Blockchain: It’s About Customers, Not Cryptocurrencies

Organizations naturally fragment into silos of focused activity. Tribes of specialized experts form, then communicate poorly among each other, even though they have the same logo on each of their office doors. Their separate streams of activity generate costly and often unhelpful streams and collections of data: separate histories of what was done by different teams at different times. Decades of progress have allowed organizations to do this more accurately, at larger scale and with nearly real-time immediacy. This kind of progress is relatively easy to achieve, measure and value. The problem: it becomes increasingly unsatisfactory to customers.

The customers, no matter how vigorously served by each of those silos, wind up feeling poorly served overall. Too often, they are forced to describe the same history in different terms to different people. Too often, their problems require “much assembly by user,” even when the pieces of the solution are being purchased from a single vendor. The problem grows worse as ecosystem offerings grow more complex.

Today, customers no longer accept this as a necessary evil. They know that they can have something better, and they vote with their wallets and go where they can get a superior experience.

Don’t just give customers what they think they want

Two massive trends are forcing customer-centered rather than product- or activity-centered behavior by organizations. These trends are also fueling rising customer expectation in both for-profit companies, and public and non-profit institutions – from health care to education to government.

First, the sheer magnitude of global capacity to connect has grown by a thousand-fold in the eighth of a century since the launch of Apple’s iPhone. Second, the aggregate power of global computation capability — not merely to record and to calculate, but increasingly to optimize and predict — has grown by comparable magnitude during that same period.

It is, therefore, time to execute on the vision offered by Peter Sondergaard (now Chairman of Denmark-based 2021.AI) when he spoke at the Gartner Symposium conference in 2015. He said that the future of fulfilling one’s customers’ desires is not to ask what they want, but to observe, measure and analyze what they seem to be trying to do.

In other words, don’t just give customers what they know they don’t have; give them what they can’t even imagine they can now readily obtain.

Dream bigger: the iPod

People stop asking for what they believe can’t be achieved. The well-balanced mind does not begin each day with a rehash of years or decades of frustrations. Rather, it thinks about incremental improvements that are practical given available time, money and talent. Offering people what they did not even imagine they could have, but what they immediately realize is what they wanted, is the playbook from which breakthroughs like Apple’s iPod emerge.

Consider, for a moment, the iPod. When Apple introduced it in 2001, the marketplace initially dismissed it as an overpriced and under-featured digital music player. The market failed to appreciate what Apple was addressing by combining simplicity of operation with the radically greater capability of Apple’s iTunes music service.

Within three years of the iPod’s introduction, the packaging of audio content for digital network download became known as a “podcast,” which word was added to the Oxford English Dictionary in 2004. That’s proof of Apple’s success in redefining audio entertainment; also a good example of Peter Drucker’s admonition in his 1973 book, Management: Tasks, Responsibilities, Practices, that “innovation is not invention: it is a term of economics rather than of technology.”

Apple was not the first to offer a digital music player, but its innovation was an enlargement of scope. It went beyond offering a product and addressed a larger customer need.

“Don’t just give customers what they know they don’t have; give them what they can’t even imagine they can now readily obtain.” Peter Coffee, VP for Strategic Research at Salesforce

Replace the old model

The enhanced computation and connection resources at hand today can be used to create new models, rather than merely improving the cost-effectiveness of the models now in place. Data, in particular, is the foundation of much value — but costs, delays, errors and lapses of governance arise from the data storage by its originators and owners in isolated databases. Limited, costly, and fragile connections are created among them to meet process and ecosystem needs.

As connection and computation become exponentially more abundant, it becomes obvious that a model of data networks — rather than data “bases” — is what we should adopt. “Distributed ledgers,” often referred to casually as “blockchains,” offer radical improvements in handling multi-party offerings of interoperating services, without reliance on a single trusted (and often rent-seeking) intermediary.

Distributed ledgers are already an example of the famous mid-1990s quote by Canadian science fiction writer William Gibson, “The future is already here. It’s just not very evenly distributed.” Blockchain services are already in use for applications ranging from payment processing to logistics management to verification of the provenance of luxury goods, resulting in a reduction of losses to counterfeiters of products ranging from handbags to prescription drugs.

With growing resources of connection and computation enabling dramatic remodeling of process, the long-awaited promises of artificial intelligence can now break out of their multi-decade cycles of hype and disappointment. Learning algorithms now have data from which to learn, without the frustrating costs and scalability limits of past approaches dependent on human “knowledge engineers.”

Its time has come

This completes the missing pieces of the picture drawn by American engineer Douglas Engelbart, who told us to prepare for “a way of life in an integrated domain where hunches, cut-and-try, intangibles, and the human ‘feel for a situation’ usefully coexist with powerful concepts, streamlined terminology and notation, sophisticated methods, and high-powered electronic aids.”

Engelbart gave us that charge in 1962. It’s time to make it happen.

Salesforce is a YPO Global Strategic Partner.

Peter Coffee


Peter Coffee, VP for Strategic Research at Salesforce, has been with the company for 12 years. He works with customers and partners on CIO strategies and emerging technology opportunities. He previously spent 18 years writing for publications including eWEEK, Computer Language and AI Expert, and worked for 10 years as an AI application analyst and desktop computing manager at The Aerospace Corporation and in project management roles for various divisions of Exxon. Coffee has lectured on innovation strategies and AI techniques at Stanford, CalTech, UCLA, Harvard Business School, and the Sloan School of Management at MIT. He advises on curriculum in analytics and “big data” initiatives for three other U.S. universities. His two published books are How to Program Java and Peter Coffee Teaches PCs; his current work appears often on the UK news site “Diginomica.” Coffee is a graduate of MIT and of the Graziadio Business School at Pepperdine University; he serves as an applicant advisor for the MIT Educational Council, and is a member of the advisory panel for the The Conference Board’s Innovation & Productivity Institute.

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