Glossary
Optimism Bias
The well-documented human tendency to underestimate the cost and duration of projects, particularly in the early stages.
Optimism bias is not carelessness or dishonesty — it is a cognitive bias that affects even experienced, well-intentioned professionals. Studies by Flyvbjerg and others consistently show that large infrastructure projects overrun their original budgets by an average of 45% and their schedules by significant margins. The pattern is so consistent that it has been built into UK government appraisal guidance (HM Treasury Green Book) through a formal technique called Optimism Bias Uplift (OBU), which adds a percentage to cost estimates at early project stages to account for the fact that the estimate is almost certainly too low.
In project controls practice, recognising optimism bias is essential when reviewing early-stage estimates and programmes. The question to ask is not 'is this estimate correct?' but 'what systematic factors might be causing us to underestimate?' Scope growth, interface risks, ground conditions, procurement delays, and regulatory requirements are consistently underestimated at early project stages. Reference class forecasting — looking at what similar projects actually cost and took — is a powerful counter to optimism bias because it bypasses the team's own (inevitably optimistic) judgement.
Optimism bias is also embedded in three-point estimates. When estimators set their pessimistic value, they tend to anchor on their most likely value and not move far enough into genuinely pessimistic territory. The result is that Monte Carlo simulations, which rely on those inputs, also produce optimistically narrow output distributions. If a QRA consistently shows P80 estimates that are barely different from the deterministic estimate, the three-point inputs are probably too narrow. Challenging the inputs — particularly the pessimistic values — is one of the most valuable things a project controls professional can do.
Frequently asked
- What is optimism bias in project management?
- Optimism bias is the systematic tendency for project teams to underestimate costs and durations and overestimate benefits at the time of appraisal. It is not a matter of dishonesty — it is a cognitive bias that causes people to believe their project will go better than the historical average for similar projects. In UK capital projects, HM Treasury's Green Book requires an explicit Optimism Bias Uplift (OBU) to be applied to cost and time estimates at project appraisal to correct for this tendency, particularly at early stages when uncertainty is highest.
- How is optimism bias corrected in UK government projects?
- The primary correction method is the Optimism Bias Uplift (OBU), a percentage added to the base cost and time estimate. HM Treasury's Green Book provides upper-bound uplift values by project type (e.g. 66% for non-standard civil engineering, 44% for standard civil engineering). These are reduced as the project matures and uncertainty is resolved through design development and risk quantification. The Infrastructure and Projects Authority (IPA) Cost Estimating Guidance builds on this with reference class forecasting — using the actual outturn distribution of comparable past projects to set a statistically grounded uplift.
- What is reference class forecasting and how does it address optimism bias?
- Reference class forecasting (RCF), developed by Bent Flyvbjerg, addresses optimism bias by taking an 'outside view' — rather than building up a project estimate from scratch (which is susceptible to optimism), RCF asks: what was the outturn distribution for a reference class of similar projects? The project's forecast is then anchored to the statistical distribution of that reference class, adjusted for project-specific factors. UK government guidance explicitly endorses RCF as the preferred approach for major infrastructure appraisals, and it is now embedded in the IPA and Treasury guidance frameworks.
- What is the difference between optimism bias and strategic misrepresentation?
- Optimism bias is a cognitive error — the team genuinely believes the project will perform better than the evidence suggests. Strategic misrepresentation is deliberate: costs are knowingly understated or benefits overstated to win funding approval. Both produce the same outcome (projects approved on an unrealistic business case), but optimism bias responds to calibration and process improvements, while strategic misrepresentation requires governance and incentive changes. In practice, the two often coexist on major programmes where career incentives reward getting a project approved regardless of forecast accuracy.
Related terms
Putting these techniques into practice?
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