Thank you for the article. I was sent here by a team member.
My intuition and what I've used in my career is the following:
1) Estimate the tasks
2) Think about everything that can go wrong, add to the estimates.
3) Satisfied with the results? Multiply by 2.
Using the log-normal distribution above, it looks like this results in roughly P75. In other words, with this estimate, my tasks will be properly estimated or over-estimated 3 times out of 4. That seems like a good cost balance for project success. (3 projects on-time, 1 project late).
Nice article. You have found a pattern quite similar to what I found comparing project estimates. When I researched further I found that this pattern was quite common. p10 at 1x, p50 at 2x, and p90 at 4x. Your pattern is a bit different as you have p50 at 1x and p90 at about 4x, but then I expect differences as you are at the task level and I measured at the project. As you say, lognormals add together and stay lognormal, but the standard deviation decreases. As tasks add up to be projects the range becomes smaller. As always one of the big challenges is that data is not readily available. Can you make the data available in some form?
Thank you for the article. I was sent here by a team member.
My intuition and what I've used in my career is the following:
1) Estimate the tasks
2) Think about everything that can go wrong, add to the estimates.
3) Satisfied with the results? Multiply by 2.
Using the log-normal distribution above, it looks like this results in roughly P75. In other words, with this estimate, my tasks will be properly estimated or over-estimated 3 times out of 4. That seems like a good cost balance for project success. (3 projects on-time, 1 project late).
I will keep using the "times 2" formula.
Nice article. You have found a pattern quite similar to what I found comparing project estimates. When I researched further I found that this pattern was quite common. p10 at 1x, p50 at 2x, and p90 at 4x. Your pattern is a bit different as you have p50 at 1x and p90 at about 4x, but then I expect differences as you are at the task level and I measured at the project. As you say, lognormals add together and stay lognormal, but the standard deviation decreases. As tasks add up to be projects the range becomes smaller. As always one of the big challenges is that data is not readily available. Can you make the data available in some form?
This is a superb article -- and that’s coming from somebody who doesn’t know much about maths or probability. Thank you! 🙏🏻