RPA In Content by Knowledge Capital Partners

RPA In Context – How Are We Doing? Knowledge Capital Partners Executive Briefing www.knowledgecapitalpartners.com

RPA In Context – How Are We Doing? By Dr. John Hindle Dr. Leslie Willcocks Dr. Mary Lacity

Knowledge Capital Partners Executive Briefing November 2017 Robotic Process Automation is hot. Why? And why now? We discover that you need to look at the past, as much as the present, for the real answers.

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Contents

Introduction �� 3 RPA Market Developments �� 4 What’s Different About RPA: The Importance of Context �� 6 Conclusion �� 9

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Introduction The quick answer to ‘Why RPA now?’ is that it has been delivering multiple business benefits and, beyond the hype, people are picking up on this. The most recent surveys are finding RPA achieving unprecedented levels of value and performance as reported by users. At the high end of the range, Gartner reports 96% of customers getting value from their RPA deployments, adding it had “never seen satisfaction that high.” HfS Research reports more modest – but still impressive – levels of satisfaction and value: 58% of RPA users achieving business value, and 57% achieving targeted cost savings. Two of our authors have studied detailed RPA use cases, and have found many examples of what they call RPA ‘triple wins’ for shareholder, customer and employees alike.i Our own KCP research in mid-2017 covering 112 RPA deployments reveals similar results: 25-50% in-year ROI from active deployments, and a very high mean level of satisfaction with both the tool and the business outcomes – averaging 6 on a 7-point Likert scale. Our findings are particularly interesting because they go across multiple dimensions: оо Scalability оо Adaptability оо Security оо Service Quality оо Employee Satisfaction оо Ease of Learning оо Deployment Speed оо ROI, Compliance, Business Agility, and Business Outcomes оо Customer Experience What’s behind these glowing results? Is RPA really the magic elixir that it seems? Or is it simply the latest “new thing” in a recurring enterprise improvement cycle spanning decades? In this KCP Executive Briefing we distill out market developments, describe the emerging challenges, then explain what’s different about RPA.

Knowledge Capital Partners

London School of Economics and Political Science

University of Missouri, St, Louis and CISR MIT

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RPA Market Developments Looking at the market, one might forgiven for being a bit cynical. By mid-2017 robotic process automation or RPA had become one of the most misused and over-hyped terms in business, increasingly applied to older or non-conforming products to add a veneer of excitement, glamor and novelty. To counter this confusion, in its recent publication “IEEE 2755-2017: Guide for Terms and Concepts in Intelligent Process Automation” the IEEE has produced a standard definition of RPA: “A preconfigured software instance that uses business rules and predefined activity choreography to complete the autonomous execution of a combination of processes, activities, transactions, and tasks in one or more unrelated software systems to deliver a result or service with human exception management.”

More simply, we can define RPA as ‘software that automates tasks currently performed by a human, by following rules to process structured data’. RPA tools produce a single correct result. Real RPA tools have two further distinguishing features: they are ‘configured’, rather than needing extensive IT development, and they are non-invasive – interacting with existing systems through user interfaces at the presentation layer. iii While the RPA market is still relatively small ($US 629 million by 2018), it is set to grow exponentially at a conservative estimate of 38% per annum over the next five years.iv Our February 2017 survey found 51% of organizations at proof-of-concept stage or already deploying RPA. As evidence of the market’s growing dynamism, by June 2017, five months later, ISG Group were reporting 50% deploying, and 30% piloting RPA projects.

Caveat Emptor… Purely in terms of market interest, then, RPA definitely looks “hot.” But in parallel with accelerating deployments and glowing satisfaction ratings, in the last 12 months we are also seeing a lot more challenges emerging with RPA as organizations newly adopt, or try to scale their deployments. Our own early exploratory case study work throughout 2015 and early 2016 focused mainly on success stories, but even so we identified 25 action principles for management to follow for effective RPA deployment.v By March 2017 we had completed rich case studies of 20 deployments involving 9 RPA provider tools, and had identified 41 specific risks across the RPA life-cycle, and 30 Action Principles needed to mitigate these.vi Other sources show a similar, more varied range of outcomes:

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• McKinsey, for example, ‘in conversations with dozens of executives’, identified challenges when companies try to scale localized proofs of concept.vii • While Ernst and Young report many successful projects, they also report having seen 30-50% of projects initially fail, not because of the technology, but through common management mistakes.viii (Management consultants, of course, are more likely to see the indifferent experiences, because a major part of their trade is helping clients when things go wrong.) More representative survey data still demonstrates varying levels of success: • HFS Research found 51% satisfied, 33% neutral and 16% dissatisfied with the business value from RPA deployment. On cost savings, 52% were satisfied, 37% neutral, and 10% dissatisfied.ix • In a June 2017 Automation and AI survey, ISG Group found 75% of clients rating automation and AI as strategic differentiators, critical to delivering products and services, and to freeing up staff to do more value-added work. But around one third were finding 4 major challenges, namely lack of budget; organizational resistance to change; governance, risk or compliance concerns; and security issues. In the face of mixed successes, emerging challenges and not insignificant failures, then, why are buyers still enthusiastic? Are the “triple wins” we identified in our earlier work – for customers, shareholders and employees – now in jeopardy as more clients deploy, and as more clients scale work volumes and automate ever more processes? Or are we seeing the emergence of a powerful new improvement operations tool in the early “learning” stages of what could be much broader adoption? Perhaps the real question is: “What’s different about RPA?”

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What’s Different About RPA: The Importance of Context We believe the answer lies in understanding RPA in the context of historical operations challenges and improvement programs. For over 25 years, enterprises have undertaken a succession of largescale programs to improve productivity, agility, efficiency and operational effectiveness – sometimes in concert, sometimes in isolation. These programs have variously sought to

exert the 3 basic

transformation levers of People, Process, and Technology, and have typically been endorsed and executed as strategic C-Suite initiatives. The significant costs for these initiatives have often been capitalized and carried as assets on company books. As the table below suggests, an inventory of these programs is studded with familiar acronyms and marked by similar implementation approaches: specialist (expensive) consultancy services, standalone budgets, dedicated deployment teams.

Figure 1 - AUTOMATION IN CONTEXT: OPERATIONS TRANSFORMATION Tools/ Levers PEOPLE

PROCESS

1990s

2000s

2010-

ITO/BPO

Shared Services Offshoring

Talent/Skill Augmentation

“Lift and Shift” “My Mess for Less”

“Labor Arbitrage”

“Digital Workforce”

Disruption: High

Disruption: Low

Time/ROI: • Years • Cost/service trade-off • 55% ‘only doing OK’ or ‘poor performance’

Time/ROI: • Years • Cost/service trade-offs • Eroding labor arbitrage gains from 2010

Time/ROI: • Weeks/Months • Optimizing human capabilities • Multiple business benefits

TQM BPR

Lean Six Sigma

BPM OI

“Don’t Automate, Obliterate!”

“Define, Measure, Analyze, Improve, Control” (DMAIC)

“Bridging IT and Business”

Complexity: High

Time/ROI: • Years • Big capability investment • 30-50% failure rate

Time/ROI: • Years • Big capability investment • Continuous improvement effective

Time/ROI: • Years • High cost and resources • Problematic customization • IT-Business gaps

ERP 2 CRM, SCM, BI Mobile

Cloud, RPA, Analytics, Blockchain

“Single version of the truth”

“360 view”

RPA “Taking the Robot Out of the Human”

Capital: High

Capital: Low

Deployment: Years

Deployment: Weeks

ROI: Years

ROI: Months; 30-200% in year 1

TECHNOLOGY DBMS ERP 1

Other technologies less tested

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To get a sense for the context in which RPA has emerged, letâ&#x20AC;&#x2122;s take a brief walk down this memory lane. In terms of technology, the introduction of Materials/Manufacturing Resource Planning (MRP) software in the early 1990s, soon led to more comprehensive Enterprise Resource Planning (ERP) software with the goal of integrating core inbound-to-outbound and back office processes. ERP kicked off a 20+ year cycle of IT investment and implementation as initial on-premises (ERP1) platforms became internetenabled (ERP2) and were extended to additional customer and supplier processes and applications. The cycle of investment continues today as native implementations move to the cloud, new functional applications continue to emerge, and M&A activities create ongoing integration challenges. In many enterprises, ERP systems have come to represent the single largest capital investment on company accounts and almost certainly their largest IT costs. ERP also meant major changes to work processes and practices, requiring extensive staff training. Large projects could take up to 18 months or longer and involve hundreds of consultants. Customization and data migration, along with development of multiple ERP instances by subsidiary or geography, soon came to absorb the majority of enterprise IT resources, creating complexity that could hinder rather than enable corporate agility. In sum: complex, disruptive, expensive, and challenging to implement and sustain, with long implementation timeframes resulting in deferred ROI. On the business process front, ERP initiatives were often accompanied by (and in sometimes integrated with) parallel process initiatives such as Business Process Re-engineering (BPR), which aimed to de-compose and re-compose core business processes around targeted business outcomes to make them more efficient and effective. Like ERP, BPR also required significant consultancy support, sustained investments and dedicated staff to reinvent core enterprise processes, diverting attention and resources from ongoing business activities and demands. Again, complex, disruptive, expensive, with long implementation programs and deferred ROI. Meanwhile, in parallel with these initiatives, companies were exploring various workforce approaches to improve productivity, including the externalization of people, technology and processes through outsourcing â&#x20AC;&#x201C; initially IT outsourcing, and later with core business processes such as finance and accounting and HR. As with ERP and BPR initiatives, outsourcing meant hiring consultants to assist with detailed, time-consuming vendor evaluation and selection, extended contracting and procurement cycles, and massive enterprise disruption as assets were sold and people transferred to third parties in exchange for the long-duration service contracts needed to achieve the business case.

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Similarly, regional and later global shared services initiatives required major corporate re-organizations, specialist consultancy support, and significant IT re-work, not to mention the political challenges associated with dis-enfranchising functional and local management, and the complex governance processes needed to demonstrate value and gain buy-in. Again, complex to orchestrate, highly disruptive, with long timescales and deferred benefit realization. Other transformation initiatives such as offshoring, Lean, Six Sigma, and Business Process Management, also carried significant time and costs to implement, required specialist skills and training, and delivered varying but relatively modest levels of ROI. In sum, the near-universal buyer experience with these now-legacy transformation programs has been marked by common characteristics and consequences. Notably, these historical initiatives have proven: • Expensive • Disruptive • Complex • Difficult to implement • Hard to sustain • Modest ROI • Long time to value

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Conclusion On reflection, one might indeed feel pity for the Operations and IT executives assigned to lead and manage previous interventions – lots of hard, painful work, using inflexible, long-cycle tools, with limited recognition and reward, for uncertain and sometimes hard-to-quantify gains. Enter RPA, which emerges in this context as a surprisingly winning solution. RPA offers a flexible, general purpose toolset that, while not problem-free or without challenges, is by comparison relatively easy to configure, offers rapid implementation, high ROI, early benefit realization, with minimal pain and mostly happy users. For business, it eliminates multi-year waits on the IT work queue for technology solutions, offers control over configuration to meet changing process demands, and allows the workforce to pursue new and more valuable revenue-generating activities while increasing productivity. Similarly, RPA enables the IT function to focus on core enterprise infrastructure, relieves pressure on shrinking resources (people and budgets), while ensuring security and governance. Moreover, because RPA tools operate at the presentation layer, they don’t disturb or compromise underlying systems of record. Is RPA a magic elixir? Given the challenges noted earlier, and the imperative for specialist implementation guidance and expertise, RPA is certainly not a panacea for all enterprise ills. But it clearly changes the paradigm for enterprise transformation and creates an essential technology platform on which to build a truly digital business. For those unsung operations leaders, the research to date offers abundant evidence why they are justifiably excited and keen to reap the benefits.

See Willcocks, L. and Lacity, M. (2016) Service Automation, Robots and The Future of Work (SB Publishing, Stratford).Also Lacity, M. and Willcocks, L. (2018) Robotic Process and Cognitive Automation: The Next Phase. (SB Publishing, Stratford). i

Quoted from the IEEE 2755-2017: Guide for Terms and Concepts in Intelligent Process Automation, October 2017.

iii

See Lacity, M. and Willcocks, L. (2017) Robotic Process Automation and Risk Mitigation: The Definitive Guide. SB Publishing, Stratford.

Figures from Horses For Sources Research, June 10th 2017. HFS note that this covers software licenses and the direct services market, including implementation and consulting services focused on building RPA capabilities within an organization. It does not include wider operational services like BPO, which may include RPA becoming increasingly embedded in its delivery. Taking these and other factors into account, we would estimate the market as over US$2 billion by end of 2017. HFS note that the broader market for what they call intelligent services automation is ten times the size of the RPA market. iv

See Willcocks, L. and Lacity, M. (2016) Service Automation, Robots and The Future of Work (SB Publishing, Stratford)

See Lacity and Willcocks (2017) op. cit.. Note that Action Principles are not the same as ‘Best Practices’ With RPA and AI one size does not fit all! Whether an Action Principle should be used depends on your objectives, the capability to deliver the practice, context and timing. vi

vii viii ix

Edlich, A. and Sohoni, V. (2017) “The bots: Why robotic automation is stumbling”. Downloaded from McKinsey site, May 24th 2017. Ernst and Young (2016) Get Ready For The Robots: Why planning makes the difference between success and disappointment. Report, December Fersht, P. (2017) The Market Outlook for Robotic Process Automation. Presentation at the Blue Prism World conference, London, June 21st 2017.

The assessments are based on a series of research studies we carried out since 1993 at Oxford, Warwick, and Missouri Universities, and at the London School of Economics and Political Science. Representative publications are Willcocks, L. Feeny, D. and Islei, G. (1997) Managing IT As A Strategic Resource. (Maidenhead); Shanks, G., Seddon, P. and Willcocks, L. (2003) Second Wave ERP. Cambridge University Press, Cambridge); Lacity, M. and Willcocks, L. (2015) Nine Keys To World Class BPO Performance (Bloomsbury Press, London); Willcocks, L. (2001) How Radical Was IT-enabled BPR? Evidence On Financial and Business Impacts. International Journal of Flexible Manufacturing Systems ( December); Willcocks, L. Venters, W. and Whitley, E. (2014) Moving To The Cloud Corporation. Palgrave, London. See also the automation texts cited earlier. x