Tuesday, April 6, 2010

The Failure of Success

I have written quite a bit about the cost of IT failure, most recently in a white paper. A number of people have criticized my analysis saying that just because a large project "fails" in the sense of being late, over budget, and/or not delivering expected functionality, doesn't mean that the project doesn't deliver value.

This may be true. The real question is this: had the business known how the project would have gone, would they still have agreed to do the project? If the answer to this is yes, then the project was a success. If the answer is no, then the project is a failure.

However even when the project comes in on-time, on-budget, and delivering expected functionality, the project may still not be a  success. These three metrics (budget, time, functionality) tells us little about the project itself and much more about our ability to make predictions about the project.

Take a simple example. The business tells IT they need a system that delivers 100 functions. IT calculates the cost at $100K/function. They tell the business the project will cost $10M and three years to deliver. Business approves the project. IT delivers the project one month early and $1M below budget. The business is happy. IT looks good. The project is a success!

Or is it? All this tells us is that IT did what they said they would do. It doesn't tell us whether what IT said they would do was really reasonable.

In most projects that size, complexity is a major cost factor. If IT and the business take appropriate steps to manage that complexity, the cost/function can be greatly reduced. If a project can be delivered for $9M without complexity management, then it is highly likely that it could have been delivered for $5M with complexity management.

So is this project a success or a failure? According to most pundits (such as Standish) this project is an unqualified success. In my book, it is a $4M failure. This is one more reason I say that looking at the percentage of IT successes is a meaningless statistic. What we need to look at is the percentage of IT budgets that are wasted.