep it healthy and watch for things that can undermine it. Everybody has the potential to be creative — whatever form that takes — and in my mind, encouraging such development is a noble thing.

As a leader, you see things that other people don’t, but your employees also see things that you don’t. That is the case everywhere. Too often, leaders think their job is to always know the answer, but it’s not. It’s to figure out the right thing to do — and that requires listening to the people around you who see all those things you don’t see. People don’t always have to agree with each other. The fact is, they are all smart, professional people; they know they can’t have everything go their way, but they do want to be heard. So, I have always taken the time to listen. You can respect a person, but just happen to disagree. Acknowledging that is important, because it builds trust.

In addition to being a legend yourself, you’ve worked with pioneers like Bob Iger and Steve Jobs. What did they teach you?

Bob was incredibly smart and took big risks. The first thing he did as the new CEO of Disney was to tell Steve he wanted to buy Pixar. But Bob admitted to Steve, “Disney Animation is not in a good state right now and I don’t know how to fix it.” Steve was blown away. He valued Bob’s honesty so much that it was the beginning of a deep and long friendship.

In the early days, Steve had a reputation. People love to write about it to this day — but in my mind they’ve missed the real story. Steve really lived the ‘hero’s journey,’ and

went through a remarkable personal transformation. Over time he became more empathetic and changed the way he interacted with people. After this change, the people who were ‘with’ Steve stayed with him for the rest of his life. The key to his success, I believe, was that he kept people around him who knew how to disagree with him. That was invaluable to him.

If you tried to match Steve in terms of thinking-speed in the moment — no one could do that. But contrary to what some might think, he didn’t need to be right all the time. If an idea didn’t work, he had a remarkable ability to switch on a dime. I witnessed this first-hand at Pixar. I worked for Steve longer than anybody in my career, and we never had an argument, even though we sometimes disagreed strongly. You don’t need to argue to disagree.

Every organization aspires to be as creative and successful as Pixar. What are the key takeaways for readers?

First, if you can embrace the fact that you don’t (and can’t) see and know everything, and that you are probably wrong half the time, it will open you up to ideas and possibilities that can transform your company. Over the years I have frequently spoken with people in the computer industry who saw a big change coming, but their leaders just wouldn’t listen to them. Being a public company, it was more important for them to hit the quarterly numbers. People think they have to be right, right now, but what you really want is to be right in the long run.

Second, it’s incredibly important to recognize the human dynamic behind every business. Your employees are all emotional beings with their own aspirations and desires. My goal as a leader has been to train people to listen to their colleagues and make a habit of genuinely helping each other. Working on difficult problems can be messy and there is always a temptation not to share the responsibility.

Without a doubt, my happiest times at Pixar were when the studio’s top leaders met as a team and we owned a problem together. If I can leave people with one ‘pearl of wisdom,’ it would be this: We are all in this together. And by ‘this,’ I mean owning hard problems and striving to solve them.

Dr. Ed Catmull is the Co-Founder of Pixar Animation Studios and the former president of Pixar and Walt Disney Animation Studios. He is the co-author of Creativity Inc.: Overcoming the Unseen Forces That Stand in the Way of True Inspiration (Random House, Expanded Edition, 2023). Pixar has produced hits including Toy Story , Frozen , Cars and The Incredibles, grossing more than US$14 billion at the worldwide box office and winning 18 Academy Awards, 10 Golden Globes and 11 Grammys.

If you can embrace the fact that you are probably wrong half of the time, it will open you up to ideas that can transform your company.

One Community. Infinite Possibilities.

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From intellectual property essentials for health sector start-ups to the science of failing to succeed, to AI and more, our diverse series covers a wide range of relevant topics for today’s business landscape. Featuring renowned authors, entrepreneurs, and industry experts, you’ll gain practical strategies, tools, and tips for success. Attend in person or virtually to ignite your learning journey, network with like-minded professionals, and stay ahead of the curve. Reserve your spot today!

september 6 | 12 – 1 pm | virtual event

Intellectual Property Essentials for Health Sector Startups

Alberto Galasso Professor of Strategic Management, Rotman School of Management, University of Toronto

Stephen Leonard Co-founder of Qvella

Tamara O’Connell Patent Portfolio Manager, University of Toronto

Ella Korets-Smith

Co-founder and Chief Business Officer, Virica Biotech; Founder,EKS Business Development

september 7 | 5 – 6 pm | in-person & virtual

The AI Dilemma: 7 Principles for Responsible

Technology

Juliette Powell Data scientist; Entrepreneur; Founding Partner, Kleiner Powell International; Faculty member, New York University

Art Kleiner Business and technology writer; Entrepreneur; Editor-in-Chief, Kleiner Powell International; Faculty member, New York University

september 12 | 12 – 1 pm | virtual event

4 Short Talks About Work-in-Progress

Featuring 4 contributors from Rotman Management Magazine’s Fall 2023 Issue

september 18 | 5 – 6 pm | in-person & virtual

Gonzo Capitalism:

How

to Make Money in An Economy That Hates You

october 2 | 5 – 6 pm | in-person & virtual

The Power of Saying No: The New Science of How to

Say

No

That Puts You in Charge of Your Life

Vanessa Patrick Professor of Marketing and Associate Dean of Research, Bauer College of Business, University of Houston

october 10 | 5 – 6 pm | in-person & virtual

The Pink Tax: Dismantling a Financial System Designed to Keep Women Broke

CPA; Founder and CEO, The Wealth Building Academy Inc.; TEDx speaker

october 16 | 5 – 6 pm | in-person & virtual

Right Kind of Wrong: The Science of Failing Well

Amy C. Edmondson

Professor of Leadership and Management, Harvard Business School; Author

november 13 | 5 – 6 pm | in-person & virtual

The Future of Us: The Science of What We’ll Eat, Where We’ll Live, and Who We’ll Be

Jay Ingram Author, broadcaster, and science communicator

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