Predicting Your Competitor’s Reaction  

Oleh:

Coyne, Kevin P.

Jenis: Article from Bulletin/Magazine - ilmiah internasional
Dalam koleksi: Harvard Business Review bisa di lihat di link (http://web.b.ebscohost.com/ehost/command/detail?sid=f227f0b4-7315-44a4-a7f7-a7cd8cbad80b%40sessionmgr114&vid=12&hid=105&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=bth&jid=HBR) vol. 87 no. 4 (Apr. 2009), page 90.
Topik: Executive; Competitors; Strategic Decision Making

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Perpustakaan Pusat (Semanggi) Nomor Panggil: HH10.38 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Any executive will tell you that understanding how competitors will respond to your actions should be a critical component of strategic decision making. But ask that same person how seriously her company actually assesses competitor reaction, and she will probably roll her eyes. In a recent survey conducted by McKinsey & Company, two-thirds of strategic planners expressed a strong belief that companies should incorporate expected competitor reactions into strategic decisions. Yet in a survey conducted by David B. Montgomery, Marian Chapman Moore, and Joel E. Urbany (published in 2005 in Marketing Science), fewer than one in 10 managers recalled having done so, and fewer than one in five expected to in the future. This disconnect arises because the only rigorous framework for explaining rivals’ behavior—game theory—often becomes unmanageable in the real world. For a start, most game theory models presume that all players use the basic principles of game theory—an assumption that is manifestly false. Further, game theory models become unwieldy when a competitor has many options, when the strategist is unsure which metrics his rival will use to evaluate them, or when there are multiple competitors, each of whom might react differently. But when strategists instead use ad hoc predictions or war-gaming exercises, the analysis can become almost entirely arbitrary. The number of qualitative considerations that enter the prediction process—personal biases and hidden agendas, for example—risk rendering the results suspect and make senior management more likely to reject counterintuitive results.

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