Systematic or random? Spotting patterns in the difference list

The difference list has 142 lines, and an explanation can be found for each one: a counting error here, a posting error there. Even so, the sum of the individual explanations remains unsatisfying, because it does not say why the same deviations keep occurring in the warehouse. Only a look at the whole shows whether a zone, an item group or a shift stands out. Behind a pattern there is usually a process that can be fixed, instead of putting every difference right one by one. This article shows how to find and test such patterns without hunting for culprits too soon.

Sort first, judge afterwards

A difference list ordered only by item number hides patterns. Group it in your spreadsheet, one after another, by these characteristics:

• zone and bin location,
• item group,
• sign, that is shortage or surplus,
• count team and shift,
• packaging unit,
• last document type, for example goods receipt, transfer or return.

This turns the list into a small analysis: where do differences cluster, and do they go in the same direction? No special system is needed for this; a pivot table is enough. Decide in advance when a cluster counts as a pattern, for example when at least five differences share the same characteristic. Individual cases remain individual cases and are cleared one by one.

Five typical patterns

1. The same sign in one zone: all surpluses point to issues or transfers that were not posted or only partly posted. All shortages point to receipts that were never posted.
2. Multiples of the packaging unit: if the quantity is off by exactly 12 or 24, a carton was probably counted wrongly or the unit was mixed up.
3. Mirror-image pairs: item A is short by 40 pieces, item B is over by 40, both with a similar number or description. This is a mix-up.
4. One team or shift with a conspicuous number of surpluses: possible causes are double counting, blocked stock counted along with the rest, or a different way of counting.
5. Shortages in small, valuable and easily saleable items: here it is worth looking at access to the warehouse and at the issue documents.

An example with figures (fictional)

The list has 142 differences. Zone C, the area for returns, accounts for 58 of them, and 51 of those 58 are surpluses, about 88 per cent. In the other zones there are 84 differences, of which 41 are surpluses and 43 shortages, so almost balanced (58 + 84 = 142). This picture argues against chance: in zone C, goods are probably being counted that have already been booked out in the system, or returns are standing on the shelf before their posting has been made. Checking the latest documents for that zone will confirm or refute the assumption.

From pattern to cause

A pattern is a hypothesis, not proof. Three questions help with the check:

• What do the conspicuous positions have in common: place, item, document, time or team?
• Since when has the pattern existed? A comparison with the last count shows whether it is new.
• What changes if the suspected cause is removed? A trial count of the zone after the correction gives the answer.

Assign every difference to a cause group, for example counting error, timing gap, wrong posting, mix-up or suspected shrinkage, and tally the groups. Where a team stands out, first check its counting method and briefing before voicing a suspicion. If there really is a suspicion of irregularities, it belongs with management or internal audit, not in the difference list.

In short

Whoever recognises patterns removes causes instead of symptoms. AuditMaster groups differences by item, batch and cause and watches for clusters by zone, team and shift, so that the difference list becomes a pointer to the process behind it.