The ABC analysis method is based on the principle of classifying products according to their importance to the company's profit. This type of analysis is one of the methods for optimizing inventory balances and can be used in the field of activity of any trading enterprise.

ABC analysis is based on the Pareto principle - 20% of all goods produce 80% of turnover. One of the main ideas of the analysis is that controlling 20% ​​of positions allows you to control 80% of revenue.

ABC analysis is widely used due to its versatility, efficiency and ease of understanding. As a result of ABC analysis, products are rated according to the degree of influence on the overall result.

Sales volumes are analyzed according to two parameters: sales volume (quantity sold) and profit received (realized trade margin).

ABC analysis is based on the Pareto rule, according to which 20% of assortment items provide 80% of the profit.

ABC analysis - analysis of inventory by dividing into three categories:

A- the most valuable, 20% of inventory; 80% of sales
IN— intermediate, 30% of inventory; 15% of sales
WITH- least valuable, 50% of inventory; 5% of sales

The product assortment analysis module calculates and indicates categories for each product item in the selected product category. The result of the calculation is the placement of a letter identifier opposite the name of the goods.

Group A- very important products that should always be present in the assortment. If sales volume was used as a parameter in the analysis, then this group includes the sales leaders by quantity. If trade margin was used as a parameter in the analysis, then this group includes the most profitable products.

Group B- goods of medium importance.

Group C- the least important products are candidates for exclusion from the assortment and new products.

Calculation of product ownership is the determination of the current position of the product, a reflection of the current contribution of this product to the overall result.

After calculating group membership, enterprise management can decide to optimize the assortment.

If the goal is to reduce the assortment, then sales volume and profit are selected as the main parameters.

If the goal is to identify and reduce the costs of maintaining inventories, then the turnover ratio, the volume of illiquid stock and the occupied warehouse capacity are selected as the main parameters.

If you want to study profitability, then the turnover ratio and the level of profitability are selected as the main parameter.

ABC analysis data helps you make informed decisions to optimize your product range.

Benefits of ABC Analysis

Simplicity.

The main advantage is ease of use. The simpler the method, the more reliable it is - this is an axiom. The simple method is easier to understand and easier to use for analysis.

Transparency.

The simpler, the more reliable and understandable. The ABC analysis method involves relatively simple calculations that are easy to check if necessary.

Versatility.

Another important advantage is its almost complete versatility. Using the ABC method, you can analyze both the turnover within a product category and the product categories themselves and their contribution to the activities of a trading enterprise. In addition to ranking products, you can analyze suppliers to determine the supplier's contribution to the financial result of the store.

Resource optimization.

Optimization is the goal of the method. Successful use of ABC analysis allows you to reduce and free up a huge amount of time and financial resources. This is achieved by concentrating work on the most important elements.

Disadvantages of ABC Analysis

ABC analysis, like any other statistical method, is not artificial intelligence that thinks for people. ABC analysis is a tool in the hands of the analyst. Constantly calculating indicators when generating Supplier Requests alerts employees to changes in ratings, but it is the operator's responsibility to decide what actions need to be taken.

First drawback- This is a one-dimensional method. This method allows you to build a rating either by the product’s contribution to revenue, or to the markup, or to the number of sales (turnover). This drawback is overcome by using multidimensional ABC analysis, when grouping is carried out according to several indicators at once.

Second drawback follows from the method of overcoming the first drawback. For analysis using several criteria, groups A, B and C are determined by several variables at once. As a result, 2 indicators are formed. The number of possible groups is 9 (nine). The maximum number of groups is determined by the number of possible combinations of ABC groups according to two indicators (AA, AB, AC, BA, BB, BC, CA, CB, CC).

If an element falls into group CA, then this means that according to the first criterion it corresponds to group C, according to the second - to group A. If the element falls into group AB, then according to the first criterion - A, according to the second - B, etc. As you can see, there can be 9 groups in total. The highest priority positions are in the AA group, the least priority ones are in the SS. The interpretation of all groups and the decisions made in this regard depend entirely on the nature of the data and the goals of the analysis. For three indicators, the number of groups already reaches 27. The interpretation of such calculations is already not so simple and requires additional actions when making decisions.

Third drawback is a rating of goods regardless of their quality characteristics. It would be more correct to say that this is a traditional analyst mistake. If the rating is calculated based on sales of a large assortment, which includes several brands or goods with different consumer properties (dairy, meat, groceries, bread, etc.). If, when calculating indicators, we mix all this and carry out an ABC classification, it turns out that in each group there will be positions that are completely incomparable with each other. With this calculation, grouping will have no practical meaning. Groups are identified so that they can be managed, but how can you manage goods that are completely different in their properties?

Therefore, before conducting ABC analysis, it is necessary to divide goods into product categories, groups that are similar in nature.

Fourth disadvantage: among the goods there may be not only those that sell poorly, but also those that do not sell at all or that are sold at a loss. That is, goods that cause damage worse than group C. For this, another group is often added - D. This results in an ABCD analysis. Or here's another example. Group A included 40-50% of the assortment, which in absolute terms can be quite a lot. Then from group A we can select group A+, which will include the very best positions.

The three groups A, B and C are not always able to qualitatively separate the data, so additional groups are often added that are not provided for in the classic version.

Fifth disadvantage: lack of seasonality. This disadvantage applies to all methods of statistical analysis. By making changes to the assortment matrix, the company strives to influence future sales. And all calculations are based on past data.

It often happens that some items fall out of sales. This happens for various reasons: the supplier does not have them, a procurement error, etc. Then it turns out that the product has not been sold for some time and the total sales volume will be lower than potentially possible. If this is a position from group A, then according to the calculation results it can easily fall into group B or even C.

To reduce the impact of the fifth drawback, it is recommended to remove from the calculations those periods when the product was unavailable, and also use shorter periods of time for analysis.

ABC analysis has advantages over other methods, which are expressed in simplicity, versatility and easy implementation.

The problems of the method, first of all, are that ABC grouping by one indicator does not always correctly prioritize. When using multivariate ABC analysis, the number of elements in group A can be significantly more than 20%. ABC analysis cannot recognize the quality and nature of the data; this must be done by the analyst before making calculations.

The purpose of analyzing the results of an enterprise’s activities is to identify problems, as well as to find ways and directions to combat them. The company's product range consists of many positions, each of which includes several varieties of the same product, differing in functionality, color and other characteristics. However, the production and sale of not all product items becomes profitable and ultimately brings the planned rate of profit. In order to prioritize between products and make a decision to exclude certain products from the range, it is necessary to conduct a comprehensive sales analysis. One of the methods of such analysis is ABC analysis.

What is ABC analysis

1. A – high priority, i.e. product groups that generate the largest percentage of income.
2. B – medium priority, i.e. product groups that generate a percentage of income that is an order of magnitude lower than high priority groups, but make up a significant part of the profit.
3. C – low priority, i.e. product groups that bring in the smallest percentage of income.

1. Selecting an object of analysis.
   At this stage, you should decide on the object. Since ABC analysis can adapt to any characteristic that has a quantitative assessment, it is very important to choose what exactly will be analyzed. For example, consumers, suppliers, product groups, product items, services, etc.
2. Selecting a parameter for analysis.
   At this stage, you should decide on the parameter in relation to which the analysis will be carried out. Such a parameter can be the share of revenue, part of profit, market share, number of sales units, sales volume, etc.
3. Ranking of objects of analysis.
   At this stage, the objects of analysis are sorted in descending order.
4. Distribution of analysis objects into groups.
   At this stage, the share of the selected parameter for each group is calculated, and based on this, the groups are saturated with objects of analysis.

1. Ease of use.
2. Visibility of the analyzed indicators.
3. Accuracy of calculated criteria and parameters.
4. Quickly identify key problems and ways to solve them.
5. Possibility of automation of each stage of the method.
6. Does not require expensive equipment or additional methods for implementing the method.
7. The speed of carrying out each stage of the method.

1. Some subtleties when constructing complex structured diagrams.
2. Some mistakes can lead to incorrect conclusions.

ABC analysis example

1. Group A contains 5 items, which is about 17% of the total number of product items in the product range under study. However, the share of revenue (at cost) for this group is 84% ​​of total sales.
2. Group B includes 10 items, which is 35% of the total number of items in the nomenclature. The share of revenue (at cost) for this group accounts for 16% of total sales.
3. Group C consists of 14 items that provide the smallest percentage of sales. Moreover, this group includes 9 product items that have been sitting in the warehouse since last year and were discontinued in the analyzed period.

1. Searching for new customers for products in group B in order to increase sales volumes;
2. The production of goods in group A, not to order, but with the aim of forming a certain reserve in the warehouse in order to satisfy the needs of customers for these goods in the shortest possible time.
3. Production of goods included in group C exclusively to order in order to avoid unjustified accumulation of product balances in warehouses.
4. Sales of goods that are left in the warehouse at reduced prices in order to free up warehouse space and increase the total sales volume.

This is a tool that allows you to study the product assortment, determine the rating of products according to the specified criteria and identify that part of the assortment that

which provides maximum effect.
The assortment is usually analyzed according to two parameters: sales volume (quantity sold) and profit received (realized trade margin). ABC analysis is based on the Pareto rule, according to which 20% of assortment items provide 80% of the profit.
Practice shows that 10% of assortment items (group A) account for 80% of turnover; 15% of assortment items (group B) provide 15% of turnover; 75% of assortment items (group C) account for 5% of turnover.
Taking this into account, the entire assortment of a trading enterprise can be divided into groups according to the degree of importance.

• Group A - very important products that should always be present in the assortment. If sales volume was used as a parameter in the analysis, then this group includes the sales leaders by quantity. If trade margin was used as a parameter in the analysis, then this group includes the most profitable products.
• Group B – goods of medium importance.
• Group C - the least important products, these are candidates for exclusion from the assortment and new products.

The first stage of ABC analysis is to identify goals. If the goal is to reduce the assortment, then sales volume and profit are selected as the main parameters. If the goal is to identify and reduce the costs of maintaining inventories, then the turnover ratio, the volume of illiquid stock and the occupied warehouse capacity are selected as the main parameters. If you want to study profitability, then the turnover ratio and the level of profitability are selected as the main parameter. ABC analysis data helps optimize the product range.
With all the many advantages of this type of analysis, there is one significant disadvantage: this method does not allow assessing seasonal fluctuations in demand for goods.

XYZ analysis

XYZ analysis is a tool that allows you to divide products according to the degree of stability of sales and the level of fluctuations in consumption.
The method of this analysis is to calculate the coefficient of variation or consumption fluctuation for each product item. This coefficient shows the deviation of flow rate from the average value and is expressed as a percentage.
The parameter can be: sales volume (quantity), sales amount, amount of realized trade margin. The result of XYZ analysis is the grouping of goods into three categories, based on the stability of their behavior:

• Category X, which includes products with sales fluctuating from 5% to 15%. These are goods characterized by stable consumption levels and a high degree of forecasting.
• Category Y, which includes products with sales fluctuating from 15% to 50%. These are products characterized by seasonal fluctuations and average forecasting capabilities.
• Category Z, which includes products with sales fluctuations of 50% or more. These are goods with irregular consumption and unpredictable fluctuations, therefore, it is impossible to predict their demand.

Combined ABC/XYZ analysis

The combination of ABC and XYZ analyzes reveals the undisputed leaders (group AX) and outsiders (CZ). Both methods complement each other well. If ABC analysis allows you to evaluate the contribution of each product to the sales structure, then XYZ analysis allows you to evaluate sales jumps and its instability. It is recommended to do a combined analysis, where ABC analysis uses two parameters - sales volume and profit.
In total, when conducting such a multivariate combined analysis, 27 product groups are obtained. The results of such an analysis can be used to optimize the assortment, assess the profitability of product groups, evaluate logistics, and evaluate the clients of a wholesale company.

Advantages of combined ABC and XYZ analyzes

Using a combined ABC and XYZ analyzes has a number of significant advantages, which include the following:
- increasing the efficiency of the commodity resource management system;
- increasing the share of highly profitable goods without violating the principles of assortment policy;
- identification of key goods and reasons affecting the number of goods stored in the warehouse;
- redistribution of personnel efforts depending on qualifications and experience.

Formation of ABC- and XYZ-analysis indicators

Before combining the indicators of ABC and XYZ analyses, it is necessary to conduct an ABC analysis of goods by the amount of income received or by the number of products sold for a certain accounting period, for example, a year.
Then an XYZ analysis of these goods is carried out for the same period, for example, by the number of monthly sales for the year. After this, the results are combined.
When combined, nine product groups are determined:

Identification of nine product groups using combined ABC and XYZ analysis

ABC analysis is a classification of research objects (resources, goods, etc.) according to their degree of contribution to the overall result. The analysis is based on the Pareto principle, which states that 20% of efforts produce 80% of the results. That is why traditional ABC analysis divides research objects into three categories:

A – 80% of the result (~20% of items)

B – 15% of the result (~30% of items)

C – 5% of the result (~50% of items)

In particular cases, the boundaries and number of categories may differ depending on the purposes of the analysis or the specifics of the company’s activities.

From a management point of view, ABC analysis is considered a simple but reliable tool for gaining insight into the current situation. The purpose of the analysis is to find out which area or product needs the most attention. Using ABC analysis you can:

• separate the essential from the unimportant;
• identify starting points for improvements;
• avoid wasteful effort;
• increase profitability;
• identify similarities and standards.

2. Where is ABC analysis used?

The analysis technique is very simple and universal, which is why it is widely used in various industries and activities. Most often, ABC analysis is associated with assortment analysis in marketing, logistics and inventory management.

Eg, assortment analysis can be done in the context of products of one brand, product group, or the entire list of company products.

Can analyze clients or consumer groups by amount of purchases, frequency of consumption, number of items purchased, etc.

Supplier Analysis can also be carried out by the amount of supplies, the number of items provided, the frequency and timing of deliveries.

In production using ABC analysis examine raw materials, for example, its costs in terms of goods produced or vice versa - product analysis for the most resource-intensive materials.

Also, using ABC analysis, you can evaluate the performance of departments and in general labor resources.

Can be classified debtors and creditors by the amount of debt or by days of delay.

Can be analyzed investments or any costs and budgets, in a word, you can analyze all numerical indicators that can be classified.

3. Description and general conclusions for ABC analysis groups

The classification of resources by their contribution to the result itself implies the compilation of a top rating by group. So, let's go through the meaning of each of the groups:

Group A– the locomotives of the company, the resources that bring maximum profit or sales. In the event of a sharp decline in the efficiency/sales of one or more elements of this group, the company will suffer large losses, therefore, the names of group A require the greatest attention from the manager - strict control and monitoring, search and maintenance of the strengths of each of the studied elements of the group.

If we are talking about forecasting promotional events for one of the products in group A, then usually such products give the least growth in comparison with other items in the product range.

Group B- these are resources that make a sufficient contribution to the overall result so as not to think about their exclusion, and at the same time, errors in the management of such resources will be less noticeable. Such resources are often called "cash cows" due to the low cost and investment required, as well as the relative stability in the short term.

In the case of forecasting promotional events for one of the goods of group B, it should be taken into account that the sales growth in this group is several times greater than that of goods of group A. Rare exceptions may be associated with very low quality characteristics.

Group C– usually the resources of this group drag the company down or do not generate income and in most cases are subject to exclusion, at the same time, management errors in the names of this segment will be the least noticeable for the company. When analyzing this group, you need to be very careful and first of all understand the reasons for the low contribution; in particular, there may be products that have just been introduced into the assortment.

This is the most dangerous group of positions when forecasting promotional events, since sales growth can be tens of times higher than for goods in group A or be just as low. Comparison of qualitative characteristics influencing buyer preferences can be very useful.

4. How to do ABC analysis - an example of product range analysis

To analyze the product range, we need initial information - sales statistics. These sales statistics have recommended requirements:

1. It is advisable in ABC analysis to compare products of the same group or products that are similar in their quality characteristics (in our example, this will be light beer packaged from 1 to 2 liters).

2. Information on all products should be for the same period, preferably a multiple of it - a week, a month, a quarter (in our example, a week).

3. If there are several sales points, then you need to compare only those products that are sold at the same points or operate with average sales per store (if you compare sales of a product that is presented in 100 stores with sales of an equivalent product that is on the shelves of only 50 stores, you can draw the wrong conclusion about the degree of contribution of each product to the overall result)

ABC analysis can be built on sales in quantitative terms or weighted, if you want to answer the question - which of the goods load the supply chain the most? But the owner, manager or marketer is more interested in the question: which products bring in the most money? The answer to this question will be an analysis by revenue or operating profit; in our example, we will conduct the analysis by the amount of sales (revenue):

In the resulting table, we need to sort the sales amount in descending order:

Then in the column next to it we will make a sum with a cumulative total by shares of the sales amount, that is, to the share of sales of a product we add the sum of the shares of all products that are above it.

Finally, we group the positions into ABC categories based on the established rule - all positions that in the column with the cumulative total of sales shares are in the range from 0% to 80% are assigned to group A, positions from 80% to 95% are group B, from 95 % to 100% - group C:

Actually, this is where the construction of ABC analysis ends; then you only need to draw conclusions)

ABC Analysis in Excel

5. Advantages and disadvantages of ABC

Each analysis method has its advantages and disadvantages, ABC analysis is no exception.

Advantages:

1. Simplicity. Fast construction, easy learning

2. Transparency. The simplicity of the method allows you to follow the logic of the analysis and interpret the calculations in any report.

3. Versatility. Analysis of the degree of contribution to the overall result can be done in almost any area of ​​activity that needs to be assessed.

Disadvantages of ABC analysis:

1. Momentum. There is only one drawback, but it is significant enough that any analyst should not forget about it. ABC analysis reflects the structure only at the current moment; by default, the analysis assumes that such a structure will remain in the future, but there may be two situations that ABC cannot adequately explain:

Situation 1. Sales of a product may fluctuate, for example, due to supply interruptions, revaluations or promotional activity; as a result, we may underestimate the contribution of such a product to the overall result or, on the contrary, overestimate it and, as a result, draw incorrect conclusions. Such jumps, as a rule, are short-term in nature and can be seen through the analysis of fluctuations in the period under study; this is why XYZ analysis is used, which, like ABC analysis, groups products, but not according to their contribution to the result, but according to their uniformity sales

Situation 2. Analysis in one group of goods with radically opposite seasonality, the fluctuations of which are much wider than the period under study, based on which ABC is built. For example, you happened to analyze tangerines and ice cream in the same group, depending on the time of year in which the analysis is carried out - the share of sales of the product, and, consequently, its contribution to the overall result will be different and in winter you can draw an erroneous conclusion for ice cream, and in summer - for tangerine. Of course, choosing products for analysis that are similar in their characteristics will help to avoid such situations; if for some reason this is impossible, then the conclusions must take into account seasonality as an additional parameter for each item.

ABC analysis is a method that allows you to classify a company's resources according to their importance. It is based on the Pareto principle, in accordance with this law, 20% of the number of elements of any array of goods determines 80% of its total value. In relation to ABC analysis, the Pareto rule may sound like this: reliable control of 20% of positions allows for 80% control of the system, be it stocks of raw materials and components, or the product range of the enterprise, etc.

ABC analysis - analysis of inventory by dividing into three categories:

· A - the most valuable (75%);

· B - intermediate (20%);

· C - least valuable (5%).

In essence, ABC analysis is the ranking of an assortment according to various parameters. In this way, you can rank suppliers, warehouse stocks, buyers, and long periods of sales - everything that has a sufficient amount of statistical data. The result of ABC analysis is the grouping of objects according to the degree of influence on the overall result.

ABC analysis is based on the principle of imbalance, during which a graph is constructed of the dependence of the cumulative effect on the number of elements. This graph is called a Pareto curve, Lorenz curve or ABC curve. Based on the results of the analysis, assortment items are ranked and grouped depending on the size of their contribution to the total effect. In logistics, ABC analysis is usually used to track shipment volumes of certain items and the frequency of requests for a particular product range, as well as to rank customers by the number or volume of orders they place.

Algorithm for ABC - assortment analysis

First step: Define the object of assortment analysis.

The object of assortment analysis can be a product category, group, subgroup, product item, client (for wholesale trade), debtor, supplier, etc.

When conducting an assortment analysis for the purpose of assortment management, it makes sense to select a product item (assortment item) as the object of analysis, which will allow for a detailed analysis of sales; and to analyze the assortment structure - product category.

Second step: Determine the parameter by which the assortment will be analyzed.

It can be sales volume (in value or physical terms), gross income, average inventory (in value or physical terms), number of orders (for example, when analyzing customers), volume of orders, etc.

When conducting an assortment analysis, two parameters (features) are most often chosen for the purpose of assortment analysis: turnover in physical terms and income. In this case, the analysis is carried out within a category for each category. When conducting an end-to-end analysis, turnover must be taken in value terms. It makes no sense to compare bottles with kilograms and pieces with liters.

Carrying out an analysis of the assortment based on two criteria, in particular, turnover and income, will allow you to understand which products are the most/least popular among consumers and what benefits they have for the retailer.

When selecting several characteristics (two or more), the analysis is carried out separately for each characteristic, and then the results are combined. For example, when analyzing an assortment, groups (ABC) are first determined by turnover, and then by profitability. Then a combination is carried out and each position is characterized by two letters (for example, BC - the name of the assortment is in group B in terms of turnover and in group C in terms of profitability).

When analyzing the assortment structure, category profitability is chosen as a feature of assortment analysis. When analyzing customers, order volume and number of orders are selected as characteristics.

Third step: Determining the total value of the selected indicator.

It is necessary to sum the indicator for each position. When conducting sales analysis (for the purpose of assortment management), we determine the total value of turnover in physical terms for each category (group) and the total value of gross income for each category (group).

When analyzing the assortment structure, we summarize the values ​​of turnover (in value terms) and gross income of all categories.

Fourth step: Determining the share of each position in the overall result.

When analyzing sales, we determine the share of turnover and income of each position in the total value of these parameters of each category (product group).

When analyzing the assortment (determining the influence of a category on the overall result), we determine the share of turnover (in value terms) and gross income of each category.

Fifth step: Sorting the assortment analysis objects in descending order of the share of each item.

Positions are ranked (analysis of assortment, categories, customers, suppliers, inventory) in descending order of the proportion of the selected attribute.

So, for example, when conducting sales analysis (for the purpose of analyzing the assortment), we rank within each category by share of turnover (in physical terms) in such a way that the higher the share contributed by a specific position to the total turnover, the higher this position will be located in the list within a category. At the next iteration, when we construct groups by profitability, the position of the position in the list will be higher, the higher the share of gross income.

Sixth step: Calculation of the share with accumulation of the result of the assortment analysis.

We calculate the share by accumulating the results of the assortment analysis. When analyzing the assortment for this, the first position is assigned the share value determined in the fourth step, the second position is assigned the sum of the share of this position, determined in the fourth step, and the accumulated result of the previous position, the third position is assigned the sum of the share of this position, determined in the fourth step, and the accumulated result of the second positions, etc. That is, in the general case, the accumulated result is equal to the sum of the position share and the accumulated result of the previous position.

For the first position there is no previous one, which is why its accumulated share is equal to the share itself.

For the last position, the accumulated share should be equal to 100%, since we ended up adding up all the shares.

Let us explain that if we consider the analysis of the assortment within each category, then we determine the accumulated result within each category, and not the end-to-end analysis of the assortment.

Seventh step: determining the number of groups and the boundaries of the groups of the assortment analysis matrix.

This step is the most complex algorithmic, but at the same time one of the most important. It defines, firstly, the number of partition groups, and secondly, the boundaries of these groups. So, for example, the group we assign this or that item (name of the assortment) to will depend, firstly, on its future fate (whether it will be left in the assortment or excluded), and secondly, on the way its reserves are managed .

The number of partition groups can theoretically vary from 2 to n, where n is the number of positions being studied. In practice, a division into 3, less often 4, groups is often used.

Group boundaries are often set at the next level (if you choose to split into three groups).

Eighth step: assigning a position to the selected group.

Based on the accumulated share and selected boundaries, we assign each position to one or another group of the assortment analysis matrix.