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The Paradox of Digitization: Two Gaps to Close

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Here’s a paradox. Digitization is supposed to be an equal opportunity program to unlock productivity gains for everyone. And it may be that. But not everyone is realizing the benefits of those opportunities.

Digitization, in this sense, reflects the use of the latest digital technologies — the shiny objects of the day, whether IoT, machine learning, artificial intelligence (AI), the cloud, and so on — and its implications on:

– Changing business models (how organizations orchestrate capabilities: skill sets and technology assets) to deliver value

– Bundling and unbundling value chains, and

– Blurring industry boundaries (after all, what *is* a car any more, or, for that matter, a computing platform?)

Ok, everyone has these opportunities. But look at what’s actually happening:

– Fewer than 12 percent of businesses in any industry capture more than 85 percent of economic profit

– Well over 75 percent of digital transformation programs fail to meet their objectives (for reasons that have been covered by many, many times)

– And the topple rate, or the rate at which companies are either disappearing or falling behind their competitors, is accelerating in many industries. Did you know that over 50 percent of companies from the Fortune 500 have either gone bankrupt or been acquired over the past 15 years, and the rate is accelerating?

Let’s go back to the first point: Only a handful of businesses in any industry capture more than 85 percent of economic profit. Which means that the majority of businesses in any industry have to wrestle with the table scraps of economic profit, and growth.

So, here’s the irony: We live in an extraordinary time of rapidity of change as technologies advance, markets shift and customer expectations change.

Yet the economic profits are accruing to a smaller and smaller number of organizations as more and more topple from their once solid competitive position.

What’s going on?

The very nature of many of the new technologies — particularly machine learning and forms of AI — is making two gaps harder rather than easier to close. The explosive growth companies of today, and certainly of tomorrow, though, are figuring out how to close these gaps.

Gap 1: The Cognitive Gap. A time lag exists between when a technology is developed and when people figure out how it’s useful. The slinky, that toy enjoyed by millions, was originally developed to stabilize navel equipment on rough seas. Viagra was designed to lower blood pressure. Virtual reality was developed because the computing capabilities were there — its applications were yet unknown. Funny stories, sure. But in a world of autonomous vehicles, of self-learning systems that take on a life of their own and that leave their developers and others to catch up with the technical “affordances” they create, the gap between technical possibilities and how we wrap our heads around what the possibilities are, much less could be, is only getting wider.

Gap 2: The Execution Gap. Once we’ve made sense of what the technology can do, this second gap kicks in: “how do” — or how to embed it within our businesses to realize impact. This is often referred to as the Solow Paradox. The Nobel-winning economist, Robert Solow, once said that the computer age was everywhere except for productivity statistics, by which he described the time lag between when a technology was introduced and when businesses started to realize business value as a result.

McKinsey recently referred to “round two” of the Solow Paradox. Round one referred to technology innovation around semiconductors and resulting process improvements. Round two refers to the digital shiny objects, which means that the investments you’re making today are likely not to pay off (within any particular industry) for 10 to 20 years, on average.

So, what do you do?

First, note that these two gaps exist and are getting wider.

Second, understand what’s driving this widening of both gaps:

– The self-learning aspect of many of the technologies often outstrips the capabilities of any particular person to understand their implications.

– It takes time (“Hey, this is cool technology, but, er, what do we do with it?”)

– No technology is an island of itself. It requires a set of complementary capabilities — other technologies, services, standards, etc. — to make it useful. Think of HDTV, Rfid tags, the Hyper-loop. Anything!

– Figuring out how to fold in a new technology (and its complementary capabilities) into a business that’s already running is like that proverbial changing a wheel while the bus is moving.

Third, recognize that the high explosive growth companies of today and tomorrow have lessons you can learn from to start closing these gaps. Learning them will stress-test what you do and how you do it. The paradox of digitization is a call to action — if you want to become one of the explosive growth organizations of tomorrow.

Ralph Welborn is CEO of CapImpact, a predictive analytics and advisory firm focused on new growth models. Previous positions included CEO of an innovation technology company, where he received the European CEO award in 2016; leader of IBM’s Strategy & Transformation business in the Middle East & Africa; and senior vice president of KPMG Consulting. He is co-author with Sajan Pillai of the new book, "Topple – The End of the Firm-Based Strategy and Rise of New Models for Explosive Growth" (Greenleaf Book Group Press, May 29, 2018) describing how to look at our changed competitive landscape through the lens of business ecosystems. Learn more at www.topplebook.com or www.capimpact.com.

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