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ABC-XYZ analysis algorithm classifies commodities and inventory depending on their significance for the company and demand stability. Based on the classification results, the optimal strategies for materials flow management are suggested. If there are commodities with a seasonal or rapidly changing demand in the inventory, then current classification is seriously influenced by the values observed before the change point emergence, which leads to increased significance for commodities already less significant, and the other way around, lower significance of the commodities with the recently increased profit or revenue. This work suggests a modification to ABC-XYZ analysis, which takes into account change point influences, allows finding better fitting groupings and decreases demand variability level by splitting sales series into sections with steady demand. Demand significance is recalculated once change point is detected as a product of a new average demand level for the period and a number of periods observed.