Why relying on average inputs leads to fundamentally flawed system performance predictions
In short: This video from MIT's Risk and Decision Analysis course explains the Flaw of Averages. It reveals why using average values as inputs often results in incorrect conclusions about how a system will actually perform, challenging a common but mathematically unsound assumption.
The Flaw of Averages is a persistent error in decision-making where one assumes that plugging average input values into a model will yield the average outcome of that system. In reality, this approach is mathematically false.
Presented by Richard de Neufville as part of the Fall 2021 MIT course IDS.333, this concept highlights the danger of oversimplifying complex variables. By relying on averages rather than accounting for the full range of potential inputs, analysts often produce forecasts that fail to reflect the true performance of the systems they are studying.
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Sources
- Summary by Intellect · source: Unit 2: The Forecast is Always wrong, Video 5: Flaw of Averages 1-the Concept
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