ABC Inventory Analysis Calculator

How the number is derived

ABC analysis ranks stock by annual consumption value, annual units × unit cost, and splits it into three classes. A items are typically the top 20% of SKUs producing about 80% of the value, B items the next 30% producing 15%, and C items the remaining 50% producing 5%.

The classes are not a judgement about product quality. They are a statement about where the capital is, and therefore where management attention returns the most.

The same thing with real figures

A catalogue of 200 SKUs with $600,000 of annual consumption value. The top 40 SKUs account for $480,000, the next 60 for $90,000, and the remaining 100 for $30,000.

The example product at $37,440 a year sits comfortably in class A. It alone is 6% of total value, and it deserves weekly review, tight service levels and a considered order quantity.

A C item at $300 a year does not. Counting it monthly, calculating an EOQ for it and holding a 98% service level on it costs more in attention than the item is worth, and the right treatment is a large order once a year and no further thought.

The catch

Consumption value ignores strategic importance. A cheap component that halts everything when missing, a product that brings customers who then buy other things, or a warranty part with a service obligation may all be C by value and A by consequence.

The classification also drifts. A catalogue reclassified once and then left alone will have last year's A items receiving this year's attention, which is worse than no classification at all because it feels rigorous.

Applying it

Set different policies per class rather than only labelling them. A items: high service level, frequent review, tight forecasting, cycle counted monthly. B items: standard policies, quarterly review. C items: large infrequent orders, low service level, counted annually.

Reclassify quarterly. It takes one query against the sales data and it is the step that keeps the whole exercise honest.

Adding a second dimension

Value alone leaves out predictability, and combining the two produces a far more useful grid. XYZ analysis classifies items by demand variability: X for steady, Y for variable, Z for erratic, and crossing it with ABC gives nine cells.

The cells that matter most are AZ and AX. An AX item is high value and predictable, which means low safety stock and tight ordering will work well. An AZ item is high value and erratic, which is where the largest buffers and the closest attention belong, and where most of the avoidable stockout cost in a catalogue is concentrated.

CZ items, low value and erratic; are the ones to stop managing altogether. Order a year at a time, accept the occasional stockout, and spend the attention saved on the AZ items where it changes the outcome. That reallocation of attention is the entire practical benefit of classifying stock, and it is lost if every class ends up on the same weekly report.

Classifying by revenue alone is the standard approach and it misses something important. A low-revenue item that is essential to a bundle, or that customers expect a serious retailer to stock, carries strategic value its sales figure does not show. A useful refinement is to classify by revenue and then review the C items by hand for exactly those cases.