Standard cost stopped resembling actual cost
Rates were set at a budget meeting and never revisited, so the products that look most profitable are frequently the ones absorbing the least of the overhead they cause.
Manufacturing
Knowing what a unit actually costs to make, before the month closes
Production, quality and finance reconciled against one another, so cost per unit is a number you can act on rather than an allocation you argue about.
In most plants the MES knows what ran, the quality system knows what failed, and the ledger knows what it cost, and no two of them agree on the same batch. Standard costs drift from actuals for a year at a time and nobody notices until margin does something unexpected. We join those three records at the level of the run, so scrap, downtime, yield and overtime land against the product that caused them, in time for somebody to change the schedule.
Discuss your operationWhat we usually find
The problems that come up in almost every one of these businesses.
Scrap is visible in total and invisible per line
The plant knows its scrap percentage. It usually cannot say which shift, changeover or material lot is producing it, which is the only version of the number worth having.
The schedule and the ledger are separate conversations
Planning optimises for throughput and finance reports on margin, and because the two run off different data neither can tell you what a rush order really cost to expedite.
Where we start
What the first engagement usually covers.
Scope depends on the state of your systems. These are the pieces that recur in this sector.
Run-level cost build
We rebuild cost per unit from the actual run: materials consumed, labour and machine time booked, scrap and rework, and the overhead you can defend attaching to it.
Yield and downtime attribution
Losses tied back to the line, shift, changeover and material lot that caused them, rather than pooled into a plant-wide percentage.
Product and customer margin
Once cost is real, the ranking of what makes money changes. We put that ranking in front of the people who set prices and accept orders.
Reporting the plant will use
Daily numbers on the floor for the supervisors, monthly reconciliation for finance, both built from the same figures so the two never disagree.
What changes
What is different afterwards.
You own all of it: the code, the written definitions and documentation aimed at whoever maintains this after us.
- Cost per unit reconciled to the ledger, by line and by run
- Scrap and downtime attributed to a cause somebody owns
- Product margin ranked on actual cost rather than standard
- One set of numbers shared by the plant and by finance
The builds behind it
Sector knowledge decides the order. The builds are the same four.
Single source of truth
Your finance, customer and operational records joined into one dataset, with each figure defined once and traceable back to the system it came from.
Analytics layer
Reporting built on top of the joined data, aimed at the few revenue and cost drivers that actually change the result.
Workflows
One defined task, automated inside a process that already exists, measured against whatever it replaced.
Financial modelling
Driver-based models built on the same definitions as your reporting, so the forecast and the actuals stop disagreeing.
Worth asking
Questions this tends to answer.
- Which products actually make money at current prices?
- What is scrap costing us, and where is it coming from?
- What did that expedited order really cost to run?
- Where is capacity being lost that we are not measuring?