McKinsey-Oxford 2012: Large IT Projects Run 45% Over Budget
The most-cited number in IT project performance. We give the source URL, sample size, definition of "large", and the full headline findings so you can quote it accurately.
What did the McKinsey-Oxford IT projects study find?
The McKinsey-Oxford 2012 study analysed more than 5,400 large IT projects (those with initial budgets above $15 million) and found they run 45% over budget and 7% over time, while delivering 56% less value than predicted. Every additional year of project duration adds roughly 15% to the cost overrun, and 17% of large IT projects go so badly they threaten the very existence of the company. Published October 2012 by Michael Bloch, Sven Blumberg and Jurgen Laartz for McKinsey's Business Technology Office.
What "large" means in this study
The McKinsey-Oxford study defined a large IT project as one with an initial budget greater than 15 million US dollars. Projects came from public and private sectors, across geographies, drawn from a McKinsey project database supplemented by Oxford Said Business School data.
The study explicitly excluded small in-house IT work (anything sub-15 million) because those projects have very different governance and risk profiles. Large IT projects, by contrast, tend to have multiple vendors, long timelines, regulatory complexity, and political stakes: the exact conditions that produce overruns.
The full headline findings
| Finding | Value |
|---|---|
| Average cost overrun | 45% |
| Average schedule overrun | 7% |
| Average value shortfall vs predicted | 56% less |
| Cost-overrun increase per additional year of project duration | +15% |
| Share that go so badly they threaten the company's existence | 17% |
The black-swan finding is the most concerning in the dataset: 17% of large IT projects go so badly that they threaten the very existence of the company. In the companion academic study (Flyvbjerg and Budzier, Harvard Business Review 2011, 1,471 projects), one in six projects was a black swan, with a cost overrun of 200% on average and a schedule overrun of almost 70%. Large IT projects do not just slip: a meaningful minority become outright disasters.
How to cite
Source URL: mckinsey.com (delivering large-scale IT projects)