Fis analysis. ABC-, XYZ-analysis of assortment. Example of ABC analysis of product groups

A successful business in many cases depends on working correctly with numbers. This can happen both at the level of simple calculations during the comparison of “debit” and “credit”, and in the aspect of complex, multi-level analytical calculations. Experts include ABC and XYZ analysis as such. What are these methods? What is their practical significance? How to use them correctly?

General information

What is ABC analysis? This is understood as a method by which one can classify a particular resource depending on the degree of its importance. The basic principle used in this type of analysis is the Pareto rule. In the generally accepted interpretation, it sounds like this: 20% of actions bring 80% of the total result.

In relation to ABC analysis as such, this principle can be interpreted as follows: reliable control of 20% of some system (optionally sales or enterprise management) determines 80% of its effectiveness.

ABC analysis involves the classification of certain operations or areas of a resource by dividing them into several categories (depending on the degree of value) - A, B and C. Type A includes the most valuable of them (those that bring 80% of the results, and they are, respectively, 20%). Actions of type B are “mediocre”, there are 30% of them, and they provide 15% of the result. Activities of type C, in turn, are the least valuable. Despite the fact that there are 50% of them, they provide only 5% of the result.

Analysis methodology

The practical use of a tool such as ABC analysis largely comes down to making a “rating” of the usefulness of certain actions. The criterion here, as a rule, is statistical information or expert assessments that make it possible to identify the “most valuable” operations.

As a rule, during ABC analysis, you can build graphs, the X axis of which will be the number of actions, and the Y axis will be performance indicators. This way you can calculate which activities will be most effective. These types of graphs are sometimes called Pareto curves. As soon as the researcher ranks the effectiveness of all actions, statistical analysis is carried out, the most useful activities are calculated according to all graphs, and, as a result, their final “rating” is formed.

Sequence of analysis

In what order should ABC analysis be performed? Experts recommend adhering to the following algorithm:

1. We pose the main question. The effectiveness of actions in relation to what result are we interested in in this case?

2. We select activities that are most relevant to the task at hand.

3. We draw up schedules for each of the actions in comparison with the performance indicators of each.

4. We select the 20% most effective, 30% - mediocre, 50% - the least significant.

The specific methodology for each of the four points can be selected based on the purpose of the analysis. In some cases, an entrepreneur, say, wants to show an investor that such and such a product sells better, and it is necessary to invest more actively in it. Another option is to analyze the feasibility of allocating resources allocated to certain purchases. Also, the purpose of ABC analysis may be to identify the effectiveness of advertising aimed at “promoting” certain types of goods.

Practical benefits of analysis

How can the analysis in question be useful in practice? There are many options here. Let's take the field of sales. Let's say we need to identify which product items generate the most revenue. A properly conducted ABC sales analysis will allow us to detect not just a scattered list of well-selling products, but 20% of them, which provide 80% of the profit. The situation is similar with the service sector. ABC customer analysis can help you find those 20% of service consumers on whose activities 80% of revenue depends. It's the same with industry. ABC analysis of stocks of raw materials or semi-finished products will identify 20% of their varieties, which are used in 80% of the volume of products, and therefore are the most valuable. That is, those who need to be given priority in the procurement and distribution of capacitive resources in the warehouse.

We see how versatile ABC analysis is. There is more than one example of its use. The areas compatible with the use of this technique are very different.

XYZ analysis

There is another method that complements the study using the ABC methodology - XYZ analysis. What is it? It is believed that this type of research makes it possible to classify the reserves available in the company depending on the intensity of their consumption, as well as forecasting the dynamics of the emergence of needs for them in relation to a specific time cycle. What does it mean?

Resources are classified into three categories - X, Y and Z. Those that belong to type X have stable dynamics of consumption, minimal adjustment over time, and, as a result, their consumption is quite easy to predict. As a rule, the difference between the minimum and maximum consumption indicators recorded within time periods does not exceed 10%, or even tends to zero.

Resources of type Y, in turn, have a noticeably less stable consumption dynamics, but still quite well predictable. The difference between the minimum and maximum indicators is 10-25%.

Resources classified as category Z are characterized by very unstable consumption dynamics. There are no clearly defined trends; it is difficult to predict anything. The values of the minimum and maximum consumption indicators for a time period may diverge by 25% or more.

An interesting fact is that the same resource can belong to different categories in different measurement periods. This may be predetermined, for example, by the time of year, yield, or the specifics of demand. For example, tangerines traditionally sell well in stores in winter. But the specific dynamics of their implementation throughout the winter will most likely be different. During the period, say, from the beginning of December to the 20th of the month, tangerines will most likely be classified as a type Y product - with relatively stable but variable demand. However, due to the fact that this fruit is very popular in the New Year, from the 20th of December to mid-January it will most likely be sold at a constantly high rate, which will allow it to be classified as a resource of type X. In turn, Closer to February, the tangerine “hype” decreases, and by spring, the demand for this product becomes close to category Z according to the criteria.

Combination of two tests

ABC and XYZ analysis can be combined. Moreover, in many cases the study will be incomplete if each method is used separately. How to carry out sequential ABC-XYZ analysis? We will now look at an example of an algorithm suitable for this purpose.

Let’s say we are faced with a task: to analyze the assortment of grocery products to determine which units of sale bring the most revenue and which of them are characterized by the most stable demand. In the first part of the study, we will need ABC analysis of the assortment, in the second - XYZ. How to proceed? What results can we have in both cases?

First, we identify the best-selling product, say, over the past month. We take data from a CRM system or other accounting source, reflecting the number of product units sold by day. We find that 80% of all revenue came from sausage, chips and carbonated drinks. These are goods of group A. Next, we look at how many receipts for each product item were punched on each day of the month. It may turn out that soda was sold in quantities of 100-102 units per day. Sausage - on one day 50, on another - 153, on the third - 10, on the fourth - 181 units. In turn, the results for chips can show that this product was sold as follows: on the first day 80 units, on the second - 125, on the third - 91, on the fourth - 114. It turns out that among the products of group A, soda is the most stable, and it can be classified as category X (and therefore can be safely purchased from suppliers under favorable sales conditions). Chips are a product with average stability of demand; it will belong to group Y. Sausage is a product of group Z, the sales dynamics of which often change.

Similar procedures can be carried out for goods of type B and C. Experts recommend, based on the results of a comprehensive study of the assortment, when the ABC analysis method is combined with the XYZ method, to identify leading products (which will be classified as type AX), as well as outsider positions ( classified as CZ). In addition to them, you will get 7 more products (in total - 9 possible combinations, 3 to the 3rd power, and when measured in different periods, when the dynamics of sales of the same products may change, the total number of options can reach 27, 3 to the 3rd power) . All of them can be ranked and a “rating” can be compiled that reflects the combination of profitability and sales stability. For the convenience of calculations, we can try to carry out the XYZ-analysis, as well as the preceding ABC-analysis in Excel. The example we've looked at is simple enough that we can use simplified tools such as a spreadsheet.

Practical usefulness of classification into groups X, Y, Z

We noted above that, having determined the most profitable and most stable product, we can adjust the policy of relationships with suppliers. However, this is not the only advantage of XYZ analysis. How else can the results of such a study help us? Let's consider the specifics of their practical use in comparison with each of the three groups of goods.

So, products of type X are characterized by the most stable demand. The most important criterion for the usefulness of having such information is inventory planning. We can establish relationships with suppliers so that our warehouses are used as efficiently as possible. We will know exactly how long the products of group X will be there from the moment they are loaded until they hit the shelf. Consequently, we will be able to plan the import of less dynamic, in terms of demand, positions Y and Z so that there is always somewhere to place them.

Priority in procurement

Products of group Y are characterized by relatively stable consumption dynamics. The main function of such products is to support the main demand generated for goods of group X. In some cases, correlations are possible, reflecting the dependence of the dynamics of demand in class X on the availability of products of type Y on the shelves. Analysts probably believe that the psychological aspect plays a role here. A buyer who sees empty shelves - let's take the case when goods of group Y are not represented by the retailer - does not dare to make purchases in such a store, even for those items that are usually characterized by stable demand. In turn, if there are enough products of type Y, then the demand for goods X is “fueled”. The main task for the store owner in this case is to ensure optimal utilization of warehouse capacity, to find the ideal combination between the costs of purchasing auxiliary Y-items and the real economic effect their presence on the shelves.

In turn, products of group Z are difficult to optimize in terms of warehouse management. They may also not have a direct impact on the sales dynamics of “flagship” products of type X. And therefore experts recommend giving them a minimum place in the total volume of purchases. Or, as an option, replace them with new products, products not yet tested on the market. In this case, there will at least be a chance that fresh brands that appear on the shelf will grow from category Z to more significant ones in terms of sales stability.

Play in your own "league"

Let’s make a reservation right away: when interpreting the result of the analysis, you should understand that, say, products of group Z belonging to category A (and this is the unusualness of the complex analysis) will be more valuable than products of type X for category B. Moreover, their direct comparison is not entirely correct - this is the same as, relatively speaking, considering the possibilities of football teams from different level leagues. Therefore, when analyzing the prospects for goods of categories A, B and C, it is incorrect to linearly compare their distribution among groups X, Y and Z. Consistency in the interpretation of results for products in relation to their “leagues” is important.

So, let's summarize briefly:

Products of category X are the “flagship” of sales, their purchase from suppliers must be stable, supply channels are established and, if possible, diversified (in case of “sanctions” and other types of phenomena beyond the control of the business);

Products of class Y must also be present on the counter, performing a supporting function in relation to goods X and stimulating general demand;

Products of type Z can, if not be excluded from circulation, then try to replace them with experimental samples, which could potentially acquire the status of products of categories X and Y.

All these conclusions take place provided that we are talking about the analysis of goods within one group - A, B or C. As we said above, identifying “averaged” indicators does not make much sense here.

Nuances of interpretation

Of course, this kind of recommendation is valid only if the results of the combined ABC-XYZ analysis can be interpreted unambiguously. The research methodology must be accompanied by multidimensional criteria that will make it possible to draw undeniable, from a statistical point of view, conclusions regarding the prospects for sales of a particular product. When we considered the question of how ABC analysis could be carried out (the sausage example), we distributed the products into the appropriate categories very conditionally. Same thing with the XYZ part. In practice, the analysis methodology is much more complex. Moreover, researchers rarely conduct, as in our example, an ABC analysis in Excel using essentially manual calculations. As a rule, much more complex analytical programs are used in order to minimize the likelihood of errors, since we are talking about real business, where miscalculations are undesirable, unlike theoretical scenarios.

Proverbs don’t appear on their own... Sometimes you get into such a jungle of analytics that your hand inevitably reaches for the liquor cabinet (oh well, we know there’s one in every office).

But let's talk a little about something else.

In retail, logistics, warehouse and inventory management there is such a thing as ABC analysis. Many theoretical publications have already been written about it. And everything seems to be relatively simple and clear, but is it really so?

When a category manager or marketer of a retail chain comes close to conducting ABC analysis, he inevitably has a whole bunch of questions, hesitations and doubts. It is with them that we will work in this article!

Let's go through the algorithm of actions for ABC analysis in grocery retail chains, exceptions to the rules that must be taken into account, and show an example of conducting an analysis for the product group of Alcoholic beverages (yes, exactly those half-liters).

If anyone is hearing about ABC analysis for the first time, here it is.

how it is done.

ABC analysis- This is the most common method of studying assortment. It is based on the Pareto law, applicable to many aspects of life. Its essence for retail is that 20% of products provide 80% efficiency, and the remaining 80% of products provide only 20%.

ABC analysis is a method with which you can determine the contribution of each product to the turnover and profit of a store, and distribute products into categories for effective assortment management.
To do this you need:

Sort all products by selected criterion (for example, turnover).
Calculate what percentage the turnover of each product is of the total turnover of the product group.
Calculate cumulative (or accumulative) interest by adding the percentage to the amount of previous interest.

We select categories, for example
category A - priority goods, bringing in up to 80% of the total turnover;
category B - ordinary goods, from 80% to 95% of total turnover;
category C - outsider goods, from 95% to 100% of total turnover (all that remains).

We define the boundaries of categories that should differ significantly from each other.

We build a cumulative curve.
We connect the extreme points of the curve with a straight line.
Find the point of tangency of the line parallel to the resulting straight line. This point will determine the boundaries of category A, for which the nature of the accumulation of the qualitative criterion is homogeneous.
Similarly, we connect the boundary point of category A and the extreme point of the curve with a straight line.
We find the point of tangency of the line parallel to the resulting straight line and determine the boundaries of category B.

When conducting an ABC analysis, the first thing that needs to be done is to determine

How, Why and What will we use it for?

It is important to answer the following questions:

What is the purpose of the analysis?
What will be the objects of analysis?
By what criteria?
What percentage will be optimal for ABC analysis?
Over what time period should the analysis be carried out? and with what frequency?
How to divide products into A, B, C categories?
What will be the interpretation and actions based on the results of the analysis?

Let's go through the points.

Purpose of analysis depends on the existing problem or, why are we doing it at all? Any analytics serves to achieve some goal, ABC analysis is by no means an exception. A clear vision of the goal is already half the success of marketing activity.

The goal predicts what we can achieve using ABC analysis, so it may differ even depending on who is conducting the analysis. Category managers most often analyze product sales, store managers analyze turnover, and marketers analyze the inclusion of goods in customer receipts.

The most popular goals are:

identify product groups that bring the greatest profit;
optimize the assortment;
highlight leading and outsider products;
manage inventory and supplies;
compare indicators with the previous period, analyze changes.

You can achieve your goal using different Objects of analysis. They can be supplies, warehouse stocks, the product range of a separate store or an entire retail chain, goods that are included in a certain product group or category.

Here it is necessary to approach the analysis quite carefully. For example, to optimize the assortment, analysis of the entire assortment of a store or chain will yield practically nothing. After all, we cannot leave only bread, milk and alcohol in the store, although these groups will be the most popular. But in the context of a separate product group, you can easily track products of group C (outsiders in terms of turnover and number of sales) that need to be disposed of.

Criteria. Again closely related to the object and purpose of the analysis.
The most common:

turnover;
revenue;
profitability;
number of sales;
number of receipts, entry into receipts - frequency of purchases of goods.

The choice of just one criterion for analysis significantly limits the reliability of the results. As a rule, two or three criteria are used and cross-analysis is carried out, which we will discuss in more detail below.

Percentage. Unfortunately, the average values proposed by the Pareto principle do not always correspond to reality. In reality, a category manager or store manager, when determining the percentage, is guided, first of all, by his experience, goals and analysis criteria, and the specifics of the assortment of a product group, store or retail chain.
80-15-5,
70-20-10,
50-30-20,
and even 40-40-20, these are all possible options for percentage ratios of categories A, B and C.
A wide spread indicates a variety of situations and the impossibility of focusing on a universal relationship between category boundaries. Thus, a category manager of a large retail chain can afford to remove a significant number of category C products from the assortment; the store shelves will not be empty in any case. Another thing is the manager of a small retail chain of 2-3 stores, where the release of 100-200 products will have a detrimental effect on the breadth of the range presented.

A period of time. Often, conducting an ABC analysis is too expensive in terms of using the working time of marketers, category specialists or store managers, and the results of such an analysis will, to put it mildly, not be obvious due to the cyclical nature of product sales by day of the week or season.

For example, an analysis of the entire product range can be carried out once every six months in order to analyze which products and product groups are the most important and what has changed compared to the previous period.

Analysis of goods in each product group is usually carried out once every 2 months, with possible options of once every 3 months. It all depends on the size of the assortment and the capabilities of the network analysts.

Division into A, B, C categories.
When analyzing a store’s product range, a marketer can use one criterion - for example, the profitability of a product or product group, but the data obtained is not always useful enough.

Therefore, cross-analysis is used according to several criteria at once. Yes, this approach is not simple, but using a larger number of criteria allows you to better see the existing situation. During this process, several options are possible:

1. Sequential division into categories.

It is worth using if the range of product groups is too large. First, the assortment is analyzed according to the first criterion (for example, turnover), then each resulting category is analyzed again according to the second criterion (number of sales), etc. As a result, we get subcategories with a relatively small list of products that are convenient to work with.

2. Parallel division into categories.

We carry out ABC analysis simultaneously (in parallel) according to several criteria, creating categories like AA, BC, etc...

Using 2 criteria, say Income and Number of Sales, we already get 9 categories:

This approach is more complex, gives a larger number of product categories, but allows you to obtain extensive information about each category.

For example, using 3 criteria for parallel analysis, products that receive AAA are the most important products for a retailer. They generate significant income, are often purchased, and generate revenue. This means they must be constantly available, with uninterrupted supplies and good reserves.

Products of the ABA, BAA, AAB categories are also quite important and should be actively worked with. For example, a product is included in category A in terms of revenue and profitability, and in category B in terms of sales. It’s worth finding the best place on the shelf for it, or carrying out promotional activities, and the store will receive a significant profit. Another option is a product group with category A in terms of sales and profitability, and category B in terms of revenue. For goods in this category, a revision of the pricing policy is possible, so a slight increase in the price of goods will lead to an increase in store revenue.

3.Usage synthetic approach to defining categories.

For each criterion, a weight coefficient (WC) is determined, depending on its significance for the purpose of the analysis.
For example, for analysis, Turnover is more important than the Number of sales of a product, and the Number of sales is more important than Entries in receipts.

For each product, a synthetic indicator is calculated.

Next, it is necessary to rank the results obtained.

This approach makes it possible to characterize each product item included in the classification with one number and conduct an ABC analysis as if only one criterion were used.

Interpretation. The results of the ABC analysis should be carefully studied; hasty decisions should not be made.
The idea of classic ABC analysis remains unchanged in any case - the distribution of goods into categories for further work. The analysis allows us to identify products that require maximum attention from marketers, category managers, and managers for their qualitative impact on the activities of the retail chain, while limiting the scope of management to the required minimum.

The number of category A is always minimal, category C is the maximum. At the same time, category A has priority in terms of maintenance and work with it. Category B has a standard level of service, category C - if goods are not removed from the range, then they have the lowest level of service and attention.

Things to remember or exceptions to the rules

Products of the main assortment and products that have fallen out of it. In the main assortment, products are sold at least 2 times a week during the period chosen for analysis. Products that for some reason are sold less than twice a week fall out of the main assortment. These may be high-end, new, seasonal or out-of-stock items. It makes sense to conduct ABC analysis on the main assortment. And it is necessary to pay attention to products that have fallen out of the main assortment and identify the reason for the drop in sales.

Promotional goods. If during the period taken for ABC analysis you had promotions in your retail chain or in a separate store, then the results of sales of promotional goods can significantly affect the reliability of the analysis. Here it is important for the marketer to decide whether to exclude products covered by the promotion from the data set for analysis, or to make a certain amendment for them depending on the conditions of the promotion.

Luxury goods. Products that are not included in the main assortment of a store or chain (sold less than 2 times a week or even much less often), but when sold can bring significant income. They can be included in the data array for ABC analysis, where with a significant probability they will fall into category C. But such products are important for the store’s assortment, which means they cannot be displayed. At the same time, due to the low frequency of sales, it is inappropriate to allocate space in the store warehouse for luxury goods; it is easier to organize their purchases upon sale.

New products. Anyone understands that no matter how advertised a new product is, at first its sales will be significantly lower than proven brands. But at the same time, new products are absolutely necessary in any store. There are possible solutions here.

New products are not included in the analysis and cannot be removed from the assortment for the first few months of sales.

If it is too technically difficult to exclude new products from the data set, they are assigned the label “New”, and when interpreting the results of ABC analysis, such products are not subject to reduction.

Another option is to automatically include new products in category A. Why is he bad? The fact that a certain number of new products in category A shifts other products lower in the ranking.

Missing products. For various reasons, sometimes a product may not be on the store shelves or in the warehouse. That is, in principle, it could be sold, and there was demand, but there is no data for analyzing sales of the product. Therefore, it is useful when interpreting ABC analysis to know the date of the last arrival of the goods at the store.

Let us give an example of conducting ABC analysis.

In a supermarket chain of 17 stores, there were certain problems with the “Alcoholic drinks” product group. Products in this group sold well and generated revenue, but took up significant shelf space in stores. Also, it was necessary to identify brands and individual products for planning autumn promotions. We conducted an ABC analysis using the BI service Datawiz.io.

So, purpose of analysis- selection of goods for promotions, reduction of the range of product groups.

Object of analysis- the main assortment of the “Alcohol” group throughout the entire distribution network.

A period of time- 2 months.
The analysis will be carried out using a parallel approach of 2 criteria: Turnover and Number of sales. The choice of these criteria directly depends on the purpose of the analysis. The managers of the retail chain needed to reduce the number of products that took up space on the shelves and did not significantly affect the turnover of the product group as a whole.

Analysis of the main assortment will allow us to obtain more accurate data without taking into account seasonal or unavailable products.

Percentage.
The optimal ratio in this option would be 75-95-100 according to the selected criteria due to the specifics of the product group.
In the screenshot below we see the number of product items that are included in each category A, B and C and the percentage of the category from the total indicator.

For greater clarity of the relationships between categories, consider them in a diagram.

Interpretation. Let's analyze the results obtained.
Analysis is possible using both tabular data and visualizations.

The first goal is to select products for promotions.
Category AA By Turnover and Number of Sales, 162 product positions fall, as can be seen in the screenshot below.

We can visualize data for each category.

For example, now to build visualization we used the following indicators:
horizontal axis - number of sales for the selected period;
vertical axis - turnover for the selected period;
circle diameter - % of the turnover of the selected category. Other options for constructing a graph are possible, depending on the goals of the ABC analysis.

As we can see, GreenDay Organic Life is the leader in sales in this retail chain in the AA category by a significant margin.

The best-selling brands are GreenDay and MEDOFF. Work with suppliers of such goods should be very well established; they are the ones who supply us with leading goods. It is possible to create special better conditions for them, additional space on shelves, organize promotional activities, etc.

But we consider it inappropriate to carry out promotions for goods of category AA; these goods sell well even without a promotion.

In this case, it is better to plan promotion for the AB category, which significantly affects the store turnover, and the number of sales of the group’s products will increase as a result of promotional activity.

The results of selecting products in category AB can be seen in the figure below.

As you can see, the most successful promotions will be for Georgian cognacs and wines, as well as Klinkov brand cognacs.

The second goal of our analysis was optimizing the assortment and getting rid of unsold goods . Let's deal with category SS.
Here visualization simplifies the analysis even more. As we remember, luxury goods can also fall into this group. For example, in the picture below there is Scotch whiskey with a price above 800 UAH. per bottle sold only 2 times in 2 months, but brought significant profits.

But products along 2 axes tending to zero and with a small circle diameter, which do not in any way affect the overall turnover, should be removed from the assortment - they are not sold and only take up space on the shelves. As an example, in the picture, the wine “Sun in a Glass” was sold only 2 times in 2 months for 32 UAH. per bottle and therefore does not affect turnover in any way.

Thus, ABC analysis allowed us to distribute the products included in the Alcoholic Beverages product group into 9 different categories and develop recommendations for the retail chain to optimize the assortment:

Category AA - leading products, the highest priority category, products must always be in stock, careful control of inventory levels is necessary;
Category AB - products that will bring maximum efficiency during promotions;
categories VA, BB, BC, SV - average products, average level of inventory management and shelf placement;
Category CC - outsider products; a detailed analysis of the category and removal of the lowest-performing products from the assortment is required.

The job is done, you can celebrate! Moreover, we are now aware of hot trends.

ABC analysis

ABC analysis- a method that allows you to classify a company's resources according to their importance. This analysis is one of the methods of rationalization and can be applied in the field of activity of any enterprise. It is based on the Pareto principle - 20% of all goods produce 80% of turnover. In relation to ABC analysis, the Pareto rule may sound like this: reliable control of 20% of positions allows 80% control of the system, be it stocks of raw materials and components, or the product range of the enterprise, etc. Often ABC analysis confused with ABC method, deciphering ABC as Activity Based Costing, which is fundamentally wrong.

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

A - the most valuable, 20% - inventory; 80% - sales
B - intermediate, 30% - inventory; 15% - sales
C - least valuable, 50% - inventory; 5% - sales

Depending on the purposes of the analysis, an arbitrary number of groups can be identified. Most often there are 3, less often 4-5 groups.

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.

Procedure for ABC analysis

We determine the purpose of the analysis (why do you actually need this analysis?).
We determine actions based on the results of the analysis (what will we do with the results obtained?).
We select the object of analysis (what will we analyze?) and the analysis parameter (by what criteria will we analyze?). Typically, the objects of ABC analysis are suppliers, product groups, product categories, and product items. Each of these objects has different description and measurement parameters: sales volume (in monetary or quantitative terms), income (in monetary terms), inventory, turnover, etc.
We compile a rating list of objects in descending order of the parameter value.
We calculate the share of the parameter from the total sum of parameters with a cumulative total. The share with a cumulative total is calculated by adding the parameter to the sum of the previous parameters.
We select groups A, B and C: we assign group values to the selected objects.

There are about ten methods for identifying groups, the most applicable of them are: the empirical method, the sum method and the tangent method. In the empirical method, the division occurs in the classic proportion of 80/15/5. In the sum method, the share of objects and their total share in the result are added up - thus the value of the sum is in the range from 0 to 200%. The groups are distinguished as follows: group A - 100%, B - 45%, C - the rest. The advantages of the method are greater flexibility. The most flexible method is the tangent method, in which a tangent is drawn to the ABC curve, first separating group A and then C.

The probabilities of demand for material resources A, B and C are subject to different laws. It has been established that in most industrial and trading companies, approximately 75% of the cost of sales volume is only about 10% of the items in the product range (group A), 20% of the cost - 25% of the items (group B), 5% of the cost - 65% of the items (group C) . There are many ways to identify groups in ABC analysis.

The ABC method is widely used in planning and forming an assortment at various levels of flexible logistics systems, in production systems, supply and distribution systems.

Experts advise caution when shifting the boundaries of ABC groups (80/15/5), the fact is that in practice the divisions of 80% 15% and 5% are usually used. If you shift the boundaries, an external listener (or an expert) may draw incorrect conclusions based on the indicators you provide, for example, for group “C”. Since his expectations about group “C” = 5% will not coincide with the rules for selecting groups that you changed.

Literature

Sterligova A. N., “Inventory management of a wide range of products. Where to start?”, LogInfo magazine dated 12.2003
Andrey Fisher, “Methods for identifying groups in ABC analysis,” Logistics and Management magazine, No. 1-2008

Links

Wikimedia Foundation. 2010.

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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: 20% of all goods produce 80% of turnover. In relation to ABC analysis, the Pareto rule may sound like this: reliable control 20%... ... Wikipedia

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SWOT analysis and synthesis are the basis for the formation of corporate strategy, Uchitel Yu.G.. In the process of solving the problems of crisis management today and effective design of the future, the Light system of methods (SWOT analysis and synthesis, strategic road map, GAP analysis, ...

To analyze the range of goods, the “prospects” of customers, suppliers, and debtors, ABC and XYZ methods are used (very rarely).

ABC analysis is based on the well-known Pareto principle, which states: 20% of effort produces 80% of the result. Transformed and detailed, this law has found application in the development of the methods we are considering.

ABC Analysis in Excel

The ABC method allows you to sort a list of values into three groups, which have different effects on the final result.

Thanks to ABC analysis, the user will be able to:

highlight the positions that have the greatest “weight” in the total result;
analyze groups of positions instead of a huge list;
work according to one algorithm with positions of one group.

The values in the list after applying the ABC method are distributed into three groups:

A – the most important for the result (20% gives 80% of the result (revenue, for example)).
B – medium in importance (30% - 15%).
C – least important (50% - 5%).

The values provided are optional. Methods for determining the boundaries of ABC groups will differ when analyzing different indicators. But if significant deviations are detected, it’s worth thinking about what’s wrong.

Conditions for using ABC analysis:

the analyzed objects have a numerical characteristic;
the list for analysis consists of homogeneous items (you cannot compare washing machines and light bulbs; these products occupy very different price ranges);
the most objective values were selected (it is more correct to rank parameters by monthly revenue than by daily revenue).

For what values can the ABC analysis technique be used:

product range (we analyze profits),
customer base (we analyze the volume of orders),
supplier base (we analyze the volume of supplies),
debtors (we analyze the amount of debt).

The ranking method is very simple. But operating large amounts of data without special programs is problematic. The Excel spreadsheet greatly simplifies ABC analysis.

General scheme:

State the purpose of the analysis. Determine the object (what we are analyzing) and the parameter (by what principle we will sort into groups).
Sort the parameters in descending order.
Summarize numerical data (parameters - revenue, amount of debt, volume of orders, etc.).
Find the share of each parameter in the total.
Calculate the share as a cumulative total for each value in the list.
Find a value in the list in which the cumulative share is close to 80%. This is the lower limit of group A. The upper one is the first in the list.
Find a value in the list in which the cumulative share is close to 95% (+15%). This is the lower limit of group B.
For C – everything below.
Count the number of values for each category and the total number of items in the list.
Find the shares of each category in the total.

ABC analysis of product range in Excel

Let's create a training table with 2 columns and 15 rows. We will enter the names of conditional goods and sales data for the year (in monetary terms). It is necessary to rank the assortment by income (which products provide more profit).

Now we have completed ABC analysis using Excel. Further user actions are to apply the obtained data in practice.

XYZ analysis: example calculation in Excel

This method is often used in addition to ABC analysis. In the literature there is even a combined term ABC-XYZ analysis.

The abbreviation XYZ hides the level of predictability of the analyzed object. This indicator is usually measured by the coefficient of variation, which characterizes the measure of data dispersion around the average value.

The coefficient of variation is a relative indicator that does not have specific units of measurement. Quite informative. Even on my own. BUT! Trends and seasonality in dynamics significantly increase the coefficient of variation. As a result, the predictability indicator decreases. A mistake can lead to wrong decisions. This is a huge disadvantage of the XYZ method. Nevertheless…

Possible objects for analysis: sales volume, number of suppliers, revenue, etc. Most often, the method is used to determine goods for which there is stable demand.

XYZ analysis algorithm:

Calculation of the coefficient of variation of the level of demand for each product category. The analyst estimates the percentage deviation of sales volume from the average value.
Sorting the product range by coefficient of variation.
Classification of positions into three groups – X, Y or Z.

Criteria for classification and characteristics of groups:

“X” - 0-10% (coefficient of variation) – goods with the most stable demand.
“Y” - 10-25% - products with variable sales volumes.
“Z” - from 25% - goods with random demand.

Let's create a training table for conducting XYZ analysis.

Group “X” includes goods that have the most stable demand. The average monthly sales volume deviates by only 7% (product1) and 9% (product8). If there are stocks of these items in the warehouse, the company should put the products on the counter.

Inventories of goods from group “Z” can be reduced. Or even go through these titles to pre-order.

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

ABC analysis is a division of the company's product range into three groups, depending on the rate of profit that each of them brings.
ABC analysis allows you to divide product items into three categories. During the analysis, more groups can be identified. The main functions of ABC analysis are presented in Figure 1.
Figure 1. Functions of ABC analysis In the process of ABC analysis, groups are designated by Latin letters:

A – high priority, i.e. product groups that generate the largest percentage of income.
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.
C – low priority, i.e. product groups that bring in the smallest percentage of income.

Thus, by dividing the entire assortment into several groups, it is possible to identify top-selling products, as well as identify the reasons why product items from low-priority groups cannot be moved to a group at a higher level.
Speaking about determining the quantitative boundaries of a group, two characteristics can be distinguished: the share of revenue and the percentage of items. The most common quantitative boundaries for each group are shown in Table 1.
Quantitative boundaries of product groups

Group name	Revenue share (%)	Percentage of titles (%)
A-group	80	20
B-group	15	30
C-group	5	50

The figures illustrated in the table do not strictly define the boundaries of each group. At each enterprise, these indicators may vary within different limits.
The ABC analysis process can be divided into several stages:

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.
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.
Ranking of objects of analysis.
At this stage, the objects of analysis are sorted in descending order.
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.

The economic content of ABC analysis is that the groups containing the smallest number of nomenclature items have the greatest impact on the results of the enterprise’s activities. This provides the principle of imbalance inherent in ABC analysis.
ABC analysis has the following advantages:

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

The disadvantages of ABC analysis include:

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

ABC analysis can be used not only to evaluate current activities and search for opportunities to improve them, but also to analyze the effectiveness of implementing a set of measures established in the process of ranking goods into groups.

ABC analysis example

As an example, let's conduct an ABC analysis of sales at company N.
Company N is engaged in the production of spare parts, mainly working to order. The assortment includes about 5,000 product items. One nomenclature group “Diamond wheels” was chosen as the object of analysis, containing 29 product units. As the primary data for ABC analysis, a balance sheet was generated for account 43 “Finished products” for 2011 using the 1C: accounting program. This report shows balances at the beginning and end of the period and turnover for the selected period of time in the context of analytics for product units included in the “Diamond Wheels” group. The balance sheet for account 43 for 2011 is presented in Table 1.
Turnover balance sheet
under account 43 “Finished products”

Nomenclature units	Balance at the beginning of the period		Period transactions		balance at the end of period
Nomenclature units	Debit	Credit	Debit	Credit	Debit	Credit
Alm. circle AS 3510-01, 100x10x5 ASN 40/28 Qty	1 070,10		1 542,82	2 612,92
Alm. circle AS 3510-02, 100x10x5 ASN (40/28+28/20) Qty	633,12		15 428,20 20,000	15 291,35 20,000	769,97
Alm. circle AS 3513-02, 100x9.5x5 ASN (40/28+28/20) Qty	1 227,82				1 227,82
Alm. circle AS 3515-03, 150x10x5 ASN 60/40 Qty			10 062,08	10 062,08
Alm. circle AC 3515-05, 150x10x5 AC6 80/63 Qty	1 115,77		70 438,76	60 054,21	11 500,32
Alm. circle AC 3515-06, 150x10x5 AC6 100/80 Qty	8 866,24			2 216,56	6 649,68
Alm. circle AC 3515-07, 150x10x5 AC20 125/100 Qty	12 998,52		42 648,80	55 647,32
Alm. circle AS 3515-14, 150x10x5 ASN 20/14 Qty			1 663,14	1 663,14
Alm. circle AS 3516-03, 150x6x5 ASN 60/40 Qty	3 958,96				3 958,96
Alm. circle AS 3520-01, 200x10x5 ASN 40/28 Qty			2 550,30	2 550,30
Alm. circle AS 3520-03, 200x10x5 ASN 60/40 Qty	21 444,20 20,000		749 273,47	732 788,28	37 929,39 29,000
Alm. circle AC 3520-04, 200x10x5 AC 6 63/50 Qty			388 764,38	349 527,08	39 237,30 30,000
Alm. circle AC 3520-05, 200x10x5 AC6 80/63 Qty	19 072,39 19,000		1 224 304,49	1 201 523,76	41 853,12 32,000
Alm. circle AC 3520-06, 200x10x5 AC6 100/80 Qty	7 456,68		703 885,79	711 342,47
Alm. circle AC 3520-07, 200x10x5 AC20 125/100 Qty			213 231,94	213 231,94
Alm. circle AC 3520-08, 200x10x5, AC20 160/125 Qty	67 098,72 39,000		1 432 125,75	1 487 172,33	12 052,14
Alm. circle AS 3521-03, 200x6x5 ASN 60/40 Qty			5 600,52	5 600,52
Alm. circle AC 3521-07, 200x6x5 AC20 125/100 Qty	6 160,04				6 160,04
Alm. circle AS 3525-03, 250x10x5 ASN 60/40 Qty			35 326,20	35 326,20
Alm. circle AS 3580-00, 80x10x5 ASN 28/20 Qty	6 248,90 10,000				6 248,90 10,000
Alm. circle AS 3580-03, 80x10x5 ASN 60/40 OS Qty	10 880,99 18,000				10 880,99 18,000
Alm. circle AC 3580-05, 80x10x5 AC6 80/63 Qty	2 999,95		31 820,10	22 949,96	11 870,09 15,000
Alm. circle AC 3580-06, 80x10x5 AC6 100/80 Qty			35 474,60	26 571,00	8 903,60 10,000
Alm. circle AS 3581-10, 85x6x10 ASN 60/40 Qty			193 596,99	193 596,99
Alm. circle AC 3581-12, 85x6x10 AC 6 63/50 Qty			227 464,95	227 464,95
Alm. circle OS 100x6x5 AC6 80/63 Qty	3 203,75				3 203,75
Alm. circle OS 100x6x5 ASN (40/28+28/20) Qty	1 483,76				1 483,76
Alm. circle OS 150x10x5 ASN 60/40 Qty	5 994,96				5 994,96
Alm. circle OS 80x6x5 ASN 28/20 Qty	4 928,70				4 928,70
Total (amount)	186 843,57		5 385 203,28	5 357 193,36	214 853,49
Total (quantity)	181,000		3818,000	3791,000	208,000

The debit reflects the receipt, and the credit reflects the disposal of inventories. For the purposes of this analysis, we will assume that the cost of all goods shipped has been paid.
Without going into details of the release and sale of each item and analyzing only the balance indicators at the beginning and end of the period by debit, you can notice that the balance of unsold goods in warehouses in monetary terms increased by 1.15 times compared to the previous year. This fact indicates that there are some problems with the sales of products, the identification of which requires a more detailed study of the assortment.
An initial examination of the balance sheet shows that there are some goods that have not been sold since last year. These items were not produced in the current period, however, they occupied some space in the warehouse. Also, their cost was not covered, which negatively affects the overall profit.
Let us calculate the share of such goods in the total volume of products of the analyzed product group. For the calculation, let's draw up table 2.
Goods stagnant in warehouse

Name of nomenclature units	Monetary value (rub.)	Quantitative expression (PC.)
	1227,82	2
	3958,96	4
	6160,04	4
	6248,90	10
	10880,99	18
	3203,75	9
	1483,76	4
Alm. circle OS 150x10x5 ASN 60/4	5994,96	6
	4928,7	14
Total	44087,88	71

Based on the data obtained in Table 2, it is possible to calculate the share of non-profit-making goods in quantitative and monetary terms:
For calculations, you can use balances at the beginning and end of 2011. Since the object of analysis is sales for 2011, the share of goods stagnant in warehouses will be calculated relative to the balance at the end of the period.
The share of non-profit-making goods in quantitative terms is 0.34 (71/208);
The share of non-profit-making goods in quantitative terms is 0.21 (44087.88/214853.49);
Having compared the obtained indicators, we can say that the share of these goods in the total cost of all goods of the enterprise is significantly less than their share in the total number of product items. This indicates that these goods take up space in the warehouse, but their share in possible revenue is not large enough.
For a more in-depth analysis of the product range, we will select the share of product cost in the total cost as a parameter.
To conduct an ABC analysis regarding the share of the cost of goods in the total cost, turnover on credit 43 accounts was used, i.e., the cost of shipped goods was examined. Based on these data, nomenclature items were sorted from the highest sales in monetary terms to the lowest.
As a result of this ranking, the goods were divided into groups A, B and C. The ABC analysis report is presented in Table 3.
Range ranking
(in monetary terms, rub.)

Nomenclature units	Period transactions
Nomenclature units	Debit	Credit
Group A
Alm. circle AS 3520-03, 200x10x5 ASN 60/40	749 273,47	1 487 172,33
Alm. circle AC 3520-04, 200x10x5 AC 6 63/50	388 764,38	1 201 523,76
Alm. circle AC 3520-05, 200x10x5 AC6 80/63	1 224 304,49	732 788,28
Alm. circle AC 3520-06, 200x10x5 AC6 100/80	703 885,79	711 342,47
Alm. circle AC 3520-07, 200x10x5 AC20 125/100	213 231,94	349 527,08
Total		4 482 353,92
Group B
Alm. circle AC 3520-08, 200x10x5, AC20 160/125	1 432 125,75	227 464,95
Alm. circle AS 3521-03, 200x6x5 ASN 60/40	5 600,52	213 231,94
Alm. circle AC 3521-07, 200x6x5 AC20 125/100		193 596,99
Alm. circle AS 3525-03, 250x10x5 ASN 60/40	35 326,20	60 054,21
Alm. circle AS 3580-00, 80x10x5 ASN 28/20		55 647,32
Alm. circle AS 3580-03, 80x10x5 ASN 60/40 OS		35 326,20
Alm. circle AC 3580-05, 80x10x5 AC6 80/63	31 820,10	26 571,00
Alm. circle AC 3580-06, 80x10x5 AC6 100/80	35 474,60	22 949,96
Alm. circle AS 3581-10, 85x6x10 ASN 60/40	193 596,99	15 291,35
Alm. circle AC 3581-12, 85x6x10 AC 6 63/50	227 464,95	10 062,08
Total		860 196
Group C
Alm. circle OS 100x6x5 AC6 80/63		5 600,52
Alm. circle OS 100x6x5 ASN (40/28+28/20)		2 550,30
Alm. circle OS 150x10x5 ASN 60/40		2 216,56
Alm. circle AS 3510-01, 100x10x5 ASN 40/28	1 542,82	2 612,92
Alm. circle OS 80x6x5 ASN 28/20		1 663,14
Alm. circle AS 3510-02, 100x10x5 ASN (40/28+28/20)	15 428,20
Alm. circle AS 3513-02, 100x9.5x5 ASN (40/28+28/20)
Alm. circle AS 3515-03, 150x10x5 ASN 60/40	10 062,08
Alm. circle AC 3515-05, 150x10x5 AC6 80/63	70 438,76
Alm. circle AC 3515-06, 150x10x5 AC6 100/80
Alm. circle AC 3515-07, 150x10x5 AC20 125/100	42 648,80
Alm. circle AS 3515-14, 150x10x5 ASN 20/14	1 663,14
Alm. circle AS 3516-03, 150x6x5 ASN 60/40
Alm. circle AS 3520-01, 200x10x5 ASN 40/28	2 550,30
Total		14643,44
Total for all groups	5 385 203,28	5 357 193,36

Analyzing the data obtained, we can draw the following conclusions:

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.
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.
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.

Based on these conclusions, the following proposals for optimizing the nomenclature group under study can be formulated:

Searching for new customers for products in group B in order to increase sales volumes;
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.
Production of goods included in group C exclusively to order in order to avoid unjustified accumulation of product balances in warehouses.
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.

In order to find the optimal solution for optimizing the entire assortment, each product group should be examined in a similar way.
Considering the above, we can conclude that ABC sales analysis helps identify problems associated with assortment items, and also provides an information base for improving product offerings. But you shouldn’t try to increase your performance in many different areas at once. Efficiency should be increased gradually, highlighting priority development prospects and focusing marketing ideas and methods of their implementation on them.

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