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McKinsey 2015: The Source for "98% of Megaprojects Go Over Budget"

The most-cited megaproject overrun statistic on the web traces to one McKinsey article. We give its exact wording, the primary source, and the distinction between the 98% share and the 80% average that almost everyone merges.

Where does the "98% of megaprojects overrun" figure come from?

From McKinsey & Company's article Megaprojects: the good, the bad, and the better (July 2015). Its exact wording: 98% of megaprojects suffer cost overruns of more than 30%, and 77% are at least 40% late. The 80% figure quoted next to it is a different McKinsey number: an in-depth review of more than 300 billion-dollar-plus megaprojects that found average cost overruns of about 80% and schedule delays of about 50%. One is a share, the other is an average, and they should not be fused into "98% overrun by 80%".

98%
of megaprojects overrun by more than 30%
77%
are at least 40% late
~80%
average cost overrun (300+ billion-dollar projects)
~50%
average schedule delay (same review)

The two figures, kept apart

The single most common mistake with this statistic is to quote it as "98% of megaprojects overrun by 80%". That fuses a count and an average that McKinsey states as separate findings. Here they are as the source presents them:

FindingFigureWhat it measures
Megaprojects with a cost overrun above 30%98%A share (how many overrun)
Megaprojects at least 40% late77%A share (how many run late)
Average cost overrun, 300+ billion-dollar megaprojects~80%A magnitude (how far over)
Average schedule delay, same review~50%A magnitude (how far late)

A project only has to slip just past 30% over budget to count toward the 98%. The ~80% average is a separate, harder number: across the 300-plus billion-dollar projects McKinsey reviewed directly, the mean overrun was roughly 80%, pulled up by a long tail of severe cases. Cite whichever you actually mean, and do not multiply one by the other.

The rounded "98% / 80%" shorthand is how the figure travels, and it is what our own construction and statistics pages use as a compact headline. This page is the long form: the two numbers, correctly separated, with the source attached.


What counts as a megaproject here

McKinsey's in-depth review covered billion-dollar-plus projects (contract values above 1 billion US dollars) across asset classes: transport, power, water, oil and gas, mining, and large buildings. That matches the $1 billion threshold Bent Flyvbjerg uses. The broader 98% / 77%-late headline is stated for megaprojects in general rather than for one named sample, which is why this page treats the 300-project review as the harder-edged, directly-attributable number.

McKinsey framed the article around a paradox it called the megaproject paradox: the world is spending more than ever on megaprojects (roughly 8% of global GDP at the time), while their delivery record barely improves. That is the same durable pattern Flyvbjerg calls the Iron Law of Megaprojects: over budget, over time, over and over again.


How it fits the wider evidence

The McKinsey megaproject figures are not an outlier. They line up with the independent, larger-sample datasets on this site:

Different methods, different samples, the same direction. When McKinsey's 300-project review, Flyvbjerg's 16,000-project database, and the Olympic record all agree, the megaproject overrun problem is about as robust as an empirical finding gets.


How to cite

McKinsey & Company (2015). Megaprojects: the good, the bad, and the better. McKinsey Capital Projects & Infrastructure practice, July 2015.

Source URL: mckinsey.com (megaprojects: the good, the bad, and the better)

The related McKinsey report The Construction Productivity Imperative (2015) carries the companion "large projects across asset classes typically take 20% longer to finish than scheduled and are up to 80% over budget" framing.


Related references on this site

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Updated 2026-06-13