Even in situations that seem relatively unambiguous, it often pays to supplement capital-budgeting and quantitative multiple scenario tools with case-based decision analyses to check for potential biases. For example, if your “certain” investment project is expected to deliver a rate of return that is unprecedented when compared with similar projects in the past, that might be more a reflection of overconfidence than of the extraordinary nature of your project. A robust analysis of analogous situations forces decision makers to look at their particular situation more objectively and tends to uncover any wishful thinking built into their return projections.
Managers don’t consider the option to delay a decision. Deciding when to decide is often as important as deciding how to decide. In highly uncertain circumstances—such as a fast-changing industry or a major shift in business model—it’s wise to borrow from a different tool kit altogether: learning-based, iterative experimentation. For instance, colleges today are being disrupted by massive open online courses (MOOCs), and most administrators don’t know if or how or when their institutions should react. Rather than make an expensive, high-risk decision now, many colleges are undertaking small-scale experiments to test the waters and learn more about what “success” in this space will look like. (They’re also using analogies, of course—for example, by trying to understand whether the unbundling of the music business has lessons for higher education.)
What can you start doing tomorrow to become a better business decision maker? Begin by developing your decision-making tool kit more fully. There is a clear disconnect between the tools that are being used and those that should be used most often. Make it a priority to learn more about quantitative multiple scenario tools such as Monte Carlo simulations, decision analysis, and real options valuation. Get some training in scenario planning. Explore the fast-growing academic and practitioner literatures on information markets. Make more rigorous use of historical analogies to inform your most ambiguous and uncertain—and usually most important—decisions. We all use analogies, implicitly or explicitly, when making decisions. The cognitive scientist Douglas Hofstadter argues that analogy is the “fuel and fire of thinking.” But it is far too easy to fall prey to our biases and focus on a limited set of self-serving analogies that support our preconceived notions. Those tendencies can be checked through rigorous case-based decision methods such as similarity-based forecasting.
Finally, and perhaps most important, make it a habit at your company to consciously decide how and when you are going to make any decision.