What are the implications of this distribution for real projects? Because the peak of the curve lies at approximately 0.6 sigma, we see that the most likely outcome (as measured by the curve's height) is an unsuccessful project! In fact, if the peak were exactly at 0.5 sigma, your probability of success would be only around 16 percent:
Because the peak is not at 0.5 sigma but closer to 0.6 sigma or 0.7 sigma, the probability of success is a little higheraround 20 percent.
Now this is starting to become very interesting, because the Standish CHAOS report, of which I have always been somewhat skeptical, implies about a 20 percent success rate. I will have more to say about this report later on. But it is interesting to note that the lognormal distribution predicts the Standish metric as the most likely outcome, which may mean that most development projects have a built-in difficulty factor that causes the lognormal distribution to obtain.