Estimate how long a new project will take based on historical team performance.
Online demo: https://skillfire.co/project-forecaster
It gives an objective view of the uncertainty around project estimation based on historical data.
Despite having the word estimation in its title, this qualifies as a #NoEstimates technique!
Single file version is monte-carlo-estimation.html using Ractive.js, ported from the older meteor.js version.
Enter the number of user stories completed by a team over a number of sprints, e.g.
| Sprint | Completed stories |
|---|---|
| 1 | 5 |
| 2 | 6 |
| 3 | 5 |
| 4 | 7 |
| 5 | 6 |
| 6 | 9 |
| 7 | 12 |
| 8 | 3 |
| 9 | 4 |
| 10 | 8 |
In the box Completed stories in past sprints you would enter
5 6 5 7 6 9 12 3 4 8
The other input is the number of stories in an upcoming project, say 85. The tool is limited to between 1 and 1000 stories.
Then press the Simulate 10,000 times button and the site will run 10,000 simulations and calculate a distribution reflecting the range and frequency of project durations.
- You could alternatively use story points (or any other units) instead of number of stories, which would make this a #Estimates technique. ;-)
- Sprint length is similarly arbitrary.
- Additional stories that occur due to scope expansion, and time diverted to other areas by the team is not reflected. You'll need to allow for that yourself.
I was introduced to Monte Carlo estimation by Adrian Fittolani. He has a blog post with spreadsheet implementation and video documenting his approach. My method is simpler (no use of Takt time or re-sampling).
My frequent collaborator Tim Newbold got this project started and kicked off the coding.