According to a new study by researchers from the Business School (, King’s Business School and the University of Malta, relying on data analysis in decision-making could be counterproductive, as this reduces the speed of decision-making without guaranteeing more precision .
The research, based on information from 122 advertising, digital, publishing and software companies, suggests that using data to inform decision-making under high uncertainty is often not optimal.
The authors asked workers how they made decisions in their most recent innovation project, including the degree to which they used data, instinct, and other simple heuristics (mental strategies). The findings indicated that among those decision-making methods were:
- Majority : choose what most people wanted.
- Count : choose the option with the most positive points.
- Experience : select the option desired by the most experienced person on the team.
Workers were asked if they believed they made the right decision and how fast they were in making that decision. The results showed that those who trusted their own gut as much as the data, using the ‘count’ more than any other metric, were the most successful.
Under extreme uncertainty, then, it seems that workers, particularly those with more experience, must trust the experience and instincts that have propelled them to such a position.