3-Points Estimating

last edited by: Frederic Casagrande on Nov 28, 2018 7:19 PM login/register to edit this page

Contents
1 Overview
2 Application
3 Example
4 Other Estimating Techniques
5 References

Overview

3-Points is a technique that involves people that are professional in the task we are estimating by this technique. In three-point estimation, three figures are produced initially for every distribution that is required, based on prior experience or best-guesses:

The first is a most likely (M)/best guess (BG) which is the average amount of work the task might take if the team member performed it 100 times. The second estimate is the pessimistic (P) estimate which is the amount of work the task might take if the negative factors they identified do occur. The third estimate is the optimistic (O) estimate which is the amount of work the task might take if the positive risks they identified do occur.

Application

Two popular formula:

1. Triangular distribution:

Triangular Distribution: E = (o + m + p ) / 3

where E is Estimate; o = optimistic estimate; p = pessimistic estimate; m = most likely estimate

2. Beta (or PERT):

Beta Distribution (PERT): E = (o + 4m + p ) / 6

The beta distribution is a weighted average in which more weight is given to the most likely estimate. This alteration to the formula and placing more weight on the most likely estimate is made to increase the accuracy of the estimate by making it follow the Normal Distribution shape. Hence, in most of the cases, the Beta (PERT) distribution has been proven to be more accurate than the 3-Point triangular estimation.

Example

For Activity A:

o = 4 hours , m = 8 hours , p = 16 hours

Triangular Distribution:

E = (4 + 8 + 16 ) / 3

E = 24 / 3

E = 9.3 hours

Beta Distribution (PERT):

E = (4 + 4(8) + 16) / 6

E = 52 / 6

E = 8.7 hours

Other Estimating Techniques

  • Bottom-Up estimate
  • Parametric estimates
  • Analogous estimates

References


last edited by: Frederic Casagrande on Nov 28, 2018 7:19 PM login/register to edit this page


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