I remember an episode from my early career. I got hired as an independent consultant to run a project for a Canadian software company that was doing a project for a much larger US organization. Right at the very beginning of the project we did a high-level estimate with the help of our sales team and came up with a budget of $1.5 million. The customer rejected the number and claimed that they would be able to pay only $750,000. Our company's management agreed (don't ask me why) with the new "forecast", contracts were signed and the work commenced.
Several month later, once we had the detailed requirements document on our hands, we went through the estimation exercise again, this time the bottom-up version. The number we came up with? The same $1.5 million. We felt it would be the right thing to do to go back to the presidents of both organizations and let them know about the results of our findings ...
The reaction from the client's side has been very interesting to say the least. "We feel that Jamal is overly pessimistic in his approach, and we want him to be replaced with a more confident project manager!"
We Still Suck at Estimating
We all know about the famous examples of projects being grossly over budget and late. These include:
- The Denver airport baggage handling system that required an additional 50% of the original
budget - nearly $200m.
- Eurotunnel - an actual cost of £10bn, over double its original estimate of £4.9bn to build
- Virtual Case File (FBI) – scrapped after $170 million while delivering only 10% of the promised scope
What are the explanations for such colossal failures? Currently there are at least three different schools of thought on this topic:
- The Standard Economic Theory
- The "Mass Delusion" Theory and
- The "Machiavelli Factor" Theory
The Standard Economic Theory Explanation
The classical economic theory states that our high failure rates on projects are very simple to explain. If companies take rational risks in order to earn abnormal incomes, these poor outcomes are inevitable. One of the key laws of the financial theory states that in a perfect market, the higher the expected return of an asset, the higher is the inherent risk associated with it.