XYZ Analysis

Classify inventory items according to the variability of their demand.

Log-hub Supply Chain Apps, XYZ Analysis

What it is

  • The XYZ Analysis is a way to classify inventory items according to variability of their demand.
  • X-items: very little variation, Y-items: some variation, Z-items: high variation

What it delivers

  • Standard templates and visualizations for XYZ Analysis.
  • Detailed result tables for interpretation and further analysis.

What are the benefits

  • Focus on interpreting the results instead of spending time with standard analysis tasks.
  • Make better decision in stock management.

What is the difference between X-, Y-, and Z-items?


XYZ Analysis classifies items according to their variability over time.

  • X – Very little variation: X items are characterised by steady turnover over time. Future demand can be reliably forecast.
  • Y – Some variation: Although demand for Y items is not steady, variability in demand can be predicted. This is usually because demand fluctuations are caused by known factors, such as seasonality, product lifecycles, competitor action or economic factors. It’s more difficult to forecast demand accurately.
  • Z – The most variation: Demand for Z items can fluctuate strongly or occur sporadically. There is no trend or predictable causal factors, making reliable demand forecasting impossible.

What are the implications on stock management?


The classes have significant implications for stock management.

  • Inventory management for X-items can usually be fully automated because of low demand volatility. And due to the predictability of demand, a low buffer inventory can be held either by the organisation itself or, in a Just In Time (JIT) arrangement, by the supplier – reducing holding costs. 
  • For Y class items, buffer stocks may need to be higher, or more manual intervention of an otherwise automated stock management process may be required. JIT supplier arrangements may be more difficult to negotiate for Y class inventory as the suppliers may not have the expertise for predicting demand that the organisation itself would have. 
  • Since it is virtually impossible to predict demand for Z class inventory items, the policy may be to replenish-to-order.

Combine XYZ Analysis with other tools


Achieve better results with our recommendations.

ABC Analysis

Optimize inventory policies by focusing on the most important articles.

Forecasting AI

Go beyond traditional forecasting and use machine learning technology.

Log-hub, Supply Chain Apps, Inventory Simulation App

Inventory Simulation

Determine the optimal inventory policy through multiple what-if scenarios.

Social media & sharing icons powered by UltimatelySocial