# Risk Management Technique – 3-Point Estimate

The 3-point Estimate is a mathematical technique for constructing an estimated distribution of probabilities reflecting the outcome of future events, based on limited information. In the project management area, it is one of the most effective techniques used to develop estimates. Dick Billows indicates its three advantages:

1. Increased accuracy over one-point estimates
2. Better commitment from the project team members because the estimate considers the risk in the assignment
3. Useful information on the risks of each task.

In 3-Point Estimate, three figures are produced initially for every distribution that is required, based on prior experience or best-guesses:

• O = the best-case (most optimistic) estimate
• M/BG = the most likely (best guess) estimate
• P = the worst-case (most pessimistic) estimate

More precisely, in project risk management, O stands for the amount of work the task might take if the positive risks team members identified do occur. M presents the average amount of work the task might take if the team member performed it 100 times. And P is the amount of work the task might take if the negative factors they identified do occur.

There are two commonly used equations of 3-Point Estimate: triangular distribution and double-triangular (or Beta) distribution. Compared with triangular distribution, the Beta distribution considers more weight on the most likely estimate. In most real-world cases, the Beta distribution has been proven to be more accurate than the triangular distribution. Moreover, the Beta distribution also is called PRET which stands for Program Evaluation and Review Technique. There are the equations of the distributions as follows.

1. Triangular distribution:

`E = (o + m + p ) / 3`

2. Double-triangular (or Beta, PRET) distribution:

```E = (o + 4m + p) / 6
SD = (p − o) / 6```

where E for both equations represents Estimate; SD is the standard deviation which measures the level of certainty of the Beta distribution.

References