XYZ analysis

What it means

XYZ analysis is an inventory management method that classifies items by how stable and predictable their consumption or sales are. Group X contains items with steady, even demand, group Y items with fluctuating demand, for example seasonal or trending, and group Z items with irregular, hard-to-predict demand.

The classification is usually based on the coefficient of variation, the ratio of the standard deviation of consumption to its mean over the period. The lower the coefficient, the steadier the demand. The company sets the group boundaries itself according to its range; values around 10 to 25 % for X and over 50 % for Z are common.

XYZ analysis is almost always combined with ABC analysis, which ranks items by value or share of turnover. The result is a nine-cell matrix, from AX, valuable items with steady demand, to CZ, cheap items with irregular demand. A different ordering strategy is chosen for each cell.

How it works in practice

AX and BX items are ideal for automatic replenishment, for example based on economic order quantity or a just-in-time system, because their demand can be forecast well. They need only low safety stock. AY and AZ items, by contrast, require individual planning, market monitoring and close cooperation with suppliers.

For group Z items it is worth considering whether to stock them at all. Cheap CZ items can carry more safety stock because little capital is tied up. Expensive AZ items are often better ordered only against a specific customer order. Such decisions reduce inventory substantially without hurting availability.

The analysis should be repeated regularly, for example quarterly, since item behaviour changes. A new product often starts in group Z and stabilises over time. The results also feed into the sales forecast and help set the parameters of the warehouse system.

What to watch out for

Beware of a short or unrepresentative period. If the analysis uses only a few months of data, seasonal items may look irregular even though their demand is predictable over the annual cycle. At least a year of history is advisable, with year-on-year comparison for seasonal items.

The analysis is based on consumption, not demand. If an item was out of stock, consumption was zero even though customers wanted it. Data on stock-outs, make-to-order sales or one-off large orders should therefore be cleaned before calculating, or the classification will be distorted.