The Hidden Forces That Undermine Project Success: Why Human Bias is Costing Your Projects
Chuck Centore | President of PM&E
Every project professional has witnessed it—optimistic timelines that crumble, budgets that balloon, and risks that get underestimated. The culprit? More often than not, it’s human nature itself.
Behavioral science has identified over 200 cognitive and political biases that shape decision-making. In project management, ten of these biases stand out as the most impactful, silently influencing decisions, forecasts, and strategies.
Why Bias Matters in Projects
We often assume that poor project outcomes stem from technical miscalculations, scope creep, or unforeseen complexities. While these factors play a role, they are symptoms rather than root causes. The deeper issue lies in behavioral biases—systematic distortions in judgment that lead teams to underestimate risks, overpromise benefits, and escalate commitment even when the warning signs are clear.
Bent Flyvbjerg and Cass R. Sunstein, in their study The Principle of the Malevolent Hiding Hand; or, The Planning Fallacy Writ Large, provide compelling empirical evidence that biases are not just common but systematically detrimental. Their research, along with insights from Top Ten Behavioral Biases in Project Management, sheds light on why so many projects fail despite well-intended planning efforts.
The 10 Biases That Sabotage Projects
Strategic Misrepresentation – When project plans are intentionally skewed to gain approval, leading to unrealistic expectations.
Optimism Bias – The tendency to believe everything will go smoothly, despite historical evidence to the contrary.
Uniqueness Bias – Assuming that a project is unlike any other, causing teams to ignore lessons learned from similar endeavors.
Planning Fallacy – Underestimating costs, time, and risks while overestimating potential benefits.
Overconfidence Bias – Believing we know more than we do, leads to risky decision-making.
Hindsight Bias – Viewing past events as more predictable than they were, leading to overconfidence in future forecasting.
Availability Bias – Overweighting recent or easily recalled information instead of relying on broader, objective data.
Base-Rate Fallacy – Ignoring statistical realities and favoring case-specific anecdotes when making project forecasts.
Anchoring – Relying too heavily on the first piece of information encountered, even when better data becomes available.
Escalation of Commitment – Continuing to invest in a failing project due to prior investments, rather than cutting losses.
The Malevolent Hiding Hand: When Bias Becomes Catastrophic
Albert Hirschman’s Benevolent Hiding Hand theory suggests that planners tend to underestimate project risks, but that this ignorance sometimes leads to unexpected problem-solving creativity, ultimately producing better-than-expected results.
However, Flyvbjerg and Sunstein challenge this idea, introducing the Malevolent Hiding Hand. Their research shows that, in reality, project teams frequently encounter hidden obstacles—but instead of ingenuity saving the day, these challenges often escalate costs, reduce benefits, and ultimately lead to project failures. Their analysis of over 2,000 large projects revealed a sobering truth:
Cost overruns are rarely offset by greater-than-expected benefits.
Projects frequently suffer from both higher-than-anticipated costs and lower-than-anticipated benefits, creating a double blow to project viability.
This isn’t just an academic theory—it’s a warning for every project manager who assumes optimism and perseverance will naturally lead to success.
The Path to Smarter Project Decisions
✔ Use Statistically Significant Empirical Data – Instead of relying on intuition or case-specific anecdotes, project estimates should be based on large datasets of similar projects. By leveraging statistically significant empirical data, organizations can better predict costs, schedules, and risks while reducing the likelihood of optimism bias and strategic misrepresentation.
✔ Encourage External Reviews – Bring in independent experts to challenge assumptions and identify blind spots. Third-party validation reduces the impact of internal groupthink and provides a more objective assessment of project feasibility.
✔ Adopt Decision Hygiene Practices – Separate decision-making from individual biases by using structured evaluation frameworks. Implementing standardized risk assessments and multi-scenario modeling ensures that planning is rooted in data rather than personal conviction.
✔ Use Empirically Validated and Statistical Cost Engineering – Incorporate parametric modeling and systemic risk evaluation techniques to create more accurate cost and schedule forecasts. This approach mitigates the effects of the Malevolent Hiding Hand by ensuring project estimates account for known statistical variances rather than overly optimistic projections.
✔ Foster a Culture of Realism – Encourage teams to acknowledge risks openly rather than pushing overly optimistic narratives. Leaders should promote transparency in forecasting and decision-making, reinforcing that identifying risks early leads to stronger project outcomes.
Conclusion
Bias is not a project management failure; it’s a human trait. The best project leaders aren’t those who avoid bias altogether—they’re the ones who recognize its presence and take steps to mitigate its effects. In a world where projects are growing in complexity and stakes are higher than ever, mastering the psychology behind decision-making could be the ultimate competitive advantage.
The research from Top Ten Behavioral Biases in Project Management and The Malevolent Hiding Hand makes it clear: optimism bias and the planning fallacy are not just theoretical risks—they are tangible threats to project success. If we continue to ignore these psychological pitfalls, we will keep repeating the same mistakes.
How have you seen bias impact projects in your industry?
About the Author
