The three shop reports that are worth reading

Most shop reporting is a dashboard nobody opens twice. It is not that the numbers are wrong — it is that knowing them does not change what anyone does. A number that cannot change a decision is decoration.

Three actually earn their place.

Cycle time

How long a job takes from arrival to handover.

This is the number the business is judged on, by customers who want their car back and by insurers and fleets who track it formally. It is also the number that most directly converts into capacity: cut average cycle time and the same shop, with the same people, finishes more cars.

Track the average and the distribution. The average tells you the trend. The distribution tells you whether you have a consistent process with occasional disasters, or no consistent process at all — and those need completely different responses.

A shop with a tight distribution and a high average has a systemic problem to fix. A shop with a low average and a long tail has a small number of jobs going badly wrong, and the useful work is finding out what those have in common.

Dwell per stage

How long jobs sit in each stage on average.

This is the diagnostic. Cycle time tells you the total is too long; dwell tells you where the time is. The stage with the largest dwell is the constraint, and it is very often not the stage anyone would have named.

It is reliably the least dramatic column. Waiting on approval. Waiting on a specific part. Waiting for one machine. Stages where nothing happens accumulate time precisely because nothing happening is not noticeable.

Dwell is only as good as the board's resolution. If active work and waiting share a column, dwell for that column is meaningless. Every stage you split is a question you can now answer.

Throughput over time

How many jobs finished this week, against previous weeks.

This is the one that separates a genuinely bad week from a week that merely felt bad. Shops run on impression, and impression tracks noise: a week with two angry customers and a supplier failure feels catastrophic even if output was normal.

Throughput over time also tells you whether a change worked. You fixed the constraint, cycle time should fall and throughput should rise. If neither moved, you fixed something that was not the constraint — which is worth knowing before you do more of it.

Why these three and not more

Every one of the three changes a decision.

Cycle time tells you whether to act at all. Dwell tells you where. Throughput tells you whether the action worked. Together they form a loop, and a loop is what makes reporting a habit rather than a screenshot for a meeting.

Most other shop metrics are either inputs to these or are genuinely accounting questions that belong in accounting software. Revenue per job, gross margin, technician efficiency — all real, all better answered by the system that holds the money.

The condition that makes them true

All three come free from a board people actually move cards on. None of them survives a board people update on Fridays.

That is the real prerequisite. Reporting built on a second data-entry step — a timesheet, a stage log, a weekly review where somebody reconciles what happened — is reporting that degrades exactly when the shop is busiest, which is when you most need it.

Numbers that come from work that happened anyway are the only kind that stay true.