Digital Disruption Requires Digital Enterprise Transformation

Stephen DeAngelis

October 28, 2015

“The obsession with digital disruption has reached a flashpoint with the arrival of the smartphone,” writes Richard Waters (@RichardWaters), “which is the platform for an invasion of older companies’ hallowed grounds.”[1] He observes that there are any number of “entrepreneurs out to attack industries once thought immune to digital upheaval.” He continues:

“Despite this, established companies still have many advantages, says Paul Willmott, a director at McKinsey who specialises in digital transformation. These include extensive customer bases, known brands and industry knowledge, which weigh in their favour. For all that, the need to overhaul business processes, forge digital links with customers and, in some cases, recast entire revenue models can still be pressing.”

The reason companies feel pressed to transform into digital enterprises is because data is only a digitized form of the kind of information that has always been at the heart of business. “The basis of commercial enterprise is information,” writes Kenneth Cukier (@kncukier).[2] He elaborates:

“Indeed, some of the earliest forms of writing and accounting come from Sumerian merchants around 8,000 BC, who used small clay beads to denote goods for trade and later kept written records of transactions. So when we look at the role of data today, it is easy to say that not much has changed. We may collect, store and use more information — but the nature of data and its importance isn’t much different. In this view, Big Data is just a fancy term to describe how society can harness more data than ever, but it doesn’t alter the timeless fundamentals of commerce from antiquity to today. This view, however, would be terribly wrong. For lots of areas of life, when one changes the amount, one changes the form.”

One of the problems with the dotcom era, whose bubble dramatically burst early this century, was that too many start-up companies ignored sound business principles. That’s never a good idea. But the dotcom era was also a wake-up call for businesses alerting them that the landscape was forever changing. There would never again be a return to “business as usual.” Cukier asserts, “We have more information than ever. The change in scale leads to a change in state. The quantitative shift leads to a qualitative shift.” It is this qualitative shift that makes transformation into a digital enterprise an imperative. McKinsey analysts, Driek Desmet, Ewan Duncan, Jay Scanlan, and Marc Singer, insist, “Few companies need to be sold on the benefits of digitization.”[3] They continue:

“Getting the engine in place to digitize at scale is uniquely complex. Since digital touches so many parts of an organization, any large digital program requires unprecedented coordination of people, processes, and technologies. A strategy to increase revenue from high-value customer segments, for example, requires analytics-based insights into which purchasing journeys generate the most value, a clear vision and plan for how to capture that value, and technologies and tools to digitize interactions with customers. New capabilities and teams are also needed to manage and coordinate the delivery of those journeys across the organization.”

One emerging technology uniquely suited to helping companies transform into digital enterprises is cognitive computing. A good cognitive computing system can serve as a conductor for the myriad data flows that pulse through an enterprise and integrate them into single version of the truth that can be used by all departments to breakdown silos and align behind corporate goals. In Accenture’s latest technology vision entitled “From Digitally Disrupted to Digital Disrupter,” Accenture analysts state that cognitive computing will provide the “ultimate long-term solution” for many business challenges. The McKinsey analysts offer six steps that can help companies transform into digital enterprises.

 

1. Strategy and innovation — “Digital strategy is intrinsic to business strategy today. … The best digital strategies don’t rely on past analyses, but instead start fresh and carve out a vision based on where they believe value is likely to shift over the next three to five years. They assess at a granular level where value is likely to be disrupted within their own business and market, and they isolate where and how they will compete. Effective digital strategies prioritize a handful of interventions where the business can exploit significant opportunities (and divest or reduce exposure in markets where value is declining), then craft a digitally enabled business model around them.”

 

2. Customer decision journey — “Our research shows that organizations able to understand and skillfully act on complete customer journeys can reap enormous rewards: increasing customer satisfaction by up to 20 percent and revenue growth by 10 to 15 percent, and lowering the cost to serve by 15 to 20 percent. Understanding those decision journeys and the fundamentally different ways that customers behave — from evaluating products to bonding with brands — is becoming the cornerstone for successful businesses. That ability is likely to become an increasingly important differentiator, since nearly 50 percent of all business-to-business purchases will be made on digital platforms by the end of 2015, and $2 trillion in retail sales will be influenced by digital by 2016. With so much data available, companies can become much more precise in their outreach to customers. By combining deep data analysis and ethnographic research, digital leaders can identify high-value microsegments, such as new mothers with full-time jobs who primarily shop online. Understanding how these customers make decisions — how they shop, for example, or what influences them — allows digital leaders to tailor their approaches.” Cognitive computing systems are particularly adept at helping companies understand the digital path to purchase and how to improve targeted marketing.”

 

3. Process automation — “Business-process automation can result in massive competitive advantage because initial investments, when well implemented, can scale quickly without substantial additional costs. Over time, cost performance can improve by as much as 90 percent as the automation effort scales across formerly siloed functions, reducing redundant processes. New business models, in fact, are emerging as companies that create revenue from sales of physical assets evolve into service businesses that focus on data as an asset. Digitizing processes has less to do with technology and more with how companies approach development. … Becoming digital often requires reinventing the entire business process to cut out steps altogether or reduce the number of documents required.” This is another area in which cognitive computing systems shine.”

 

4. Organization — “Companies know that rigid, slow-moving models no longer cut it. The challenge is to move toward a structure that is agile, flexible, and increasingly collaborative while keeping the rest of the business running smoothly. Successful incumbents become agile by simplifying. They let structure follow strategy and align the organization around their customer objectives with a focus on fast, project-based structures owned by working groups comprising different sets of expertise, from research to marketing to finance. While companies often obsess about the ‘boxes and lines’ of organizational structure, it’s more important — and significantly more difficult — to focus on processes and capabilities.”

 

5. Technology — “Most incumbents have been through waves of IT transformation in the past and understand that overhauling legacy architecture is a multiyear process. Yet today’s fluid marketplace requires technology that can drive innovation, automation, and personalization much more quickly. So, the best are moving to a two-speed IT model that enables rapid development of customer-facing programs while evolving core systems designed for stability and high-quality data management more slowly.”

 

6. Data and analytics — “Companies that make extensive use of customer analytics see a 126 percent profit improvement over competitors. Companies that see that kind of return are adept at deciding which data to use (both inside and outside the organization), focusing the analytics on delivering on goals with clear and useful insights, and having the right capabilities and processes in place act on them. That requires people with the right kinds of skills — particularly ‘translators’ who can articulate business goals and use cases with respect to analytics requirements and turn data output into business insights. With the Internet of Things and new technology developments, analytics are opening new doors for growth.”

 

Cognitive computing systems can help a company improve performance during each of those steps. They can achieve better focus and make a company more collaborative. And, importantly, cognitive computing solutions need not replace legacy systems. In fact, more often than not, cognitive computing systems build upon and improve legacy systems. Another of the benefits of using a cognitive computing system is that both corporate objectives and tribal knowledge can be built in. That often means that human “translators” aren’t necessary in order to achieve desired results. Paul Willmott (@WillmottPaul), a director at McKinsey who specializes in digital transformation, told Waters, “A key question is where the value in digital lies. Typically, the answer involves either looking to take costs out of the supply chain or recasting customer relationships through online channels. … Incumbents may tend to favour old ways of doing things, as changes can dent profits and cause dissension. But it is better than finding the world has moved on without you.” Because cognitive computing systems can be used in so many ways, there are few areas of an organization that can’t be helped through their use and they can certainly make the transformation into a digital enterprise less painful.

 

Footnotes
[1] Richard Waters, “Transformation is crucial when digital disruption is the norm,” Financial Times, 30 September 2015.
[2] Kenneth Cukier, “Big Data and the Future of Business,” OpenMind, 23 August 2015.
[3] Driek Desmet, Ewan Duncan, Jay Scanlan, and Marc Singer, “Six building blocks for creating a high-performing digital enterprise,” Telecom, Media & High Tech Extranet, 23 September 2015 [registration required].