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Jira Estimation and Story Point Practice Review

Table output

Review story points, subtasks and estimate-versus-actual patterns in a Jira export to see if estimates help planning, without grading people.

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Please review how our team uses estimates in Jira and whether they help us plan. This is about the practice, not individuals. Mark any statement about Jira estimation fields or reports [VERIFY].

Inputs: completed issues with key, type, story points or hours, created, started and done dates, and sprint [ESTIMATE_EXPORT], how we estimate (planning poker, one person, no rules) [ESTIMATION_METHOD], our sprint length [SPRINT_LENGTH], and what decisions we make using estimates [ESTIMATE_USE].

Return: (1) a distribution table: each point value, count of issues, median and range of elapsed days; (2) an assessment of whether bigger estimates actually take longer, in plain language and with a simple correlation described in words, noting that the sample may be too small; (3) a list of items that were far off, with possible reasons stated only if the export supports them; (4) subtask usage: how many parents have subtasks and whether subtasks have separate estimates that double count; (5) a velocity or throughput view for the last six sprints with the arithmetic and a plain comment on variability; (6) a recommendation on whether to keep points, switch to counting items, or use size buckets, with trade-offs; (7) a short agreement the team could adopt, no more than six lines.

Guardrails: do not use velocity to compare teams or to set targets. Do not invent numbers. If data is missing, name it. Present options, not mandates.

Add a worked example with invented sprint figures: 21, 18, 25, 19, 30, 22 points. Show the average 22.5 and range 18 to 30.

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