Theoretical vs actual yield: accounting for loss in a supplement BOM

Put 100 kg of material into a process and you don't get 100 kg of finished product out. Material is left in the mixer, lost as dust, stuck to equipment, rejected at inspection. The difference between what the formula says you should get — the theoretical yield — and what you actually get is loss, and ignoring it makes your costing, purchasing, and planning quietly wrong. Accounting for yield in the BOM makes them realistic. Here's why it matters.

Theoretical yield is the math; actual yield is reality

The theoretical yield is what the BOM implies: add up the inputs, and that's how much product you should get. The actual yield is what comes out the other end after real losses. The gap between them — expressed as a yield percentage — is a real, measurable property of a product and process. A process with 95% yield loses 5% of its material somewhere, every batch.

Where the loss goes

Loss has many sources: material retained in mixing and filling equipment, dust and fines, spillage, samples taken for testing, and units rejected for quality. Different processes and formats lose different amounts — a fine powder dusts more, a complex process has more transfer steps. The loss isn't waste in the sense of error; it's an inherent feature of making the product, and it's predictable enough to plan for.

Why it changes your numbers

Loss affects the things that matter commercially. Cost: if you lose 5% of your material, your real cost per finished unit is higher than the naive BOM suggests, because you paid for material that didn't become product. Purchasing: to make a target quantity of finished product, you have to buy more input than the theoretical amount, scaled up by the loss. Planning: a batch yields fewer units than the math says. Ignore yield, and you under-cost, under-buy, and over-promise.

Build yield into the BOM

The fix is to hold the expected yield (or loss) as part of the product's BOM, so the software accounts for it: the true cost per unit reflects the loss, the purchase quantities are scaled up to deliver the target output, and the planned batch size yields the right number of units. Yield turns from an ignored fudge factor into an explicit, managed number that makes the whole BOM realistic.

Actuals refine the estimate

Over time, real batch results show the actual yield, which refines the expected figure. A product whose batches consistently yield 94% should carry that, not an optimistic 100%. Tracking actual against theoretical yield also surfaces problems — a sudden drop in yield signals a process issue. The yield figure becomes both a planning input and a quality signal.

This is general information, not regulatory or legal advice. Confirm process and yield assumptions for your specific products with your manufacturer before relying on a general summary.

Where Lemoniq fits

Lemoniq lets a product's BOM carry its expected yield, so cost per unit reflects real loss, purchase quantities scale up to deliver the target output, and planned batches yield the right number of units — turning yield from an ignored fudge factor into an explicit, managed number.

The takeaway

A batch never yields exactly what the BOM math says — material is lost to equipment, dust, and rejects — and ignoring that loss under-costs, under-buys, and over-plans. Accounting for theoretical versus actual yield in the BOM makes costing, purchasing, and planning realistic. That's the difference between a BOM that looks right and one that is.

Lemoniq builds yield and loss into your BOM, so cost, purchasing, and planning reflect reality. See how it works