Addressing Over-Optimism on Megaprojects
Research on megaprojects has shown that initial cost and schedule estimates for megaprojects are often overly optimistic and driven by incentives to support project approval rather than project accuracy. This over-optimism leaves the project exposed to increased likelihood for significant cost and schedule increases, particularly for megaprojects with large first-of-a-kind aspects.
Within this article, we discuss why this over-optimism persists on megaprojects, governance mechanisms that can address over-optimism, and demonstrate practical steps to reduce over-optimism throughout the project lifecycle.
Why Does Over-Optimism Persist on Megaprojects?
Research from Bent Flyvbjerg found that 92% of megaprojects come in over budget, over schedule, or both, regardless of industry sector or region and observable across decades of megaproject execution. This persistent cost and schedule growth on megaprojects suggests structural issues surrounding their planning and governance that may be rooted in:
Optimism biases – unintentional psychological tendencies to underestimate cost and schedule, including risks and their resulting impacts.
Strategic misrepresentation – intentional understatements to secure approval (politically, financially, or within the organization itself).
The tendency for megaprojects to experience optimism biases or strategic misrepresentation is amplified by common characteristics of megaproject execution including specifically: long planning durations, incomplete early designs, and multi-party decision processes.
Mechanisms to Address Over-Optimism on Megaprojects
How should owners/project sponsors plan and structure megaprojects to address the inherent over-optimism often present? Below we outline specific steps that when implemented act to alleviate and reduce potential over-optimism in cost/schedule estimates.
Reference Class Forecasting – utilizes external, empirical data from comparable projects to anchor estimates to observed outcomes. It can be difficult to fully implement with novel, first-of-a-kind projects, though can still be leveraged for common elements and general productivity rates.
Independent Assurance/External Validation – engages support from outside the project development team to independently review cost/schedule estimates at appropriate points of development (e.g. pre-FEED, post-FEED). This provides an informed view that the various estimate factors (productivity, labor requirements, procurement lead times, sequencing, etc.) are reasonable.
Two-Tier Baselines – utilizes different probability levels from quantitative risk analyses to present two different baselines, with the higher confidence (e.g. P80, P90) baseline serving as the official baseline that includes additional contingency to address potential risks, while the lower/medium confidence (e.g. P50) baseline may be used for day-to-day project management and for measuring contractual incentives/disincentives. The concept behind this dual-baseline approach is that the higher confidence baseline presents a “what will it actually take” view that reduces the likelihood for surprise cost/schedule growth, while a P50 baseline presents a potentially challenging, but achievable goal for project management to target.
Incentive Realignment – within the organization, executive or project team incentives can be tied to the accuracy of early/authorization estimates with an approach that rewards transparent risk disclosure and addresses systemic underestimation.
Stage-Gate Funding tied to Design Completeness – withhold major funding releases until engineering maturity advances to provide adequate confidence in the scope (e.g. 30% design), further supported by independent (i.e. outside the project team) verification of design completeness.
Risk-Adjusted Cost/Schedule Modeling – integrate the influence and impacts of potential risks on the cost/schedule through use of Monte Carlo simulations to provide quantification of uncertainty.
Transparency and Auditability – require record-keeping that provides a traceable view of the assumptions, quantities, vendor quotes, productivity data, etc. relied upon to develop the estimate.
Organizational Support to Reduce Over-Optimism
Complementing the above mechanisms are organizational structures that support implementation of those mechanisms and can further reduce over-optimism in cost and schedule estimates. Such supporting organizational structures, and the support they bring, includes:
Independent Project Review Boards
Report to the Board or State entity, not to the project team.
Hold veto authority over early estimates and risk classifications.
Project/Program Management Offices (PMOs)
Maintain historical data across projects.
Implement reference class and benchmarking data.
Provide standardized estimating methodologies.
Procurement/Commercial Management Groups
Engage EPC/EPCM contractors early to validate constructability and productivity assumptions.
Utilize contract models that share risk rather than push it downstream.
Prohibit award based solely on lowest price bid without realism checks.
Practical Workflow to Reduce Over-Optimism
We shift now to taking a look at specific steps to implement across the megaproject development lifecycle to reduce over-optimistic cost and schedule estimates.
1. Conceptual Stage
Utilize reference class forecasting to establish a realistic cost/schedule range.
Identify project-specific risk factors.
2. Pre-FEED
Independent reviews of scope, interfaces, and risk.
Updated reference class forecasting.
3. FEED
Require 30%+ design maturity before establishing cost/schedule baseline.
Run integrated cost-schedule-risk assessment.
4. Final Investment Decision
Approve two baselines (e.g. public and target).
Lock in and document assumptions, requiring change management for any deviation.
5. Execution Stage
Monthly variance reporting against the two baselines.
Independent assessments at major milestones.
Closing Thoughts
Megaprojects routinely experience cost overruns and schedule delays that are often driven by early estimates that are shaped more by the need to secure approval than by realistic delivery conditions. Within this article, we outlined a practical set of governance and estimating measures to counter these risks, including reference class forecasting, independent estimate assurance, two-tier baselines, incentive realignment, stage-gated funding tied to design maturity, risk-adjusted modeling, and stronger transparency in estimate development. These measures, when supported by organizational structures such as independent review boards, PMOs, and disciplined procurement functions, can materially improve estimate reliability and reduce the likelihood of avoidable cost and schedule growth across the project lifecycle.