Why Too Many Projects Fail, and What Better Measurement Could Change

The Statistic Nobody Wants to Discuss

Only one in every two hundred projects finishes on time, within budget, and delivers the benefits outlined in the original business case. Yet the project management profession essentially treats this figure as inevitable. Rather than questioning the fundamental assumptions that produce this outcome, organisations accept it as the cost of doing business.

This alone warrants serious attention. But there is something more troubling beneath this statistic: the authors argue that this abysmal success rate is not due to poor project management. It is the result of bad project selection.

This is the starting point for Douglas Hubbard , Alexander Budzier and Andreas Leed's recently published book, How to Measure Anything in Project Management. Their central claim is direct: if we measured uncertainty more accurately, we would choose different projects and achieve better results. The measurement problem is fundamentally a selection problem.

In this episode of the Project Flux podcast, we discuss the importance of measuring uncertainty in project management with authors Douglas Hubbard and Andreas Leed. They explore the challenges faced in different industries, the role of AI in improving project outcomes, and the need for a quantitative approach to decision-making. The conversation emphasises the human element in project management, the necessity of adapting to emerging technologies, and the future implications of AI on jobs and project management practices.

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See you soon,

James, Yoshi and Aaron—Project Flux