The description of business operating environments as “ecosystems” was born an instant cliché. Its appeal was in the way “ecosystem” suggests a coherent, self-supporting system with a predictable logic.
Except that the natural world isn’t like that. Natural ecosystems are profligate with resources and in perpetual evolution. Existence is short. New growth happens, of course, but only because other things lie dead on the forest floor.
A natural ecosystem is anything but self-contained. Darwin spoke of a “tree of life” endlessly branching and changing. Change to the tree can be shockingly abrupt.
Big disruptions typically come from outside the existing ecosystem. The intrusion of some factor that the system does not account for—a new predator, a poison, change elsewhere—can alter everything.
A good example is what we still call “newspapers”.
It is now more than 25 years since the Internet become a consumer technology, a change that to people outside the world of computer science seemed to happen amazingly fast. A generation later newspapers are still dealing with the shock. The damage to their old ecosystem is immense. News “deserts” have appeared. Jobs—not just in newsrooms but in adjacent businesses—have experienced a great die-off. Meanwhile, invasive species have filled in gaps in the ecosystem. The decline of what might have seemed an ecological niche—local news—has made painfully clear how much the larger social ecosystem depended on it for health.
Here’s the thing: A generation ago the threat to newspapers from the blossoming Internet was immediately perceived. What happened next might be described as a failure of imagination.
Sometimes scenario planning is mistaken for the superpower of being able to see around corners. This is magical thinking. FSG scenario planners would be the first to say that the tool’s power is in the way it makes organizations alert to change and ready to embrace its opportunities and to manage its risks.
There is a vogue right now for applying Big Data predictive learning to scenario planning. The odd thing about this vogue is that data is, necessarily, backward looking. How useful would predictive learning have been for a newspaper chain in, say, 1990? The danger in such an approach is the false confidence it promotes in a system that is becoming incoherent.
There are ways to ready an organization for a future ecosystem without relying on prediction. The first is to remember that ecosystems, in the natural world and otherwise, change. All the time. They cannot be somehow perfected to a successful steady state.
Second, time and again the greatest disruption to an environment comes from some direction outside the system. Just ask radio-station owners about the invention of streaming media and what it has done to their business. This is the reason why when we build scenario “worlds” with clients they are rigorously made larger than what the client conceives as their special patch of the operating universe.
Third, think about customer pull. Future customers will live in a context different from the one they inhabit now. The further out in time we go the harder it will be to predict that context. With an expansive imagination forces for change, and the multiple ways they might play out and interact, can be explored.
Consider the fabled visit of Steve Jobs to Xerox Parc in 1979. The moral of that story is typically that Xerox was indifferent to the brilliance of what its engineers created, and that only Jobs had the foresight to see these breakthroughs for what they were. It is a story that has been debunked multiple times. What Jobs and Apple brought that was new was their imagining of a mass consumer market for Xerox’s innovations. Xerox, Jobs would say later, was a great company imaginatively constrained by its stubborn roots in the photocopier ecosystem.
Ten years ago a weak understanding of changes in its ecosystem brought Microsoft thisclose to being the next Xerox. While the rest of its world was realizing that software as a service was the future of computing CEO Steve Ballmer fought that idea for fear it would cannibalize Windows and Office—which were then the source of 80 percent of Microsoft’s revenue. Microsoft reoriented itself in time. Today its rapidly growing Intelligent Cloud segment is its largest contributor to earnings.
Alexa emerged out of Amazon’s failed effort to enter the mobile-phone business. Consumers did not like the phones but they did like the Alexa technology that emerged out of the effort to build them. Amazon was not locked into an ecosystem called “phones” in which it either succeeded or it didn’t. Its world was bigger than that. But first that expanded world had to be imagined.