Downtime Pareto & Top-Loss Report: Target the Vital Few, Not the Anecdotes

The problem this kills

Every morning meeting has the same fight. The line missed its numbers, and now three people are arguing from memory about why. One blames the changeover. One blames the old labeler. One blames "material issues." Everybody has a story, nobody has the ranked truth, and the action items that come out of it are whatever the loudest person wanted anyway.

Meanwhile the answer is sitting right there in your downtime and scrap logs — already coded by reason. The trouble is that a pile of coded events isn't an answer. Someone has to pivot it by reason and machine, total the minutes and units, sort it, and figure out which handful of causes are actually eating most of the loss. That's a spreadsheet chore nobody has time to redo every day, so it doesn't get done, and the meeting keeps running on anecdotes. You don't need to be a developer to fix this.

What you'll build

A simple internal web tool. You import your downtime log (and/or scrap log) — the CSV you already keep, where each event has a reason code, a machine, a timestamp, and a duration or quantity. The tool aggregates the losses by reason × machine × line × period, ranks them largest-first, and draws the classic Pareto view: bars for each loss reason plus the cumulative-percent line that shows you the "vital few" causing 80% of the pain. You can filter by machine, line, and date range, so the daily huddle and the weekly review each get the cut they need. Your CI lead reviews the ranked losses, selects the focus items to act on, and assigns an owner to each one. Only then does the tool email the report out via Resend and produce a clean CSV.

What's inside the Implementation Plan

The downloadable plan is a step-by-step file you paste into an AI coding agent. It opens by interviewing you about your plant — what your downtime and scrap logs are exported from, exactly how your columns are named, what your reason codes and machine/line naming look like, whether loss is measured in minutes or units (or both), your typical and peak event volumes, who runs which meeting, and the messy edge cases like uncoded events and overlapping stoppages — and then it tailors the data model, the aggregation, and every later step to your answers. This is not a generic template; the agent reflects a short spec back to you and waits for your thumbs-up before it builds anything. From there it walks the agent through the import, the aggregate-and-rank logic, the Pareto chart with filters, the CI-lead review-select-and-assign-owner screen, and the email send — each step with a ready-to-copy prompt. There's also a fallback so you can build the whole thing today even with no API to your MES or historian: log CSV in, Pareto report CSV out.

The governance it includes (this is the point)

Even a "just a report" tool earns trust by shipping the controls a plant needs: login so only your team can use it, row-level security so you only ever see your own plant's data, a complete audit trail of who selected which focus items and assigned which owners and when, and a hard human-approval gate so the report isn't distributed until your CI lead signs off on the focus items and owners. Re-importing the same log is safe — duplicate guards keyed on each event's source reference mean the same stoppage can't be double-counted and skew the Pareto.

Who it's for

Continuous-improvement leads, plant managers, and shift supervisors who run the daily and weekly improvement meetings and are tired of debating anecdotes. If you can describe how your reason codes work and where your downtime log lives, you can build this.

You've got this — start with the plan, paste the first prompt, answer the interview, and you'll see your top losses ranked into a Pareto the same afternoon.