- Cost Transformation
XYZ inventory management
What is it?
The XYZ analysis is a way to classify inventory items according to variability of their demand.
- 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 to an extent. 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.
The following charts illustrate the characteristics of the three classes.
The classes have significant implications for stock management. Due to low demand volatility, A class inventory management can usually be fully automated. 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 B 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 B 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 C class inventory items, the policy may be to replenish-to-order.
The variability of demand for an inventory item can be expressed as a variation coefficient. The steps for classifying items by degree of demand volatility are:
- Determine the items to be included in the analysis.
- Calculate the variation coefficient for each item.
- Sort the items by increasing variation coefficient and accumulate.
- Agree and set the boundaries between cumulative variation coefficients.
For XYZ analysis to work, it's vital to understand and apply an appropriate time span for assessing demand volatility. For example, if demand for items is seasonal, computing volatility over a month may not be appropriate. Alternatively, where product lifecycles are short, computing the volatility of items with sporadic demand could mean stocked items become obsolete.
The cost of items could also influence inventory management policy. For example, some A class items could be high cost and the organisation may not wish to rely on full automated replenishment. At the other extreme, some C class items may be very low cost. So it may be more cost effective (and improve customer service) to manually set buffers and automate replenishment to maintain the buffers, rather than to replenish-to-order. Combining the ABC with XYZ approaches is a useful way of thinking about inventory management policy.
What benefits does the approach provide?
- Improves accuracy of forecasting.
- Reduces stock-outs, which:
– Improves production stability and efficiency.
– Improves customer satisfaction.
- Increases stock churn.
- Reduces stock obsolescence.
- Clarifies service levels for items with volatile demand.
Implementing XYZ inventory management? Questions to consider
- Is there reliable and accessible cost and demand information by item?
- Will your inventory management systems and processes facilitate efficient and effective implementation and operation of the XYZ approach?
- Have the costs and benefits of implementing and operating XYZ been quantified and is the business case compelling?
- Has the impact of the change to XYZ on capability been assessed and planned for?
|Actions to take / Dos||Actions to avoid / Don'ts|
|Related and similar practices to consider|