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?
The New Patterns of Innovation
Reprint: R1401G
The search for new business ideas—and models—is hit-or-miss at most firms. Tackling the problem systematically, of course, will improve your odds of success. Traditional ways of framing this search examine competencies, customer needs, and shifts in the landscape. This article proposes adding a new IT-based framework. It involves asking, How can data and analytic tools be used to create new value?
The authors have explored that question with many clients. In their work, they’ve seen IT create new value in five patterns: using data from sensors in objects to improve offerings (think smart energy meters); digitizing physical assets (such as health records); combining data within and across industries (to, say, coordinate supply chains); trading data (as mobile providers do with information on users’ whereabouts); and codifying best-in-class capabilities (such as online expense management) as services.
Drawing on examples from their own experience and their clients’, the authors walk readers through each of the five patterns and how to apply them. They also provide advice and questions that will help executives get started on their own searches.
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