Why do so many large computing projects end up being costly failures? History shows that we, not our machines, are the problem—and it's time we address that.
The UK's National Health Service might seem like a local topic for this column. However, with 1.7 million employees and a budget of over $150 billion, it is the world's fifth-largest employer—surpassed only by McDonald's, Walmart, the Chinese Army, and the US Department of Defense. Therefore, its successes and failures offer valuable lessons for institutions of all sizes.
Take, for instance, the recent revelation that an abandoned attempt to upgrade its computer systems will cost over £9.8 billion ($15 billion). The Public Accounts Committee described it as one of the "worst and most expensive contracting fiascos" in public sector history. This won't surprise anyone who has worked on large computing projects. Planning is often inadequate, with projected timelines and budgets based on wishful thinking rather than a solid analysis of requirements. Communication breaks down, with side issues taking over discussions and overshadowing core functions. Meanwhile, the world moves on, turning yesterday's technical marvel into tomorrow's outdated burden, complete with endless administrative headaches and little room for technical development.
According to a 2011 study of 1,471 Information and Communication Technology (ICT) projects by Alexander Budzier and Bent Flyvbjerg of the Said Business School, Oxford, one in every six projects costs at least three times more than initially estimated. This is about twenty times the rate at which projects in fields like construction encounter such issues.
Costly IT failures are an unsurprising part of 21st-century life. What's important is not just what went wrong this time, but why the same mistakes keep happening over and over. These issues were evident during one of the first and most famous project management failures in computing history: the IBM 7030 Stretch supercomputer. Started in 1956, IBM aimed to create a machine at least one hundred times more powerful than its previous system, the IBM 704. This goal helped win a prestigious contract with the Los Alamos National Laboratory. In 1960, the machine's price was set at $13.5 million, and negotiations began for other orders.
The problem was that when a working version was tested in 1961, it was only 30 times faster than its predecessor. Despite having several innovations that would be important for the future of computing, the 7030 failed to meet its target, and IBM didn't realize this until it was too late. The company's CEO announced that the price of the nine systems already ordered would be reduced by almost $6 million each—below cost price—and that no more machines would be made or sold. Cheaper, more agile competitors filled the gap.