The New Patterns of Innovation
12 December, 2014 / Articles
The search for new business ideas and new business models is hit-or-miss in most corporations, despite the extraordinary pressure on executives to grow their businesses. Management scholars have considered various reasons for this failure. One well-documented explanation: Managers who are skilled at executing clearly defined strategies are ill equipped for out-of-the-box thinking. In addition, when good ideas do emerge, they’re often doomed because the company is organized to support one way of doing business and doesn’t have the processes or metrics to support a new one. That explanation, too, is well supported. Without a doubt, if you tackle business innovation systematically—rather than hoping people will get creative during an “innovation jam” or a special offsite—you improve the odds of success (and decrease the chances you’ll be left staring at a blank sheet of paper). Traditional, tested ways of framing the search for ideas exist, of course. One is competency based: It asks, How can we build on the capabilities and assets that already make us distinctive to enter new businesses and markets? Another is customer focused: What does a close study of customers’ behavior tell us about their tacit, unmet needs? A third addresses changes in the business environment: If we follow “megatrends” or other shifts to their logical conclusion, what future business opportunities will become clear?
We’d like to propose a fourth approach. It complements the existing frameworks but focuses on opportunities generated by the explosion in digital information and tools. Simply put, our approach poses this question: How can we create value for customers using data and analytic tools we own or could have access to? Over the past five years, we’ve explored that question with a broad range of IBM clients. In the course of that work, we’ve seen advances in IT facilitate the hunt for new business value in five distinct—but often overlapping—patterns. Those patterns form the basis of our framework. We believe that by examining them methodically, managers in most industries can conceive solid ideas for new businesses. (To learn about the underlying technical trends, see the sidebar “Why Are These Patterns Emerging Now?”)
None of the patterns depends on bleeding-edge technology. The first one, in fact, is very familiar: using data that physical objects now generate (or could generate) to improve a product or service or create new business value. Examples of this include smart metering of energy usage that allows utilities to optimize pricing, and devices installed in automobiles that let an insurance company know how safely someone drives. The second pattern is also familiar: digitizing physical assets. Fifteen years ago you could have read this article only in a printed magazine; now you can read it on half a dozen different digital platforms, send it to friends, and say what you think of it via social media. The third pattern is somewhat more recent: combining data within and across industries. (Here we start to enter the realm of “big data.”) An example of this would be a smart-city initiative like the one in Rio de Janeiro, where private utilities, transportation companies, and city agencies consolidate information so that they can deal with natural disasters more effectively. The fourth pattern is trading data; here, a company whose information is valuable to another company sells it, as when a cell phone service identifies traffic jams by seeing where customers in cars are slowed down and shares the information with a navigation-device company. The fifth pattern, codifying a capability, allows a company to take any process in which it is best-in-class—managing travel expenses, for instance—and sell it to other companies, using cloud computing.
