estimates of a key outcome, and the person who comes closest to the actual number receives a payoff of some kind (which may or may not be monetary). The second is similarity-based forecasting: Individuals are asked to rate how similar a particular decision or asset is to past decisions or assets. The ratings are then aggregated using simple statistical procedures to generate forecasts for revenues or for completion times or costs, depending on the goal. (This is actually a case-based decision analysis tool.)
Ask yourself: Is the information you need centralized or decentralized?
If it’s decentralized, can you tap the experts you need and aggregate their knowledge?
Is it feasible and helpful to use “the crowd” for some portions of your information gathering?
Is it possible to aggregate useful information from the crowd without having to reveal confidential information?
Complicating Factors
For the sake of clarity, we’ve presented a simplified set of examples above. In practice, of course, all kinds of complications occur when major decisions are being made. We explore a few of those below.
Executives don’t know what they don’t know. The model we’ve developed for choosing decision support tools is dependent on managers’ being able to accurately determine the level of ambiguity and uncertainty they face. This may be problematic, because decision makers—like all human beings—are subject to cognitive limitations and behavioral biases. Particularly relevant here are the well-established facts that decision makers are overconfident of their ability to forecast uncertain outcomes and that they interpret data in ways that tend to confirm their initial hypotheses.
In essence, executives don’t know what they don’t know, but they’re generally happy to assume that they do.
Cognitive bias creeps in. Managers’ biased assessments of the level of uncertainty they face might lead some to conclude that our diagnostic tool is of limited practical use and might point them toward the wrong approach. Our consulting experiences suggest that most organizations can manage those biases if, when a strategic decision is being considered, managers choose their decision-making approach in a systematic, transparent, public manner during which their judgments can be evaluated by peers. (This will require process and culture change in many organizations.)