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AI PromptsCategoriesOperations Intelligence

⏳ Measure How Long Work Actually Takes

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Measure How Long Work Actually Takes

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We tell customers a lead time based on nothing and then miss it. Build me a cycle time app. For every piece of work, record when it was received and when it was genuinely finished from the customer point of view, along with the intermediate stage timestamps, so the measure includes all the waiting rather than only the time we were working on it. Show the distribution of cycle times rather than only the average, since the average is not what you should promise, and identify a realistic percentile to quote from. Break it down by work type, customer, size and period, and show variability alongside speed. Add an AI agent that reviews the data and tells me what the items in the slowest group have in common, whether that is a particular type, customer, entry point or time of week, and what lead time we could confidently promise for each work type. Automate two things: a scheduled monthly cycle time report, and an alert when any live item passes the point where it will breach the quoted lead time, while there is still time to act. Two logins: a team member who sees their own work, and an operations owner who sees the analysis.

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01 / Spark - intelligence awakens

Measure How Long Work Actually Takes

Measure real end-to-end cycle time with variability, derive a defensible quoted lead time, and find what makes work slow.

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// the spark catches · intelligence awakens · the answer unfolds

Lead times are quoted from memory and usually from the best case. This measures real end-to-end time including the waiting, so what you promise is what you deliver.

What's Included

  • End-to-end time measured including every wait.
  • A realistic quoted lead time from your own distribution.
  • Variability shown because consistency matters as much as speed.
  • An assistant that finds what makes an item slow.

How To Use

  1. Measure end to end, including waiting. Customers experience the whole thing.
  2. Quote from a realistic percentile, not from the fastest job you ever did.
  3. Track variability. Unpredictable is worse than slow.
  4. Compare by type. One category often drags the whole average.

Diagnose it with bottleneck analysis, and set expectations in quote prompts.

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