Your Variance Report Reads Zero Because Nobody Told It the Truth
Startup scrap, off-spec output, offcuts and the remainder nobody will sell are written off as yield loss against a standard that was set to make the arithmetic balance. A variance report with nothing in it is not a well-run factory. It is a factory that is not measuring.
· 7 min read · Written by Faceela Research & Editorial Team
A production manager is asked why the cost variance report shows almost nothing. The answer, given honestly, is usually that the standard was adjusted at some point so that it matched what actually happens. Once that is done the report reads zero every month, everybody stops looking at it, and the factory loses its only instrument for knowing which of its losses are normal and which are not.
The losses have not gone anywhere. They have been merged. Startup scrap, off-spec output, process yield loss and unsellable remainder are four different things with four different causes and four different fixes, and in most factories they are one number called yield. Separating them is the entire exercise, and it is worth more than any amount of effort spent driving the merged number down — because two of the four are bought deliberately, one is a process problem and one is a planning problem, and the actions are unrelated.
That is the answer. The rest of this article is what the four are, why the standard has to be a decision rather than an average, and the sequence for getting real numbers without stopping production.
The four losses, and why merging them hides the money
Startup scrap. The material consumed bringing a process into specification — the first shots, the first metres, the run-up on a line. It is largely a function of how often you change over rather than of how well you run, which means it is a scheduling cost dressed as a production cost. A factory that reduces changeovers reduces it; a factory that exhorts operators to be careful does not.
Off-spec output. Product made outside specification once running. This is the one that is genuinely a process problem, and the one that responds to the interventions everybody reaches for first — which is why it gets the attention and the other three do not.
Process yield loss. Material that simply does not become product by the nature of the process: trim, evaporation, the kerf, the offcut. Some is irreducible physics and some is a design choice, and telling those apart is a technical argument worth having once a year rather than a monthly performance conversation.
Unsellable remainder. The part of a batch, a roll or a drum that is left after the orders it was made for are satisfied, and that nobody will ever buy in that size. A cable maker cutting a 500-metre drum for three orders is the clearest case. This is a planning and order-combination problem and it has nothing to do with the shop floor at all, but it lands in the same account.
Merge them and you get one percentage that moves for reasons nobody can attribute. Separate them and each has an owner: scheduling, process engineering, product design, planning. That is the whole value, and it is available before any of them is reduced by a single unit.
The standard is a decision, not an average
The temptation is to set the standard to the historical average, because then the variance is small and the accounts look clean. This is a category error worth naming, because it is committed by people who know better under pressure from people who do not.
A standard is a statement of what the process should consume when it is running properly. Its purpose is to make the difference visible. Setting it to the average guarantees the difference is nil, which is not a good result — it is the deliberate destruction of the measurement. The report then says what it was configured to say, which is the general failure mode described in why a report can be technically correct and completely uninformative.
Three practical rules keep it honest. Set the standard against a deliberately good run, observed, with the conditions written down. Review it on a schedule rather than when the variance is embarrassing — a standard revised the month it is missed is not a standard. And record the reason whenever it moves, because a standard whose history nobody can explain becomes untrustworthy within two years and then gets quietly averaged again.
The general version of this is that a number nobody owns drifts towards whatever makes the nearest problem go away, which is the argument in giving every data domain one named owner.
Reason codes are the whole instrument
Scrap without a reason code is a quantity. Scrap with a reason code is information.
The design of the list decides whether you get either. Three failure modes, all common:
Too many codes. Forty options on a screen produce a distribution in which the first three are used for everything, because the operator is holding a part and a scanner and it is Thursday. Aim for a number a person can read in one glance.
A catch-all that absorbs the truth. "Other" will become the largest category within a month unless somebody reviews it weekly and creates a real code for whatever keeps appearing in it. That weekly review is the maintenance cost of the whole system, and skipping it is how the data quietly becomes worthless while continuing to be collected.
Codes that describe the symptom rather than the stage. "Damaged" tells you nothing. Recorded against the operation, the machine, the shift and the material lot, the same event tells you where and when. The recording context matters more than the vocabulary.
And one design point that is not obvious: a scrap record needs to say what happened to the material afterwards. Regrind, rework, sale as second quality, disposal. In a plastics or a textiles operation the material that becomes regrind re-enters production, and if the system cannot follow it, the question an auditor eventually asks — which lot went into the scrap that became the regrind that went into this part — has no answer. That is the same chain relied on in tracing a batch forward and backward within two days, and scrap is the link most often missing from it.
Where the numbers have to come from
Real variance needs three things declared at the point of production, and the third is the one that usually fails.
Quantity good, which everybody records. Quantity scrapped with a reason, which many record partially. And material actually issued, which is where the fiction usually lives: if consumption is backflushed from the bill of material, then by construction the material consumed always equals the standard times the quantity produced, and the material variance is arithmetically zero forever. A factory can run this way for years and believe it has no material variance, because it has built a system incapable of reporting one.
The remedy is not to abolish backflushing, which is a reasonable mechanism where the material is stable and cheap. It is to know which items are backflushed and which are issued against the order — and to make sure the expensive, variable and regulated ones are in the second group. That is a deliberate item-by-item decision, and it is one of the decisions that separates a manufacturing implementation that produces usable cost from one that produces plausible cost, as set out in what a manufacturing system has to establish and in what order.
The same applies to time. If labour and machine hours are booked by dividing a shift across the orders that ran, the labour variance is an allocation rather than a measurement, and it will always look reasonable.
Doing it without stopping the factory
The instinct is to do it all at once and the result is usually that the shop floor quietly reverts. A sequence that survives:
- Pick one product family and one line. Not the biggest — the one with the most argument about where the losses go.
- Agree the four categories and a short reason-code list with the people who will use it, in a room, on a whiteboard. Twenty minutes with the shift leaders is worth more than a month of design.
- Record for four weeks, changing nothing else. Resist improving anything. You are establishing a baseline you can defend, and any improvement made now destroys the comparison.
- Set the standard from a deliberately good run in that period, with the conditions noted.
- Publish the split weekly to the people who cause it, not monthly to finance. The distribution is the message.
- Then act, and expect the first real action to be a scheduling change rather than a process one.
The order matters because the most common way this fails is that the improvement programme starts before the measurement does, so nobody can tell afterwards whether it worked. That is the same discipline required of any change with a saving attached, and the general case is set out in measuring what an automation actually saved.
None of this is expensive. Reason codes and issued material are configuration in any competent manufacturing system, and the weekly review is an hour. What it costs is the decision to let the variance report say something uncomfortable, which is the part that has to be agreed above the production manager before any of it is worth starting — and it is exactly the kind of governance question that an independent look at what the system is actually measuring is useful for settling.