The License Application Mitigation Project (LAMP) initiated by the state of Washington, US aimed at automating the state’s vehicle registration and license renewal processes. The project began in the early nineties and was supposed to be online in 1995. It planned to create a relational, client-server system using IBM’s MVS/CICS architecture. Initially budgeted at $16 M, the project cost climbed to $41.8 M in 1992, $51 M in 1993 and was last estimated (March 1997) at $67.5 M of which $40 M had been spent without result. In 1993, LAMP faded when it became clear that it was doomed to be a colossal money-waster and in 1997, the project was abandoned. Even if the plug had not been pulled it would have been much too big and obsolete by the time it was finished. LAMP was turned off in 1997, after legislators calculated that the project ultimately would cost $4.2 million more annually to run than the state’s $800,000 per year incumbent system. Though not as drastic, the situation is very typical and a common one in many companies.
In their 2009 bi-annual report, the Boston based consulting firm ‘The Standish Group’ reported a significant increase in failed projects. Measured by cancellation prior to completion or delivered but never used, the failure rate in 2008 was 24%. 44% of projects were defined as late, over budget, and/or with less than the required features and functions. 54% of projects had cost overruns and 79% had time overruns. The cost of these failures and overruns are just the tip of the proverbial iceberg. The lost opportunity costs are not measurable easily, but could easily be in the trillions of dollars. Is it not surprising and in fact an irony, that projects are not able to be within the two fundamental constraints of project management – budget and timeline.
Cost/Timeline overruns are typically associated to what are called as “forecasting errors” or “technical errors” such as imperfect techniques, inadequate data, honest mistakes, inherent problems in predicting the future, lack of experience on the part of forecasters, etc. They can happen at all point in the life cycle and for a variety of reasons – incomplete requirements, poor design, lack of skills to manufacture the design, inadequate testing, etc. These reasons are valid and inadequacies because of these can be mitigated by following many of the standard project management methodologies and best practices across organizations and industry with rigor.
An aspect not often discussed is whether the planned budget and/or timeline were correct and realistic or was it underestimated and impractical. It could very well be that a rosy picture was painted – intentionally or unintentionally – and what we are seeing now is actually manifestation of the reality. The objectives set were themselves too lofty and were never possible to be achieved.
What is more surprising is that all project estimates – whether in public or private domain do go through a series of reviews for validation and to ensure their correctness. How is it that then that for majority of the projects we don’t seem to get it right? Is it simply oversight or there is something running much deeper influencing the final outcomes.
There are two phenomenon’s that could very well hold the answers to this mystery – optimism bias and strategic misrepresentation. We will dig into them deeper in the next post – Estimation Number Games – to understand.
Hrishikesh is an enterprise agile coach with interests in varied disciplines. Frequently writing on Agile and Lean related topics, he also occasionally ventures into other stuff like Artificial Intelligence as well..
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