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Data & AnalysisDATA & ANALYSIS
ABC XYZ Inventory Value & Variability Analysis
Combine period usage value and demand variability from CSV into an ABC-XYZ matrix, with configurable cutoffs and explicit zero-demand handling.
ABC-XYZ analysis calculator
Combine period usage value and demand variability from CSV into an ABC-XYZ matrix, with configurable cutoffs and explicit zero-demand handling.
YOUR RESULT LIVE CALCULATION
Value and variability segmentation
5demand-active SKUs
6 EQUAL PERIODS / POPULATION SD| Value / CV | X | Y | Z |
|---|---|---|---|
| A | |||
| B | |||
| C |
- Total period usage value
- $16,700
- All SKUs / no-demand SKUs
- 6 / 1
- X: CV at or below
- 50%
- Y: CV above X, at or below
- 100%
- Z: CV above
- 100%
Value is for the entered periods, not automatically annualized. The item crossing an ABC cutoff stays in that class. Zero-value items are C; zero-demand items are N and sit outside the nine-cell matrix. These are configurable classifications, not automatic stock policies or forecast-quality guarantees.
SKU value and variability classifications
6 rows
| SKU | Unit cost | Period units | Period usage value | Value % | Cumulative % | Mean / period | Std deviation | CV % | ABC | XYZ | Combined |
|---|---|---|---|---|---|---|---|---|---|---|---|
| SKU-A | 20 | 600 | 12,000 | 71.86 | 71.86 | 100 | 0 | 0 | A | X | AX |
| SKU-B | 5 | 600 | 3,000 | 17.96 | 89.82 | 100 | 100 | 100 | A | Y | AY |
| SKU-C | 20 | 50 | 1,000 | 5.99 | 95.81 | 8.33 | 18.63 | 223.61 | B | Z | BZ |
| SKU-D | 2 | 240 | 480 | 2.87 | 98.68 | 40 | 0 | 0 | C | X | CX |
| SKU-E | 2 | 110 | 220 | 1.32 | 100 | 18.33 | 17.72 | 96.64 | C | Y | CY |
| SKU-F | 15 | 0 | 0 | 0 | 100 | 0 | 0 | N/A | C | N | CN |
BEHIND THE NUMBER
How the calculation works
Include 2-52 consecutive equal-length period columns named p1 through pN for every SKU. Enter actual zero demand as 0; missing values are rejected. ABC ranks the usage value in that window, retaining the item that crosses a cutoff in that class. XYZ classifies CV at or below X as X, above X through Y as Y, and above Y as Z. The sample/population denominator is explicit. All-zero demand has undefined CV and class N outside the nine-cell matrix.
Usage value = sum(period demand) x unit cost; CV % = standard deviation / mean demand x 100; ABC uses ranked cumulative value, XYZ uses entered CV cutoffs
When this calculation helps
Use ABC to describe annual usage value and XYZ to describe demand variability under the selected coefficient-of-variation method. Their intersection supports a more specific review than either letter alone.
Check the interpretation
Keep periods comparable and distinguish inactive zero-demand items from active, low-variation items. Thresholds and population versus sample deviation can change classifications. Add criticality, replenishment lead time, and service requirements before assigning a stocking policy to each cell.
The cutoffs are user assumptions, not universal thresholds. A low historical CV is not a guarantee of forecastability; trends, seasonality, intermittent demand, and short histories need separate review. Zero-cost items have zero usage value and ABC class C. Use one currency and consistent per-SKU units; the window is not automatically annualized.
SAP variability classification: mean, standard deviation, CV and configurable thresholdsGood to know
Why are there items outside the nine cells?
SKUs with zero demand have no meaningful CV denominator. They are marked N instead of being labeled perfectly stable X or erratic Z.
Should the history be monthly?
It may be daily, weekly, or monthly, but every period must cover the same duration and basis. Use p1, p2, and so on without skipping periods.