The perils of overconfidence
The decision to sanction a large complex project is usually the culmination of a long process of study and analysis. Senior managers have decided to ‘take the risk’. Now it’s time to get to work. At this point, the new mission generates energy throughout the organisation.
A big new project signals a desire to invest in growth, scale up, enter new territories and markets. It’s a positive thing. Yet it comes with a price.
Much rides on the decision to proceed, as resources and reputations are committed to a journey fraught with uncertainty. Executives now rely on their managers and teams to deliver the project within the expectations set out.
The problem, though, is optimism bias. Or simply overconfidence. Which is not, actually, that simple. According to a 2007 paper by Don Moore and Paul Healy, overconfidence comes in three flavours: 1) overestimation of performance, 2) overplacement of performance relative to others, and 3) excessive precision.
We tend to conflate them, but each can pop up in different situations. We might overestimate a contract negotiating position. Or we overplace our ability to achieve a due date, even when the industry benchmark for this kind of project is months longer. Or we might be too precise in our assessment of task durations, given the risks and uncertainties involved.
Optimism affects your team’s understanding of the scale of the challenge they face, and misjudging the capability required to meet it. Overconfidence can also mean underestimating. Downplaying the impacts of known risks, especially, will leave your project exposed and vulnerable to value erosion.
As a colleague said on an appraisal during the construction of an ultra-deepwater drillship: ‘You can’t be pessimistic enough when it comes to these things.’ That phrase inspired one of our five maxims:
Pragmatic pessimism over energetic optimism.
We’re not talking about personal pessimism—the doom and gloom of a killjoy. It’s rather a structural approach and mindset that you encourage in your team, so people recognize optimism bias when it shows up.
Most people only quote Murphy’s Law once something has gone wrong. Instead, from day one, you need to imagine ‘anything that can go wrong, will go wrong’.