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Cognizanti Journal Volume 9, Issue 1, 2016

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Digital Business 2020 Part III: Getting There from Here

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Cognizanti Journal Volume 9, Issue 1, 2016

  1. 1. An annual journal produced by Cognizant VOLUME 9 • ISSUE 1 2016 Part III Digital Business 2020: Getting there from here! Cognizanti
  2. 2. Cognizanti is an annual journal published by Cognizant. Our mission is to provide unique insights, emerging strategies and proven best practices that globally-minded companies can use in their quest for business and IT performance excellence. All articles published in Cognizanti represent the ideas and perspectives of individual Cognizant associates and contributors who have documented expertise in business-technology strategy and implementation. The content of the articles published in Cognizanti represents the views of the individual contributors and not necessarily those of Cognizant. They are put forward to illuminate new ways of conceptualizing and delivering global services for competitive gain. They are not intended to be, and are not a substitute for, professional advice and should not be relied upon as such. For more insights, and to continue the conversation online, please visit our e-community at http://connections.cognizant.com or download our Perspectives app from the Apple App Store or Google Play at http://cogniz.at/itunescognizantperspectives or http://cogniz.at/googleplaycognizantperspectives, respectively. © Copyright 2016, Cognizant Technology Solutions No part of this publication may be used or reproduced in any manner whatsoever without written permission of Cognizant.
  3. 3. The Cognizanti Team Publisher: Malcolm Frank, Executive Vice-President, Strategy & Marketing Editor-in-Chief: Alan Alper, Associate Vice-President, Corporate Marketing Editor: Reshma Trenchil, Senior Manager, Corporate Marketing Thought Leadership Program Management: April Vadnais, Senior Manager, Corporate Marketing Art Director: Jason Feuilly, Director, Corporate Brand/Design­ Design/Print Production: Diana Fitter, Contributing Art Director Contributing Editor: Mary Brandel, Contributing Editor Columnist: Bruce J. Rogow, Independent Advisor Digital Distribution: Nikhil Narayanan, Manager, Social Media Marketing Editorial Advisory Board Kaushik Bhaumik, Senior Vice-President & Market Leader, Communications & Technology Industry Group Nagaraja Srivatsan, Senior Vice-President, Emerging Business Accelerator Mark Livingston, Senior Vice-President, Cognizant Business Consulting Ramkumar Ramamoorthy, Senior Vice-President, Corporate Communications Anand Chandramouli, Director, Cognizant Research Center Ben Pring, Vice-President, Cognizant Center for the Future of Work Gary Beach, Publisher Emeritus, CIO Magazine VOLUME 9 • ISSUE 1 • 2016 An annual journal produced by Cognizant Cognizanti
  4. 4. 5 Editor’s Note Progress on the Path to Digital Authenticity 7 The First Word Digital Reinvention Requires a Radical CIO Makeover 13 Being Digital Making Digital Real and Rewarding 27 Commentary Jumping on the Gig Economy 33 Bots at the Gate Intelligent Automation: Where We Stand — and Where We’re Going Table of Contents
  5. 5. 41 Foundational Technologies Laying the Groundwork for a Platform Business 53 Commentary Making Dollars & Sense of the Platform Economy 59 Data Ethics Return on Trust: The New Business Performance Indicator 67 Internet of Things From Strategy to Action: Driving IoT to Industrial Scale 75 Connected Lives Where Smart Vehicles Meet the Intelligent Road 83 The Last Word The 50-Year Journey to Digital Business
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  7. 7. Cognizanti • 5 Progress on the Path to Digital Authenticity As the late musician Frank Zappa once observed: “Without deviation from the norm, progress is not possible.” Zappa lived this axiom quite well throughout his extraordinary career, breaking every sonic and lyrical convention underpinning progressive rock until his untimely death in 1993. Business leaders could take a lesson from Zappa’s and other true rock-n-rollers’ zealous approach to their craft as they prepare their organizations to “be digital,” flouting the status quo with each new initiative and establishing themselves as die-hard practitioners of a whole new way of doing business. With this in mind, Part III of our 2020 digital business sojourn charts the early progress made in re-orchestrating business. We build on the learnings shared in the previous two editions of Cognizanti journal (Volumes 7 and 8), in which we established that – at least for most long- standing organizations – the transition to “being digital” is a journey, not a sprint. And despite the ever-increasing technological cacophony of the world in which we live, work and play, businesses must deliver simple, in-the-moment experiences that blend the physical with the digital – if they want to be heard above the din. This edition of Cognizanti explores the essence of what it means to be digital (think of a digital-to- the-core attitude and customer autonomy as critical operating constructs) and amplifies the role that the thoroughly modern CIO can play in helping organizations achieve progress, both from a leadership and “gig” economy point of view. From there, we examine the evolving world of intel- ligent automation (systems that do, think, learn and adapt), as well as the emerging landscape of business platforms, where companies of all sizes and shapes can plug and play in ecosystems that they either own, manage or merely participate in. This new approach introduces an interesting variation on the “co-opetition” theme that has pervaded business for the past few decades. We also probe what it takes to scale up Internet of Things pilots to fully realized implementa- tions and the critical role of trust in today’s digital economy. We take a deep dive into how many of these themes are playing out among forward-thinking road warriors and businesses that are navigating the nascent intelligent transport infrastructure. Lastly, we conclude with industry guru Bruce Rogow, who exhorts established business to move forward with their digital transformation plans, through all the seasonal shifts of business and IT. In this final edition of our digital business trilogy, we’ve covered the challenges that we believe are core to your organization’s digital business mandate. Feel free to share your thoughts on these topics and any others that you believe are a part of the digital mandate at Alan.Alper@cognizant.com, or on our e-community, Cognizant Connections https://connections.cognizant.com/. Editor’s Note
  8. 8. Cognizanti • 7 To lead digital transformation, CIOs need to go beyond technology prowess and develop new work styles, people skills and political savvy to energize the organization for change. When it comes to being digital, two equal and opposing forces are in play. On the one hand, digital promises to transform orga- nizations into more personalized, relevant, real-time businesses that use social, mobile, analytics and cloud technologies to engage with customers in a more value-driven way. Along with the upside, however, come challenges, as organizations and employees must substantially change how they work, reconfigure their skill sets and even recast their work personalities. No one personifies this need for reinvention more than the CIO. Not long ago, the CIO was tasked primarily with keeping IT humming. The business outlined its needs, and the CIO executed on them. That’s table stakes in today’s digital age. Now, CIOs must be influential, innovative and connected, capable of con- fidently collaborating with business leaders across functional silos to steer the organiza- tion on the digital path. To understand this ongoing transformation, we surveyed 200 CIOs across the U.S. and in multiple industries. Our findings illuminate the new challenges many CIOs face, as well as the skills and work styles necessary to successfully cross the digital chasm. What we found: While CIOs are well-positioned to lead the digital program, they need to up their game in terms of cross-functional rela- tionships, especially with the CEO and chief marketing officer (CMO), while adopting a leadership mindset toward identifying talent, inspiring and managing change, and enabling innovation. CIOs Play a Crucial Role in Digital Transformation First the good news: An overwhelming 89% of respondents said CIOs are critical to the success of the organization’s digital transfor- mation (see Figure 1, next page). Further, CIOs are more apt to lead digital programs (34%) than the CEO (29%) or others in the C-suite. The First Word Digital Reinvention Requires a Radical CIO Makeover By Reshma Trenchil
  9. 9. 8 But this pivotal role requires a new set of strengths and skills not traditionally associated with CIOs, such as the need to be socially and politically savvy, leadership oriented, innovative and willing to take risks (see Figure 2, next page). Ideal CIOs are also experienced with leading digital programs or a digital company (88%), possess cross-industry and business experience (78% and 82%, respectively) and have moved up through the ranks to their current position (79%). A core IT education (86%) is slightly more crucial than a business management education (82%), and certifi- cations in technical and professional skills (78%) can be a plus, our study reveals. Becoming a Digital Leader A large majority (87%) of respondents believe successful digital CIOs are those who have adopted a transformative mindset rather than focusing merely on improving IT operations or even influencing business strategy with digital know-how. Respon- dents also emphasize the need to spend more time on cross-functional collaboration (85%) and aligning the digital strategy with business needs (84%). CIOs need to focus outside the four walls of the organization (82%) – working with customers, partners and suppliers – since digital is the glue that connects all constituencies across the business ecosystem. Situated at the intersection of business and technology, CIOs are positioned to inform and drive “digital-first” strategies. To accomplish this, respondents said CIOs should seek to be a major contributor to the enterprise digital strategy (85%) and take time to study market trends and customer needs to identify digital opportunities (77%), in addition to finding, evaluating and deploying new digital technologies (82%). All told, the successful digital CIO must function in multiple roles (see Figure 3, page 10), including: OO Chief talent officer, working closely with the human resources organization to bridge skills gaps (87%). Response base: 200 Source: Cognizant Research Center Figure 1 Key Elements to Enable the Digital Transformation CIO plays a key role in digital transformation A digital strategy that is clearly articulated, communicated and understood  Strongly disagree  Disagree  Neither agree  Agree  Strongly agree 1% 10% 41% 48% 4% 12% 45% 39% 1% 4% 13% 39% 43% 3% 15% 43% 39% 4% 15% 43% 38% 4% 16% 40% 40% 2% 1% 17% 40% 40% 6% 16% 38% 40% 5% 19% 34% 42% Actively collaborating with talent acquisition teams to acquire the required skills Understanding the benefits of digital programs and having the metrics to measure the success of digital initiatives Identifying the skill gaps that impede digital transformation An annual planning process to align departmental objectives with the company’s overarching digital strategy/objectives Common understanding between the CIO and CMO teams about the identified shared goals Understanding the costs of digital transformation programs and having realistic ROI expectations Identifying the appropriate digital technologies to deliver on business objectives nor disagree
  10. 10. Cognizanti • 9 OO Chief influence officer, maintaining excellent working relationships with other business leaders (86%). OO Change agent, transforming the culture to embrace digital approaches (82%). OO Chief inclusion officer, promoting an open and innovative enterprise culture (82%). Influencing Key Stakeholders Because digital is an enterprise-wide effort, the CIO’s relationships with other business leaders are critical. In fact, over 80% of our respondents said success hinges on the ability to build and maintain relationships, as well as use these relationships to obtain buy-in and support for digital initiatives. Of all these relationships, the most important is with the CEO (90%). In fact, a majority (63%) believe they’d be most successful if they reported directly to the CEO; little wonder, as in most cases, the CEO sponsors digital programs in the organization (42%) vs. the CIO (24%) or others in the C-suite. Conversely, the lack of CEO support can pose a significant challenge, with many respondents believing they do not receive enough backing from the CEO and board of directors to deliver on digital’s promise (66% and 49% of respondents in banking and healthcare, respectively). A close second to the CEO relationship is the importance of the partnership with the CMO (87%). This is critical given ongoing in-fighting between CIOs and CMOs at many companies for budget and strategic influence over the digital agenda. The need to collaborate is a matter of necessity; 83% of respondents indicated that a major portion of the funding for digital projects originates from marketing IT and CIO budgets. And since CIOs believe customer experience is largely shaped by digital technology (79%) and that marketing is increasingly becoming digital (85%), the two camps have a vested interested in collaboration. For instance, while marketing often owns the digital customer experience, execution is typically the CIO’s responsibility (84%). As a result, a vast majority of respondents believe Response base: 200 Source: Cognizant Research Center Figure 2 Critical Skills & Competencies of the Digital CIO Socially savvy (engage with regulators, clients, media and analysts) Politically savvy (push digital transformation enterprise-wide) 1% 1% 12% 50% 36% 2% 13% 46% 35% 1% 16% 43% 36% 4% 17% 40% 39% 3% 17% 43% 35% 16% 40% 35% 21% 39% 34% 1% 22% 38% 34% Lead from the front (have solid knowledge of business and industry) Game-changer (reflect on challenges and opportunities to find the best way forward) Transformational leadership (mobilize commitment, create shared vision and work toward digital transformation) Innovator/co-creator (create new business models in partnership with cross-functional CXOs) Networking and relationship-building (actively forge partnerships internally) 4% 4% 6% 5% 2% Risk-taker (ability to justify actions and investments) 2% 7%  Strongly disagree  Disagree  Neither agree  Agree  Strongly agree nor disagree
  11. 11. 10 digital initiatives are strengthened by the joint participation of CIO and CMO teams (81%). Not surprisingly, winning CEOs promote collaboration between the CMO and CIO (77%). Tips for Becoming a Digital CIO To successfully steer their organiza- tions throughout the digital journey, we recommend CIOs consider the following: OO Become embedded in key digital initiatives, advising and serving as a key influencer or “center of excellence” for all things digital. Specify new tools, tech- nologies and sources of talent, and suggest necessary business model and process changes. OO Ensure the IT organization moves toward digital maturity, starting by tackling the legacy IT portfolio. The fail-fast digital credo must replace IT’s traditionally more cautious approach in order to inspire and support innovative approaches. OO Establish IT as the primary channel through which digital products and services are realized. Play a central role in the development and commercialization of digital initiatives, regardless of where they originate in the organization. Seek ways to integrate meaningful shadow IT projects into the enterprise information architecture. OO Be the change you wish to see. An enterprise-wide digital mentality will not happen on its own. CIOs need to become digital change agents and catalyze business transformation in order to evolve into true digital champions and trusted advisors to the CEO. Note: This article is based on our recently published report “Being Digital: How and Why CIOS Are Reinventing Themselves for a New Age.” Response base: 200 Source: Cognizant Research Center Figure 3 The Evolving Digital CIO Role Chief talent officer (work closely with HR team to bridge IT/business skill gaps) Chief influence officer (maintain excellent working relationships with other business leaders) 1% 12% 46% 2% 12% 42% 44% 1% 13% 39% 43% 1% 17% 37% 45% 18% 38% 43% 15% 39% 41% 16% 37% 42% 10% 20% 35% 35% Change agent in transforming culture Chief inclusion officer (promote an open and innovative enterprise culture and enforce talent value chain seamlessly) IT evangelist (discuss how to leverage IT to implement digital strategy and engage IT in digital transformation) Change agent in leading the digital journey (shape the vision and ignite passion for digital transformation) Governance champion (enforce the value equation across business functions and lead continuous improvement) 4% 5% 1% 4% 1% Digital coaches (scout the latest digital technologies and blend with IT to enforce value creation) 41%  Strongly disagree  Disagree  Neither agree  Agree  Strongly agree nor disagree
  12. 12. Cognizanti • 11 Author Reshma Trenchil is a Senior Manager on Cognizant’s thought leadership team. She has 15-plus years of experience in business writing and research. Before joining Cognizant, she worked in equity research at UBS and thought leadership research at Deloitte. She has a master’s degree from Boston University and a bachelor’s degree from Stella Maris College. She can be reached at Reshma.Trenchil@cognizant.com. Acknowledgments This report is based on research conducted by Sanjay Fuloria, Senior Researcher within the Cognizant Research Center.
  13. 13. Making Digital Real and Rewarding By Rob Asen, Ted Shelton and Burkhard Blechschmidt Being Digital Businesses can “do” digital by focusing on isolated initiatives. But to truly “be” digital, they need to ensure they are digital to the core, and redefine the nature of customer centricity. “A lot of us play rock-and-roll, but not a lot of us are rock-and-roll.”1 — Dave Grohl (Foo Fighters and Nirvana), describing the late Lemmy Kilmister from Motörhead Business leaders have heard the call to “become digital.” With good reason: They’ve seen established enterprises across the globe be disrupted by the likes of Uber, Spotify, Waze and others that showed up seemingly out of nowhere and then turned an industry on its head. Savvy business leaders would be remiss if they didn’t seek a digital remedy to avoid becoming the next victim. Some have set out to transform themselves, in piecemeal or big-bang ways, and come away wondering why the markets didn’t respond to their digital dynamism. But for all their efforts, established companies might well consider the maxim: “know thyself.” Because their customers certainly know them – and instinctively recognize that a few mobile apps, tweets from the CEO (or more likely a marketing intern) or zip-code targeted ads do not a digital brand make. Focusing on isolated digital initiatives and taking a watered-down approach to customer centricity and personalization won’t enable established enterprises to keep pace with, much less leapfrog, companies that either were born digital or quickly learned to be from market pioneers. If the threat of disruption weren’t enough, digital transforma- tion can also boost the bottom line by more than 50% when approached holistically, according to a study by McKinsey & Co.2 The core difference is “being” vs. just “doing” digital. We all know what “doing digital” looks like. Even the most non-digitally-savvy among us write e-mails – not letters – and have our paychecks directly deposited into our bank accounts or use our smartphones for navigation. As a society, we have embraced digital tools to replace analog ways of working. But we also know people and companies that operate as though they never even knew the analog precursor to the digital tools and work styles they use so naturally, and whose very first step toward solving problems is digital in nature. Uber, Facebook, Airbnb – each began their journey by answering fundamen- tal questions in a digital way, and each has arrived at a very different place from their traditional counterparts as a result. So, what distinguishes “doing” from “being?” From our experience and research, the Cognizanti • 13
  14. 14. key lies in reflecting a digital mentality in everything the business does and to the very core of the organization, including operations, processes, business models and the culture itself. Think of a cable provider or airline that provides a great new digital device or mobile app but then turns right back into an old-school business the minute a billing question arises or a bag is lost. At a digital business, the contextually-relevant, hyper-personalized experiences, agility, mobility and social linkages continue, no matter which part of the journey the customer is on. Secondly, digital businesses fully embrace customer centricity as a guiding strategy, using digital to not just support but also redefine how customers interact and engage with each other and the business. In addition to understand- ing what customers really want and enabling hyper-personalized products, services and experiences, fully digital companies ultimately strive to take customer centricity to a whole new level – to “customer autonomy.” The end goal is to enable customers to leverage their assets and capabilities to design their own experience, even embedding the customer into previously closed processes and establishing them as a main actor in the value chain. In short, digital businesses act as if older, legacy ways never existed. We believe that many non-digitally native companies can – and will – make this transition, by invoking substantive changes to their mindsets, attributes and operating models that truly enable them to focus on a digitally-defined customer experience – issues that not even the best technology and skills can cure. By doing so, they can achieve a performance boost, whether in traditional economic terms or in realizing entirely new forms of value. The Bright Line Test: Customer Centricity As noted, the defining characteristic of digital businesses is customer centricity. But this concept has come a long way from the playbooks of the 1970’s fast-food chains, whose “have it your way” motto embraced customer participation by personalizing hamburgers. Today, businesses can do that digitally, taking “hyper-personalized” recom- mendations, products and services to an extreme by empowering customers to take command and control of part of the supply chain, themselves. With customer autonomy, businesses make key assets and capabilities available to customers, who pick and choose among them to design an experience that suits their needs. They often figure out ways to leverage these capabilities that the originat- ing business might never have imagined – creating even more value for both customers and the business. This requires organizations to open up their ecosystem and allow new levels of transparency, even if it means canni- balizing a piece (or pieces) of their business. Such an approach requires a new mindset and attitude toward value creation. Customer autonomy capabilities are emerging at companies that were born digital or mindfully became that way (see Quick Take, next page). For example, autonomous customers already expect to design their own cable TV experience and telecommunications plans; it won’t be long before these expecta- tions spread to hard goods, as consumers begin to design their own brands. Further, 3-D printing shops already offer design interfaces and 3-D print services to customers who wish to create their own products or gadgets. 14 With customer autonomy, businesses make key assets and capabilities available to customers, who pick and choose among them to design an experience that suits their needs.
  15. 15. Cognizanti • 15 The Many Faces of Customer Autonomy Quick Take Customer autonomy is an old concept made new in the digital age. Examples include: OO Co-innovation: Through the Nike+ social platform, customers share their running experiences with their peers, defining not just a new experience for themselves but also providing Nike with firsthand product design ideas through real user journeys, like marathons and suggestions to personalize products. OO Sharing economy: Customers and businesses can personalize their parcel delivery experience through a platform developed for DHL. The platform enables a sharing-economy approach to package delivery, using the flexibility of private couriers to enable personalization of when and where parcels are delivered. This approach is enabling not just one company to adopt customer autonomy but also an entire industry. OO Prosumerization: Some utilities are enabling consumers to become “prosumers” who produce and consume energy at the same time. Consumers who reduce their consumption or generate/store energy can sell their excess energy via a peer-to- peer model, significantly reducing energy retail costs. In another prosumerization model, energy consumers connect on social platforms to coach each other on energy consumption; in one case, this resulted in a 17% reduction in energy consumption.3 OO API-enabled business ecosystems: As the channels and devices to expose data exponentially scale, many organizations are sitting on a gold mine of information assets. Telecommunication companies, such as AT&T, were the first to create API platforms, enabling app developers to easily incorporate telco services into their appli- cations. Today the “API economy” provides the glue that ties together disparate data and systems, exposing a uniform data layer to the end-customer through devices like smartphones, wearables and IoT devices. (Read about the growing role of APIs in our look at platform businesses on page 41.)
  16. 16. The fact is, once businesses established a cus- tomer-centric approach, they would do well to stop thinking about “customer centricity” and begin viewing themselves through the eyes of the customer; after all, what looks like customer centricity from inside a company is customer autonomy from the point of view of the customer. Customer autonomy can even extend beyond the supply chain and into the organizational model itself; might your organization’s chief customer officer eventually be chosen from among your best customers? The idea of everyone on the board of directors potentially being a customer has already been realized: A decentralized autonomous organization running on the blockchain defines the extreme end of the continuum of “being digital.”4 At this level, the company’s mission and decision- making processes could be encoded in “smart contracts,” run by intelligent software that uses machine learning and algorithms. Top management decisions could be increasingly made through advanced algorithms and big data, and funding and ownership could be “open-sourced” based on encoded rules. Becoming Digital Of course, digital leaders have the freedom to operate as though there were no legacy processes to consider. Such is not the case for the majority of companies today. However, we believe even the most traditional businesses can shake free from entrenched structures and seemingly inviolable processes and mindsets, and begin moving in a digital direction. They can do this by assessing the gap between their own capabilities and those that are intrinsic to being digital (see Figure 1). By doing so, organizations can begin moving toward full digital enablement, in which a digital mindset pervades all business processes, the corporate strategy and the operational and business models. 16 Assessing Digital Gaps Figure 1 Digital Capability Result Challenge for Pre-Digital Organizations STRATEGY AND INNOVATION Agility QQ The culture nurtures innovation principles, such as think big/start small/fail fast; move quickly, learn quickly, reorient without remorse. QQ Processes are heavy, with decision-making bottlenecks, extensive testing, long cycle times. Continuous, iterative planning cycles QQ Strategies are geared toward big-picture thinking and lifetime relationships, not transactions. QQ The quarterly focus is on making the numbers, which typically requires rote thinking and execution, with no time to experiment. Openness to risk and failure QQ Experiments yield confirming or non-confirming results, and both are valued; ongoing testing ensures continuous improvement. QQ There is little tolerance for failure and lack of appreciation for lessons learned from experimentation. Institutional innovation QQ Idea-generation extends beyond the enterprise, redefining accepted truths and “givens.” QQ The business model is open for reinvention, even if that means cannibalizing pieces of the business. QQ Systemic barriers to entry are challenged, and new industry standards/protocols are defined. QQ Innovation is applied only at the product or service level. QQ The current business model and modes of profitability are protected at all costs. USE OF INSIGHTS Data-driven culture QQ The organization is flat and data-driven, with a welcome attitude toward diverse opinions to generate and test ideas. QQ Decisions are made on metrics, not opinions. QQ A top-down command-and-control culture exists, in which the “HiPPO” (highest paid person’s opinion) rules, shooting down contradictory opinions and dismissing input from underlings. Continued on next page
  17. 17. Cognizanti • 17 Assessing Digital Gaps (cont’d. from previous page) Figure 1 Digital Capability Result Challenge for Pre-Digital Organizations LEADERSHIP AND CULTURE Employee empowerment QQ Everyone is an owner, and every employee represents the company. QQ Employees are well treated because management values their contributions. QQ Ossified labor structures maintain the status quo. QQ Management believes employees are easily replaced commodities. New approaches to measuring success QQ Economic values are often transcended and replaced by new, digitally-driven value for both customer and company: information equity, social equity, reputation equity, cyber/trust equity. QQ Decision-making is driven by short-term, lagging financial indicators. Growth targets are linear projections based on past growth rates. QQ Business leaders fail to recognize that outcome- based economic valuation of success can be misleading in an age of digital disruption and an emerging digital generation with a different value system. Transparency and trust QQ An open-source culture utilizes APIs to leverage company assets/data for bolt-on innovation, and sells on reputation and product transparency. QQ The company believes it needs to keep knowledge secret, leading to an inward focus. PRODUCTS & SERVICES Smart, connected design QQ Products are designed to be digitally enhanced with data for software-based customiza- tion, enabling remote services, upgrades and maintenance. QQ Open interfaces comply with the connected “Internet of everything.” QQ Products and services are highly personal- ized, as the cost of customization for digitally enhanced products and services is minimal. QQ Product design is based on what is digitally possible, not what the customer will value. Interoperability with ecosystems and platforms QQ Platforms and ecosystems are real-time-enabled by open source protocols for the Internet of everything. QQ Companies try to monopolize their smart products and services into closed ecosystems. QQ Ecosystems are defined within the boundaries of the industry. QQ Protection of personal data related to smart products and services is only guaranteed in closed ecosystems. Focus on marketing and monetization QQ Marketing enables mass customization and predictive customer experiences. Monetization is based on personal customer value. QQ Market segmentation, pricing and business models follow industry truths and givens. QQ Many monetization ideas are based on customer data or hard-to-measure assumptions around creating customer loyalty and a trusted brand, sometimes creating customer lock-in. SYSTEMS & PROCESSES Scalability QQ Scalability is a required design consideration for every process and system. QQ Structural limitations exist, constrained by company-owned assets, traditional entry barriers, legacy systems and concerns. Automation QQ Planning and budget processes include not just employee headcount but also how many software bots are required in the next planning cycle. QQ No thought is given to applying automation and innovation to how work will get done. Labor costs are focused only on full-time employee headcount. CUSTOMER TOUCHPOINTS Customer centricity QQ The company has an obsessive focus across the entire customer lifecycle. In many cases, the ultimate end state is “customer autonomy.” QQ Interactions with customers beyond the sale are considered a cost of doing business. QQ Internal systems and IP are closely protected.
  18. 18. 18 To make this pivot, organizations must: OO Ensure digital initiatives are aligned with changing industry dynamics. OO View digital initiatives as programs that require not just technology change but also corresponding changes to business processes and operating models. OO Consider digital initiatives from a cross-functional view, across the end-to-end value chain, and assess how they redefine the customer experience and the organization itself. OO Create a focused organizational unit to drive the digital agenda in collaboration with all functions across the organization; digital endeavors require a centralized effort but cannot be the responsibility of a single team. OO Spark a culture of innovation by creating dedicated incubation centers that foster ideation and experimentation, with executive support for non-traditional funding and business case development. OO Rely on customer input to drive ongoing and continuous ideation, innovation and renovation, both directly and by tracking and analyzing customer journeys, interactions and expe- riences. OO Empower associates to understand the customer’s view and make in-the- moment decisions that improve customer engagement. OO Understand that digital initiatives are not run-of-the-mill projects but instead require new thinking around implementa- tion and ROI analysis, outside the usual framework of annual budget cycles. Adopting these new mindsets and practices can only happen with active sponsorship from senior-level executives, most typically the CEO. In our experience, digital transfor- mation efforts that are led exclusively by the CMO or CIO often fall short of addressing transformational needs across the business, as they fail to prevent insular, departmental or divisional agendas from overtaking the enterprise digital mandate. Most established organizations adopt a staged approach toward a fully digital posture. They might start with skunk-works digital experi- ments, nurturing a culture of innovation until they can eventually expand to all aspects of the operating model. Such initiatives typically include a range of digital deploy- ments involving emerging digital technologies beyond social, mobile, analytics and cloud technologies (the SMAC Stack)5 to the Internet of Things (IoT) and intelligent automation. To help organizations in this journey, we have developed a maturity model that describes how various operating model parameters need to change, in order to evolve from “thinking,” to “doing” to “being” digital (see Figure 2, next page). Digital transformation efforts that are led exclusively by the CMO or CIO often fall short of addressing transformational needs across the business, as they fail to prevent insular, departmental or divisional agendas from overtaking the enterprise digital mandate.
  19. 19. Cognizanti • 19 Thinking Digital Doing Digital Being Digital STRATEGY AND INNOVATION QQ Digital plans are articulated at a high level. QQ Technology refresh initiatives are declared to be “digital.” QQ Digital innovation is driven only by the CIO, and innovation is primarily aimed at products and services. QQ Digital initiatives are a core part of the strategy and significantly funded. QQ Larger parts of the company get involved in the innovation process related to digital (internal crowd innovation). QQ Principles of design thinking have been adopted; workshops are frequently held throughout various functions. QQ A digital innovation spin-out/spin-along is set up to spur digital innovations and new market models. QQ The strategic planning process has been replaced by a continuous innovation process involving people inside and outside the company. QQ Multiple, diverging long-term scenarios are defined as potential futures. The strategic roadmap is replaced by a strategic compass that indicates whether the company is headed toward one or more of the envisioned future states. QQ Innovation is not a function but a capability and leadership style deeply rooted in the culture of the company. USE OF INSIGHTS QQ Big data pilot projects are initiated. QQ A big data platform is selected and rolled out. QQ A big data/data science state-of-the-art platform is in place, and a data science or big data group works closely with the business. QQ Investment plans for data monetization initiatives are in the pipeline or prototyping phase. QQ Some processes have adopted data-driven/ evidence-based decision-making. QQ Big data startups are funded by an in-house-funded venture group. QQ Evidence/insights-based decision-making has become the new way of working. Many decisions are made by AI or bots. QQ Customers opt-in on their data and have transparency on their personal data in use by the company. QQ Customer insights are used to personalize products and services and predict emerging customer behavior patterns. Data is also used to enrich products and services with information and make them social. LEADERSHIP AND CULTURE QQ Digital innovation is led by the CIO or another C-level executive. A digital team is in place, mainly working on positioning the company and its products and services on the corpo- rate website. QQ A C-level executive is charged with con- solidating/ prioritizing digital ideas across the company and driving a digital agenda. QQ Digital innovation is a board-level agenda item; all major functions and business units fund digital innovation. QQ Digital innovation is crowd-sourced from inside the organization through social channels. People with the best ideas become the digital leaders. QQ Existing employees are trained on innovation techniques and encouraged to participate in digital initiatives for short periods of time. QQ A hiring strategy is established to source the best digital talent and creative skillsets. QQ Digital is no longer seen as a function led by a top executive but as a way of doing business that transcends traditional functions. While basic business operations continue to be executed (partially automated through bots), strategic programs are defined around business themes requiring multidisciplinary leadership, which is partially provided through external partners and key customers. QQ Organizational intermediation through middle management is minimal; the organization is flat, and interpersonal relationships, trust, collabora- tion are key. QQ Hiring criteria are less driven by functional role descriptions and digital capabilities but by success stories in a digital ecosystem. Talent is attracted by the company’s digital (social and reputational) equity. Digital Business Maturity Model Figure 2 Continued on next page
  20. 20. 20 Digital Business Maturity Model (cont’d. from previous page) Thinking Digital Doing Digital Being Digital PRODUCTS & SERVICES QQ Product information is available through various digital channels. QQ Online shops are available as an additional channel. QQ Some products are digitized, and digital channels are in place. QQ Frequent product enhancements are delivered, through open-sourced innovation. QQ Mass customization is enabled through digital technologies (user product configuration portals). QQ Products are enhanced through sensors and digital product memories embedded on the product. Product IP and proof of authenticity is secured (i.e., on blockchain). QQ Product experience is enhanced through social channels. Products and services are continuously innovated and personalized based on customer data and open innovation. SYSTEMS & PROCESSES QQ Process integration is in place through standard ERP solutions. QQ Individual systems and processes are customer- focused but lack cross- channel linkages. QQ Fully-integrated systems and processes are harnessed across channels. QQ Digital innovation processes and teams are consolidated into a shared- service setup and leveraged across the organization. QQ Global sourcing (if any) for digital work is handled by the central digital function, led by a C-level executive. QQ All processes are redesigned to align with the digital strategy, with a built-in periodic review. QQ Processes are largely standardized across the entire value chain in an industry or ecosystem and provided by business process as a service (BPaaS) providers. Internal non-standard processes are largely automated through bots. QQ Next-generation IT is in place; some principles include the “Uberization” of enterprise IT, with mostly federated IT architecture layers, and first preference given to construction of loosely- coupled modular apps (microservices).6 QQ Business cloud capabilities are highly verticalized, scalable and self-service-based, with autonomous management to address volume and velocity of unstructured data. CUSTOMER TOUCHPOINTS QQ Customer journey is understood, but there is little management across digital touchpoints. QQ Customer journey is integrated across channels, but the strategy is primarily channel-focused. QQ Customer journeys are mapped across multiple channels and cascade into back-end operational processes in order to ensure a seamless transition and a standard experience across channels. QQ A strategy is in place to leverage social media to connect with customers and gather customer insights/feedback that feeds into future strategy. QQ Customer autonomy is enabled, with customers becoming part of companies’ value chains and ecosystems. Customers are invited to share data, experiences and knowledge but remain in control of what they share, with whom, and for what purpose. QQ Customer touchpoints are highly personalized across all channels, creating valuable, emotional and meaningful experiences for each individual customer. QQ Companies build reputational equity through the quality of customer interactions. QQ Managing customer reputational equity is the company’s core capability, extending well beyond the classical marketing function. Figure 2
  21. 21. Cognizanti • 21 Being Digital: A Call to Action Growing into digital maturity is a process of evolution, accompanied by experiments and failures. It might start at the edges of the organization, but it ultimately redefines the enterprise. A bundle of digital experiences – no matter how innovative – won’t bring lasting change to the enterprise by itself, as digital businesses require a reimagining of the operating model. Companies intent on being digital must foster leadership behavior that encourages difficult questions, challenges truths and industry givens, and sees beyond boundaries both across and outside the organization. The shift to a digital operating model requires understanding, engagement and commitment at the senior leadership levels, along with the strategic programs and change structure and operational reset that would accompany any other enterprise-wide transformation. So, why should organizations even bother to make such a dramatic transformation? Some argue that a fully digital approach interrupts traditional streams of revenue and profitabil- ity, and is simply the only way to stay in the game. In many cases, however, being digital is also a path to customer loyalty and trust and, thus, higher revenues, better reputation and higher employee satisfaction. As evidenced by our own work and other market studies, companies can realize bottom-line improvements even when taking initial steps into digital approaches. But while such forays can help attract digitally savvy spenders, these same customers will also be the first to leave if they bump into limits in digital capabilities. To maintain the momentum and establish themselves in the new digital economy, organizations would do best to go the full distance on the digital journey.
  22. 22. 22 “Being” Digital: One Company’s Lessons By William Shea & Jagan Ramachandran Quick Take Defining a digital strategy, prioritizing invest- ments and designing a roadmap are the first steps toward digital transformation. However, as one organization is finding, truly being digital requires an even deeper understanding of how digital initiatives will affect business operations. We are working with a healthcare payer that is shifting its focus from marketing health insurance policies to employer groups, to selling policies directly to consumers via online marketplaces. Business leaders are keenly aware that delivering compellingly re- imagined digital experiences will be critical to gaining share in this highly competitive market segment. We initially worked with the organization to define and prioritize the key administrative and clinical capabilities it needed to deliver via digital channels and jointly develop a robust technology roadmap. Knowing that digital transformation goes well beyond IT, and requires significant business and operating model change, we also enabled the company with strong change management capabilities and organizational design acumen, both of which are foundational for being digital. Like other healthcare payers, our client is finding it must concurrently address the following critical factors to deliver on its digital agenda: OO Institute strong digital governance: As is often the case, our client’s initial investments in digital capabilities were ad hoc. Business leaders often bought, built and deployed digital assets as disparate point solutions without an overarching governance or maintenance strategy. The company risked creating an amalgam of “shiny new objects” that would not deliver on its overall objective of creating a unified consumer experience. An early lesson learned was to establish a digital owner, or chief digital officer, as well as a supporting strategy office. Now in place, this governance team vets all key initiatives and programs related to digital capabilities to head off incongrui- ties. Doing so enables the health payer to optimize its digital investments, ensure organizational alignment and deliver a seamless user experience. OO Create a culture of innovation: “Being digital” requires organizational change that spans both business and IT, making it imperative to continuously iterate, prototype, fail-fast and try again. It is not a one-and-done type of investment. Successful companies must launch new products and services quickly. Our client has realized that embedding innovation into its business culture, as well as rewarding innovators, are key factors to succeeding in the new digital economy. Institutionalizing innovation has required the healthcare payer to consider investing in in-house innovation labs, hackathons and shark tanks, as well as new ways of opening up its data to external application developers. OO Take a platform-based approach: The organization quickly discovered the impos- sibility of “out-innovating” the market, thanks to the explosion of healthcare venture capital creating a frenzy of new developments. The business needed a way to harness best-of-breed innovation from the marketplace while still control- ling the end-to-end customer experience. As a result, a platform-based approach to digitization is underway. Standard frameworks for digital platforms that are emerging in healthcare typically consist of four layers: a foundational layer that includes the systems of record,
  23. 23. Cognizanti • 23 a data integration layer that supports an intelligence layer, topped off by the experience and engagement layer. Using this platform-based approach, our client will be able to plug the best commercially available innovations into the experience layer, while capturing and exploiting the data needed to optimize the end-to-end customer journey. OO Increase IT responsiveness: This healthcare player realized early on that traditional software development lifecycle processes cannot keep up with the speed of digital business. The company realized it needed to master the art of agile software delivery to support the rapid releases and frequent enhance- ments required by the highly competitive healthcare marketplace. Equally critical is the need to understand new ways of organizing IT develop- ment operations, such as DevOps, which involves cross-departmental integration and iterative collaboration between devel- opment teams and business operations. Digital initiatives, even seemingly simple ones, also require new types of IT leadership and skills. Investing in training and/or hiring new categories of talent, such as data scientists or human-centered experience designers, must be part of the roadmap from day one. As this organization has learned, there is no single playbook for being digital. Each health plan, and every company in every market, must understand its position on the digital maturity continuum (see Figure 2, page 21) and invest and move forward accordingly. That said, there is an ever-increasing set of best practices and lessons learned that organizations and digital integrators can tap to better navigate the shift to digital business models. Authors William “Bill” Shea is a Vice-President within Cognizant Business Consulting’s Healthcare Practice. He has over 25 years of experience in management consulting, practice development and project management in the health industry across the payer, purchaser and provider markets. Bill has significant experience in health plan strategy and operations in the areas of medical management, claims management, product development and digital transformation. He can be reached at William.Shea@cognizant.com. Jagan Ramachandran is a Director within Cognizant Business Consulting’s Healthcare Practice. He has over 17 years of experience in management consulting, technology strategy, practice development and project management across industries. Jagan focuses on health plan transformation in the areas of consumerism, digital transformation, public exchanges, private exchanges and core administration modernization across nationals, “Blues” and regional plans. He can be reached at Jagannathan.Ramachandran@cognizant.com.
  24. 24. 24 Authors Rob Asen leads Cognizant Business Consulting’s North American Strategy & Transformation Practice. His primary areas of client service include CIO advisory, the digital IT organization, M&A/post-merger integra- tion and business/IT transformation, focused on delivering measurable client business value. Over his 25-year career, Rob has led multiple client programs with over $100 million budget, served as advisor to IT leaders and organizations, more recently as related to the digital mandate, and led varied industry and technology strategy consulting practices on a national scale. Rob received his bachelor’s and master’s degrees in computer science from the University at Albany (SUNY). He can be reached at Robert.Asen@cognizant.com | LinkedIn: https://www.linkedin.com/in/robasen. Ted Shelton is a Vice-President with Cognizant Digital Works. He leads cross-disciplinary teams of technolo- gists, strategists and designers in delivering digital innovation projects across multiple industries, including retail, consumer goods, travel, hospitality, energy, utilities, manufacturing and logistics. Prior to his 11 years in management consulting, Ted served in leadership roles in both public and private companies in the technology and Internet sector. Ted received his bachelor’s degree from the University of Chicago. He can be reached at Ted.Shelton@cognizant.com | LinkedIn: https://www.linkedin.com/in/tshelton. Burkhard Blechschmidt is a Senior Director with Cognizant Business Consulting’s Strategy & Transformation Practice, where he leads initiatives in the areas of digital business strategy and innovation, transformation and business model innovation, mainly in the telecommunications and media, energy and manufacturing sectors. Burkhard is also working with clients on blockchain-based business model innovation, such as how smart contracts can enable the Internet of Things. Burkhard studied at HEC, Paris and the University of Cologne and holds a master’s in business administration and economics. He can be reached at Burkhard.Blech- schmidt@cognizant.com | Linkedin: https://www.linkedin.com/in/bblechschmidt. Acknowledgments The authors would like to acknowledge the thoughtful contributions of Uma Kasoji, a Director within Cognizant Business Consulting. Footnotes 1 Grammy Awards, Feb 15, 2016. 2 “Finding Your Digital Sweet Spot,” McKinsey & Co., November 2013, http://www.mckinsey. com/business-functions/business-technology/our-insights/finding-your-digital-sweet-spot. 3 “Social Physics Can Change Your Company (and the World),” Harvard Business Review, https://hbr.org/2014/04/social-physics-can-change-your-company-and-the-world/. 4 Blockchain – the underlying technology to Bitcoin – is a distributed public ledger of verified transaction records that is publically available (thus transparent) and secured through cryp- tography. It is an open, searchable, easily-verified record that ensures the integrity, indelibility and sequence of each data entry. 5 Malcolm Frank, “Don’t Get SMACK’ed: How Social, Mobile, Analytics and Cloud Tech- nologies Are Reshaping the Enterprise,” Cognizant Technology Solutions, November 2012, http://www.cognizant.com/InsightsWhitepapers/dont-get-smacked.pdf. 6 “Overcoming Ongoing Digital Transformational Challenges with a Microservices Architec- ture,” Cognizant Technology Solutions, November 2015, http://www.cognizant.com/Insight- sWhitepapers/Overcoming-Ongoing-Digital-Transformational-Challenges-with-a-Microser- vices-Architecture-codex1598.pdf.
  25. 25. Cognizanti • 25
  26. 26. Cognizanti • 27Cognizanti • 27 Jumping on the Gig Economy By Gary Beach Commentary As demand for digital talent reaches a crescendo, CIOs are increasingly embracing an Uber-like approach to filling key technical roles throughout their organizations. If you’ve ever used Uber, you’ve already experienced a model that is poised to redefine the very nature of work across disciplines, including IT. The ride-sharing service not only provides a new approach to transportation but also restructures the employer/employee relationship – a transformation so disruptive that ignoring it puts businesses at competi- tive risk. This trend is particularly relevant to participants in the thriving global economy, in which “talentism” is the new capitalism.1 This movement even comes with a popular moniker: “the gig economy.” The phrase might at first sound like a benign term that conjures up images of IT workers whimsi- cally hopping from one project to another, deciding when and where to work, and more focused on enjoying work/life balance than receiving a regular paycheck. But on closer inspection, there’s far more going on, especially in light of the gig, or contingent, economy’s rapid emergence alongside what the World Economic Forum (WEF) calls “the fourth industrial revolution.” In the WEF’s view, the fourth industrial revolution is a global phenomenon that builds on and accelerates the ongoing digital revolution by blending the physical and virtual worlds, adding incredible advances in artificial intelligence, automation and machine/deep learning to the simmering business-technology mix. In fact, the contingent economy represents an entirely new way of attracting and retaining highly sought-after IT talent – as long as IT organizations choose talent wisely, on-board effectively and protect IP where need be. Work: Historical Consequences, Future Implications When I read a recently published WEF manifesto on this topic, entitled “The Future of Jobs,”2 I had to double-check my eyeglasses: At 400 surveyed companies, CEOs expect to eliminate seven million jobs – or 54% of their total payrolls – within the next four years. Fortunately, they also said they expect to create two million additional jobs over that time, mostly in science and engineering positions. While eye-popping, these seismic changes have been a long time in the making. In the mainframe/minicomputer era of the 1950s and 1960s, tech workers were full-time employees, paid a salary, benefits and often a pension. By the late 1970s, the move to industrial-strength PCs and local-area networks caused businesses to augment full-time staff with IT professionals employed by value-added resellers who better understood the vast business implications of these seemingly toy-like new technologies. As tech infrastructures expanded in the 1980s to include distributed networks of mainframes, midrange and client/server systems, payrolls swelled accordingly. To counter rising costs, and focus on core business capabilities, companies such as
  27. 27. Eastman Kodak in 1989 embraced a bold new employment model for IT that entailed the wholesale sourcing of talent. Meanwhile, concerns about rewriting billions of lines of aging computer code for Y2K compliance introduced yet another classifica- tion of IT worker in the mid-1990s: those employed by global services providers. After that challenge was met successfully, many cor- porations expanded their arrangements with sourcing companies to include e-business and strategic consulting assignments. Today’s IT Talent Mandate This brings us back to 2016, an era in which a total of 67 companies reportedly account for 99% of the tech market’s total value. That’s a major departure from 30 years ago, when industry-compatible technology originated primarily from one company – IBM – representing 95% of the market’s value. While competition is good for customers, it also translates into incredible complexity for frontline tech workers tasked with deploying, connecting and securing cloud, big data, analytics and mobile Internet projects. All that complexity comes with a silver lining for IT workers: strong demand for their skills. According to Dice.com, an IT career website, the search for highly skilled tech talent will be a top hiring priority in 2016, with a record 78% of hiring managers anticipating more hiring in the first half of this year vs. the second half of 2015. A total of 71% of companies are looking to add to their tech teams by 11% or more in the first six months of 2016.3 That high demand is the prime motivational force leading to the gig economy. In its most recent contingent workforce study, Ardent Partners reports that 95% of U.S. corpora- tions perceive contingent workers to be a key element of doing business, and that by 2017, these workers will account for 25% of the IT workforce.4 As estimated by Edelman Berland, a global market research firm, the contingent workforce is now 53.7 million people strong in the U.S. alone (see Figure 1).5 It is such a key component of today’s labor market that Five Contingent Worker Types The U.S. contingent workforce can be categorized into five primary segments. Source: 2015 online survey by Edelman Berland of 7,107 U.S. workers, of whom 2,429 were freelancers. Figure 1 5% 26% Diversified Workers (Balance multiple assignments) Business Owners (Employ one or more contingent workers) 9% Moonlighters (Fully employed but perform an additional job after work hours) 25% Temporary Workers (Assigned out by employment firms) 36% Independent Contractors (Commit to one job at a time) (Due to rounding, percentages add up to more than 100%.) 28
  28. 28. Cognizanti • 29Cognizanti • 29 the U.S. Department of Labor will begin to gather and report official data on its size in its 2017 “Current Population Survey.” This is a critical development because it will give federal and state lawmakers access to “official” information on the size of this emerging workforce, as well as the data needed to craft policy to guide its development. According to the CIO Executive Council’s “IT Talent Assessment Study,” 2016 will be a good year for contingent/gig workers.6 When the council surveyed CIOs about their hiring projections for the next six months, 45% reported plans to hire contingent workers with specific skills to work on project-based assignments. In terms of which projects and skills will be in demand for contingent workers, a review of job data from Foote Partners LLC offers some visibility and insight, naming enterprise architects, data architects, big data/data management experts and cyber security pro- fessionals, in that order.7 Robert Half Inter- national adds wireless network engineers and mobile application developers to the list.8 Virtues, Vices of the Gig Economy Ardent Partners advises CIOs to tap the brakes before rushing into a contingent workforce model. Its study reveals several concerns, including a lack of visibility and intelligence into the ultimate ramifications of this approach, the difficulty of fully assessing and verifying a contingent workers skill set, the need to craft realistic budget estimates, and the overwhelming volumes of federal and state labor guidelines that come with employing contingent workers. The most difficult challenge CIOs face in onboarding contingent workers is intellec- tual property protection. As Foote Partners reports, CIOs have a fiduciary responsibility to protect confidential product and process information, “which you don’t want walking out the door with the contingent worker.” On the other hand, Foote Partners says, “contingent workers with the right skills and talent experience can greatly contribute to the creation of intellectual property.” Smart companies balance these risk-reward IP issues by requiring all contingent workers to sign a “work made for hire” contract that ensures the company, not the worker, owns the IP of the work being performed and that the firm is notarized as the author and automatic copyright owner of the work. Many also have crafted a customized training course on IP property ownership and confi- dentiality and require all contingent workers to take the course before starting work. Get Ready to Gig Not only are most CIOs on the gig economy bus, but some are actually driving it. In my recent travels and discussions with CIOs, IT leaders are well beyond the experimentation phase. By a wide margin, they are engaging contingent workers on high-value tasks, such as mobile application development, cloud- managed services and information security. Only one CIO mentioned low-level develop- ment work. Interestingly, CIOs are not leveraging the gig economy with the goal of balancing their budgets. As one told me at a recent CIO confab, “Many IT executives mistakenly think cost savings is the primary driver of using contingent workers. But the project prepara- tion, detailed scope, design and documenta- tion costs associated with contingent workers largely offset any potential cost savings. It is much more about having access to the best talent than trying to save a few bucks.” Surprisingly, intellectual property protection was not a primary concern for the CIOs with whom I spoke. One said, “IP is not a big deal. It is rather straightforward, and in fact, most contingent workers are quite flexible and willingly sign the necessary documents.” Contingent workers typically report directly to the manager responsible for the project, CIOs told me. Several mentioned the silver lining that contingent workers form a solid talent pipeline and are sometimes eventually hired into full-time positions.
  29. 29. 30 Footnotes 1 Klaus Schwab, “The End of Capitalism – So What’s Next?” The Huffington Post, April 4, 2012, http://www.huffingtonpost.com/klaus-schwab/end-of-capitalism----_b_1423311.html. 2 In its “The Future of Jobs” report, The World Economic Forum postulated that the fourth industrial revolution would cause widespread disruption not only to business models but also to labor markets over the next five years, with enormous change predicted in the skill sets needed to thrive in the new landscape. See more at: http://www.weforum.org/reports/the- future-of-jobs. 3 “December 2015: Special Report, Hiring Survey,” Dice.com, http://media.dice.com/report/december-2015-special-report-hiring-survey/. 4 “The State of Contingent Workforce Management 2015-2016,” Ardent Partners, http:// ardentpartners.com/2014/08/the-state-of-contingent-workforce-management-a-guidebook- for-2015/. 5 “Freelancing in America 2015: A National Survey of the New Workforce,” Edelman Berland, 2015, http://www.slideshare.net/upwork/2015-us-freelancer-survey-53166722. 6 “IT Talent Decoded,” CIO Executive Council, 2015, https://council.cio.com/event/it-talent-decoded/. 7 “2016 IT Skills Demand and Pay Trends Report,” Foote Partners LLC, 2016, http://www.footepartners.com/2012TrendReports.htm. 8 “2015 Salary Guide for Technology Professionals,” Robert Half Technology, 2015, https://www.cs.utexas.edu/~cannata/dbms/web-pages/Class%20Notes/03%20Relational%20 Modeling/03%20RHT_2015_salary-guide.pdf. Author Gary Beach is the Publisher Emeritus of CIO magazine. He is also a guest columnist for The Wall Street Journal and author of the best-selling book The U.S. Technology Skills Gap. He can be reached at Garybeachcio@gmail.com and on Twitter @gbeachcio. And one thing is sure: CIOs don’t see the trend ending any time soon. Those who par- ticipate in the gig economy said contingent workers comprise roughly 20% of their IT staff, and could reach an even split by the end of the decade. Further, gig workers seem to like the work arrangement. According to the reports that I’ve read, nearly 90% of individuals who have completed at least one contingent project claim they will never go back to working full-time for one company. The schedule flex- ibility, passion to work on what they want to work on and ability to learn new skills are the most cited reasons. For me, the contingent/gig workforce has a more interesting moniker. It is nothing less than the “uberization” of IT work, and taking it for a test drive in the second half of 2016 would be a smart thing to do. Happy ride- sharing!
  30. 30. Cognizanti • 31
  31. 31. Intelligent Automation: Where We Stand — and Where We’re Going By Matthew Smith Bots at the Gate By seeing intelligent automation through a ‘do, think, learn’ and ultimately ‘adapt’ framework, businesses can begin benefiting from this powerful set of technologies now. Ever since the first mainframes were installed, automation has been a hot topic in the business world and a source of fascination in the public imagination. The focus has shifted over the decades, from automation of tasks, to data center operations, to entire processes. In 2011, robotic process automation (RPA) officially claimed front and center of the business stage and quickly became a dominant topic for industry observers and participants alike. Across Twitter, blogs and other social media, the RPA story caught fire, and an array of automation experts appeared overnight, ready to help companies reap the benefits of this “newly discovered” technology. The idea was compelling: non-programmers able to hard-code business rules into software that could be triggered by particular events to execute a computer-based process previously performed by a human. But as has often been the case in automation’s rich history, opinion was divided. While some in IT dubbed it as just “macros on steroids,” others foresaw the end of the workforce, and civilization, as we know it. Little wonder, then, that many today are questioning where society and business currently stand – and where we’re going – with automation, especially with related advanced technologies like natural language processing, machine learning and other cognitive computing capabilities appearing on the scene. No matter which perspective you take, the fact is that forward-thinking businesses are taking advantage of RPA and advanced forms of intelligent automation – right now – that will result in step-changes in their performance, agility and competitive capabilities. We believe that the use of intel- ligent automation will ultimately elevate the human role in operations by enabling Cognizanti • 33
  32. 32. workers to emphasize their uniquely human capabilities. The need for business leaders to understand the real opportunities and chart the best path forward is more of a priority than ever. In actuality, it’s much more informative to predict not the faraway future of automation but what will happen in a mere 12 months from now. That’s why we’ve set out to consider the state of automation – and specifically intelligent software automation – by the summer of 2017, just three years short of the journey to 2020. Introducing Systems that Do, Think and Learn In our estimation, RPA is vitally important to understand, as it’s the starting point for what we see as the evolution of automation, from systems that “do,” to systems that “think,” to systems that “learn” and, ultimately, “adapt” (see Quick Take, next page). Organizations today are investing much time and effort in the first category, of which RPA is a great example. Systems that Do It’s true that RPA saw its share of hype, extreme expectations and undue concerns, with claims it would cut delivery costs in half, leave workers without jobs and kill off the sourcing industry altogether. Today the hype continues, with a recent study proclaim- ing, “Software Robots Can Reduce Operating Costs by 90%.”1 But as with most over-hyped technologies, the reality is somewhere in the middle. Without getting overly technical, automating processes with most RPA tools is more like creating traditional flowcharts than writing code, especially when screen and keystroke recorders are employed to make it even easier. Once built and tested, libraries of automated tasks can easily be reused or quickly customized to make future automa- tions go faster. Meanwhile, teams of “virtual RPA workers” can be scaled up or down instantaneously or, even better, autonomous- ly, as task volumes ebb and flow. Business tasks ideal for RPA include loan application processes, claims adjudication, accounts payable and receivable, invoice reconciliation, data entry/extraction and report generation. Essentially, any rules- based, multi-application activity is likely to be a viable RPA candidate. While RPA has yet to live up to the hype surrounding it, it is far more flexible and secure than macros are, scales quickly and is relatively low-cost compared with tradi- tional business process management systems. Business users with minimal development skills can automate many types of work processes in just weeks or a couple of months at most. Getting the same thing done using traditional automation technologies, such as business process management suites, custom APIs or even complex macros, could take overloaded IT teams multiple quarters to complete, assuming they could even get the project funded and scheduled. Essentially, RPA defines the first stage – the “do” stage – of where we are with automation today. In some ways, it’s a modest advance- ment: While the technology is neither complex nor difficult to master, it is taking organizations far more time to reach RPA scale than was expected. There are several reasons for this, as getting RPA right for most companies means understanding the automation vendor landscape, reviewing and prioritizing processes, launching pilots and proofs of concept and, finally, determining the ideal model that will best support them in the long term. Gradually, however, the early adopters are creating lessons-learned for others to follow, and best practices are beginning to emerge. The other change that will accelerate RPA adoption is the shift by many full-service providers to deliver more industry-oriented offerings tailored to the unique needs of sectors such as banking, healthcare, life sciences, insurance, etc. Other provider changes will be the introduction of more “out of the box” solutions and even automa- tion-as-a-service – all of which require less customization and implementation time than do-it-yourself RPA. 34
  33. 33. Cognizanti • 35 Illuminating the Automation Continuum Quick Take ADVANCED STANDARD Deep Learning Artificial Intelligence IoT & Smart Devices Cognitive Computing Machine Learning Sentiment Analysis Autonomic Automation IT Process Automation Natural Language Processing Smart APIs Robotic Process Automation Data Collection/ Data Preparation Speech-to-Text Conversion Refers to software that can operate more dynamically, making decisions autonomously when variances are encountered. Example processes: ■ Service desk incident resolution ■ Complaint management and resolution ■ Network security management ■ Customer service and support Corresponds with software that replicates repetitive, rules-based human actions. Example processes: ■ Claims processing ■ Accounts payable/receivable ■ Record or account data reconciliations ■ Data consolidation/validation Systems that Learn Systems that Think Systems that Do Applies to software that executes highly dynamic, non-rules-based processes, and can make optimal adjustments when variables change. This category will ultimately evolve to "systems that adapt," enabling a rich partnership between humans and software bots. Example processes: ■ Prescriptive pricing engines ■ Virtual service agents services ■ Retail engagement systems
  34. 34. 36 Systems that Think While organizations are investing much time and effort into understanding and applying “systems that do,” the real excitement is around what’s coming next, as systems that “think” and “learn” become more prevalent. Whereas RPA systems can work only with structured inputs and hard-coded business rules, the next level of automation – systems that think – are able to execute processes much more dynamically than the first horizon of automation technologies. The big advantage with automation tech- nologies that think is the introduction of logic, which allows these programs to make decisions autonomously when they encounter exceptions or other variances in the processes they execute. If you look at IT service automation as an example, these systems can analyze a user-gen- erated request or trouble ticket for keywords or other triggers, and then based on embedded algorithms and logic, they can make decisions about prioritizing and addressing each case. Even better, their performance improves over time as they develop comprehensive histories of resolution data, which they can apply to improve future decision-making. These thinking systems deal far more effectively with less defined processes and unstructured data, and in this way they differ from RPA and other systems that “do,” which operate best with defined, rules-based processes. Natural language processing (NLP) is another example of an automation technology that thinks. NLP is a fast-evolving form of software automation that can interpret spoken or written communication and translate it into executable actions to be taken by the system. Smartphones increasingly rely on NLP for hands-free use, and call centers increas- ingly deploy NLP-based automated agents to help them handle more calls with greater efficiency, scale and consistency. Systems that Learn Looking at the third horizon in our intel- ligent automation continuum – systems that learn – we see a range of fast-evolving technologies that are characterized by their ability to analyze vast amounts of dynamic and unstructured input, as well as execute processes that are highly dynamic and non-rules-based. As an example, machine learning improves the diagnostic capabilities of medical imaging systems, enables online retailers to create highly-individualized catalogs and enhances the ability of software companies to test for security vulnerabilities in future application releases. These learning systems are also adaptive, in the sense that they can apply one set of rules in one situation and then make optimal adjustments when variables change, such as location, resource availability or the presence of suspicious activity. In the enterprise world, imagine systems that learn running in tandem with work conducted by research and development teams, sales organizations, manufacturing and logistics operations, or customer service departments. Data-intensive processes and decisions predicated on understanding several complex variables and large volumes of information could move at machine speed and produce far more accurate, reliable and timely results. The impact – on everything from financial The big advantage with systems that think is the introduction of logic, which allows these programs to make decisions autonomously when they encounter exceptions or other variances in the processes they execute.
  35. 35. Cognizanti • 37 trading systems, to real-time pricing engines, to patient care, to completely individualized insurance programs – is enormous, and is just beginning to be recognized by early adopters. What is most important to understand in terms of the intelligent automation continuum is that every organization has a vast opportunity to apply all the technologies of do, think and learn to improve business processes, accelerate outcomes, increase data quality and enable powerful and predictive analytics. Even more powerful than this digitization of work is the ability of these technologies to elevate the human role in operations. People are now more empowered than ever to do what we do well: think creatively, problem-solve, prioritize and interact with clients, partners and coworkers in smarter, more productive ways. Automation Circa 2017 By 2017, here’s where we believe organiza- tions will be, in terms of their adoption of intelligent automation: OO Automate first. Rather than looking at wholesale system changes, process reen- gineering or complex studies, companies will realize that intelligent automation can be tried, tested and scaled in very short cycles. They will choose to automate first and begin capturing the benefits right away, while in parallel taking the time to consider the costlier and more complex approaches to creating efficiency, such as rebuilding or replacing underlying systems, developing new applications and redesign- ing end-to-end processes. OO Automate ambitiously. Intelligent automation will span many technology approaches and address a wide variety of process challenges, from low-volume to high, simple to very complex, structured to unstructured, and rules-based to dynamic. Companies will take a multidimen- sional approach to applying intelligent automation and will apply it ambitiously and in parallel to back-, middle- and front- office processes. OO Automate with purpose. The ability for intelligent automation to drive new types of outcomes will be well understood by mid-2017. We already see evidence of this as existing manual processes are reborn with automation and wend their way into the market. Well-known use cases now exist in areas such as loan handling, claims processing, order management, invoice rec- onciliation, service desk event management and others for which automation has dra- matically reduced cycle times, error rates, cost per transaction and data quality issues. That awareness and insight will inform the benchmarks by which implementation success will be determined, rendering the incremental successes delivered today by “systems that do” inadequate. As time goes on, we expect embedded intelligence to become table stakes, even in consumer technologies. Imagine your cable TV set-top box without DVR or your smartphone without a voice-activated personal assistant. Expect similar transitions to occur in automation as today’s “systems that do” vendors build or buy their way to smarter technologies. This change will make implementations faster and easier, extend applicability to more dynamic processes and improve outcomes by creating fewer exceptions, improving output data and further compressing cycle times. Systems that Adapt We also expect the automation continuum to take on a new dimension, which we call “systems that adapt.” As the technolo- gies that enable intelligence become more pervasive across the ecosystem, the “systems Data-intensive processes and decisions could move at machine speed and produce far more accurate, reliable and timely results.
  36. 36. 38 that do” horizon will become narrower and less useful. “Systems that think” will become the entry tier as learning systems become mainstream. By mid-2017, the do-think-learn model will shift to think-learn-adapt, as the current systems that learn gain additional self- awareness and begin to apply that learning to provide smarter, more effective outcomes. Systems that adapt will be characterized by their ability to modify themselves or optimize performance depending on changes to their environment; divert or defend themselves from security threats; and interact more seamlessly with other systems and the people they serve and support. The adaptive realm will see an even greater degree of interaction and partner- ship between humans and software “robots” that augment our work and personal lives. Starting Your Automation Journey Shifting back to today, business leaders have no choice but to embrace automation, as it is already playing a role in their organization’s future. Taking a wait-and-see stance is not an option when systems that do, think and learn are already fast at work helping competi- tors, markets and whole industries reposition themselves for the “fourth industrial revolution” now upon us.2 To help chart their path forward, organizations should consider three different approaches to moving toward adopting intelligent automation. OO Think big, scale fast: With this approach, organizations identify automation as a top strategic initiative across their entire enterprise. They appoint an experienced executive to assume the role of automation leader, with the responsibility of accelerat- ing the adoption of intelligent automation simultaneously across both IT and business operations. A life sciences organization we work with has taken this approach; the company has established a joint internal/ external team of automation experts but plans to ultimately formalize its own internal automation practice that is capable of moving at the speed and coverage the business believes will be necessary. The team first prioritized just three unique processes that allowed the organization to begin developing experience in several different “do, think and learn” technology categories. The processes they chose – complaint management, invoice processing and report generation – allowed them to explore first-hand the capabilities of RPA, natural language processing, machine learning and intelligent image conversion. Based on those early learnings, the team has now developed an automation roadmap for the next 12 months that will encompass more than three dozen process areas across five different functions. OO A winning partnership: No organization has the capacity to learn about, absorb and manage all things automation-related. Businesses will need strong partners that can help them quickly assess and take advantage of potentially game-changing but little-known intelligent automation technologies, often offered by small, emerging vendors. We worked with a multinational financial services company to deploy an intelligent automation system across large-volume, rote and rules-based processes in its market research and supply chain operations. We benchmarked the vendor’s technology, validated the product’s capabilities and then supported the design, testing and deployment of the automated solution into the client’s operations. In one process, post-automation cycle times decreased from a 15-minute average to 30 Business leaders have no choice but to embrace automation, as it is already playing a role in their organization’s future.
  37. 37. Cognizanti • 39 Footnotes 1 “Software Robots Can Reduce Operating Costs by 90%,” PR Newswire, Feb. 9, 2016, http://www.prnewswire.com/news-releases/software-robots-can-reduce-operating-costs- by-90-300217347.html. 2 Klaus Schwab, “The Fourth Industrial Revoluion,” World Economic Forum, http://www.weforum.org/pages/the-fourth-industrial-revolution-by-klaus-schwab. Author Matthew Smith leads the Automation Venture for Cognizant’s Emerging Business Accelerator organiza- tion. His responsibilities include automation strategy, enablement and market communications. In this role, Matt works closely with Cognizant internal automation and related technology practices, client-facing teams and leading external providers of automation, AI and other cognitive technologies. Matt has a bachelor’s in business administration from Stetson University. He can be reached at Matthew.Smith@cognizant.com. Acknowledgments This article would not have been possible without the research and writing contributions of Vivek Asija, a Product Marketing Director within Cognizant’s Emerging Business Accelerator. He can be reached at Vivek.Asija@cognizant.com. seconds. In the other, throughput increased by 50%, while required full-time equiva- lents (FTE) decreased by 72%. By leveraging a partner’s industry expertise and specific knowledge of the company’s operations, processes and systems, businesses can reduce the risk of integrating innovative technologies into their environment. OO Automation on-demand: Some organizations have no intention of becoming automation experts but still want the benefits provided by intelligent automation. We worked with a healthcare payer to implement an as-a-service approach to quickly and accurately process out-of-network claims. The technology in this case is our intelligent automation platform with “do” and “think” capabilities that can perform straightforward process automation, as well as apply intelligent algorithms for handling exceptions based on analyzing past transaction data. In just weeks, the automated claims system was in place, and the intelligent agents eliminated a backlog of 8,000 claims in just five days, at 99% first-pass accuracy. Today, the solution handles every out- of-network claim for this provider. The always-available automated agents not only determine who should be reimbursed but also complete all necessary documentation to ensure the health plan pays the right party for each and every claim. Advancing the Journey The promise of intelligent automation is real, and it’s here now. Business leaders should get started on taking the aforementioned steps and begin building plans to understand current and future opportunities and chart a path forward. It’s important to keep in mind that while the progression from “do, think, learn” and ultimately “adapt” has evolved over time, the entire continuum will play an important role in new digital delivery, operational and human capital management models, and organizations should be prepared to adjust and evolve their automation ecosystem. Organizations that get started on the automation journey will soon experience the benefits of process acceleration, greater efficiency, quality gains and optimized work teams, and begin collaborating, creating and improving results like never before.
  38. 38. Laying the Groundwork for a Platform Business By Dharmesh Mistry and Stan Iyer Foundational Technologies By building, buying or plugging into emerging business-technology platforms, organizations can discover new forms of value in the digital era. Here’s what enterprises need to know to create a foundation for platform success. Not long ago, “doing business” was a fairly straightforward concept, largely revolving around the physical exchange of tangible goods and services for payment, along with pre- and post-purchase services. In today’s digital economy, however, the most successful organizations are tapping into entirely new forms of value creation and monetization that threaten to make traditional approaches to business obsolete. This new way of doing business is premised on the formation of open and flexible digital ecosystems – or “platforms” – that enable new insights, relationships, partnerships and marketplaces, using the power of data and process digitization. In simple terms, plat- form-based business models are characterized by the following: OO A market-specific, business function- specific or cross-industry ecosystem of producers and consumers, beyond tradi- tional business boundaries. OO Business value generated through the digital interactions and transactions of employees, partners and customers, pertaining to either physical assets outside the platform or digital assets created on the platform (data, content, APIs and apps). Such ecosystems are cropping up all around us, whether as transaction-, content- or innovation-focused platforms.1 We have worked with several companies to establish a platform business, including a pioneering provider of financial software products (see Quick Take, page 43), a large electronics manufacturer that is monetizing its supply chain data, and a pharmaceuticals industry consortium whose platform enables col- laboration among the bio-pharma research community and provides insights to various stakeholders. (For an in-depth look at a new platform we are building for healthcare payers and providers, see page 46.) Increasingly, platform businesses are unlocking user experience insights based Cognizanti • 41
  39. 39. on transactions and content usage patterns. To enable these new types of engagements, platforms combine systems of record, systems of engagement and systems of intelligence, using recommendation engines, predictive analytics and other means to provide value to partners and participants. In this way, forward-thinking enterprises are expanding their value proposition further into the customer lifecycle, the value chain and adjacent marketplaces. (See Figure 1 for other platform business drivers.) Shaking Up the Enterprise With the emergence of the platform economy (see commentary, page 53), the question becomes how, where and when to participate, and overcome the many business- technology challenges along the way. These challenges are systemic and impact each and every platform participant. Importantly, they require individual companies – be they platform operators or plug-and-play partici- pants – to rethink their change management conventions, beginning with business mindset, and flowing through corporate culture, business processes and technology infrastructure. Rethink 1: Business Mindset Change Platform success depends on the contribution and compliance of ecosystem participants outside traditional organizational boundaries. But encouraging platform use cannot be mandate-driven; it is more a matter of inspiring and influencing participants, using continuous engagement models that keep the ecosystem vibrant. Further, some platform participants may be competitors, as well. Business leaders will need to establish a balance between their larger aspirations for the platform and competitive pressures that might exist in a subprocess layer addressed by the platform. For example, Amazon partners with logistics companies but also competes with these businesses through its logistics capability offerings. Organizations also need to rethink their business models. Compared with one-time product licensing or selling models, platforms will often drive monetization in new ways, influencing such as through “freemiums,”2 try-before-you-buy offers, subscriptions or usage-based models. Marketing, sales and business management must be empowered to 42 Platforms: The Business Drivers Figure 1 Integrate contextual data to influence buying behavior Develop targeted, granular solutions Drive value from technology investments Provide rich data insights ORGANIZATIONAL NEEDS Make costs predictable Create new business models
  40. 40. Cognizanti • 43 A Small-Business Platform Transformation Quick Take In our work with businesses in the telecom- munications and technology industries, we’ve seen organizations successfully embrace platforms after ascertaining the market challenges they faced, the opportunities inherent in digitization and the enabling digital technologies that would bridge their journey into the future. One example is a technology-savvy provider of financial and accounting software products for consumers and small businesses. Through market and customer research, the software provider realized it could serve its small-busi- ness customers better by branching into areas beyond financial management. The company also faced new, nontraditional competitors, particularly in digital payments, that had launched innovative solutions that infringed on its own offerings. These market forces led the company to change its model to a small-business-focused platform that provides an ecosystem for financial services organizations, small- business customers and other providers, based on the power of its brand, market presence and rich transaction data. Using an open platform, it enabled the integra- tion of multiple third-party products, such as Salesforce.com, to cover the entire business lifecycle, starting from the early stages of marketing. Through the platform, the company absorbs contributions from ecosystem partners – including customer management and payment capabilities – and positions itself as a provider of solutions that span the small business lifecycle. For example, banks are leveraging this platform to provide more meaningful personal finance management to consumers. Further, by analyzing the rich data contained in transactions processed by the platform, the company can form deeper insights into the needs of small businesses and provide contextual recommendations for additional attached services. For instance, depending on the complexity of inventory managed, advanced inventory management services can be recommended; similarly, specific loan products can be recommended based on the business’s financial details. As consumers derive value from these financial insights, they drive more financial transactions and actions through the platform, which increases the value of the platform. For instance, predictive analytics can help convert small-business customer insights into consumer spend insights and financial product recommendations that inform near- and long-term business strategies.
  41. 41. 44 embrace and experiment with these models, as well as address the associated revenue predictability and cash flow issues. Further, platforms become profitable only after reaching a critical threshold in the number of unique users or partners participat- ing in the ecosystem, as well as the corre- sponding monetized transaction flows. This financial reality must be supported by strong business vision and multiyear business plans. Rethink 2: Culture Change A data-driven culture is a key aspect of platform businesses, particularly in the marketing and production development realms. The business needs to develop more targeted marketing approaches with opt-in offerings, as well as customized products and services based on deep customer insights. This makes it essential for the organiza- tion to embrace frequent, objective and data-driven decision-making processes that combine science with the art of marketing and innovation. (For more on this topic, see our white paper “How to Create a Data Culture.”3 ) To that end, we have helped customers build analytics capabilities for data flowing from a variety of user touchpoints across the customer lifecycle, including awareness, engagement, trials, onboarding, usage, support and upgrade. Data is consolidated across the customer journey, including social interactions, product experiences and other platform transactions, and predictive analytics approaches are used to discover near-real-time patterns. Content platform companies, for example, can improve the content consumption experience through a better understanding of usage patterns, or even expand their base of content-provider partners. Similarly, e-commerce platform providers can design more effective loyalty and upsell/cross-sell programs through insights into customer lifetime value. Another area of culture change is agility, which requires more fluid and seamless col- laboration and communications across lines of businesses and functional groups. Key to success is a cross-functional organization that operates under a clear mandate, com- municated by a strong leader in an external or future-facing role, such as the CMO or CTO. Barriers across functional groups – market research, product development and support – must be dissolved, and quick cycles of “launch and learn” need to be established. To enable this, businesses need to build systems instru- mented for influencing user behavior, using near-real-time analytics and cross-functional response to enable the resulting insights in short cycles. Rethink 3: Business Process Change While much platform activity – the interac- tions, engagements and transactions – is intended to be conducted in a mostly digitized and automated way, internal processes remain that require human intervention, particularly to handle exceptions. This is often the case with content quality assurance workflows on consumer data platforms, and with customer onboarding touchpoints on digital advertise- ment platforms. Because manual interventions can restrict scal- ability, businesses should strive for relentless automation across the enterprise lifecycle, even Businesses need to build systems instrumented for influencing user behavior, using near-real-time analytics and cross-functional response to enable the resulting insights in short cycles.