To develop a language for improved business decision making, we created a survey with questions that cover five classes of decision-making biases, which we summarized in earlier work: action-oriented, interest, pattern-recognition, social, and stability biases. The questions drew out preferences by asking people to choose between two neutral, equally defensible statements. Responses fell along a range from a strong preference for intuitive decision making to a strong preference for making decisions after exhaustive deliberation.
We received nearly 5,000 responses to the survey from McKinsey Quarterly and Harvard Business Review readers, and we conducted detailed analysis of 1,021 respondents, whose demographics and response characteristics were statistically indistinguishable from the full sample’s. We used these responses and factor analysis to identify six objective dimensions of the respondents’ preferences, which roughly correspond to common steps in the decision-making process. Cluster analysis then yielded five groups of decision-making preferences. This research is still in its early stages; presented here are the five decision-making styles, including the percentage of respondents who fell into each group.
The percentages in particular are preliminary, since the self-selected nature of the respondent pool could have introduced sample bias. Also, the number of questions tested and the sample size are far below those of a standard psychometric tool such as Myers–Briggs. That said, we believe the current survey has within it the core of a tool to help individuals reflect upon the trade-offs they make as decision makers.
For more on how to improve decision-making effectiveness, see our interview with Stanford’s Chip Heath and McKinsey’s Olivier Sibony, “Making great decisions.”