October–December 2017
The Official Journal of the International Association for Human Resource Information Management
IHRIM.ORG
Technology is driving the Creation of New Roles in the HR Organization
See the Buyer’s Guide, Page 17
Contents
Volume 8, Number 4 • October-December 2017
From the Editors 3 Bruno Querenet, Darshana Z. Narayanan, and Michael Rudnick
featured articles in this issue… Overview of the Impact of Technology and Science on HR organizations
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By Bruno Querenet, Think Surgical Technology cannot be just the realm of HRIS teams; it needs to permeate the whole organization to digitally transform each component of the HR function. The HRIS team needs to build a tech culture within HR to enable its digitalization and federate its tech investments. It needs to ensure that processes and data are tied together, creating pathways between process owners and data scientists so that they can feed each other. But it cannot be anymore the unique and focal point for all tech investment.
Why Digital Success needs the “Human” to be at the Forefront of HR
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By Margaret-Ann Cole, Accenture As digital transformation takes hold, HR teams will require the development of new roles such as employee experience designer, business change catalyst, adaptive workforce manager and social media specialist. HR will have to be prepared to address and take advantage of the emergence of the adaptive workforce. That means increasing organizational flexibility by understanding how intelligent platforms can allocate and deploy talent more flexibly across a variety of new roles and tasks.
Lean Enterprise: Using Agile and Lean Practices to Transform Organizations 9 By Mariya Breyter, Ph.D and Darshana Z. Narayanan, Ph.D. Agile and Lean dictate new ways of thinking about our professional ecosystem: collaborative, outcome-oriented, customer valuedriven. It is time we updated our framework of thinking. The LeanAgile mindset calls for a new revolutionary approach to hiring,
recognition, and career growth; and in this brave new world, HR professionals become key players in creating, maintaining, and sharing that forward-thinking ecosystem.
HR Data Science: Delivery Model Alternatives
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By Jason Ezratty and Michael Benyamin, Brightfield Strategies Every service delivery model has the potential to be successful in some way, but eventually client demand will exceed the people analytics team’s internal capabilities and/or capacity. You certainly don’t have to spend time building the function one person at a time, which can slow down your ability to deliver additional value quickly. The authors provide five steps to take to figure out how to approach the next evolution in service delivery.
The Back Story:
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Build for an Unknown Future: Preparing for Digital Jobs that Don’t Yet Exist. By Katherine Jones, Ph.D., Mercer Perhaps the first step in digitization transformation is to get today’s workers the technical tools they need to more easily accomplish the tasks of today. From the HR perspective, however, automating the workers is not the same as creating a truly digitized business. Digital transformation surpasses how work is conducted and with what tools. It is a concept that covers people and technology — but also requires a change in policies: a relook at not just how work is done but what work needs to be done. In this, jobs as we know them today will change. It’s our job to start getting ready.
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Buyer’s Guide Workforce Solutions Review (ISSN 2154-6975) is published quarterly for the International Association for Human Resource Information Management by Futura Publishing LLC, 12809 Shady Mountain Road, Leander, TX 78641. Subscription rates can be found at www. ihrimpublications.com. Please send address corrections to Workforce Solutions Review at the address above.
www.ihrim.org • Workforce Solutions Review • October-December 2017
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Volume 8, Number 4 • October-December 2017
Workforce Solutions Review is a publication of the International Association for Human Resource Information Management, whose mission is to be the leading professional association for knowledge, education and solutions supporting human capital management. Opinions expressed herein are not necessarily those of the editors, the IHRIM board of directors or the membership.
SCOTT BOLMAN, HR Transformation & HR Excellence Practice, Deloitte, bolmanscott@yahoo.com
© 2017 All rights reserved
ELENA M. ORDÓÑEZ DEL CAMPO, Senior VP Global Delivery Unit, SAP AG, Frankfurt, Germany elena. ordonez@sap.com
EDITORIAL COMMITTEE Managing Editor BRUNO QUERENET, Head of HR, Think Surgical Bruno.querenet@gmail.com
Co-Managing Editor MICHAEL RUDNICK, Managing Partner, Prescient Digital Media, Michael.rudnick@gmail.com
Associate Editors ROY ALTMAN, HRIS Manager - HR Analytics & Application Architecture at Memorial Sloan-Kettering Cancer Center, New York, NY roy@peopleserv.com SCOTT BOLMAN, HR Transformation Consulting Leader, Deloitte, bolmanscott@yahoo.com
YVETTE CAMERON, Global Vice President Strategy, SuccessFactors, Littleton, CO Yvette.cameron@successfactors.com LEW CONNER, Executive Director, Higher Education User Group, Gilbert, AZ USA lconner@heug.org
GARY DURBIN, Chief Technology Officer, SynchSource, Oakland, CA USA hacker@synchsource.com Dr. CHARLES H. FAY, Professor, School of Management & Labor Relations, Rutgers University, Highland Park, NJ USA cfay@smlr.rutgers.edu DR. URSULA CHRISTINA FELLBERG, Owner & Managing Director, UCF-StrategieBeraterin, Munich, Germany ucfell@mac.com ALSEN HSEIN, President,Take5 People Limited, Shanghai, PRC Alsen@take5people.com CARL C. HOFFMANN, Director, Human Capital Management & Performance LLC, Chapel Hill, NC USA cc_hoffmann@yahoo.com JIM HOLINCHECK, VP Customer Deployment Applications, Workday, Chicago, IL USA james.holincheck@workday.com
LISA STERLING, Executive Vice President, Chief People Officer, Ceridian, Lincoln, NE USA, lisa.sterling@ceridian.com DR. DANIEL SULLIVAN, Professor of International Business, University of Delaware, Newark, Delaware USA sullivad@lerner.udel.edu MARK SMITH, CEO, Chief Research Officer, and Founder of Ventana Research, San Ramon, CA USA mark.smith@ventanaresearch.com DAVE ULRICH, Professor, University of Michigan, Ann Arbor, MI USA dou@umich.edu JULIE YOO, Founder and Chief Data Scientist, Pymetrics, julie@pymetrics.com DR. MARY YOUNG, Principal Researcher, Human Capital, The Conference Board, New York, NY USA mary.young@conference-board.org
IHRIM BOARD OF DIRECTORS Officers and Executive Committee JIM PETTIT, HRIP, SHRM-SCP, Chair MICK COLLINS, Vice Chair GARY MORLOCK, HRIP, CFO, Finance Committee Chair JOYCE BROWN, Secretary SHAFIQ LOKHANDWALA, Executive Director
CATHERINE ANN HONEY, VP Strategic Partner Relations, Safeguard World International, Boston, MA USA catherinehoney@safeguard.com
Board Members
DAVID GABRIEL, ED.D., Global Reach Leadership, Berkeley, CA USA, davidgabriel@gmail.com
DR. KATHERINE JONES, Partner and Director of Research, Mercer, San Mateo, CA USA Katherine.Jones@mercer.com
STUART RUDNER, Director of Meeting & Events
JEFF HIGGINS, CEO, Human Capital Management Institute, Marina Del Rey, CA USA jeff.higgins@hcminst.com
SYNCO JONKEREN, VP, HCM Applications Product Development & Management, EMEA, The Netherlands synco.jonkeren@oracle.com
ERIC LESSER, KPMG, Eric.l.lesser@gmail.com
MICHAEL J. KAVANAGH, Professor Emeritus of Management, State University of Albany (SUNY), Albany, NY USA mickey.kavanagh@gmail.com
SHAWN FITZGERALD, Managing Director, Total Rewards and HR Technology, Blue Cross Blue Shield Association, Chicago, IL, USA shawn.fitzgerald@bcbsa.com
MICHAEL H. MARTIN, Partner, Aon Hewitt Consulting, Organization & HR Effectiveness, New York, NY michael.martin.6@aonhewitt.com
BOB KAUNERT, Principal, Deloitte, Philadelphia, PA USA bkaunert@yahoo.com
DARSHANA NARAYANAN, PH.D. Princeton University darshana@alumni.princeton.edu
DAVID LUDLOW, Global VP, HCM Solutions, SAP, Palo Alto, CA David.ludlow@sap.com
EDITORIAL ADVISORY BOARD
RHONDA P. MARCUCCI, CPA, Consultant for GruppoMarcucci, Chicago, IL USA rhonda@gruppomarcucci-usa.com
CECILE ALPER-LEROUX, VP Product Strategy and Development, Ultimate Software, Weston, FL cecile_leroux@ultimatesoftware.com MARK BENNETT, Work Life and Collaborative Products Strategy Director, Oracle Corp., Redwood Shores, CA USA mark.bennett@oracle.com ERIK BERGGREN, VP of Research, IDC, San Mateo, CA USA
LEXY MARTIN, Independent Consultant/Researcher, Meadow Vista, CA Lexy.martin1@gmail.com BRIAN RETZLAFF, VP of Information Technology, Voya Financial, Atlanta, GA USA LISA ROWAN, Program Director, HR, Learning & Talent Strategies, IDC, Framingham, MA USA lrowan@idc.com
JOSH BERSIN, Principal and Founder, Bersin by Deloitte, Oakland, CA USA jbersin@bersin.com
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CATHERINE HONEY, Director of Member Services & HRIM Foundation Director MARYANN MCILRAITH, Director of Communities DOUG SAMPSON, Director of Marketing & Communications SHARON THOMPSON, HRIM Foundation Director
PUBLISHING INFORMATION TOM FAULKNER, Publisher, Futura Publishing LLC, Austin, TX USA, tomf@futurapublishing.com PATTY HUBER, Advertising Manager, Austin, TX USA phuber2@austin.rr.com
Bruno Querenet, Managing Editor
Bruno Querenet is the head of HR for Think Surgical, a company building robots for orthopedic surgeries. He worked previously for Genentech where he led the deployment of Workday for Roche US. He has been head of HRIS for Intuitive Surgical, Varian Medical Systems and Spansion, and worked previously for HP and Agilent Technologies in different capacities. He can be reached at bruno.querenet@gmail.com. Darshana Z. Narayanan, Contributing Editor
Darshana Z. Narayanan has over 10 years of combined academic and industry experience in the study of human behavior: at multiple levels (individual and organization) and time scales (ontogeny and evolutionary history). She is currently at Composites Collective, leveraging her extensive understanding of complex social behaviors, and AI technology, to build tools and processes for greater and more effective collaboration and participation. She can be reached at darshana@alumni.princeton.edu. Michael Rudnick, Contributing Editor
Michael Rudnick is managing partner at Prescient Digital, a leading digital consultancy that plans, designs, and implements world-class enterprise digital experiences for employees. He has spent more than 25 years helping HR create and deliver consumer-grade digital experiences that are aligned to business and HR strategy. Before Prescient, Rudnick was VP at Logical Design Solutions. He can be reached at michael.rudnick@gmail.com.
from the editors The business world is rapidly evolving: Machine Learning, Big Data and AI have become commonplace terms in present times, and many successful companies—both within and outside the technology sphere—are reimagining their business processes with a variety of cutting-edge technology. Not surprisingly, technological advancement is also changing the traditional perspective of HR. These rapid advances are now, and will continue to be, dramatically reshaping the structure of HR departments, the roles within organizations, and the skillsets required to fulfill those roles. In this issue of WSR, we will discuss some of the fundamental changes in businesses and HR departments; providing lessons for the future of HR. We do not aim to be exhaustive. Instead, we hope that the articles in this issue will provide you with inspiration, triggering new thoughts and new action. We will start with an article from Bruno Querenet, lead editor for WSR, in which you will be presented with an overview of technological impacts on different components of HR. His article is titled “Overview of the Impact of Technology and Science on HR Organizations.” In the article titled “Why Digital Success Needs the ‘Human’ to be at the Forefront of HR” from Margaret-Ann Cole at Accenture, you will learn how HR can evolve into a true digital partner by transforming its own capabilities, roles, and skills to match digital capabilities; and, more importantly, act as the engineer of change to help organizations realize the value of digital. Mariya Breyter and Darshana Z. Narayanan, both Ph.Ds in their respective fields, will explain the shift to “Lean Enterprise” and discuss the fundamental change to HR professions in a Lean-Agile enterprise. Their article is titled “Lean Enterprise: Using Agile and Lean Practices to Transform Organizations.” In “HR Data Science: Delivery Model Alternatives,” Michael Benyamin and Jason Ezratty, from Brightfield Strategies, will explore the most common challenges businesses face in delivering credible and repeatable people analytics and will review alternative models for your consideration. This WSR issue concludes with our recurring Back Story article from Katherine Jones, Ph.D. at Mercer. Her article is titled “Build for an Unknown Future: Preparing for Digital Jobs that Don’t Yet Exist.” In her article, she will tell you what HR needs to do to keep pace for the future.
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Bruno Querenet, Think Surgical
Overview of the Impact of Technology and Science on HR organizations When I recently visited my parents (they are in their 80s), and tried to explain the nature of my job to them, I told them, “I am a technology guy within HR.” This did not resonate with them. They looked me in the eyes to probe further. “Really! What has technology to do with HR?” I went on to explain to them how exciting it was to work in this field, how beneficial science and technology could be in the management of the most precious resource of the enterprise: its workforce. Here is what I shared with them.
The Workforce The first myth to debunk is the true scope of HR. It does not only include the employees working in the enterprise, a very traditional view of HR and, still, a prevailing one in a lot of organizations. The scope of HR is the workforce at large — all resources investing time and engaged in the achievement of the company’s goals. This means employees, contractors, consultants, or service providers. The categorization of this workforce may fluctuate based on the characteristics of the company and its maturity; in all cases, it goes beyond just the consideration of its employees. The market for resources is not as fluid as it could be, the memory of the enterprise is not as strong as it could be on its resources, their skillsets, or performance – and this is clearly an area where technology can help. Where are we? Where do we want to go? What does it mean for today’s resources? How to source the needs of tomorrow? What mix of workforce makes sense to acquire? We cannot just use a piece of paper or an Excel table anymore to figure this out. Workforce planning has to enter with weight into the
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organization of HR, extending the traditional budget-planning cycle driven by finance with the key consideration of the resources needed to execute per the business objectives. Where does this activity sit? This process is crossfunctional within HR, needs strong links with the other functions, is business oriented, and requires the use of modeling and simulation techniques. This is a role which, if staffed, could lead to critical competitive advantages. I have seen it sometimes linked to Analytics, but could stand on its own or being part of an HR PMO. The key is to make it visible across the enterprise and not only within HR. Why not, then, have a functional PMO and locate this role there?
Profiling How do you select, on board, and grow talent within your organization? With technology, we can now move past the traditional screening and interview process to integrate the ability to profile individuals. The idea here is not to pigeonhole everyone, but to reveal strengths, weaknesses, or blind spots of individuals, and understand how they would play within the culture of the enterprise or the context of the specific roles to be fulfilled. The progress made in the field of psychometrics is phenomenal, and coupled with behavioral measures that test behavior in job context (e.g., simulations), talent acquisition and management processes can be transformed. We all have attributes which we use to analyze situations and make decisions. Our ladder of inference makes us think that others use the same views or principles to come to conclusions, but this is not the case. Acknowledging that, staying open minded, being able to
probe the other for their perspectives are key attributes of individuals’ abilities to work in teams and should all be tested when screening candidates. Recruiters ought to be “profilers,” they need not only to be able to assess individuals against a position; they need to be able to use tools to profile individuals and assess their ability to insert themselves in the life of the team hiring them, as well as to prepare the team to host someone with a potentially different but complementary perspective on the work at hand. How many of your recruiters are true profilers? And do it well?
Activity Management Project management and techniques such as Six Sigma or Agile/Lean practices to manage processes are now broadly used. They impact the structure of organizations, their mode of operations and, hence, should be understood and incorporated into the landscape of tools and concepts used by HR business partners or the organizational development team. Those techniques all address the collective part of work and bring leadership and teamwork to a new level of meaning. Leadership is a critical quality needed by everyone, as teamwork cannot happen without everyone taking responsibilities according to their role. Now that we have sophisticated tools to analyze data, those project management techniques take on a whole new dimension and HR needs to understand how to leverage them. When will a Six Sigma black belt be seen within OD, and the ability to manage projects strongly entrenched within HR? When will the analysis of relationships between individuals through social networks be pervasive? When will a “team” be an entity which is studied and offered services by HR as much as employees, managers, and executives?
Culture Contrary to popular belief, culture can be measured; it is hard to do but measurement is possible. Models allow an enterprise to characterize its culture and assess it against concepts such as innovation or flexibility, or against the characteristics of a new business
strategy. Culture is nebulous. It is made of myriad words, attitudes, decisions, behaviors, which together build and evolve that culture. In a short article for Harvard Business Review, Nilofer Merchant1 summarized it nicely: “Culture is the set of habits that allows a group of people to cooperate by assumption rather than by negotiation. Based on that definition, culture is not what we say, but what we do without asking. A healthy culture allows us to produce something with each other, not in spite of each other.” Progressively, we have seen consulting firms propose tools to measure culture along a defined set of dimensions. For example, CulturePath from Deloitte, allows companies to analyze their culture and assess how it changes. Other models2 look at specific characteristics such as the ones mentioned above — innovation, flexibility, or risk management. The outcome of the use of those models is a more conscious and explicit management of the culture of the enterprise. Getting a pulse on it, being able to assess its strength and evolution per desired characteristics is exciting; as we know, a strong and adequate culture is the best competitive advantage a company can have. As commonly admitted, culture trumps strategy. Are you measuring your culture? Where is it monitored and managed? How are you driving it with your executive team? How are you allowing diverse voices in the company to contribute to company culture? This is another area where the science behind those models is entering into the organization of HR. Are we ready for it? Where to host these new tools and the ability to dig into the intangibles of the company?
The Web Today, we could not live anymore without web and mobile-enabled services. The data gathered across a vast array of customers allows websites to make suggestions, to compare your choices with the choices made by others and analyze them to identify trends, relationships, and redefine the information with which you make purchase decisions. Take the simple example of Amazon and its sell of books. Whether on the Kindle, or through purchases online, Amazon has www.ihrim.org • Workforce Solutions Review • October-December 2017
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Endnotes
In “Culture trumps strategy, every time,” Nilofer Merchant, HBR, March 22, 2011. 1
For example: The InnovationOne Health Index, based on research from C.B. Dobni, to assess innovation cultures; The OCAI model, developed by K. Cameron and R. Quinn to assess organizational cultures. 2
Nudge, Improving Decisions About Health, Wealth and Happiness, R. Thaler and C. Sunstein, 2009. 3
The concept of Holocracy, or self-managing organization, is best described in Holocracy, The New Management System for a Rapidly Changing World, B. Robertson, 2015, or in Reinventing Organizations, F. Laloux, 2014. 4
About the Author
Bruno Querenet is the head of HR for Think Surgical, a company building robots for orthopedic surgeries. He worked previously for Genentech where he led the deployment of Workday for Roche US. He has been head of HRIS for Intuitive Surgical, Varian Medical Systems and Spansion, and worked previously for HP and Agilent Technologies in different capacities. He lives in California and can be reached at bruno.querenet@gmail.com.
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gathered a unique set of information used now to re-define the concept of brick and mortar booksellers. When going to an Amazon book store, you will be presented with books in a very different way than traditionally. You will have books read in less than three days (measured on Kindles), books that you may like if you liked another one, books that have a high number of reviews, books part of the 100 books you should read in your life, books recommended by people with the most followers, etc. This establishes new connections that could drive you to buy more or different books than those you were initially thinking of buying. This is all data driven, but derived largely from interests and choices made by all of Amazon customers. It is a kind of benchmark, powered by techniques such as machine learning and data mining. Now that the world of HR is massively moving to the cloud, why not do the same and establish new HR services to contractors, employees, managers, executives and teams by leveraging what we can learn from the profile and choices made by everyone within the enterprise – but also, why not by people from other enterprises using the same cloud application? This space is wide open (without yet a lot of ready-made insights available to the different segment of customers of HR services), but it’s poised to be populated soon. Think about “If you like this team, you will like these other teams,” or “Others with your profile have those roles,” or “You should consider connecting with so-and-so person as you may be able to learn from them!” You could even think about reaching the holy grail of being able to build standard KPI for HR that could be compared to other organizations through cloud services. Think also about new possibilities to build “choice architectures”3 to successfully “nudge” people toward decisions concerning their health and wealth. [It must be mentioned that we will all have to exercise caution to make sure that algorithmic biases and other biases do not create big societal issues as we implement those new online services.]
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Digital Transformation The concept of a self-managing organization, or Holocracy, is also beginning to make inroads and would require a solid data infrastructure to work. Whether implemented globally in all aspects of the management of a company or feeding only part of it, it will influence the organization of work. The most prominent example of the adoption of this new organization is Zappos. Whether applied to Holocracy or other more traditional organizational structures, the technology and the science available today are creating new possibilities for HR and new ways to look at the usual components of HR, from talent acquisition and management, to learning, organizational design, compensation and benefits, HRIS or analytics. Each of those components needs to redefine itself, to revisit its set of services and how it operates, to look at its dependencies with the other components of HR and act more coherently with them to provide a set of integrated services. Moving from silos to integration is one of the big challenges forced on HR by new technology and science. For the teams traditionally responsible for systems and processes within HR and analytics, the challenge is even greater. Technology cannot be just the realm of such teams; it needs to permeate the whole organization to digitally transform each component of the HR function. The HRIS team needs to build a tech culture within HR to enable its digitalization and federate its tech investments. It needs to ensure that processes and data are tied together, creating pathways between process owners and data scientists so that they can feed each other. But it cannot be anymore the unique and focal point for all tech investment. This fluidity requires leadership, open mindedness, curiosity, collaboration, and the ability to sense what science could mean for the organization of work and the well-being of the workforce, so that it can be “in the flow.” Human Resources clearly needs to redefine itself or it will not play the vital role that is expected from it in our 21st century.
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Margaret-Ann Cole, Accenture
Why digital success needs the “Human” to be at the forefront of HR. In the era of the intelligent enterprise, technology is not an end in itself. It’s for people. Technology augments and enhances human skills to unlock tremendous value and shape a positive future for all. To capture their share of that value, businesses will use digital for new customer experiences and new talent models, ecosystems and enabling tools that unleash the power of the workforce. The HR workforce will be at the center of this evolution. They’ll have two key parts to play. They’ll see their own capabilities, roles and skills transformed by the impact of digital. But, more importantly, they will act as the engineer of change to help their organization realize the value of digital. It’s a sizeable prize. The World Economic Forum1 estimates that digital transformation could unlock $100 trillion for business and society. It will fundamentally transform the way we work and live and help enable workforces to do more, achieve more and be more. Different generations entering and exiting the workforce in the context of a rapidly changing technological landscape are redefining the nature of work. To support this new kind of work, along with the evolving and diverse workforce that will do it, HR must become a business collaborator, a talent driver and a key strategic partner contributing to the business agenda.
New world, new work, new talent models…
The new world that digital is shaping requires companies to develop new talent models to support new types of work. Their leaders and employees will have to be equipped with those capabilities and experiences that will drive business outcomes. This urgent need to evolve is well-recognized by senior executives. Accenture research shows that 80 percent of
them believe HR should shift its mandate to become a driver of workforce performance.2 Furthermore, 84 percent of executives believe HR should take responsibility for leading talent innovation throughout the organization.3
Disrupted companies need a disrupted HR.
So how should HR evolve to take on this new strategic responsibility? HR will steer digital transformation as a strategic partner to the business. It will do this by adopting innovative people strategies—enabled by Artificial Intelligence (AI), automation and analytics—to drive business outcomes. HR will be the engineer behind building the digital capabilities of leaders and employees to enable them to thrive in what is fast becoming the new normal. As we reimagine how HR carries out its role in this digital age, it will be imperative to keep people at the center of work that requires strategic thinking, innovation, complex decision making and personal interaction. The reimagined organization will consist of three layers: 1. Strategic: employing empowered talent to innovate and lead. This is where the future vision is set and the road to achieve it mapped out. 2. Analytical: combining human and machine for precision at scale. The vast amounts of data coming into an organization offer the opportunity to unlock new value and discover insights that can help set a new direction for talent. Technologies such as AI, machine learning and advanced analytics offer the ability to achieve this at unprecedented scale and speed. But, rather than replacing people, these technologies will augment human capabilities, enhancing decision-making and reinventing the art of the possible. www.ihrim.org • Workforce Solutions Review • October-December 2017
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3. Execution: artificial intelligence, automation, and robotics will take over work that is more effectively performed by technology. Routine administration and transactional work, for example, will be handled by machines at unprecedented levels of efficiency. And by doing so, it frees up people to focus on higher-value activities.
Endnotes 1
“ Digital Transformation Initiative: Unlocking $100 Trillion for Business and Society from Digital Transformation”, WEF and Accenture, 2017.
2
Accenture Strategy HR & Employee Experience research, 2017.
3
Ibid.
4
h ttps://www.techrepublic. com/article/ai-will-eliminate1-8m-jobs-but-create-23m-by-2020-claims-gartner/
About the Author
Margaret-Ann Cole is a managing director in Accenture’s Talent & Organization practice specializing in enterprise transformation, based out of the New York office, and leads T&O consulting for the Southeast region. She has spent a majority of her career consulting with chief human resources officers, chief talent officers and other C-Level executives on building high performance businesses that drive optimization and growth through HR strategy, talent management, HR service delivery, and HR technology. She can be reached at @Margaretanncole.
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Technology amplifies the human.
The progress of automation over the next three to five years will change work dramatically. Advanced analytics enable HR and the business greater insight into workforce performance, resources needs and, availability of talent. The growth of the freelance workforce (critically, both internal and external), and workers’ desire for more gig work, will drive a new view of how work gets done, using contractors, outsourcing partners, vendors, and other non-traditional employees. Digital technology, including social, gamification, cloud, mobile, big data and consumer applications, is transforming how people carry out their work. HR will need to adapt to address all of these changes. As organizations become digital and adaptive, roles will evolve. Students in school and college today will graduate to take up new roles that have yet to be invented or defined. That creates a requirement for new skills in both the overall organization and HR. While some roles will be lost before 2020 due to AI, RPA and other technologies, those same technological advances are estimated to create 2.3 million new jobs in the same timeframe.4 Many of the skills that success in this new digital world rests on are distinctly human. Some of the most important include social skills such as empathy and cooperation. Creativity, critical thinking and leadership will also be fundamental alongside technical prowess in math and computer science. In addition, there’s a clear role for such invaluable, though hard to acquire, qualities such as wisdom and seasoned experience. In the clamor for millennial talent (important as that is) the cultivation of experienced and “wise” leaders can be overlooked. But they can provide an effective balance of needed skills. Wise HR departments will make the best use of these often-neglected pools of talent.
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As digital transformation takes hold, HR teams will require the development of new roles such as employee experience designer, business change catalyst, adaptive workforce manager and social media specialist. HR will have to be prepared to address and take advantage of the emergence of the adaptive workforce. That means increasing organizational flexibility by understanding how intelligent platforms can allocate and deploy talent more flexibly across a variety of new roles and tasks.
Getting ready for the future, now.
HR leaders understand that their organizations need to evolve into a true partner in digital transformation. To do that, they must take the right actions to shape a positive future for the business and the HR workforce. But, the key question is: how do they get started? In my view, there are five steps that all should start taking now: 1. Set a future-state VISION, based on what automation will mean for the business, the HR organization and the individual worker. 2. Create a DIGITAL WORKFORCE STRATEGY and agile implementation plans that take into account future talent requirements, the potential of automation, and the need for new roles. 3. Identify opportunities to automate HR tasks, according to their value potential and the effort required to achieve it. Select one or two areas for PILOT programs that can demonstrate value. 4. Make the HR organization CHANGEREADY. Define a new operating model and roadmap. Explore opportunities to form an Adaptive Workforce. Refine jobs/ roles, and establish new governance, leadership and performance management practices. Establish a culture aimed at continually enhancing the workforce experience. 5. IMPLEMENT business automation and augmentation plans more broadly. Transition to an adaptive workforce and build skills, as needed. Establish new talent pools, platforms and development programs, and identify new metrics (beyond cost and efficiency gains) for success.
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Mariya Breyter, Ph.D and Darshana Z. Narayanan, Ph.D.
Lean Enterprise: Using Agile and Lean Practices to Transform Organizations Introduction Starting from the late 1990s, the Agile framework has introduced a distinctive thinking to the way organizations operate. Agile originated in software development and created a set of values and practices based on Lean thinking, a business methodology that came out of the manufacturing industry. The main tenets of Lean include delivering value to customers, elimination of any waste (including extra resources, skills, or materials) and, individuals taking ownership over how they work. The Agile framework added two important aspects to Lean thinking: iterative delivery and team-based structure. As simple as it sounds, this approach was revolutionary to the traditional mindset of software delivery, which at the time, used non-iterative phased (or “waterfall”) delivery and competency-based organizational structure. The Waterfall methodology treated projects as a predefined endeavor thus limiting opportunities for employees to apply ongoing learning throughout implementation. In terms of professional growth, waterfall focused on a narrow skillset while many people were seeking opportunities to enhance their skills in adjacent areas of competency (horizontal career moves) rather than staying focused on one narrow field throughout their professional life. Agile has replaced the waterfall methodology and in less than 20 years, Agile has become a mainstream approach in software delivery, has found applicability outside the technology industry and, has shown value across the whole enterprise—leading to the concept of a “Lean Enterprise.” In this article, we will explain the shift to “Lean Enterprise” and discuss the fundamental change to HR professions in a Lean-Agile enterprise.
Lean Thinking
In his book “Smarter Faster Better,”1 New York Times reporter Charles Duhigg tells the story of a General Motors plant in Fremont, CA. This plant had earned the title of “the worst auto factory in the world” and was shut down in 1982. One of the main reasons for the plant’s terrible reputation and eventual shut down is reflected in the words of Rick Madrid, a factory worker at Fremont plant— “Workers were just cogs in a machine. You were just there to do what they told you to do.” he said, “I was there to earn money. I really didn’t care about the quality of the job and neither did GM. They just wanted to get as many cars out as they could.” Not surprisingly, GM sales reflected the unhappiness and unproductivity of their workforce; the plant had to shut down. In the meanwhile, by introducing the “Toyota Production System (TPS)”— labeled “Lean” by the Western management practice—Japanese manufacturer Toyota had earned a reputation for producing cars of very high quality, at very low costs. Lean thinking included “just-in-time” inventory and planning approach, which advocated for reducing planning and inventory overhead while delegating decision-making and ownership to the people doing the work.2 In 1984, two years after shutdown, GM reopened the Fremont plant in a new partnership with Toyota. By 1986, productivity had doubled, and absenteeism was down from 25 percent to 3 percent. This was due to the change in process and as importantly, due to the changed culture of the work place where people now assumed ownership, appreciated the transparency, shared the vision, and felt safe about speaking up. The most fascinating detail of this story is that the sweeping change was orchestrated by the GM Fremont’s original labor force, who were rehired by Toyota.
In all instances of Lean application, process changes are sustained by the changing culture and sense of ownership.
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As Charles Duhigg states, “A sense of control can fuel motivation, but for that drive to produce insights and innovations, people need to know their suggestions won’t be ignored, that their mistakes won’t be held against them. And they need to know that everyone else has their back.” By the end of the 20th century, Lean thinking had spread to many manufacturing organizations — from car manufacturing, to aerospace engineering, to even the United States Air Force (which implemented Lean concepts to achieve operating excellence throughout the entire organization).3 In all instances of Lean application, process changes are sustained by the changing culture and sense of ownership.
The Agile Framework: History, Values, Principles. History
Despite the Lean revolution in manufacturing industries, up until the end of the 20th century, software development followed a linear sequential (non-iterative) process — a so-called “waterfall” approach. This approach included specific phases of work to be done — design, document the design, program, deploy, User Acceptance Testing (UAT), and product release. Each phase was executed by a separate competency — business and system analysts created requirements documents, programmers wrote the code, quality analysts tested it, and internal user groups delegated staff to do UAT. This created conflict of interest and lack of collaboration between the groups. From a hiring perspective, developers, testers, and analysts were viewed as distinctly different professions with minimal overlapping skills. Compensation and recognition systems were specific to each individual competency and reflected “output” (e.g. individual efficiencies) rather than “outcome” (e.g. customer value creation). The value was defined based on the number of features or complexity of requirements. For example, it was a known practice to assess and compensate programmer’s performance based on the lines of code written and tester’s performance based on the number of defects they found. Instead of measuring outcome (e.g. working code: quality, productivity, predictability of delivery) or impact (e.g. customer feedback, usage statistics, other related analytics), success was defined based on pure output; which
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may or may not lead to business and customer success. These practices prevented collaboration between developers and testers who had conflicting interests based on the metrics that defined “success’ in the traditional approach. According to Organizational Behavior expert James A. March and Economic Sciences Nobel Laureate Herbert Simon,4 this type of behavior is damaging to the organization as it brings into conflict individual goals and organizational goals, thus negatively impacting the success and ultimately, survival of the organization. In the traditional method, focus on quantity of “output” (i.e., pure productivity or “busy work”) also led to multiple unnecessary loops and “gold plating” when features were added to a software product that were rarely or even never used by customers. According to The Standish Group data presented by Jim Johnson in 2002,5 45 percent of features in released software they analyzed, were never used (Figure 1). This was because customer needs were not taken into consideration.
Figure 1. 2002 Standish Group Data on the Percentage of Software Features of a Product Used by Customers.
The goal of any business is to deliver product or service for successful customer use. In the 1990s and even early 2000s, when the traditional “waterfall” framework was used for project management, it was frequently the case that, when a project was “successfully” delivered after two or three years of work, the customers would respond “this is good software but this is not what we wanted” because they had no visibility into the progress throughout delivery cycle or “this is not what we need anymore” because the market or the internal needs had changed. The waterfall methodology was frequently described using the Iron Triangle model (Figure 2). In this model, three parameters were
used to operationalize success: scope (what is it to be built), schedule (when it is going to be built), and resources (how much is it going to cost). The parameters were set up such that you could not change one parameter without impacting the others.
weight software development processes. According to one of the creators of Agile Manifesto, “The Agile movement is not antimethodology, in fact, many of us want to restore credibility to the word methodology. We want to restore a balance. We embrace modeling, but not in order to file some diagram in a dusty corporate repository. We embrace documentation, but not hundreds of pages of never-maintained and rarely-used tomes. We plan, but recognize the limits of planning in a turbulent environment.”
The Agile Manifesto states four values and twelve principles in the following way:
Figure 2. Iron Triangle model of project management (a “waterfall” approach).
A project was considered successful if all three parameters of the Iron Triangle Model were met. The problem was that a change in any of the parameters broke down the whole triangle, while the change was impossible to avoid. Therefore, the more the project progressed, the more opportunities there were to uncover new features, new costs, new complexities; and each time this happened, the whole project had to be re-balanced via a painful change management process, causing misaligned expectations, missed deadlines, damaging trust across the organization, and negatively affecting employee satisfaction. The analogy would be a person carrying out an action, say crossing the road, with no regard for the environment and only shifting course once they have been hit by a passing bicycle. It was becoming increasingly clear to software professionals that the “waterfall” mentality had to be changed—the answer came in the form of the Agile framework.
“We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value:” • Individuals and interactions over processes and tools • Working software over comprehensive documentation • Customer collaboration over contract negotiation • Responding to change over following a plan “That is, while there is value in the items on the right, we value the items on the left more.” 1. Our highest priority is to satisfy the customer, through early and continuous delivery of valuable software. 2. Welcome changing requirements, even late in development. Agile processes harness change for the customer’s competitive advantage. 3. Deliver working software frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale. 4. Business people and developers must work together daily throughout the project. 5. Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done. 6. The most efficient and effective method of conveying information to and within a development team is face-to-face conversation. (In Agile, there is a hierarchy of communications channels with conversation always being preferred to written communication, and especially one-way communication like email, which is easy to misinterpret and misaddress.7) 7. Working software is the primary measure of progress. 8. Agile processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely. 9. Continuous attention to technical excellence and good design enhances agility.
The Agile Framework
On February 11-13th, 2001, at the Lodge at Snowbird Ski Resort in the Wasatch mountains of Utah, 17 forward-thinking members of the software delivery community met to talk, ski, relax, and find common ground. What emerged was the “Manifesto for Agile Software Development,”6 which provided an alternative to documentation driven, heavy-
10. Simplicity — the art of maximizing the amount of work not done — is essential. (This principle directly correlates with Lean concept of elimination of “waste” — any effort that is not necessary to achieve desired outcome.) 11. The best architectures, requirements, and designs emerge from self-organizing teams. (An excellent reference on how this is done is in the works by Henrik Kniberg who describes organizational structure at Spotify.8) 12. At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.
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One of the shortest and seemingly simplest delivery frameworks in history, Agile is a mindset change and a complex implementation system once it is translated into delivery methods. There have been numerous flavors and methodologies within Agile such as Scrum, Extreme Programming (XP), Crystal, Feature-Driven Development (FDD), Dynamic Systems Development Method (DSDM), lean-based Kanban, and others; but in all cases, Agile is based on the main principles of Lean methodology including: • Eliminating waste, • Amplifying learning, • Deciding as late as possible (“just-in-time (JIT)” approach to avoid excess effort in a fast changing environment), • Delivering as fast as possible, • Empowering the team, • Building in quality, and • System thinking. Agile focuses decision-making authority and ability on individuals and small teams, since research shows this to be faster and more efficient than hierarchical flow of control.18 Similar to lean, agile also concentrates on the efficiency of the use of team resources, trying to ensure that everyone is productive as much of the time as possible. A helpful tool to enable this type of culture is referred to as “objectives and key results” (OKRs).9 Cascading OKRs, used for example by Google, provide a bi-directional bottom-up top-down alignment mechanism across a large enterprise. By focusing on iterative planning, Agile puts the “iron triangle” upside down by removing the scope constraint and splitting the monolith into a series of smaller scopes deliverable with a framework of adjusting all three parameters at every iteration. The only parameter that is fixed is the quality of delivery, which is still the goal for every Agile team. The Agile framework has transformed software delivery — the speed and quality of delivery is many times over “waterfall” and employee morale has increased dramatically, due to the removal of unrealistic upfront planning constraints and delegating decisionmaking to the delivery teams. The Agile framework is even more pertinent today, in the age of the Big Data, AI and
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wearable technology — planning is best done by modeling and alignment, not by setting up milestones and giving promises.
Leveraging Agile and Lean in a Modern Enterprise
Iterative delivery by cross-functional selforganizing teams and empowered individuals is a reality of today’s workplace, within software delivery and far beyond. Agile and Lean thinking is now reflected in the concept of a Lean Enterprise,10 which reflects the way an organization responds to changing market conditions, customer needs, and emerging technologies. Applying Lean and Agile principles and methodologies throughout the whole organization, rather than with just one department or team help organizations move fast, at scale. These days, successful enterprises have, in the pursuit of radically improving performance and employee morale, re-thought everything from governance and financial management, to systems architecture, to human resources and organizational culture. Although adopting Agile and Lean takes time and commitment, it is vital for harnessing the cultural and technical forces that are accelerating the rate of innovation in today’s world. Below are a few examples showing how the principles of Agile and Lean have resulted in sweeping changes across modern enterprises: • Iterative Delivery. The nature of planning has changed; long-term planning is no longer set in stone. Instead of setting milestones for a whole year, the planning is being done at portfolio level with the milestones being set iteratively via Objectives and Key Results (OKR) which reflect organizational goals in SMART (specific, measurable, attainable, relevant, and timebound) format. Goal-driven planning also changes how budget is allocated. Instead of previous-year based budget allocation, finance departments allocate budget incrementally and make ongoing decisions based on product portfolio progress and customer feedback. • Embracing Change. Change and improvement are continuous. Take for example, a financial services company that
provided data services to its partners. Each received request was processed by multiple departments: customer services, sales, pricing, legal, technology, IT Operations, then back to sales, customer services with any inquiry by the customer resulting in another interaction with legal and pricing. When the involved subject matter experts from all these teams gathered in one room and visualized a “value stream map” providing end-to-end flow of information delivered to a customer, they were able to optimize the process and reduce delivery time from 3-4 weeks to 7 days. As the second step, the organization created two separate self-organizing cross-functional teams (each comprising of one subject matter expert from each division), and the end-to-end process was reduced to 3-4 days within 3 months. • Ongoing Innovation. In modern days of disruption — when paper books or landline phones are becoming a rarity and when the GPS industry which disrupted paper maps has already been disrupted by smartphone — innovation is a matter of survival. Lean Startup is a lean-agile approach to validating a hypothesis for new products and services, via constant market research and a build-measure-learn loop, while they are being built.11 • Team-Oriented Thinking. Organizations embrace change by giving decision power to teams and individuals who perform the actual work. This allows them to respond to customer and market needs fast and establishes direct contact between customers and those who build products or services for them. Once an improvement is identified, the ownership of implementation goes to the person who suggested it. Team structure needs to be intentional to reduce dependencies and enable system thinking. As an example, one of the software teams I was coaching continuously reported dependencies on a database team and the design team (both were so-called “shared services” within an engineering organization). Once we made a decision to eliminate this model and allocated one database administrator and one user experience designer to each of application teams,
i.e., make the teams cross-functional, we were able to increase productivity by 50 percent. In addition, employee satisfaction tripled within one year. • Customer-Value Driven Approach. In their book Sense and Respond,12 Jeff Gothelf and Josh Seiden use multiple business examples to show organizations with distinctively new operating principles: shifting from managing outputs to what the authors call “outcome-focused management;” forming self-guided teams that can read and react to a fast-changing environment; creating a learning-all-the-time culture that can understand and respond to new customer behaviors and the data they generate by constantly innovating their products and services; and finally, developing the new universal skills of customer listening, assessment, and response, in everyone at the company. To summarize the change, we can review how Geoffrey Moore’s holistic view on entrepreneurial marketing and survival for a modern enterprise in the era of high disruption and low market entry is affected by Agile and Lean13 (Figure 3). •
Organizations embrace change by giving decision power to teams and individuals who perform the actual work.
Figure 3. Lean Enterprise — Holistic View.
According to Geoffrey Moore, in a modern enterprise, core is where companies should invest their time and resources. Core is what allows a business to make more money and/or more margin, and make people more attracted to a business than to its competitors. For a technology company, this is their product.
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In general, we need to think of HR as the backbone of the Lean and Agile ecosystem.
For a big data company, it is data and related analytics. Core gives a business bargaining power: it is what customers want and cannot get from anyone else. The Agile framework allows a company to move fast and execute on core business, collaboratively, quickly, and in partnership with customers. To increase this partnership, companies benefit for Lean Startup techniques in validating new ideas with their customers. Everything else is context. Context helps run the business — these are HR, Marketing, Finance, and other functions that support the value chain delivery. The more successful a company becomes and the more it grows its competitive advantage, the more context it generates and the more important it becomes to handle this context efficiently and effectively. This is where the enterprise applies Lean principles to reduce waste, increase efficiency, and ensure high quality. Any specific functions, e.g. IT infrastructure hosting, training for specific skills (technical or other) etc. can be outsourced to the companies that specialize in this type of training and services. In sum, agile, lean, and lean startup principles can be applied across the enterprise depending on the nature of each business function, to achieve rapid innovation, growth, and customer-centricity.
What does the new thinking change in the HR Profession?
Everything covered so far applies to people and teams within the enterprise and also applies to almost every function of the HR profession, from recruiting to job satisfaction. Therefore, HR needs to develop a model for developing and sustaining the Lean and Agile culture in the organization. Some questions HR professionals need to answer are: •A gile and Lean professionals: who are they? The recruiting function needs to look for people with Lean-Agile mindset — the ones who are customer-oriented and team-driven, the ones who have had a chance to work in a similar environment. Too often, the hiring process at any level becomes heavily based on referrals and behavioral interviews to reveal
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servant/leader nature of the individual, in addition to job-specific competencies. Within the agile and lean framework, a good topic for a behavioral interview is job dynamics and team-level collaboration. For example, tell about a situation where you disagreed with your team’s decision and whether you ended up following the team or confronting the decision. In his book Six Secrets of Powerful Teams: A practical guide to the magic of motivating and influencing teams,”14 Michael Nir describes fundamental principles leading to the creation of successful self-organizing collaborative teams. •H ow is the HR function changing with Agile and Lean? Performance review as a concept does not apply anymore. First, the feedback process is continuous. For example, Scrum, one of Agile frameworks, builds feedback into its cadence. At regular intervals of time, the team meets and team members provide direct feedback to each other, resulting in 2-3 action items they agree to implement within the next iteration. This process is ongoing. Meanwhile the team performance is intentional: driven by Objectives and Key Results, teams self-assess their performance against pre-defined objectives (quality, productivity, predictability, customer satisfaction, employee happiness); also cascading goals are used and the results are transparent across the organization. •W hat is the new take on compensation, recognitions, and awards? There are two fundamental changes in the Lean-Agile approach to employee recognition: first, recognition comes from peers and customers rather than managers. Second, awards are no-longer individual and depend on the team’s success. In his book Managing for Happiness, Jurgen Appelo11 describes multiple ways of recognition in an Agile environment. An interesting example that he provides is a peer-to-peer bonus system which he calls “merit money” where team members reward each other with credits (later translated into bonus money) for their collaboration and support. He provides the following example: “Last month on my team, Jennifer
gave 15 credits to Lisette ‘for being the backbone of the organization.’ Lisette gave 25 points to Sergey ‘for all the feedback and support.’ Sergey gave 10 credits to Chad for his ‘terrific illustrations.’ And Chad gave 20 credits to Hannu for his ‘friendliness and clarity of communication.’ And on and on it went...” There is a prerequisite for such a system — a mature team culture and the expectation that each award is well explained and acknowledged. Otherwise, there is a potential drawback that it would promote wrong behaviors where team members care about being “liked” more than achieving outcomes or “quid pro quo” behavior where team members reciprocate each other’s awards irrespective of the performance. In addition, in the learning culture there is no shame for failure — mistakes are seen as a learning opportunity, hence “fail fast, succeed faster” approach to failure is taken. Some companies even establish “failure walls” where employees share their failures to allow others to learn from their mistakes. •D ifferent take on titles and promotions Lean-Agile culture requires a different thinking about organization hierarchy and the role of management. Managers are no longer assigning work or evaluating performance, rather, their role is to support employee development and growth, and provide tools for issue-resolution and team-based delivery. In most instances, mid-level managers are “playing coaches” on their teams. This philosophy goes all the way to C-level management. For example, Bob Carrigan, CEO of Dun & Bradstreet, refers to this principle as an “inverted pyramid”19 where his role is to support and enable from the bottom of the inverted pyramid where employees are the ones on top of the pyramid. While the managers no longer assign work to individual team members, this does not mean that there is chaos or anarchy with everyone doing what they like. With clear definition of company’s objectives and team’s goals, there is a clear understanding of outcomes, alignment of deliverables, and transparency about the progress. •H R Ecosystem in an Agile and Lean enterprise In general, we need to think of HR as the backbone of the Lean and Agile ecosystem—
empowering employees and teams and providing all the underlying functions, from employee hiring development to team enablement and recognition, is the key to a lean enterprise. This is one of the reasons why the success of LeanAgile transformation for a modern enterprise is measured by two sets of parameters: the first set is in relation to business objectives and product delivery metrics, such as time to market, quality, customer satisfaction; the second set is employee driven and is represented as “employee happiness”, collaboration within the teams, and employee retention rate. This is also why work-life balance and sustainable pace for teams and individuals has become so important. We do not talk about “work-life balance” where there is a 9AM-5PM “work day” but rather a “work-life fusion” which allows a person to dedicate to family without sacrificing commitments. This can be done with the aid of iterative planning and team collaboration throughout the workweek and with the aid of modern technology and communication modes. For example, when I am writing this article in the evening after my work day, is it “work” or “life”? Another key item is employee “self-selection” into teams. There are multiple examples of how thoughtful and well-executed self-selection mechanisms take teams to the next level in terms of their productivity and work happiness. In her example of how HBC Universal ran their self-selection campaign, Dana Pylayev outlines a thoughtful step-by-step orchestrated process that provided a platform for team self-selection at an organizational level.15
Conclusion Agile and Lean dictate new ways of thinking about our professional ecosystem: collaborative, outcome-oriented, customer value-driven. In his book “The Startup Way”16, the founder of Lean Startup Erik Ries, provides an example of how Sheryl Sandberg responded to an employee’s question about performance management. At one of Facebook’s company-wide meetings, an employee complained about the “unfairness” of having their performance evaluated based on the success of the projects they had worked on, rather than just their individual contributions to their projects. Sandberg acknowledged these concerns and asked the employees to imagine a favorite company of theirs that had been disrupted, such as Kodak or RIM. Then,
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she suggested to think of all the people who got positive reviews, got promoted, got paid bonuses for their contribution—all while the company was going down in ignoble defeat. Last, she asked whether they really wanted to be one of those managers? It is time we update our frameworks of thinking. In his book Joy, Inc., Richard Sheridan,17 CEO, Chief Storyteller and co-founder of Menlo Innovations states: “Every organization
Endnotes 1
2
harles Duhigg. Smarter Faster Better: The Transformative Power of C Real Productivity (Random House Publishing Group, 2016). J ames P. Womack, Daniel T. Jones, Daniel Roos, The Machine That Changed the World: The Story of Lean Production– Toyota’s Secret Weapon in the Global Car Wars That Is Now Revolutionizing World Industry (Rawson Associates, 1990).
needs to make room for the time or effort a person needs for his or her personal life, and the dividends of this effort are not measured in business terms.” The Lean-Agile mindset calls for a new revolutionary approach to hiring, recognition, and career growth; and in this brave new world, HR professionals become key players in creating, maintaining, and sharing that forward-thinking ecosystem.
10
Jez Humble, Joanne Molesky, Barry O’Reilly. Lean Enterprise: How High Performance Organizations Innovate at Scale (O’Reilly Media, Inc, 2014).
11
Jurgen Appelo. Managing for Happiness: Games, Tools, and Practices to Motivate Any Team (2016).
12
Jeff Gothelf, Josh Seiden. Sense and Respond: How Successful Organizations Listen to Customers and Create New Products. (2017).
13
Geoffrey Moore. Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers (Harper Collins, 1991).
14
Michael Nir. Six Secrets of Powerful Teams: A practical guide to the magic of motivating and influencing teams (2013).
15
Dana Pylayev. Let’s Run an Experiment! Self-Selection at HBC Digital (Gilt.com, 2017) (http://tech.gilt.com/agile/2017/05/31/self-selectionhbc )
3
ichael Joyce, Bettina Schechter. The Lean Enterprise – A Management M Philosophy at Lockheed Martin. (Lockheed Martin, 2004).
4
James G. March and Herbert A Simon. Organizations, (Wiley, 1958).
5
Jim Johnson, chairman of The Standish Group, “ROI, It’s Your Job,” (Keynote: Third International Conference on Extreme Programming, Alghero, Italy, May, 26-29, 2002).
4
The Agile manifesto http://agilemanifesto.org
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7
Scott Ambler, Communication on Agile Software Teams. (http://www. agilemodeling.com/essays/communication.htm )
Eric Ries, The Startup Way: How Modern Companies Use Entrepreneurial Management to Transform Culture and Drive Long-Term Growth (2017).
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enrik Kniberg Scaling Agile @ Spotify with Tribes, Squads, Chapters & H Guilds (a blog post 2012). (https://labs.spotify.com/2014/03/27/spotifyengineering-culture-part-1/ )
Richard Sheridan, Joy, Inc: How We Built a Workplace People Love (Penguin Group, 2013).
18
Burke, W. Leadership as empowering others. In S. Srivastra (Ed.), Executive power (pp. 51-77), San Francisco: Jossey-Bass, 1986.
19
Inverted Pyramid, https://www.glassdoor.com/Overview/Working-atDun-and-Bradstreet-EI_IE213.11,29.htm
9
Ben Lamorte and Paul R. Niven. Objectives and Key Results: Driving Focus, Alignment, and Engagement with OKRs (Wiley, 2016).
About the Authors
Mariya Breyter brings 20 years of leadership experience to the Agile and Lean community. Her passion for creating high performance teams and delivering superior products to clients through efficient, lean processes had produced success after success in companies ranging from Big 4 consulting and Fortune 100 insurance and financial services firms to mid-sized educational and media businesses. She has a Ph.D. in Computational Linguistics followed by a Post-Doctorate at Stanford University. She has built her career optimizing and improving software delivery and instilling Agile and Lean values at multitudes of companies while keeping the primary focus on the people within those processes. The list of her certifications includes CSP, SPC, CSM, PMP, PMI-ACP, ITIL 3.0, Agile Facilitation, and Agile Coaching from ACI. She is a frequent presenter at agile and lean conferences, from Agile Games in Boston to Lean IT Summit in Paris and Agile Development Conference in Orlando, FL, and a popular blogger. Her free coaching website, www.agileleantransformation.com, offers tips and advice to individuals who want their professional life to be one of growth and meaning, and to the organizations interested in delighting customers and empowering their employees. She is passionate about Agile and Lean, and uses personal Kanban at home with her family. Darshana Z. Narayanan has over 10 years of combined academic and industry experience in the study of human behavior: at multiple levels (individual and organization) and time scales (ontogeny and evolutionary history). She is currently at Composites Collective, leveraging her extensive understanding of complex social behaviors, and AI technology, to build tools and processes for greater and more effective collaboration and participation. She works with businesses, non-profits, universities, governments, and communities. Her previous job was Head of Research at a machine learning, organizational behavior, gaming startup. She is a passionate explorer. She and her collaborator, CS, travel the globe to see interesting experiments in organization reform. Their last trip was to Taiwan, to study Taiwan’s open government movement. She has a Ph.D. in Psychology and Neuroscience from Princeton University and M.S. in Neuroscience from Brandeis University. She can be reached at darshana@alumni.princeton.edu.
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October-December 2017 Buyers Guide The October-December 2017 Buyer’s Guide will serve as a valuable reference tool. For your convenience, the guide has two sections: a Categorical Listing and an Alphabetical listing. In the Categorical Listing, companies are listed under the product and service categories of their choice. For information on a specific company and its products and/or service, please refer to the Alphabetical Company Listing. While a listing in this guide does not constitute an endorsement by IHRIM, it does indicate that these companies are interested in serving the needs of HRIS professionals. We hope this Buyer’s Guide will assist you in your 2018 purchasing decisions.
Product Categories
Core HRMS
StarGarden Corporation
Compensation Consulting
Enterprise Information Resources Inc.
Paid Advertising
Compensation Management
Deferred Compensation DECUSOFT Executive Compensation DECUSOFT Incentive Compensation DECUSOFT Enterprise Information Resources Inc.
Performance Management
Enterprise Information Resources Inc.
Alphabetical Company Listing* *Systems and applications referred to in this section are trademarked, registered, or in progress. These names should not be used generically.
DECUSOFT
70 Hilltop Rd. Suite 1003 Ramsey, NJ 07446 Leslie O’Connell 201-645-5652 201-785-0774 Leslie.OConnell@Decusoft.com www.decusoft.com You have an HCM software suite, but you are managing compensation outside the system. Now what? You need COMPOSE, a specialized compensation management software solution that handles any variable compensation complexity, reduces your total costs of compensation administration and integrates with existing HR solutions. Not so suite but oh so right. See our ad on the Inside Front Cover.
Enterprise Information Resources Inc.
StarGarden Corporation
271 Waverley Oaks Rd. Suite 207 Waltham, MA 02452 Gin O’Leary 855.589.9451 www.eir-inc.com info@eir-inc.com Enterprise Information Resources Inc. (EIR) EIR is a certified SAP SuccessFactors build and services partner. We are a team of compensation and talent management solutions experts specializing in Perform & Reward bundle implementations and configuration optimization. Our transformational services help clients maximize the value of their SAP SuccessFactors investment. See our ad on the Inside Back Cover.
300-3665 Kingsway Vancouver, BC V5R5W2 Marnie Larson 800-809-2880 info@stargarden.com www.stargarden.com Let StarGarden’s 30 years of experience help manage your most important resource. Get the right resource on task at the right time with StarGarden’ss advanced HCM, Payroll, and Workflow functionality. Visit us at www.stargarden. com to learn more.
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Jason Ezratty and Michael Benyamin, Brightfield Strategies
HR Data Science: Delivery Model Alternatives The amount and quality of HR data generated by HR systems has grown and alongside, so has interest in HR Data Science—often referred to as people analytics. As HR systems drive efficiencies and controls through automation, they also leave behind tomes of data that memorialize each action and its conclusion. Over the last five years, HR has become increasingly sophisticated in how to leverage the resulting data beyond the basics of who, when, how many and how much. Now the state of the art allows for HR systems to go beyond just what programming logic can be committed to code, it can glean insights learned from the data such as predicting candidate fit and employee retention risk. However, data science in HR is still relatively immature compared to other functions such as Marketing (e.g., ad targeting). There are several challenges confronting HR along the way, not the least of which is a lack of clarity around what “good” looks like. Meanwhile, the marketplace is evolving rapidly—faster than many HR organizations can absorb in order to understand how to incorporate new ways of delivering people analytics services and products to their customers. There are several articles (e.g., “Student’s favorite analytics articles” by Amit Mohindra1) written about how to improve an internal people analytics capability. In this article, we contend that to deliver more value, some co-sourcing of people analytics will be required as business demands mature over time. We will explore the most common challenges businesses face in delivering credible and repeatable people analytics and review alternative models for consideration.
Challenges With so much hype about the value people
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analytics can deliver, why has the function so rarely lived up to its potential? There are a dozen different obstacles any organization may have to contend with, which are well documented in numerous articles and blogs. In our opinion, the top five common challenges are described below, and each deserve their own article. Skills: “I just read an article about analytics, why aren’t we doing those kinds of things here?” Delivering people analytics requires a diverse set of capabilities ranging from business acumen, to data management, to applying the best scientific method to data visualization and storytelling. Of course, that doesn’t even include programming skills to train and deploy machine learning algorithms. These capabilities are rarely found in one person and an organization may be missing the sufficient level of capability in one or more of these areas. Capacity: “We can only take on a few projects and they may take months to complete.” There are several manual steps that can occur when performing analytics even when using tools. For example, getting the right data, which often includes data not normally available through existing integrations, loading data into an analytics tool, performing the actual scientific calculations, evaluating results, refining the calculations and/ or data, determining what’s most important, and displaying information for an executive audience to absorb. The above is the most common approach of most data analytics teams (which can be just one person in some organizations) to perform the analysis just once. Automation: “Refreshing our analysis will take weeks.” To deliver true business value, data analysis must be repeated to track progress for whatever the analysis was trying to improve and
identify if the analysis changes in any way based on updated data. Some analytics teams have people dedicated to just refreshing data for existing analytics. However, some organizations have invested in talent or tools for creating machine learning, which allows the analysis to repeat and improve in an automated way. Data Quality: “I don’t trust the conclusions because I ‘know’ the data has certain problems.” All data has issues. What’s the alternative… simply ignore data? Teams spend a lot of time creating data quality checks, cleansing data and conforming disparate data to a common view. However, rarely do analytics teams get involved in how to improve execution of business processes so that data continuingly improves. We sometimes get stuck in the infinite loop of finding new issues with data, cleaning data, and then distrusting/discounting the data anyway. Client Receptivity: “Thank you for this ‘report,’ but experience tells me otherwise.” Let’s face it…not every leader is comfortable with understanding data to make decisions, especially if they have been successful in their career without it. Every people analytics team runs into one or more of these leaders. Not every analytics team is equipped to navigate these types of discussions and often these types of objections can be deflating for the team. There are ways of uncovering leadership views in advance, bringing people along the journey and learning more about objections to have a productive dialogue and not get trapped with significant work simply sitting on a shelf. By working with leaders along the way, you may also learn that they have a different question that needs solving rather than the one being worked.
Evolving Analytics Demand & Market Landscape Beyond conventional head count and turnover reporting, not every organization’s demands for people analytics are the same. For example, a company going through significant M&A activity is going to be focused on analyzing how to combine strengths, retain key people, and optimize redundant work. But an organization in a stable environment may be more interested in broad performance management, leadership pipeline, and employee retention. In addition to understanding the business
focus, identifying analytics needs is further complicated by leaders not asking the right questions or the main question on their minds. A leader may be asking a direct question to answer a different question they didn’t articulate/disclose. For example, being asked about the average cost of database administrators (DBAs) in Manhattan may not be about benchmarking if we are paying people correctly. Instead, the objective may be about saving money on DBAs and there are other questions on the leader’s mind like how do I spend less on DBAs, what factors drive price, and can DBA work be done differently? Lastly, there is the need to deliver HR services efficiently and effectively. Like any other business function, HR is contemplating what work can be automated and where it can benefit from more intelligent decision support. Apps and chatbots that constantly and automatically learn and improve themselves are evolving from concept to reality. Chatbots now can apply natural language processing (NLP) to understand the context of statements and learn from them to have a real dialogue with the human they are interacting with. In the HR space, the most popular area for chatbots is in talent acquisition – either for improving the hiring manager or candidate experience. For hiring managers, products like Beeline’s Virtual Assistant allow hiring managers to describe the role they are trying to fill, and the Virtual Assistant performs all the transactional work associated with the request. For candidates, there are several virtual assistants to help with candidate engagement such as, gathering initial candidate data, scheduling interviews, and maintaining an ongoing connection with candidates – all of which recruiters don’t have time for. Specialized apps such as, Brightfield’s Talent Data Exchange (“TDX”), offers AI-based decision support for niche use cases, i.e., labor cost and relationship to quality for contingent labor. The people analytics marketplace is rapidly changing to attempt to cash-in on opportunities. Seemingly every software provider, outsourcer/ service provider, and consulting firm has some type of offering related to people analytics. Part of the confusion is that these companies use the same terminology of “analytics” but they mean very different things. There is a lot of noise in the www.ihrim.org • Workforce Solutions Review • October-December 2017
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by buying siloed solutions. To reach Level 4, most organizations will need to have a mature service delivery model that uses co-sourcing to leverage external capability and tools. Stela Luposhor talks about broadening our thinking beyond traditional data and impact on analytics technology in her article “3 ways to bring out the best in people with workforce analytics”.2
Spectrum of Delivery Alternatives
marketplace for analytics and plenty of opportunity to chase “bright and shiny objects.” Not only is it hard to keep up with the changing landscape and what’s possible to buy these days, there is a disconnect with leadership in perceived investment in people analytics. Companies may own multiple HR systems, data warehouses, reporting platforms, and analytics software. Yet, many teams can’t execute analytics effectively and efficiently, which causes leadership to be wary of additional investment in a capability that doesn’t always meet expectations. People analytics must be ready to answer questions about “how is ‘this’ different than what we already have” and “how do we know that ‘it’ will create the value we need.” Part of the disconnect may be that the business demand is at a different level of maturity compared to the solution being proposed as shown in the Demand and Supply Maturity exhibit above. The Demand and Supply Maturity model is a good way to help level-set leaders about what existing investments are meant for and the types of investments to be made to respond to more complex needs such as, total workforce planning and routine AI-based decision support. What “good” looks like will need to evolve as business needs and readiness matures. Even the simplest demands (i.e., Level 1) require investment in technology and change management to ensure organizations are using the same definitions and efficiently deliver reporting. Without a consolidated strategy for analytics, organizations with needs at Level 3 can easily overspend
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Most people analytics teams start small— often just one to three people. In doing so, these teams may excel in some of the required capabilities for people analytics but rarely all. There are several articles and blog posts written about people analytics capabilities such as, “What Constitutes Best Practice Analytics Teams” by David Green.3 David’s view on people analytics competencies, built on Morten Kemp Anderson’s original model,4 explains what happens when certain capabilities are missing. Our view is summarized into top three capabilities: (1) understand the problem, (2) apply science to make data-based decisions, and (3) change management to help the organization understand the data and incorporate it into routine decision-making. Change management is probably the toughest for people analytics teams to get right because they may not have the ability to present the story/findings in an “exec-ready” way or lack the relevant experience to know the types of practical solutions that may work to impact findings. For example, if a people analytics team found that “distance between home and work” is a top predictor for turnover of retail workers, what can/should the organization do about this finding? The people analytics team may not know the answers to these questions, but should bring in the right subject-matter experts from talent acquisition, legal, etc., to include them in the process of determining which findings matter and building practical recommendations. Navigating the organization to get the right people involved in previewing findings, recommending next steps based on those findings, and understanding the full context of the problem are just as critical as coming up with the right answer.
There are alternatives to getting to the right mix of talent to have all the capabilities needed. Starting with a small internal team is often how organizations begin their journey—often sharing descriptive analytics to create visibility to what areas need attention. A people analytics team can evolve further by growing organically, creating an extended team and/or incorporating external resources.
To create an extended team, HR functions will need to get past their concern about having non-HR people see confidential HR data. Dealing with HR data is about confidentiality and ethics as described in Ian O’Keefe’s article “The Biggest Risk - And Opportunity - For Talent Analytics.”5 Trusted relationships with named individuals
outside of HR can be created and offer immense value for the people analytics team by adding extra capacity and expertise. The extended team member can benefit as well from increased employee engagement by doing new interesting work that may have significant business impact. Large internal teams typically have specialized resources that are expert in one or two of top analytics capabilities described in the exhibit on the left. In addition to executing on analytics projects, these teams often create routine deliverables such as, helping the organization get comfortable with making data-based decisions with “Did You Know” newsletters and manager guides. Most organizations have some sort of cosourcing in place with the most common being an outsourced engagement survey that delivers drivers of engagement results. This use case has been around for many years. As described above with the changing marketplace, outsourcing other use cases (e.g., matching internal and external talent to work, incorporating contingent workers into
workforce planning, simplifying manager experience with bots) are becoming more common and simpler to implement.
Conclusion Every service delivery model has the potential to be successful in some way, but eventually client www.ihrim.org • Workforce Solutions Review • October-December 2017
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Endnotes 1
“Student’s favorite analytics articles” by Amit Mohindra (https://tinyurl. com/ycqmpczk)
2
“ 3 ways to bring out the best in people with workforce analytics” by Stela Luposhor (https://tinyurl. com/ycan2fub)
3
“ What Constitutes Best Practice Analytics Teams“ by David Green (https:// tinyurl.com/yc5eawyt)
4
“ Six must-have competencies in a world-class analytics team” by Morten Kemp Anderson (https:// tinyurl.com/yavqkew2)
5
“ The Biggest Risk - And Opportunity - For Talent Analytics” by Ian O’Keefe (https://tinyurl.com/ y8h7lcw6)
6
“ 10 Golden Rules of HR Analytics” by Patrick Coolen’s (https://tinyurl. com/yd23zqav)
demand will exceed the people analytics team’s internal capabilities and/or capacity. You certainly don’t have to spend time building the function one person at a time, which can slow down your ability to deliver additional value quickly. Here are steps to take to figure out how to approach the next evolution in service delivery: 1. Prioritize business needs. If clients are approaching you with questions, ask: what has the most business value and are they willing to change? As mentioned earlier, even if clients are approaching you with questions, keep probing to understand the underlying reasons for the demands to ensure you are solving for the right problem. If clients are not approaching you with questions, ask if they are not ready or simply don’t know. Patrick Coolen’s article “10 Golden Rules of HR Analytics”6 is an excellent resource of things to explore and test with clients. 2. Determine what’s outsourceable. Part of being a business leader is making rational decisions about what work is “mission critical.” Whatever isn’t, can be done by others (i.e. extended team members, outsourced) and managed by you. This creates focus for the people analytics function and avoids chasing hobbies that are time consuming and/or expensive.
3. Take stock. Understand your company’s readiness for data-based decision making, ask: what is your people analytics function strength; what delivery challenges are most important to solve, and are there existing leadership biases for service delivery alternatives? 4. Do some homework. What will it take to help your clients answer their questions, not just one time but include ongoing machine learning or refresh the analysis? What capabilities exist internally and how easily can you tap into that capacity? What providers offer faster approaches and expertise as an alternative to performing the data science work from scratch? 5. Create the case for change. What is the collective business value for being able to support client needs? At current capacity and expertise, when can you deliver? What alternatives are there for different business needs (build, buy, rent, outsource capability) and how does that change speed and likelihood for execution? Understanding your organization’s maturity and readiness for analytics, how to respond to current and future demands, and having a business leader’s mindset of the analytics function are critical for delivering anticipated value in people analytics.
About the Authors
As co-founder and president of Brightfield Strategies, Jason Ezratty drives the strategy and R&D behind Brightfield’s service and data offerings. With a successful track record designing contingent workforce programs and models rooted in empirical data analysis, he has helped the contingent workforce (CW) industry define its lexicon and is widely regarded as one of the key forward thinkers in CW evolvement and management. Having created multiple software tools for human capital sourcing, he is well versed in the language behind the technology; bringing a keen eye, unique understanding, and unequaled perspective to current state assessments. Ezratty also leads Staffing Industry Analysts’ CCWP Module 7 - Analyzing and Acting Upon Quality & Efficiency Data, and Module 9 – Contingent Workforce Maturity Model. He was consecutively named in 2014 and 2016 to the Staffing 100 by Staffing Industry Analysts, a biennial listing of the staffing industry’s 100 most influential people. In addition to his work in predictive analytics with workforce data, he holds a U.S. Patent for the invention of a real-time biomonitoring device employing bivalve mollusks and neural network-based pattern recognition. He can often be heard saying “your data is trying to tell you something.” As the global head of Brightfield Strategies’ consulting and new business efforts, Michael Benyamin leads a client-facing team that ensures the solutions and analytics offered stay relevant and forward-thinking in the rapidly changing environment of workforce management and contingent labor. Prior to joining Brightfield, he was at Bank of America where as the HR Executive leading HR Reporting and the Workday Center of Excellence he played a significant role in implementing Workday’s largest client at the time. He was also the Data Steward responsible for HR data quality and controls. Prior to Bank of America, he spent 15 years at HR consultancy, Towers Watson. While there he advised global corporations on a broad range of talent and HR service delivery related topics and led various firm offerings such as Human Capital Benchmarking. He has an MBA in Human Resources and Information Systems from the University of Albany.
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The Back Story
Katherine Jones, Ph.D., Mercer
Build for an Unknown Future: Preparing for Digital Jobs that Don’t Yet Exist Technology gets more sophisticated every day – what are the implications for the workforce of tomorrow? How will smart technologies change the way work gets done? Virtual or augmented reality, machine thinking and learning, voice-response tools, drones, robotics and more change, the nature of jobs and the ways in which they might be accomplished. What does HR need to do to keep pace for the future?
Who moved my…….typewriter?
Sometime we forget how fast technology has changed, just over the recent past. Remember the PC—with a fairly large box that had to be attached to the keyboard and the monitor? Or floppy discs with which you had to load your own software? When was the last time you opened a Yellow Pages book or saw a public phone booth? Often these changes creep up on us in little ways: the tools we use became more powerful, smaller and more connected; now we take them for granted. But radical change rarely happens overnight. Consider the following: • When did the health-care industry start talking about digitizing patient information and moving to electronic records? It was more than 40 years ago in 1972, when the first electronic medical record system was developed by the Regenstrief Institute. • What about the ubiquitous cell phone? In this century? Nope. Motorola was the first company to produce a handheld mobile phone, where a researcher made the first call on April 3, 1973. • Drones? Un-peopled flight, especially in warfare, has been around for over a century. While Austria tried, apparently unsuccessfully, to use balloons to drop bombs on Venice in 1849, the term “drone” was first coined in 1936, as the head of the Navy’s research group used it to describe radio-controlled aerial targets. • Let’s consider robots: the first known robot was created around 400 BC and was a mechanical
bird, apparently a steam-powered pigeon. One of the first recorded designs of a humanoid robot was made by Leonardo da Vinci around 1495. Leonardo’s notebooks, rediscovered in the 1950s, contain detailed drawings of a mechanical knight in armor that was able to sit up, wave its arms and move its head and jaw. The first digital and programmable robot was invented by George Devol in 1954 and was named the Unimate. It was sold to General Motors in 1961 where it was used to lift pieces of hot metal from die casting machines, becoming the first industrial robot to work on an assembly line. Unimate may have replaced someone in the removal of hot metal from those machines, or perhaps was able to complete a task that wasn’t safely doable by a person. And the mechanical knight? Perhaps it was a decoy that kept a real knight alive. Technologies that can replace people at work aren’t new—and once the initial disintermediation is addressed, employees can and do learn new and more relevant skills (Queen Victoria once banned knitting machines since they affected the livelihood of young women who knitted woolies by hand at home). Employers’ concern today is how to prepare the existing workforce for change, and plan for understanding and then locating the skillsets needed for an increasingly digital future. Clearly, predictable, repetitive work (often requiring few skills) is most vulnerable to replacement by computerization. Beyond physically manual jobs, the most obvious candidate for technology infusions is redundancy in computerized “paperwork:” If an employee, admin, or HR professional has to enter the same information or response more than once, it is a place for automation. While jobs that include reiterative tasks are prime candidates for replacement, other occupations, generally those that rely on judgement rather than rote behaviors are less at risk (see Figure 1).
No one likes repetitive, mind-numbing jobs; deploy a robot or a chatbot.
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Figure 1.
From the use of robotics on assembly lines and warehouse floors, increasingly sophisticated programming and machine learning has eroded the need for humans in both picking and packing, leaving people to monitor sets of machines. Current pickers and packers, for example, can be upskilled to monitoring the “behavior” of several robotic machines, as a check for accuracy and About the Author quality control. The likely outcome after the initial investment is higher productivity with less variDr. Katherine Jones is a ance in quality and lower error rates. With time partner and director of Reand improved accuracy and reliability, the totally search at Mercer in Talent Information Solutions. With automated warehouse may require very little huboth academic and technolman supervision. In this scenario, the new jobs ogy industry experience, created will require skills in programming robotic she has been a high-tech market analyst for 18 years. activity, maintaining a fleet of such machines and Her doctoral degree is from recognizing machine obsolescence. Cornell University. She can be reached at
Katherine.Jones@mercer.com or @katherine_jones.
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While companies such as IBM and Yahoo recently insisted that people work in their offices, much of the corporate world is supporting “work where you are” policies, easing time and cost of commuting, often increasing productive work time, and facilitating team work across sites through computerization. The technologies for virtual face-to-face are not new, but becoming more widespread as shared-work communication applications are readily accessible at lower price-points. Will the giant industrial parks of office workers become tomorrow‘s dinosaurs? The cost of physical infrastructure is great and upkeep and maintenance extensive: will tomorrow’s jobs necessitate “going to work” or simply “being at work?” Employees responding to Mercer’s 2017 Global Talent Trends research said the number one thing they most needed to improve their life at work was “the tools to do my job.” Right now, a worker commonly sees a five to 10 year technology drop every time he or she enters the office (see Figure 2).
Digitization and the Future of Work
Automating what people do now is just table stakes when considering what the future of work will look like – tomorrow’s “work” will be much different than it is today. Technology has reached a leap-frog point, pivoting on cloud capabilities, increased computing power and “smarts,” machine learning from data rather than programming, support for natural language, among others. Consider Uber or Lyft, common examples of travel disintermediation: without a high-speed internet, integrated account and credit card handling, and exceptional locational and mapping capabilities, the success of these businesses would be very doubtful. This technology also impacted how people work. Rather than traditional shifts, Uber drivers can drive when they want, perhaps augmenting another job, and can go home when they are tired—they work for themselves.
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Figure 2. Technical Gap between Work and Life. Source: Oliver Wyman, 2017.
Perhaps the first step in digitization transformation is to get today’s workers the technical tools they need to more easily accomplish the tasks of today. From the HR perspective, however, automating the workers is not the same as creating a truly digitized business. While 97 percent of CSuite executives surveyed in Mercer’s 2017 Global Talent Trends research recognized the need to use technology to shape their employees’ experience at work, digital transformation surpasses how work is conducted and with what tools. It is a concept that covers people and technology—but also requires a change in policies: a relook at not just how work is done but what work needs to be done. In this, jobs as we know them today will change. It’s our job to start getting ready.
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