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1. Alan-Tactical Nuclear 🐧 (alan@mastodon.technology)'s status on Friday, 11-Feb-2022 15:24:04 UTC Alan-Tactical Nuclear 🐧

   I'm against scrum in general, but even more so for scrum applied to Data Science or research in general. If you had to do proper scrum with these things you'd have tasks like: thinking hard about this - 5 points; staring at the screen looking at charts - 8 points; redoing everything with slightly different parameters - 8 points.

   Does it make sense?

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   • Alan-Tactical Nuclear 🐧 (alan@mastodon.technology)'s status on Friday, 11-Feb-2022 15:39:15 UTC Alan-Tactical Nuclear 🐧

     in reply to

     • Jens Finkhäuser 🌻

     @jens you need to be managed 😜
     Jokes aside, the point is that it's "needed" only for non-working people, aka managers/product managers/etc., if I'm spending 3 months on a topic I know all the ins and outs, and I know how to record the things I care about along the process. I don't need to be handheld and I'm perfectly capable to help the people who need some organization without standups, kanbans and whatnots.

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   • Jens Finkhäuser 🌻 (jens@social.finkhaeuser.de)'s status on Friday, 11-Feb-2022 15:39:17 UTC Jens Finkhäuser 🌻

     in reply to

     @alan Scrum is generally better for production than for research. But research also needs to be managed, and doing that usually means defining the task goal as having answered a question or three.

     And if time runs out, you still have partial answers that allow you to define the next question better, etc.

     It works, if you want it to.