Mapping competitive prediction capability: Construct conceptualization and performance payoffs

The strategy literature routinely emphasizes the importance of competitor assessment as part of strategic analysis and planning. In particular, the ability to sense and accurately predict competitors' future moves – referred to here as the competitive prediction capability – can form a basis for sustainable competitive advantage. Yet, managers are not always well-skilled at assessing competitors and often do not accurately anticipate competitors' actions. Apart from human factors that inhibit astute competitive reasoning, managers also lack the motivation to develop a competitive prediction capability because of perceived low payoffs from performing such an activity. Indeed, research has neither fully explicated the rare and difficult-to-develop nature of competitive prediction capability nor offered much empirical evidence of its rent-producing potential. Accordingly, this article conceptualizes competitive prediction as a learned, organizationally-embedded capability and empirically establishes its performance payoffs. Results from a tracking study via the Markstrat simulation show that firms that develop a competitive prediction capability achieve greater improvements in profitability and stock price performance over time. In addition, firms that employ data-driven approaches to competitor assessment make more accurate predictions than do firms that primarily rely on informal intelligence gathered from the grapevine. These findings hold important theoretical and managerial implications.