
Workers prepare the S-IC first stage in the transfer aisle of the Vehicle Assembly Building at NASA's Kennedy Space Center, February 21, 1969. The Apollo program met its schedule objective of landing a man on the Moon "before the decade was out." Its original projected cost was $7 billion. Actual cost was about $25 billion. Image courtesy U.S. National Aeronautics and Space Administration.
As I noted last time, projects often take longer — and cost more — to complete than their planners initially projected. This phenomenon is accounted for, in part, by a cognitive bias known as the planning fallacy. [Kahneman & Tversky 1977] [Kahneman & Tversky 1979]. This cognitive bias operates by causing planners to rely too much on data about the project at hand, which Kahneman and Tversky call singular data. Likewise, planners tend to pay too little attention to data about past similar projects, which Kahneman and Tversky call distributional data.
In the decades since Kahneman's and Tversky's work on the planning fallacy, they and other researchers have discovered many more cognitive biases, some of which could act so as to exacerbate the effects of the planning fallacy. I explored two of these last time — the Fundamental Attribution Error and Choice-Supportive Bias.
Three more cognitive biases also come to mind in this connection: Confirmation Bias, the Overconfidence Effect, and Optimism Bias. In what follows I provide insights as to how these three cognitive biases could affect planners who are conducting a retrospective investigation of the performance of the project teams that executed projects in the not-too-distant past of their own organization.
Confirmation Bias
Confirmation bias is a cognitive bias that causes us to seek information that confirms our preconceptions, and avoid information that might disconfirm them. [Nickerson 1998] It can also cause us to tend to overvalue information supporting our preconceptions, and undervalue information in conflict with them. And confirmation bias can even affect memory, causing us to remember more clearly incidents and situations that align well with our preconceptions, and to fail to recall — or recall incorrectly — incidents and situations at odds with our preconceptions.
Confirmation bias can distort the planning process by biasing the set of past projects that planners consider, and by biasing interpretations of past results. For example, suppose a planning team adheres to the "greatest-breadth-of-experience theory" of project performance — the idea that the project team does best when it has the greatest breadth of experience in project management. That planning team is more likely than most planning teams to devise a plan that incorporates their preconception by seeking examples that support the greatest-breadth-of-experience theory of project performance. That planning team is less likely than most to be persuaded by disconfirming evidence from project management research. [Salvador, et al., 2021]
Overconfidence Effect
The Overconfidence Effect is a cognitive bias that causes us to have confidence in the validity of our judgments at a level beyond what their accuracy could reliably support. [Brenner 2015.4] [Moore & Healy 2008] The effect is more pronounced when confidence is high.
For project planners, the overconfidence effect can manifest itself in any part of a project plan that's sensitive to the judgment of planners. For example, in risk planning, judgment plays a role in estimating the probability of a given risk event occurring. Specifically, a planning team affected by the Overconfidence Effect might decide that a risk is so unlikely to materialize that they'll decide against investing in mitigation activities that an unaffected planning team might attend to more carefully.
Optimism Bias
Optimism bias is a cognitive bias that causes us to underestimate the probability of an undesirable event, or to overestimate the probability of a desirable event.
This bias can affect project planners in two ways. When assessing risk, the bias could lead to underestimates of the probabilities of unwelcome events. And when judging the relative wisdom of two options, say A compared to B, planners who are attracted to A for any reason are more likely than others to assess option A as more likely than option B.
Last words
In this post and the previous one, I assumed that those devising the plans actually wanted the project to come to a successful conclusion. And in most cases, success would entail meeting budget and schedule expectations. But there are situations in which some people — rivals, political enemies, or ambitious challengers — seek to make projects fail. In these cases, those seeking failure can exploit these cognitive biases to incline plans toward failure. Proposals and arguments consistent with the biases noted above can be an early sign of actions by these political actors. First issue in this series
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