Spot anomalies and plausibility checks

Bad fuel data usually shows up as an implausible price, an out-of-range quantity, or spend that overshoots a budget. This article explains the plausibility checks the module applies at capture and how to hunt down anomalies afterwards using the reports and exports. You need tankmanagement:view to read the reports and tankmanagement:refuel or tankmanagement:manage to enter data.

Plausibility checks at capture

The module refuses obviously wrong values when a refuelling is saved, so the first line of defence is automatic:

• Quantity must be greater than zero.
• Cost per litre, total cost, and odometer reading cannot be negative.
• The refuelling date is required and cannot be more than one day in the future.
• If you supply only one of cost per litre or total cost, the other is derived, so the two can never contradict each other.

Imported fuel-card rows go through the same idea: rows that fail validation are flagged as Error and are excluded from commit, and rows with no vehicle match are flagged Unmatched for you to resolve.

Spotting cost anomalies

The cost-analysis report is your best tool for outlier prices. It groups spend by tank and cost center and, for each group, shows total cost, total litres, and the average cost per litre. A group whose average cost per litre is far from your others points to a mistyped price or a wrong quantity.

1. Open the cost-analysis report and set the period.
2. Scan the average-cost-per-litre column for values that stand out.
3. Cross-check the current fuel price for that fuel type as a sanity reference.

Spotting consumption anomalies

The consumption report shows average litres per refuelling per tank. A tank whose average jumps suggests over-dispensing, a leak, or fills recorded against the wrong tank. Combine this with per-vehicle odometer readings to find a vehicle whose litres-per-100-km has drifted.

Budget and level warnings

• Budget-versus-actual surfaces overspend directly: a negative variance or a utilisation above 100% means actual fuel spend has passed the cap for that period, cost center, and fuel type.
• The dashboard shows low-level alerts — active tanks whose current level has fallen below their minimum threshold — which catches a tank that has been drawn down faster than expected.

Tip: Export the refuelling history to CSV and sort by cost per litre or by quantity. Extreme highs and lows at the top and bottom of the sort are the quickest way to eyeball data-entry mistakes across a whole period.

Note: The module does not run an automated anomaly-detection engine. Plausibility is enforced at capture, and everything beyond that is review-driven — use the cost-analysis, consumption, and budget-versus-actual reports plus the CSV export to investigate.

When you find a bad record

Correct the cost on the linked Beleg (receipt/expense document), fix a tank's level with a tank reading, and keep cost-center codes consistent so groups do not fragment. See the article on correcting a refuelling record for the full procedure.

Related

• Correct a refuelling record
• Fuel cost overview and reporting
• Track fuel consumption per vehicle and tank
• Import fuel-card transactions