Private sector IT projects just as bad as in public sector
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One in six IT projects goes drastically over budget – and businesses are as bad as governments, Oxford and McKinsey research finds
One in six IT projects goes drastically wrong because organisations fail to plan for low probability, high impact risks, a study by researchers at Oxford University's Said Business School and management consultancy McKinsey has found.
The researchers analysed 1,471 IT projects with an average cost of $33 billion. They found that on average, projects overran by 27%, and that there was little difference between government organisations and private businesses.
"But that figure masks a far more alarming one," wrote Bent Flyvbjerg of the Said Business School and McKiney’s Alexander Budzier in an article for Harvard Business Review. “One in six of the projects we studied ... had a cost overrun of 200%, on average, and a schedule over-run of almost 70%.”
Interesting Links
Why your IT project may be riskier than you think – Harvard Business Review (.pdf)
Black swans in the cloud An outage at Amazon Web Services and a catastrophic data breach at Sony show that when Internet-scale systems fail, they do so spectacularly
The authors described these projects as black swans, using academic Nicholas Nassim Taleb’s term meaning low probability events that have a disproportionally disruptive impact.
“It’s not that [IT projects are] particularly prone to high cost over-runs on average. It’s that an unusually large proportion of them incur massive overages— that is, there are a disproportionate number of black swans."
The authors recommend that before launching a major IT initiative, organisations assess their ability to cope with it going drastically wrong.
And to reduce the risk of that happening, the suggest that organisations “break big projects down into ones of limited size, complexity, and duration; recognize and make contingency plans to deal with unavoid- able risks; and avail themselves of the best possible forecasting techniques—for example, “reference class forecasting,” a method based on the Nobel Prize–winning work of Daniel Kahneman and Amos Tversky.”
