Back to Use CasesOperations & Costing

Batch and order costing is guessed, not measured

You know the sales price, but you don't know the true cost per good unit — so margin is a mystery.

Complexity: MediumTime to value: 2–4 weeksWorks with machine counters: Partial

The problem

Who feels it most

Finance/controlling, plant managers, and operations teams who can't explain cost variances.

How common is this?

Cost of poor quality and internal failure costs are significant in most manufacturing operations, implying meaningful variance when yield and rework are unmanaged.

Typical workaround today

Standard cost plus occasional variance analysis spreadsheets. Post-hoc explanations that arrive weeks after the batch was produced.

Why ERP / WMS doesn't solve it

ERP costing relies on standards and delayed postings. It doesn't automatically connect real-time yield loss, downtime, and labour to specific batches without heavy configuration.

Business impact

1

Margin erosion by product family that stays invisible

2

Wrong product mix decisions based on inaccurate cost data

3

Inability to identify which lines, shifts, or products are actually profitable

Operational batch cost per good unit from live production data

01

For each batch or order, compute cost per good unit from three components: material (standard or captured lots), labour (shift allocation or operator check-in), and yield (good/scrap from counters).

02

Dashboard shows top cost drivers per batch: downtime cost, scrap cost, giveaway cost, and speed loss cost — not just totals but breakdowns.

03

Compare cost per good unit across products, lines, shifts, and time periods — surfacing where margin is being lost.

04

Avoid full cost accounting complexity: start with 'operational cost' using readily available data, not theoretical allocations.

05

Export cost summaries for ERP reconciliation — optional integration, not a prerequisite.

Ready to solve this?

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