Back in the dark ages when access to computers was not all that common, I was faced with developing a project schedule for, to me, a complex construction project. I was not that long out of school, so I sought out my boss with the hope he would give me some guidance on how to approach the problem.

He told me to use three-point estimation and to talk to some of the older engineers in the firm to get their ideas on the likely outcomes. So, I did and learned that the three points he was talking about were the worst case, the best case, and the most likely case for what would happen during the project. (Wikipedia, n.d.)

He also directed me to consider using PERT. I did and learned that form of project management scheduling including consideration of the optimistic time estimate (o), the most likely or normal time estimate (m), and the pessimistic time estimate (p). In PERT, instead of using probabilities for each estimate of the time required, the task time is calculated as (o + 4m + p) ÷ 6. (Taylor Jr., 2011)

To model a three-point estimate with a probability distribution you need to use a triangular distribution. Today, three-point estimates are commonly used in business and engineering, so it is somewhat surprising that Excel does not have a built-in function to help. I was recently faced with this dilemma in my quantitative methods course which I am trying to migrate away from expensive software solutions. [Read more…] about “Easy” Excel Inverse Triangular Distribution for Monte Carlo Simulations