Anchoring : Using the first “best guess” as a starting point for subsequent estimating.
Availability : Recalling values that are memorable, easily accessible, recent, or extreme.
Bandwagon bias or groupthink : Conforming one’s beliefs based on participation with a group norm. This is an especially strong bias if deviating from the group norm can result in ostracism or shaming, and participation in the group is considered a particularly valuable association. The experiments of Solomon Asch1 in 1956 demonstrated just how powerful this effect can be.
Blind spot bias: Failing to recognize that one’s thinking is influenced by any biases at all.
Confirmation bias: Selecting or using only information that supports a preexisting belief or perception.
Entitlement : The SME provides an estimate that reinforces his or her sense of personal value.
Expert overconfidence : Failure of creativity or professional hubris (e.g., “I know this information and can’t be wrong because I’m the expert”). This often leads an SME to consider fewer possibilities associated with an event, leading back to false precision.
False precision : Reporting anticipated outcomes with an unjustified level of certainty, usually as a single point estimate rather than a range.
Frame bias: Failing to consider that there might be alternate ways to structure the context of a problem.
Incentives : The SME experiences some benefit or cost in relationship to the outcome of the term being measured, adjusting his or her estimate in the direction of the preferred outcome.
Sand bagging : Underreporting potential outcomes to appear heroic when better than anticipated outcomes materialize.
Selection bias: Using information that is unintentionally filtered either by the method for collecting data or by an underlying mechanism (e.g., survivorship) such that the relevant population is not represented in an unbiased or randomized manner.
Unwarranted optimism : Personal enthusiasm or a natural disposition to believe that desired outcomes will most likely occur; or, inflating initial estimates of desired outcomes to appear more effective than is warranted.
Familiarizing yourself with these biases will help you identify opportunities to gently challenge an SME’s thinking in the elicitation process . For example, several years ago I helped a chemical manufacturing company develop a cost and schedule forecast for a new kind of chemical reactor. In an interview with an engineer about the possible duration required to construct one of the key mechanical structures, he began his discussion by telling me about a recent significant schedule overrun on another project of a similar nature. The situation had caused no small amount of internal controversy as late fees were incurred, fingers were pointed, and professional careers took abrupt redirections. As you might guess, I recognized his verbal rumination as an expression of the availability bias. By guiding the engineer to recall other projects that actually occurred on or within schedule, I was able to allow him to think more clearly about factors that might lead to a favorable duration. As a result, the development team was able to design acceleration plans for the project while reporting a historically consistent go live date to their client. In the end, everyone was delighted by the outcome.
In another situation, a sales team asked me to support their development of a revenue forecast for their government contracting company. To save some time, they provided a list of their target opportunities, some of which were current engagements that were up for contract renewal, each with an assigned probability of deal closure. The most important target was their key client, to which they assigned a 95% chance of closing their contract renewal. The sense of entitlement was, to put it mildly, palpable. Someone actually stated, “They’d be crazy not to re-up with us, but we discounted this 5% just so we don’t look too arrogant to the CFO.” Based on some background conversations that I had been privy to over the previous year, I believed this group was most assuredly not considering some important threatening information because they were blinded by their sense of entitlement. I asked them to turn the question around. Rather than thinking about what the probability of closure was, I asked them, instead, to think about what would lead to their losing the renewal. That conversation was much more sobering. The resulting revenue forecast, which included this “negative thinking” applied to all the other opportunities, indicated the need for bridge funding. Unfortunately, they needed it. Fortunately, they were prepared.
I want to clarify, though, that recognizing a given bias does not guarantee that favorable outcomes will occur or that disasters will be avoided. These two examples do not demonstrate that more accurate assessments cause the anticipated outcomes, as I’ve actually witnessed people think causality works in this manner. Rather, you will be better prepared to develop contingency plans for undesirable outcomes (or exploitation plans for the desirable ones) that will be uncovered by acknowledging the bias that would have otherwise kept these potential outcomes veiled from consideration. By recognizing thought-limiting biases, you can actually take more constructive steps to realize a future you or your clients desire.
A comprehensive list of cognitive and motivational biases can be found at the Behavior Economics Group web site ( https://www.behavioraleconomics.com/mini-encyclopedia-of-be/ ). I also recommend taking in the delightfully entertaining and informative web site and podcasts of David McRaney at You Are Not So Smart: A Celebration of Self Delusion ( https://youarenotsosmart.com ). McRaney delivers engaging discussions about the biases and delusions that shape all our thinking.