Strategic Innovation and the Science of Learning

Entrepreneurship is a competence in only the rarest corporation. Pity, as its absence has led to the death of many revered companies. In an economic environment characterized by dramatic change, the ability to explore emerging opportunities by launching and learning from strategic experiments is more critical to survival than ever.

A strategic experiment is a risky new venture within an established corporation. It is a multiyear bet within a poorly defined industry that has no clear formula for making a profit. Potential customers are mere possibilities. Value propositions are guesses. And activities that lead to profitable outcomes are unclear.

Most executives who have been involved in strategic experiments agree that the key to success is learning quickly. In a race to define an emerging industry, the competitor that learns first generally wins. Unfortunately, habits embedded in the conventional planning process disable learning. A better approach, theory-focused planning, differs from traditional planning on six counts.

The Need for Strategic Innovation

In the late 1990s, Corning Inc. began to explore a possibility far beyond its existing lines of business. The strategic experiment, Corning Microarray Technologies (CMT), sought to usher in a new era in genomics research. (See “About the Research.”) DNA microarrays, glass slides with thousands of tiny DNA samples printed on their surfaces, were a key piece of experimental apparatus for measuring DNA interactions in large sample sizes. Seeking to disrupt a status quo that offered researchers a devil’s choice between time-consuming self-printing and the purchase of an expensive closed-standard system, CMT sought to introduce reliable, inexpensive microarrays as part of a new open-standard system.

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References

1. The need to reinvent strategies during times of discontinuous change has been noted in C.K. Prahalad and G. Hamel, “Competing for the Future” (Boston: Harvard Business School Press, 1994); G. Hamel, “Strategy as Revolution,” Harvard Business Review 74 (July–August 1996): 69–82; W.C. Kim and R.A. Mauborgne, “Value Innovation: The Strategic Logic of High Growth,” Harvard Business Review 75 (January–February 1997): 103–112; and C.C. Markides, “All the Right Moves: A Guide To Crafting Breakthrough Strategy” (Boston: Harvard Business School Press, 1999).

2. This definition of strategic innovation is consistent with the perspective advanced by V. Govindarajan and A.K. Gupta, “Globalization in the Digital Age,” chap. 9 in “The Quest for Global Dominance: Transforming Global Presence Into Global Competitive Advantage” (San Francisco: Jossey-Bass, 2001); and C.K. Prahalad and G. Hamel, “Competing for the Future,” Harvard Business Review 72 (July–August 1994): 122–128.

3. This observation has been made by other researchers. For example, see C.M. Christensen, “Discovering New and Emerging Markets,” chap. 7 in “The Innovator’s Dilemma: When New Technologies Cause Great Firms To Fail” (New York: Harper Business, 1997); and Z. Block and I.C. MacMillan, “Developing the Business Plan,” chap. 7 in “Corporate Venturing: Creating New Businesses Within the Firm” (Boston: Harvard Business School Press, 1993).

4. See A. Wooldridge, “A Survey of Telecommunications,” Economist, Saturday, Oct. 9, 1999, p. 1; and “Cellphone Ownership Soars,” USA Today, Friday, Aug. 2, 2002, sec. A, 1A.

5. The study of whether and how individuals or organizations can learn from experience has a long tradition in the organizational-learning literature. See, for example, D.A. Levinthal and J.G. March, “The Myopia of Learning,” Strategic Management Journal 14 (winter 1993): 95–112; B. Levitt and J.G. March, “Organizational Learning,” Annual Review of Sociology 14 (1988): 319–340; J.E. Russo and P.J.H. Shoemaker, “The Personal Challenges of Learning,” chap. 8, and “Learning in Organizations,” chap. 9, in “Winning Decisions: Getting It Right the First Time” (New York: Doubleday, 2002). However, the subject of how control systems can be improved to support learning better has not received treatment in this literature.

6. See K.A. Merchant, “Rewarding Results: Motivating Profit Center Managers” (Boston: Harvard Business School Press, 1989); and J.A. Maciariello and C.J. Kirby, “Management Control Systems: Using Adaptive Systems To Attain Control” (New York: Pearson Education, 1994).

7. This notion has also been advanced by R.G. McGrath and I.C. MacMillan, “Discovery-Driven Planning,” Harvard Business Review 73 (July–August 1995): 44–54. Theory-focused planning is based on the same premise — that conventional planning is inappropriate when more is unknown than known. However, it differs in most particulars. The discovery-driven planning approach is appropriate when the industry being entered is established, the business model well known, and the uncertainties for the venture can be reduced to identifiable operational parameters. Theory-focused planning is appropriate when the industry is emerging, the business model is experimental, and the uncertainties so great that the basic nature of the relationships between activities and outcomes is unknown.

8. See, for example, R.N. Anthony and V. Govindarajan, “Management Control Systems,” 11th ed. (New York: McGraw-Hill, 2004), which focuses on the use of planning and control systems to implement (as opposed to test) strategies. Within this context, there have been several important developments in the field of management planning and control. One example is the value in combining financial measures (“outcome measures”) and nonfinancial measures (“performance drivers”) in evaluating the performance of managers, a development that goes as far back as the “measurement project” at General Electric Co. in the 1950s. See Anthony, “Management Control Systems,” 557–564. The notion of blending financial and nonfinancial measures in the context of implementing strategies has been refined by others. See, for example, J.K. Shank and V. Govindarajan, “Strategic Cost Management: The New Tool for Competitive Advantage” (New York: Free Press, 1993) for a development of the concept of “key success factors,” or R.S. Kaplan and D.P. Norton, “The Balanced Scorecard: Translating Strategy Into Action” (Boston: Harvard Business School Press, 1996). Our objective in this article is to redefine planning and control for a different purpose — testing a highly uncertain strategy through experimentation and learning, when a priori predictions of the future are not possible.

9. Again, refer to McGrath and MacMillan’s concept of discovery-driven planning (DDP). In this example, DDP would be appropriate if the question were whether the necessary student-to-faculty ratio is 10:1. But for Universitas 21 Global, the question is much more fundamental: To what extent does student-to-faculty ratio have an impact on student satisfaction? Theory-focused planning is designed to facilitate resolution of this type of unknown.

Acknowledgments

Support for this project was provided by the Center for Global Leadership. The authors also gratefully acknowledge comments from Arvind Bhambri, Guy Hocker and Anant Sundaram.