Daily management

Performance board

Performance board is licensed CC BY 4.0. Attribution: Katafacts (katafacts.com).

1 · What it is

What it is

A performance board tracks the vital few KPIs that matter to a function — a Plan and an Actual for each, period by period — and computes each period's status directly from the numbers: green if the actual meets or beats plan, red if it misses. Any KPI with a real sustained problem (two or more consecutive red periods) is named directly, and so is a single isolated miss — kept separate, deliberately, because reacting to both the same way is a well-documented failure mode: teams end up root-causing ordinary noise instead of a real trend, and credit a countermeasure for a recovery that would have happened anyway. When a period does come in red, that's the trigger to log it in the abnormality log (a direct, gemba-observed root cause, never speculation) and open a countermeasure with a real owner and a target date.

2 · When to use it

When to use it — and when not to

Use it when

A function already has (or can name) a small set of KPIs with real plans, and wants an honest, computed record of how each one is actually tracking, not a subjective status update.
You want misses to trigger real root-cause work automatically, with a closed loop back to a countermeasure and a verification step, not just a color that gets glanced at and forgotten.
You want to know honestly which misses are worth chasing (a real, sustained pattern) and which aren't (a single blip that already recovered) before spending root-cause effort on the wrong one.

Not when

You don't have a real plan or target for the KPI yet, just a hope it goes the right direction — set a real plan first, or every period will just read as an ungrounded pass/fail.
The KPI genuinely doesn't have periodic data behind it (it's a one-time measurement, not a recurring one) — a performance board tracks something reviewed on a real cadence, not a single number.
You're tempted to list every KPI you could possibly measure — a board with thirty rows nobody actually reviews is worse than five that genuinely get discussed every cadence.

3 · How to fill it in

How to fill it in

KPI matrix: Describe the function and what matters to it — a first-pass set of KPIs gets drafted, each with a monthly plan. Enter actuals yourself as each period actually closes; a real number is never invented.
Coverage: Computed for you from your KPIs, once actuals are entered — nothing to enter here.
Abnormality & root cause log: Log one whenever a period comes in red — a real gemba-observed cause and a 5-why root cause, not a guess.
Countermeasures: What will restore the standard, owned and dated — containment (fast, protects delivery now) or permanent (fixes the root cause).
Narrative: Drafted from the board actually built.

4 · What good looks like

What good looks like

The example below is a fabrication cell's quality board — first-pass yield genuinely is a sustained problem (two consecutive red months, the first countermeasure closed on time but didn't actually hold), while scrap rate had a single red month that recovered the next one and correctly doesn't get flagged the same way.

Same example, as a downloadable xlsx workbook.

Download .xlsx

Performance board · Fabrication Cell 3 — Quality · Monthly Quality Review

Fabrication Cell 3 — Quality performance board

Dana Ruiz, Cell Lead · 2026-04-10 · H1 2026

Team: Raj Patel, Controls Engineer · Sponsor: Marcus Lee, Quality Manager

KPI matrix

First-pass yield

Quality · % · JOP 91 · higher-is-better

Sustained miss

	Jan	Feb	Mar	Apr	May	Jun	To date
Plan	96	96	96	96	96	96	96
Actual	96.8	96.1	94.5	93.8	—	—	95.3

Scrap rate

Quality · % · JOP 3.2 · lower-is-better

	Jan	Feb	Mar	Apr	May	Jun	To date
Plan	1.5	1.5	1.5	1.5	1.5	1.5	1.5
Actual	1.3	1.2	1.9	1.4	—	—	1.45

On-time delivery

Delivery · % · JOP 88 · higher-is-better

	Jan	Feb	Mar	Apr	May	Jun	To date
Plan	97	97	97	97	97	97	97
Actual	97.5	98.1	97.2	98	—	—	97.7

Coverage

On track

2 / 3

Sustained miss

Not yet reported

Unresolved abnormalities

Open countermeasures

Abnormality & root cause log

Scrap rate — Mar
closed
1.9% vs 1.5% Plan (+0.4%)
Gemba: A single bad reel of solder paste ran across two shifts before QC flagged it during the routine incoming-material check
Root cause: No hold point existed for a new solder paste lot until after it had already been consumed on the line
First-pass yield — Mar
closed
94.5% vs 96.0% Plan (-1.5%)
Gemba: Reflow oven zone 3 temperature drifted outside spec for several hours before the daily calibration check caught it
Root cause: Daily calibration check runs at shift start only, so a mid-shift drift isn't caught until the next day's check
First-pass yield — Apr
open
93.8% vs 96.0% Plan (-2.2%)
Gemba: Same reflow oven zone 3 drift recurred mid-shift, despite the March containment action
Root cause: The March fix added a second daily check, but a twice-a-day check still misses a drift that develops and self-corrects within a single shift

Countermeasures

Add a mandatory incoming-lot hold point: no new solder paste lot releases to the line until QC signs off
permanent · Marcus Lee, Quality Manager · Target: 2026-04-05 · Closed: 2026-04-02
Add a second daily calibration check at shift change, in addition to the existing start-of-shift check
containment · Raj Patel, Controls Engineer · Target: 2026-04-01 · Closed: 2026-03-28
Install continuous zone-3 temperature logging with an automated out-of-spec alert, replacing the twice-daily manual check entirely
Open
permanent · Raj Patel, Controls Engineer · Target: 2026-05-15

Narrative

First-pass yield is a genuine sustained miss, not noise: two consecutive red months ending in April, after the March containment action (an extra daily calibration check) failed to actually hold. That's exactly why a second, permanent countermeasure — continuous temperature logging instead of periodic manual checks — is now open rather than closed. Scrap rate tells the opposite story: March's spike was a real, closed abnormality with a real root cause, but April's recovery means it correctly reads as an isolated miss, not a trend worth re-alarming on. On-time delivery has stayed on track all four reported months with nothing to flag.

5 · Common mistakes

Common mistakes

Reacting to every red period identically, whether it's an isolated blip or part of a real trend.
A single miss with no real pattern behind it is usually ordinary variation — root-causing it wastes effort, and when performance drifts back to green on its own, a countermeasure often gets wrongly credited for a recovery that would have happened anyway.
Logging an abnormality's cause from a guess instead of direct gemba observation.
A root cause written from speculation is usually wrong, and a countermeasure built on the wrong root cause doesn't actually fix anything — go and look before writing the cause down.
Tracking so many KPIs that none of them get real attention at the review cadence.
The vital few discipline applies here the same as everywhere else in this catalogue — a shorter list that genuinely gets discussed beats a long one that gets skimmed.

6 · What it connects to

What it connects to

upstream

First-pass yield tracker
A quality KPI tracked here often already has its own dedicated first-pass yield tracker feeding the real numbers this board's Actual row needs.

downstream

Escalation matrix
A sustained miss that a quick countermeasure can't resolve is exactly the kind of thing an escalation matrix's trigger condition should be checking for.

7 · Where AI helps

Where AI helps

Judgement — stays yours

Deciding which KPIs are actually the vital few worth tracking
Deciding whether a miss is worth chasing now or watching another period

Analysis — AI helps

Drafting a first-pass KPI set and monthly plan from a description of the function
Drafting the narrative from the board actually built

Drudgery — automated

Computing red/green status per period and the plan-to-date vs. actual-to-date rollup
Counting on-track, sustained-miss, and not-yet-reported KPIs
Exporting to xlsx in the house format

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