This is a cross-check of whether different data sources support a consistent conclusion. If a company declares a production volume and recycled content, the available quantity of material must support both.
Why check plausibility?
A single document may be correct while the dataset as a whole is impossible. The auditor therefore compares information from different sources and checks whether it forms a coherent picture of the operation.
Example
If a company declares 1,000 tonnes of product with an average recycled content of 50%, there must be a credible source of approximately 500 tonnes of recycled material, taking inventories, losses and other flows into account.
Which data can be compared?
- purchases and weighing records;
- opening and closing inventory;
- recipes and dosing settings;
- production reports;
- sales and dispatches;
- line capacity;
- losses, waste and internal regrind;
- quality control results.
Process capacity as a logical check
If the declared output exceeds what can reasonably be obtained from the input material and the line capacity, the data needs explanation. The same applies to an unrealistically high or low yield.
Plausibility checks and volume reconciliation
The reconciliation is an important tool, but plausibility checks have a wider scope. They may also compare unit weights, production capacity, operating hours, delivery frequency or laboratory results.
How should the system be prepared?
Identify the main data sources and establish which datasets should be compared periodically. The earlier a company detects a discrepancy, the easier it is to find its cause.
Key takeaway
Reliable data does more than exist in a system: it matches the physical process and can be corroborated by independent sources.