alt Hacker NewsWhen teams don't need strong estimates, then Kanban works well.
When teams do need strong estimates, then the best way I know is doing a project management ROPE estimate, which uses multiple perspectives to improve the planning.
https://github.com/SixArm/project-management-rope-estimate
R = Realistic estimate. This is based on work being typical, reasonable, plausible, and usual.
O = Optimistic estimate. This is based on work turning out to be notably easy, or fast, or lucky.
P = Pessimistic estimate. This is based on work turning out to be notably hard, or slow, or unlucky.
E = Equilibristic estimate. This is based on success as 50% likely such as for critical chains and simulations.
Replies
Three-point or PERT estimates are in the same vein, but are just an old and established business process concept and not a trademarked "project" from a (defunct?) consultancy.
https://en.wikipedia.org/wiki/Three-point_estimation
https://projectmanagementacademy.net/resources/blog/a-three-...
And yeah, they can be useful when you can must put numbers to things and can decompose the work into familiar enough tasks that your estimation points are informed and plausible. Unfortunately, in a field often chasing originality/innovation, with tools that turn over far too often, that can be a near-impossible criteria to meet.
This sounds like that if you don't trust a fortune teller, you can mitigate it by going to 4 different fortune tellers, and then somehow combining their predictions into your much more certain future.
So now you have 4 wrong estimates to work with :) To have some predictability you should have small features. That's the only thing that can give you strong estimates. No industry has solved giving strong and correct estimates - it's in the name, it's estimation!
> E = Equilibristic estimate. This is based on success as 50% likely such as for critical chains and simulations.
I've found giving probabalistic estimates to be hopeless to effectively communicate, even if you assume the possible outcomes are normally distributed, which they aren't.