The ABC/XYZ analysis is a portfolio view of the product spectrum in which all items of the product portfolio are classified both according to turnover (ABC) and according to their demand regularity (XYZ). From the ABC/XYZ analysis, important insights can be gained regarding the challenges of inventory management and product availability as well as regarding cost optimisation and structural optimisation in the supply chain and in the product portfolio.
ABC/XYZ Analysis: The blood count of logistics
Anyone who occasionally takes a look at the economic success of their products uses the ABC analysis and anyone who regularly deals with the management of supply chains also knows the XYZ classification. Both observations together result in the blood count of logistics, from which essential insights for improving the product portfolio and optimising supply chain management by be derived. Surprisingly, the application is far less widespread as one might expect.
The classical structure of the ABC analysis
In the ABC analysis, all finished products, semi-finished products, raw materials or merchandise are classified according to their economic significance. Typically, the turnover and the annual consumption value (stock issue quantity x manufacturing costs/piece) are used as the assessment value, sometimes also the annual contribution margin of the last full 12 months. Since the contribution margin can also take on negative values, the classification is usually structured somewhat differently here. Sorted by decreasing assessment value, e.g. annual consumption value, the articles that account for the first 80% of total annual consumption across all articles considered are classified as A articles. The next 15% as B-articles and the last 5% as C-articles. Items that had no turnover or annual consumption value in the last 12 months are classified as “N”. In practice, more classes and other class boundaries and class designations are sometimes used.
The limits of the ABC analysis
The ABC analysis alone only gives a one-sided picture of the contribution to success of the articles under consideration. An item’s contribution to success also depends on the logistical effort it causes. A major driver of the logistical effort is the regularity with which articles are requested by the market. An expensive or inexpensive article that is demanded in small or large quantities, very regularly and in quantities that fluctuate little per unit of time, e.g. months, causes less logistical effort than an article that is equally expensive and demanded in the same quantity, whose demand quantity fluctuates very strongly and which is demanded sporadically.
The more irregular the demand, the more fluctuating the quantity demanded, the higher the safety stock required to ensure a desired delivery capability and the higher, for example, the warehousing costs associated with the average stock level. In general, the planning effort for these items also increases considerably, which causes further costs and depresses the item’s contribution to success.
The principle of the XYZ analysis
The aspect of demand regularity is evaluated by the XYZ analysis. Items with low fluctuations in demand are classified as X and items with high fluctuations in demand are classified as Z; Y items lie accordingly in between. In practice, various variables are used as evaluation criteria for the classification. We use the coefficient of variation of the demand fluctuation of each article, combined with the so-called “zero share”. The coefficient of variation results from the quotient of standard deviation and mean value. This makes it possible to compare demand fluctuations between items with different demand quantities. The zero component records the proportion of the total number of periods in which no consumption took place. For example, if an item has not been in demand in 3 of the last 12 months, the zero share is 25%.
In our XYZ classification, items with a zero share of more than 50% are classified as Z2. For items with a zero share of 50% or less, the class separations are at coefficients of variation of 0.5 (X to Y) and 1 (Y to Z). Items that had no consumption in the analysis period are classified as N. In contrast to the ABC analysis, the XYZ analysis does not compare rankings between articles, rather each article is evaluated on its own.
The ABC/XYZ analysis provides interesting insights
Evaluating each item according to ABC and XYZ and thus assigning it to one of the resulting portfolio fields reveals interesting characteristics of the item portfolio.
Mostly, in the ABXY segment, 60% to 80% of the turnover (or annual consumption value) is generated with 20% to 40% of the material numbers. At the other end of the portfolio, in the CZZ2 segment, 2% to 4% of turnover is achieved with 40% to 60% of the material numbers. In the CZZ2 segment, much higher inventory ranges are required to achieve the same delivery readiness as in the ABXY segment.
Our advice: No money is earned with finished goods in the CZ2 segment
Since at least part of the costs of a contribution margin calculation are determined according to cost carrying capacity and not according to cost causation, the contribution margins in the CZZ2 segment of finished goods often give a false picture of the profitability of this product portfolio. In random activity-based costs audits, we have repeatedly found that positive contribution margins are not being generated, at least in the CZ2 segment and also by many items in the CZ segment. Assortment constraints may require articles to be offered in this segment. In this case, however, the principle of “no AX, no CZ” must be followed consistently. Customers who switch to the competition with their ABXY articles must no longer be able to order CCZ2 articles.
Furthermore, in the CZZ2 segment of a finished goods portfolio, the readiness to deliver shoud be reduce or it should be switch to „minimum stock planning“. Furthermore suitable tools to ensure automatical planning of the CZZ2 portfolio should be installed.
Experts gain numerous further hints from the ABC/XYZ portfolio, e.g. regarding kanban suitability, automatability of planning and scheduling or incorrectly set logistical decoupling points.
However, discussing these would take us too far at this point.