ABC Analysis Calculator
Classify inventory with ABC (Pareto) analysis. Work out each item's share of total usage value and see how A, B, and C classes are drawn, with thresholds and cycle-count guidance.
ABC analysis applies the Pareto principle to inventory: a small share of items accounts for most of the usage value, so control effort should follow the money. A-items — few in number but carrying most of the value — get the tightest control, B-items moderate attention, and the long tail of C-items minimal effort. It starts with one number per item: its share of total annual usage value.
How it works
For a single item, divide its annual usage value by the total across all items and multiply by 100. To run a full classification: compute this share for every SKU, rank items by descending share, accumulate the percentages, and draw class boundaries on the cumulative curve — enter your SKUs and the tool returns the ranked, classified list.
The formula
Share % = 100 x item annual usage value / total annual usage value. Classes come from the cumulative ranked shares: a common convention takes A-items up to ~80% of cumulative value and B-items up to ~95%, with the remainder as C. These cut-offs are conventions, not standards — corpus textbook examples show A/B/C value splits of 54/41/5 and roughly 65/25/10 — so fit the boundaries to your own Pareto curve.
Worked example
If the A-class group of items is worth 54,000 of a 100,000 total annual usage value, its share is 100 x 54,000 / 100,000 = 54% — matching the textbook table where 11% of items held carry 54% of the value.
Frequently asked questions
How many classes should I use?
Three (A, B, C) works for most inventories. Very large item files sometimes add a D class to dump the lowest-value half of the lines, which may hold only 2-3% of the value. More than four classes rarely changes any decision.
Where should I draw the class boundaries?
Common convention: A = items up to about 80% of cumulative value, B = up to about 95%, C = the rest. But published examples vary widely (54/41/5 and 65/25/10 value splits appear in standard texts), so plot your cumulative curve and place boundaries where the slope visibly flattens.
How does ABC classification drive cycle counting?
Count frequency follows value: A-items might be counted weekly or monthly, B-items quarterly, and C-items once or twice a year. This concentrates counting effort where record errors cost the most and enables rolling counts instead of a full annual stock-take.
Should classification only consider value?
Value is the standard measure, but it misses criticality: a cheap part that stops a production line deserves A-class treatment. Many teams overlay a criticality flag or run a second dimension (XYZ for demand variability) on top of the value classes.
Related tools
This is a planning estimate. Results depend on your inputs and assumptions; confirm against your own data before ordering.
- Annual usage value (not unit price or volume alone) is the classification measure.
- ABC class thresholds (e.g. A = top ~80% of cumulative value) are conventions, not standards; corpus examples use 54/41/5 and roughly 65/25/10 value splits.
- Items are ranked by descending share before drawing cumulative-percentage class boundaries.