Feed Shrinkage & Silage Auditor

Where it works well

It does the one reconciliation no one finds time for — tonnes in against tonnes fed, on a dry-matter basis, across a whole season.

Best for a grain-fed lot carrying enough commodity that a few percent of shrink compounds into real money across a season — where commodity is bought at the weighbridge, mixed through a mixer wagon, and stored partly as bunker silage and partly in open bays.
It ranks the gap into dollar sources biggest-first, so the feed manager works the $84k silage face before the $21k batch overrun, instead of chasing the loss that is easiest to see.
The recaptured time goes back into the feed manager walking the bunks and the commodity bays, not reconciling spreadsheets after harvest.

The shrink is felt in the feed-conversion books but never traced. The weighbridge dockets, the mill batch weights and the bunk reads all exist, but they sit in three different places, on an as-fed basis, and nobody sits down to convert them to dry matter and line them up — so a few percent of the biggest variable cost on the lot goes missing without a name on it.

Where it works badly

It is confidently wrong when the moisture figures are stale — a clean dollar number built on a dry-matter conversion that no longer holds.

The reconciliation is only as good as the moisture testing behind the DM conversion; a 5-point moisture error on a wet commodity moves the shrink number more than most of the real losses it is trying to find.
It infers the lower-confidence sources — bay weathering, batch overrun — from indirect evidence, so it can name a loss source that is really just two scales that were never cross-checked.
Weak where the records don't tie to the same loads — if the mill scale and the weighbridge weighed different trucks on different days, the "2.1% drift" is noise, not a drifted scale.

The honest test

If you cannot say, right now, when each wet commodity was last moisture-tested and whether the mill scale and the weighbridge ever weighed the same load — this tool makes your shrink number more precise, not more true.

Commodity moisture drifts — a silage pit that tested at 65% moisture in autumn is not the same feed by spring, and cottonseed and hulls weather in the bay. Feed the tool last quarter's moisture and it converts as-fed to dry matter against the wrong figure, then reconciles a shrink gap that is partly a measurement error dressed up as a $196k loss. That is the trap.

What it doesn't do — and shouldn't

It surfaces and ranks the shrink. A person owns each fix. That boundary is deliberate.

WHAT IT DOES

Shows the tonnes purchased, delivered and fed, and the gap between them on a dry-matter basis

Names the evidence each loss source rests on and flags its confidence — high where two independent records disagree, lower where the loss is inferred

Pairs each finding with one suggested fix and holds it for accept, assign, or dismiss

WHAT IT WON’T

Re-calibrate the mill scale or adjust the ration on its own

Decide a moisture-driven figure is real rather than a measurement error

Touch the feed-conversion books or the commodity orders

Feed is the biggest variable cost once cattle are on feed, and acting on the wrong source costs twice — once in the loss you didn't fix and once in the change you made for nothing. Re-calibrating a scale, narrowing a silage face, or tightening a mixer cut-off changes how cattle are fed and how feed is booked. The feed manager or nutritionist stands behind that call because the cost of getting it wrong lands on the lot, not the tool.

What your data has to look like

Three weight streams that tie to the same loads, and current moisture figures to put them all on a dry-matter basis.

Typical readiness

across orgs we see, before the first job

Commodity intake on an auditable basis

Needs shaping

Mixer-wagon batch weights, delivered-to-bunk

Usual weak point

Bunk reads net of refusals

Usual weak point

Current moisture figures for wet commodities

Needs shaping

Silage face-advance and bunker logs

Needs shaping

The real first job

The moisture figures are usually the weak point — tested at fill, then assumed for the season. Getting wet commodities onto a regular moisture-testing rhythm, and getting the weighbridge, mill and bunk weights to tie to the same loads, is usually the real first job — larger and more valuable than the reconciliation layer on top. Once the inputs are clean and current, the shrink number is true, and every source it ranks is a real one.

Right fit if…

You run a grain-fed lot carrying enough commodity that a few percent of shrink is real money across a season

Commodity is bought at the weighbridge, mixed through a mixer wagon, and stored partly as silage and partly in open bays

You moisture-test your wet commodities and can tie weighbridge, mill and bunk weights to the same loads

Your shrink shows up in the feed-conversion books but is never traced back to a source

Walk away if…

You feed a fixed bought-in ration with little commodity storage of your own

Your only feed figures are monthly invoice totals that can't be matched to loads

Wet commodities are tested once at fill and assumed for the rest of the season

You want a tool that re-calibrates the scale and adjusts the ration for you

Open questions

The worried-buyer questions, answered straight

It can rank a loss source wrong — which is exactly why nothing is changed on its say-so. Each finding shows the evidence it rests on and a confidence flag: high where two independent records disagree, like the mill scale reading heavier than the weighbridge on the same loads, and lower where the loss is inferred, like bay weathering. The feed manager checks the evidence before acting. The tool surfaces and ranks; the person decides what gets changed and who closes it.

It works from weights it can tie to the same loads, converted to a dry-matter basis using your moisture figures. If the mill scale and the weighbridge weighed different trucks on different days, or a wet commodity hasn’t been moisture-tested in months, the reconciliation is only as good as that — and the tool can’t tell a measurement error from a real loss. Getting the three weight streams to tie up, and the wet commodities onto a regular moisture test, is usually the first piece of work, and the piece that pays off across every season after.

No. It removes the reconciliation — pulling three sets of weights together, converting them to dry matter, and lining up the shrink — so the feed manager or nutritionist spends their time on the judgement: whether a flagged loss is real, whether re-calibrating the scale is worth the disruption, whether the silage face can actually be narrowed. The decision stays theirs. The capacity it frees goes back into walking the bunks and the bays.

Current enough that the dry-matter conversion holds. Wet commodities like silage, cottonseed and hulls are usually tested once or twice a week because their moisture drifts, and a few points of moisture error on a wet feed moves the shrink figure more than most of the real losses it’s looking for. The honest test: do you know, today, when each wet commodity was last moisture-tested, and whether the weights you’re reconciling came off the same loads?

Your weighbridge dockets, mill batch weights, bunk reads and commodity costs are commercially sensitive — they expose your feed-conversion and your buying. Any deployment runs against your own systems and data handling, not a shared pool; we scope where the records sit and who can see them as part of the build. The demo here runs entirely on fabricated data — the lot, the tonnages and the dollar figures are invented for illustration.

It surfaces where feed went missing and ranks the cost, but it does not touch the books or certify the number. A drifted mill scale that books more feed than was delivered is a finding for a person to confirm against the weighbridge and then act on — re-calibrate, re-book — not something the tool corrects itself. It gets the shrink picture most of the way; the accountable person closes the gap and owns what changes.

What it takes to build

3–5 weeks · 4 phases

Reused from template~65%

Bespoke to this skin~35%

stack · Claude · Power Platform · Excel/mill-log feed · review UI

What it would cost

Fixed scope, fixed price, fixed dates.

Bite-sized first piece

One contained change, low risk

Pilot build

Most builds land here

Embedded support

Scale on proof

Considering this for your lot?

The honest place to start is a bite-sized first piece — one contained change, low risk. Tell us where the feed shrink hurts; we'll play it back, scope it, and show you what's possible.

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