Research shows that, when for example doing budgetting and planning, we tend to ignore historic data. We are not only overconfident and optimistic (unrealistic), but we also do not consult statistics of similar cases, even if we have access to that kind of data.
This “planning fallacy” (coined by Nobelprize winner Daniel Kahneman) makes us miss budgets and plans, even if we have the means to use available data to make better estimations. In these cases we only look at the estimation task at hand, without consulting history. We even ignore the fact that (similar) projects have failed. Basically, we estimate based on our current perception, without looking at past data that may provide another view.
And even if we look at past data, we tend to ignore it — again — because the case is “different”. The cases from which the statistics were derived are not similar to our case with better people, better defined requirements, better technology, etc.
We overlook data, and we do not trust it. Instead we humans prefer to operate based on intuition. This may work in life-threatening situations as coming across a mountain lion. It does not work when we try to plan or otherwise organize.
For example, in a process like setting service levels (responding to support requests, delivery of goods, etc.) with customers it is worth knowing what — under current conditions — kind of service levels the organization is able to provide. Unfortunately most of the time organizations define levels without any guarantee if these levels can be met, or what happens in case more customers need to be serviced.
One note of caution. Past data does not account for so-called Black Swans, outliers with extreme consequences that are not necessarily present in the available data.