"Try not to become a man of success, but rather try to become a man of value.”- Albert Einstein
I completed the series on the well-formed schedule, but the final post, on adding risk buffers, was pretty light. I want to take a couple of posts and expand on the topic of risk-based or risk-adjusted scheduling, which also will start some interesting metrics discussion.How tough is the job of project management? Planning a new project, the PM prepares a schedule that documents months in advance a completion date. What is that PM’s probability of success?
It turns out that this is a fairly easy mathematical calculation. If you have all of the tasks estimated and know the probability of success for each individual task, then you can calculate the project’s probability of success – the probability of completing the project on schedule. You merely multiply the probabilities of success for each task (in the critical path) together.For a simple example, if you have a 10-task project (each task in the critical path) and you’ve estimated each task with a 50% likelihood of success (i.e., equally likely to finish early or late), then the likelihood of completing the project on time is 0.50 x 0.50 x 0.50 x … or 0.5010 or 0.09.8%. With a very simple project, you have less than 1 in 1,000 likelihood of completing your project on schedule.
Even if you upgrade the individual tasks to a 90% probability estimate, you only have a 35% chance of success (1in 3) in this example. And with each task you add, the probability of success drops proportionately. To emphasize the point: even when you use aggressively conservative scheduling, you will miss the date more often than you hit it.In other words, we’re screwed before we start.
This sounds very pessimistic. What are the best practices that can improve this performance? I explore that in my next post. Stay tuned…How do you generate estimates on individual tasks? What is your expectation for the task success?