At my work, we have P1 and P2 tickets. Ideally you get them all done in a week, but you're only supposed to have 3 days worth of P1 tickets, so it's required to have all the P1s done.
It worked really well for a few weeks. Then the PM started putting 4, 5, I even had one week where I had 9 days worth of P1 tickets assigned.
I'm growing very tired of this company.
Are P1/P2 designations? If so, how in the world can those be correlated to time/workload?
They have a priority + estimated number of hours
I guess it makes somewhat intuitive sense. When I give an estimate, I'm probably more like to say "it'll take 2 weeks. Maybe less, maybe more" and that maybe/maybe is 50%/50%, which suggests that the estimate is the median, not the mean.
I like the thinking. I think looking at task uncertainty is much more useful than task size. Task size can easily be managed by breaking it up. Uncertainty can't be managed in the same way.
My favorite approach I’ve seen is just units of time -“this task will take a few [days/weeks/months/years]”.
No specific number. Instead, the scale of the task is measured in one of those units and I can give you an estimate but it’s just a guess.
If it’s task that might take “a few days”, it could be done tomorrow or it could take 5 days. If it’s one that takes “a few weeks”, it might be done next week or maybe next month.
Breaking larger tasks down effectively removes uncertainty.
My general rule of thumb in planning is that any task that is estimated for longer than 1 day should be broken up.
Longer than one day communicates that the person doing the estimate knows it’s a large task, but not super clear about the details. It also puts a boundary around how long someone waits before trying to re-scope:
A task that was expected to take one week, but ends up going 2x is a slide of a week, but a task that is estimated at one day but takes 3x before re-scope is a loss of 2 days.
You can pick up one or two days, but probably not one or two weeks.
I think that's neat but I doubt a lot of product managers would like that 😅.
What happened to estimating the pessimistic, most likely and optimistic times and apply that to a beta distribution? That's how I was taught back in the dark ages.
agile happend
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