Performance visibility: seeing losses while the shift can still act
This pillar looks at how a plant records its losses and how quickly the people running a line see that they are behind. The test behind all five questions is whether the right figure reaches the right person in time to change the shift, and whether they believe it.

Why visibility sets the ceiling for the other five pillars
Every other practice in the index runs on information someone captured. A daily meeting can only discuss the stops that were recorded. A Pareto can only rank the reasons operators were able to choose. An escalation rule only fires if somebody sees the stop in time.
When visibility is weak, the rest of the system works hard on a partial picture. Teams argue about whether a loss happened instead of why it happened, and improvement projects target the losses that were easy to record rather than the ones that cost the most.
Timing is the other reason this pillar carries weight. A loss found in next week's report can only be explained. A loss seen within the hour can still be recovered in the same shift, or at least contained before it repeats. Most of the distance between Level 2 and Level 4 here is the distance between explaining a shift and steering one.
The pillar is not about screens. A paper hour-by-hour board filled in honestly by the team scores higher on speed of knowing than a dashboard in an office nobody at the line looks at. We score the practice around the data, whatever tool carries it.
Nothing in this pillar depends on how high your OEE or TRS is. If you want to compare figures between plants, benchmarks are covered at oee-benchmark.org and monitoring set-ups at factorymetrics.org. Here the only question is whether your measure is captured, defined, trusted and used.
The five levels as you would see them on the floor
The table describes what a plant typically looks like at each level of this pillar. Your pillar index from the assessment places you in one of these rows. The overall level follows the weakest-pillar rule explained on the levels page, so a low score here holds the whole plant back.
| Level | What you see on the floor | What the numbers look like in meetings |
|---|---|---|
| 1 Reactive | No stop records at the line, or a logbook listing only the big breakdowns. Any boards are weeks out of date. Operators cannot say what yesterday's output was. | Output is discussed from memory or taken from the ERP at month end. Downtime is described in anecdotes: 'the press was down a lot on Tuesday'. |
| 2 Aware | Paper sheets per shift, typed into a spreadsheet later, often days later. An efficiency or OEE figure exists, but each line or shift calculates it its own way. | Yesterday's or last week's figures. Output counts are accepted, downtime is argued over, and some supervisors bring their own tallies to the meeting. |
| 3 Structured | Operators log stops during the shift against a reason list. Results are posted at the line once per shift. One written definition of the measure applies plant-wide. | End-of-shift figures on one definition, mostly accepted. Short stops are missing, so a gap between recorded downtime and lost output stays unexplained and nobody owns it. |
| 4 Proactive | Stops are detected from a machine signal and operators assign reasons within the shift. An hour-by-hour plan-versus-actual board or screen sits at the line. Operators see their losses in the categories management uses. | Figures within the hour. Losses are split into availability, performance and quality and reconciled weekly with good-part counts. Discussion is about causes, not about whether the figure is right. |
| 5 Excellent | Every stop and speed loss is captured, reasons are assigned within minutes, and unexplained stop time is tracked as a data-quality measure. Alerts fire on set thresholds with a pre-defined response. | The same data serves every level, cut to scope, and is used directly for staffing and investment decisions. Definitions are aligned across the group's sites and data quality has a named owner. |
The five questions and how plants misjudge themselves
Each question below is answered on a five-point scale. For each one: what we are really asking, where self-assessments usually go wrong, and a check you can run this week before you answer. Answer for your bottleneck line on a normal week, not your best line on your best week.
1. How are stops and losses captured? We are asking whether the record of lost time on your bottleneck is complete enough to act on, and how soon after the event it is written. The usual over-rating is answering 3 or 4 because a terminal or a reason list exists, while stops of a minute or two never reach it.
Take five recent shifts on the bottleneck. For each, work out what the line should have produced in the time it was recorded as running (running time divided by ideal cycle time) and compare it with actual output. Convert the difference back into minutes by multiplying it by the ideal cycle time: that is lost time your records do not explain. If it is larger than your biggest single recorded stop reason, short stops and speed loss are going uncaptured. Also count entries coded 'other': if 'other' sits in your top three reasons, the list is not working.
2. How quickly does the line leader know the line is behind? Knowing means seeing it, not sensing it. Plants over-rate when a live screen exists in the supervisor's office but not at the line, or when an hour-by-hour board is filled in at the end of the shift in one go. The handwriting usually gives that away: same pen, same slant, every hour.
On three different days, at a random time mid-shift, ask the bottleneck line leader how many parts they are ahead or behind plan right now. Then check. If the answer takes more than a minute to find, or turns out to be a guess, you are at end-of-shift visibility whatever equipment is installed.
3. Which measure do you use, and how is it defined? OEE, TRS or an efficiency ratio all qualify. The question is whether everyone calculates it the same way. Over-rating happens when lines disagree on planned time: whether breaks, changeovers, preventive maintenance or no-order periods count. Under-rating also happens: plants with a clear written definition of a home-grown ratio sometimes answer 2 because it is not called OEE.
Ask two supervisors and the plant controller, separately, to calculate last Tuesday's figure for the same line and to write down the planned time and ideal cycle time they used. If the three sheets differ on either input, you do not yet have one definition.
4. Do people trust the numbers? Watch what happens in the morning meeting when a figure looks bad. The trap is answering from the manager's chair. The people who distrust the figures are often not in the room, and they show it by keeping their own counts.
Walk the bottleneck line and the maintenance office and list every private tally you find: notebooks, personal spreadsheets, whiteboard counts. Each one is a vote of no confidence. Then time how many minutes of the next three morning meetings are spent debating whether a number is right.
5. Who sees line performance, and in what form? We are asking whether the people who can change the result see it while they still can, in the same terms as management. Plants over-rate when results are posted at the line in a format nobody reads, such as a printed pivot table, or when the line uses different loss categories from the monthly review.
Ask an operator on the bottleneck what the biggest loss on their line was last week. Ask the plant manager the same question. If they name different losses, or the operator cannot answer, you are not yet at Level 4 on this question.
What Level-4 plants do differently
Plants at Level 4 on visibility rarely have more data than others. They have fewer arguments about it, because they set explicit rules for how data is captured, checked and shown. These are the practices that tend to separate them.
- Unexplained time is treated as a defect. No shift closes with stop time that has no reason. The team leader checks it before the handover, and the share of unexplained time per shift has a named owner.
- The capture threshold is a written decision. They decide the shortest stop that must carry a reason, write it in the definition, and group anything shorter as short stops so it stays visible as a block of time rather than vanishing.
- Operators have one data job. The machine signal records when the line stops; the operator only assigns the reason. Asking operators to log start and end times as well is what made earlier systems fail.
- A one-page definition, signed. Planned time, ideal cycle time per product and what counts as a good part, with a worked example. Production, maintenance and finance sign it, and only one named person can change it.
- A 15-minute weekly data check. Counts against shipments or the ERP, recorded time against calendar time, and a written list of corrections with the cause of each. The same errors appearing twice become a problem to solve.
- Hour-by-hour boards the team fills. The team writes the number each hour and a reason next to every missed hour, in their own words. The supervisor initials the board on their walk, which is how you know it was filled live.
- Alert thresholds with a named response. For example, two missed hours in a row, or a stop longer than the escalation limit, brings a named person to the line within a set time. The threshold and the response are written on the same sheet.
- One loss tree from line to plant. The categories on the line board match the ones in the monthly review, so an operator and the plant manager can talk about the same loss without translating.
A 90-day plan to move up one level
Your report gives a specific next move for each question, based on where you answered. The plan below combines them for one typical starting situation: stops logged on paper or in a spreadsheet, figures seen the next day, and a measure that varies between lines. Run it on the bottleneck only. Extending to other lines comes after it holds.
- Weeks 1–2Name the bottleneck line and the owner of this plan. Write the one-page definition of your measure and recalculate last month with it. Run the unexplained-gap check on five shifts and keep the result as your baseline. Put up a plan-versus-actual board on the bottleneck, even if it is filled at the end of the shift for now.
- Weeks 3–6Turn the free-text stop reasons from recent weeks into a list of 15 to 25 codes. Move data entry into the shift. Switch the board to hour-by-hour, with a reason next to every missed hour. Start the weekly 15-minute data check and log every correction. If the equipment allows, connect one run/stop signal on the bottleneck machine so stops are detected without anyone writing them down.
- Weeks 7–12Publish unexplained stop time per shift, with the named owner. Post the shift's losses at the line using exactly the categories management reviews. Write one alert threshold and the response that goes with it. At week 12, repeat the unexplained-gap check and the mid-shift question, then retake the assessment and compare your answers question by question.
Who owns what during the 90 days:
- Production manager: owns the definition, chairs the weekly data check and decides the alert threshold.
- Team leaders: the hour-by-hour board, reasons assigned before handover, and explaining the biggest loss to the next shift.
- Maintenance lead: checks every downtime entry over 30 minutes against the maintenance log for the first month and flags mismatches.
- Controller or finance: co-signs the definition and supplies the good-part count used for reconciliation.
- Engineering or OT: the machine signal and the ideal cycle times per product.
- Continuous improvement lead: builds the reason list with operators and runs the week-12 checks.
Evidence a jury looks for in verification
In verification, the plant uploads evidence and then holds a 45-minute video interview with two jurors. For this pillar, jurors look for artefacts produced by the routine itself, dated and in use, rather than documents prepared for the review.
- Photos of the hour-by-hour board over several consecutive days, showing different handwriting and reasons next to missed hours.
- The written definition of the measure, dated, with the functions that agreed it.
- A raw export or copy of one week's stop log for the bottleneck, showing how much stop time carries a reason.
- Records of the weekly data check: the corrections found and their causes.
- What operators see at the line next to the management report for the same week, so the jury can compare loss categories.
- The alert or escalation threshold sheet as it is posted at the line.
- A trend of unexplained stop time, if you claim Level 5 on the first question.
What does not count: an undated dashboard screenshot, a board photographed freshly written, monthly management slides on their own, or a system specification. A system being installed is not a practice. Be ready in the interview to walk the jurors through one recent shift from the log, and to explain one correction the data check found.
Pitfalls that keep plants stuck on this pillar
- Buying a screen before agreeing a definition. You get faster numbers that are still disputed, and the disputes now happen in front of operators.
- Reason lists that keep growing. Past a few dozen codes, operators pick the first plausible one or 'other', and the Pareto stops meaning anything. Prune the list every quarter.
- Flattering planned time. Excluding changeovers or no-order time until the figure looks good. The number rises and nothing on the floor changes.
- Asking operators to record everything. Start time, end time, reason, part number and comment for every stop. They comply for a month, then the log thins out.
- A percentage without the loss behind it. Showing operators an OEE figure tells them how they did. Showing the three biggest losses tells them what to do.
- Comparing lines on different ideal cycle times. One line uses the nameplate speed, another the best demonstrated rate, and the league table between them is meaningless.
- Handing data quality to IT alone. The errors come from the floor and the fixes are in the routine, so production has to own it.
Where to go next
If you have not yet scored your plant, the FEI assessment takes 12 to 15 minutes and gives you this pillar's index alongside the other five, with a 90-day move for your three biggest gaps. The methodology explains how answers become scores. Visibility gives your teams information; the next pillar, daily management and shift routines, covers how that information turns into action on the same day.
Questions
Can we reach Level 4 on this pillar without connected machines?
Yes. Only the Level-4 answer to the first question requires a machine signal. An hour-by-hour board filled by the team, a shared definition reconciled weekly, a routine data check and operators seeing losses in management's categories can all be done on paper. Four answers at 4 and one at 3 give a pillar index of 700, which is inside Level 4.
Does it matter whether we use OEE, TRS or our own efficiency ratio?
No. The assessment asks whether the measure is written down, applied the same way everywhere and broken down into losses. A home-grown ratio that meets those conditions scores the same as OEE.
Should we answer for the whole plant or for one line?
Answer for your bottleneck line on a normal week. It is the line whose losses cost the plant output directly, and it is where jurors will ask to start if you apply for verification.
How short a stop do we need to capture?
The model does not fix a duration. What it looks for is that the threshold is written down, that stops below it are still counted as a block of short-stop time, and that the unexplained remainder is visible. A plant that writes its threshold down and measures what falls below it is ahead of one that captures more but cannot say what it misses.
How is this pillar different from Data and connectivity foundations?
Visibility is about practice: what is captured, how fast people see it and whether they trust it. Data and connectivity foundations covers the infrastructure underneath, such as machine connections, reference data, integration and OT security. Plants with strong routines but low scores on both often fall into the 'strong routines, blind data' profile in the report.