Raw Materials, Yields & Waste: Making the Production Line Tell the Truth
Between the raw store and the finished shelf, margin disappears through yields, waste, and unmeasured issues — the batch discipline that makes a Kenyan processor's production line tell the truth.
Ask a miller what their extraction rate was last week and you learn everything about the business. The ones who answer with a number — "78.2%, down half a point, we are checking the conditioning" — run production as a measured system. The ones who answer "good" run it as a hope. The difference is not equipment or scale; it is whether raw materials are issued against recipes and outputs are weighed against inputs, batch by batch.
The batch loop
- Plan: a production order states what will be made and the recipe computes expected material consumption.
- Issue: the store releases materials against the order — weighed, recorded, and nothing more. Open-door stores where production "takes what it needs" cannot be measured.
- Produce: the run happens; downtime, rework, and waste get recorded as they occur, with reasons.
- Receive: finished output is weighed/counted into finished-goods stock; by-products (bran, cake, offcuts) are received as their own items.
- Reconcile: input vs recipe (consumption variance) and output vs input (yield) — two numbers, every batch, reviewed weekly.
Reading the two numbers
| Signal | Likely cause | First move |
|---|---|---|
| Consumption above recipe, yield normal | Over-issuing, spillage, or store leakage | Tighten issuing; weigh at the store door, not the mixer |
| Consumption normal, yield falling | Process problem — moisture, settings, raw quality | Check the input batch quality records; inspect the line |
| Both drifting together | Recipe no longer matches reality | Re-baseline the recipe with a supervised test run |
| Numbers perfect, always | Records are being written backwards from output | Weigh independently; separate the recorder from the operator |
Waste is a transaction
Damaged output, floor sweepings, burnt batches, trimmings — every kilo of waste is recorded with a reason, or it becomes the line's all-purpose explanation. Processors who start recording waste typically discover it was covering for something else: a scale that reads heavy, a recipe that drifted, or product leaving through the side gate.
Raw material quality is a yield input
Agri inputs vary: moisture in maize, fat content in milk, fiber in cane. A batch that yields poorly often traces to a delivery that was accepted generously — which is why receiving records (weight, moisture, grade, supplier) belong in the same system as production. Over time, yield-by-supplier is one of the most valuable reports a processor owns: it converts "we like this supplier" into "this supplier's maize yields 2% better, which is worth KES 1.80 per kilo more than we pay them". Quality holds at receiving enforce the standard; the yield data justifies it.
Committed stock: the promise ledger
A confirmed order for 500 cartons next week is a claim on raw materials today. Systems that show only physical stock let sales promise the same materials twice — production then chooses which customer to disappoint. Available-to-promise = physical − committed − quality-held, and it is the number sales should see. The costing side of the same chain — what those materials truly cost — is the landed cost discipline; together they make the manufacturing margin honest.
Make the line tell the truth
Recipe-based issuing, batch yields, waste with reasons, and yield-by-supplier — running on your production within a month.
See production control in AWRAFrequently asked questions
Our production is continuous, not batch-based. Does the loop still apply?
Yes — define a batch as a shift or a day and run the same reconciliation on that window. Continuous processes actually benefit more from the weekly trend line, because drift compounds quietly when there is no natural batch boundary to force a count.
How accurate do recipes need to be before we start?
Start with your best current estimate and let the variance reports correct it: three weeks of real consumption data produces a better recipe than three months of pre-launch measurement. The discipline of issuing against something matters more than the initial precision of the something.
Where does rework go in the numbers?
Rework re-enters as an input to a new run, recorded as such — its materials were already consumed once, so hiding it inflates yield and flatters the week that produced the defect. Visible rework is annoying; invisible rework is a margin lie.
What is a realistic yield improvement from doing this?
Sector-dependent, but the pattern is consistent: the first quarter of measurement typically recovers 2–5% — not because anything was optimized, but because measurement itself closes the deniability that leakage and drift lived in. Optimization comes after, on top.
