Debiasing is using insights from the fields of psychology and behavioral economics to help organizations take bias as much as possible out of risk decisions. Biases are predispositions of a psychological, sociological, or even physiological nature that can influence our decision making. They often operate subconsciously and by definition are outside the logical process on which decisions are purportedly based. While we may readily acknowledge their existence, we often believe that we ourselves are not prone to bias.
Bias is costly. Take the effect of one kind of bias, stability bias, in one dimension of business, capital allocation, as an example. McKinsey research has shown that companies that allocate capital dynamically—rebalancing regularly according to performance—return between 1.5 and 3.9 percent more to shareholders than companies with more static and routinized budgeting. The study suggests that companies with dynamic capital allocation could grow twice as fast as those without it. Yet in a classic example of stability bias, we found a 90 percent correlation in budget allocation year after year, for a 20-year period.2 The latest McKinsey research only underscores the relevance of these findings. A 2016 survey of nearly 1,300 executives worldwide revealed that higher-performing companies more tightly link reallocation to performance and value creation, using rigorous bias-reducing principles.
Biases affect how we process information, make decisions, and construct strategies (see sidebar "An overview of business-relevant biases"). They do not, however, always work in the same direction nor are they equally distorting in all situations. Companies have so far tapped only a small part of the potential of debiasing in business contexts. One reason is that no ready formulas exist that address the many different biases and business contexts. But corporate efforts to diagnose biases and take debiasing actions can be very effective, especially when prioritized by business need. Prioritization involves zooming in on the handful of decisions with the greatest business impact and then, decision by decision, identifying the actions that will reduce or eliminate the biases that may be present.
