In his recent book, Thinking Fast and Slow, Economic Nobel Laureate Daniel Kahneman speaks of the “planning fallacy,” a term he and his former collaborator, Amos Tversky, coined “to describe plans and forecasts that are unrealistically close to best-case scenarios [and] could be improved by consulting the statistics of similar cases.” In “forecasting the outcomes of risky projects, executives too easily fall victim to the planning fallacy. In its grip, they make decisions based on delusional optimism rather than on a rational weighting of gains, losses, and probabilities. They overestimate benefits and underestimate costs. They spin scenarios of success while overlooking the potential for mistakes and miscalculations. As a result, they pursue initiatives that are unlikely to come in on budget or on time or to deliver the expected returns—or even to be completed.” Sound familiar?

I first encountered this situation roughly 35 years ago, when designing a system for a client. My estimates said it would take two years, but the client said they needed it done in less than one. I said it couldn’t be. Shortly thereafter I left [on my own, I might add] before the project commenced, and never learned of its outcome, though I am confident that even two years was an optimistic guess.

A few years back, a client asked us for an estimate to conduct a GIPS(R) (Global Investment Performance Standards) verification for them. We knew the client well, and what their status was vis-a-vis the Standards, and were surprised they were asking for a proposal, given the huge gap they had before they’d be ready to even consider compliance. We lost to a firm that gave them a very low price, and confidence that they’d be ready to be verified in three months. This firm won the assignment partly because of pricing, but perhaps more because of their confidence in getting them into compliance in but a few months time [since that time, bringing the client into compliance and then verifying have been clearly deemed in violation of verifier independence]. Their optimism was impressive, but failed to materialize. Too often scenarios like this play out: the consultant promises to complete a project earlier than is realistic and wins the assignment. This is not to suggest that the competing firm necessarily knows they’re providing an unrealistic estimate, but their optimism still results in a win, when their competitor offered a more realistic plan.

I have, on occasion, been a victim of the planning fallacy [who hasn’t?]. I estimate what is needed to complete a project, and believe [with confidence] I’ve done an effective job in identifying risks, only to fail to see the multitude of events that might arise that introduce delays.

More than 40 years ago, Fred Brooks coined the term “mythical man-month” (I guess today, an enlightened and politically correct person would make it “person-month”) addressed the false belief that adding resources will speed up a project. The idea of placing nine women on the job of having a baby should result in one in only one month (since it takes one woman nine months to produce one) serves as a good metaphor for the concept.

Projects are routinely missed; deadlines exceeded; costs surpassed. The notion of referring to a “base case” of past performance as a guide is helpful to try to develop more realistic estimates, be they the time to achieve compliance or build a new system. Being at least aware of the “planning fallacy” can be helpful when beginning projects, to try to enhance the estimates and likelihood of success.