Horse Manure spreader photo by Don O'Brien on Flickr. Used under a Creative Commons license

Tomorrow is not like yesterday, only more so

Here is the thing about the future. Every time you look at, it changes, because you looked at it, and that changes everything else.

Cris Johnson (Nicholas Cage) in Next (2007)

Most companies’ innovation is focused on sustaining the current business model—doing what Sergio Zyman calls “selling more things to more people for more money more often more efficiently.” That’s because it’s difficult to predict the future: Without a crystal ball, “tomorrow is like yesterday, only more so” is the wisest course of action.

This ignores the discontinuities that arise in markets, which are the things that unseat giants and spawn new industries. They’re obvious in hindsight, but notoriously hard to anticipate. Now that it’s easier to experiment and prototype, and now that ideas propagate in days instead of years, discontinuities happen faster, and spread more quickly, catching companies off guard.

Discontinuities have always existed, and they tend to work in one of two ways. Either something completely new eliminates what was perceived as a huge problem, removing an entire market; or something completely new takes off because it enjoys a rebound effect in which more supply generates an even bigger demand.

Let me illustrate these two cases with a couple of examples.

Sometimes, the world fixes itself

The story of the Great Horse Manure Crisis of 1894 has been retold dozens of times as an example of why technology fixes the problems it creates. Here’s a quick recap:

As the industrial era and urbanization drove more and more people into cities, the shit piled up—literally. Horse manure lined the streets, and removing it required even more teams of horses.

the streets were “literally carpeted with a warm, brown matting . . . smelling to heaven.

Grim projections suggested that Manhattan would be neck-deep in horse excrement in just a few years, and urgent meetings among the mayors of the world saw no possible solution.

Of course, a few short years later, the personal automobile had solved the problem. Anyone building companies to remove manure was out of work, no matter how efficient they might have been. A fundamental replacement by something better eliminated the problem.

Incumbents often miss such shifts:

  • Blockbuster dominated the video rental business. But it made money from real estate, late fees, and the sale of merchandise (films, popcorn, candy.) It missed the zero-footprint, no-late-fee model that Netflix dominates—or at least, dismissed it until it was too late, partly because it didn’t realize the postal service was an efficient source of bandwidth before consumer-grade broadband was widely available. Of course, the end result was better for other reasons: nobody wanted to go to the store to rent some bits, and Netflix won. Blockbuster closed its doors.
  • Server manufacturers focusing on higher-density, more energy-efficient machines aimed at CIOs and bought by CFOs missed the market for less-reliable, pay-as-you-go cloud computing aimed at CTOs and startup founders, which Amazon Web Services targeted with amazing accuracy. As with Netflix, the end result was better for other reasons: Cloud architects found ways to stitch together dozens of unreliable, relatively slow servers into a reliable, fast computing fabric. Amazon won—today its web services division is bigger than all other players combined—and now server manufacturers are scrambling to remain relevant.

Sometimes, the consequences overwhelm the cause

On the other hand, some predictions fail because they go too well.

Early steam engines (designed by Newcomen) were less efficient than their successors (designed by Watt.) One British economist, William Stanley Jevons, hypothesized that this should extend the supply of coal as a result. But Jevons’ analysis showed the opposite: a more efficient engine resulted in greater demand, because of what was now possible. Cheaper power meant people found new uses for the thing. Abundance begets new markets.

CottonopolisCroppedThis happens often in technology adoption. In Why Things Bite Back, Edward Tenner talks about the unintended consequences of inventions. Football helmets were supposed to protect players; instead, they caused many more injuries by arming players with head-mounted weapons. The personal computer, far from ushering in the anticipated era of paperless offices, turned everyone into a desktop publisher, driving the consumption of office paper to an all-time high.

Driving adoption in unexpected ways

metcalfeIncumbents frequently miss this reversal of scarcity, which drives adoption in unexpected ways. I once spoke with Bob Metcalfe, the inventor of Ethernet, who told me, “we got the Internet exactly backwards.” He explained that, at the outset, the Internet used wireless for long distances (via satellites) and wired for local connections (CAT-5 wires or coaxial cable carrying Ethernet and Token Ring.)

But as computers became portable and smartphones added wifi, local connections became wireless; as demands for low-latency, high-bandwidth connections between countries grew and enterprises gave up their private WAN connections for Virtual Private Networks, carriers pulled fiber optic cable across the world’s oceans. (You could even argue that a huge percentage of the last decade’s revenues for companies like Cisco have been from turning the Internet around.)

Jevons’ paradox isn’t without limits, of course; while cited by proponents of supply-side, trickle-down economics, “cutting tax rates from 100% to 50% would certainly raise revenues. Cutting them from 50% to 0% would just as surely lower them,” points out Dr. Jim Barrett in a considered rebuttal of claims that cheaper energy will drive consumption.

The key is that for some innovations, there is a “rebound effect” of the efficiencies that come from reduced cost, turning, for example, the mobile phone from a tool for high-powered executives into a toy for every teenager. Anticipating which innovations will experience this kind of rebound is hard to do ahead of time.

What smart innovators do about it

Over the last year, I’ve noticed several common threads among companies who get innovation right. They break themselves into three distinct groups, focusing on three kinds of innovation.

  • 70% of resources are devoted to core, or sustaining, innovation, and Zyman’s five mores. This is innovation, but often it’s innovation to extend the life of a cash cow, erect barriers to entry, or keep margins high. This is what Clay Christensen calls Sustaining Innovation, and it’s responsible for keeping the oxygen flowing. It’s scored by traditional business metrics: return on investment, margins, revenues, and so on. It’s work done by the rank and file employees, who increasingly need to be retrained on digital marketing, experimentation, and data-driven decision making. This is when the business knows both the problem the consumer needs solved, and the way to solve it.
  • 20% of resources go to adjacent innovation. This means changing one aspect of the current business model—either the product being sold, the market to which it is sold, or the method with which value reaches the consumer. Changes are incremental, and unlikely to cannibalize the existing business. This work is done by innovation teams within the line of business, tasked specifically with finding growth opportunities. It’s scored by changes from the current business, the speed that adjacencies are tested, and growth rates. It’s more about stars and less about cash cows, and it works when the business knows the problem the consumer needs solved but not how to solve it.
  • 10% of resources go to transformative, or disruptive innovation. This is a complete rethinking of the buyer’s value network, and it might cannibalize the business if it’s successful. It’s DHL looking at 3D printing; Metlife looking at apps to become a digital curator of your online legacy; Amazon building compute services. This group is usually isolated from the existing lines of business—Apple’s new product design team; Google’s Project X team—in part because of the conflicting nature of its work. It’s scored by how many ideas have been generated, how many assumptions have been validated or repudiated, and whether a batch of early adopters has been found that can test the idea.

This is a more detailed version of the table I described in Four Things Innovators Do Differently.

Core actionOptimizing and improving the current business modelExperimenting with a new product, new market, or new methodSearching for discontinuities and inventing
Located inExisting job descriptionsInnovation teams within the business unit"Skunkworks" isolation or the CTO's office
Focus onImproving known metricsRemoving risk from possible business changesValidating assumptions and rate of discovery
If successful, lives inWithin current business unit, run by the people who made the improvementIncubated, then integrated into an existing business unit, run by othersAs new or separate entities, possibly cannibalizing existing lines of business
Problem isKnownKnownUnknown
Solution isKnownUnknownUnknown
Resources allocated70%20%10%

I’ve got plenty of other thoughts on this—what makes something disruptive; how to divide the three dimensions; innovating to stand still; and so on. It’s increasingly looking like this Tilt the Windmill thing might become a book. But in order to avoid this post becoming one too, I’ll stop here and leave those for another day.

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