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 (sold quantity) 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.
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. Define 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 items to pre-order.
This example of ABC analysis of an assortment is universal in application, will demonstrate a quick way to compile a rating and includes step-by-step instructions and detailed recommendations for the correct conclusions to the ABC analysis.
This example can be used to:
- ABC analysis of products of a separate brand or the entire range of the company
- ABC analysis of company reserves
- ABC analysis of raw materials and any purchased materials
- ABC analysis of clients or consumer groups
- ABC analysis of suppliers
- ABC analysis of department performance and labor force analysis
- ABC analysis of budget, investment or any costs
Theoretical information
Create a list of all analyzed resources
The first step in conducting an ABC analysis is to simply list all the items being analyzed.
Depending on the type of ABC analysis, this can be: a list of assortment, a list of raw materials, a list of clients or consumer groups, a list of personnel, a list of budget items.
Determine the indicator by which you want to sort positions.
Depending on the type of ABC analysis, this can be: sales volume or profit, cost of purchasing raw materials, costs per person or profit/sales per unit, level of investment.
Sort all items in descending order of sales/profit
Determine the share (contribution) of each position
This action is expressed in dividing the amount of an individual item by the total amount of sales.
In a separate column, calculate the cumulative percentage
Cumulative % is calculated cumulatively, starting from the top rows of the table
Assign each item the corresponding group A, B or C
Select groups according to the ABC method for each position based on the “Cumulative contribution” column.
- All positions from the beginning of the table to the 80% border are category A
- All positions from the 80% border to the 95% border are category B
- All positions from the 95% border to the 100% border are category C
Prepare conclusions from ABC analysis
It must be remembered that the calculation of ABC analysis only allows us to summarize the available information and present it in a convenient form. It is one of the development tools. It is advisable to understand and study in more detail the reasons why products fall into one group or another.
1 Group A– the most important resources, the locomotives of the campaign, bring maximum profit or sales. The campaign will suffer large losses if the effectiveness of this group of resources sharply decreases.
Group A resources must be strictly controlled, clearly forecasted, frequently monitored, be as competitive as possible and not lose their strengths. Maximum investments and the best resources should be allocated to this group of resources. The successes of group A should be analyzed and transferred to other categories as much as possible.
2 group B– a group of resources that provide good stable sales/profits for the campaign.
These resources are also important for the campaign, but can be moderated at a calmer and more moderate pace. These resources are usually relatively stable in the short term. Investments in this type of campaign resources are not significant and are only necessary to maintain the existing level.
3 group C– the least important group in the campaign. This group may include: resources that need to be disposed of, that need to be changed, and improved.
When analyzing this group, you need to be very careful and first of all understand the reason for the low contribution.
For example, when analyzing the range of goods and services, there may be the following options for a product to fall into group C:
- the product is not in demand by the buyer, is not sold and has low liquidity in comparison with other assortment. In this case, it should be discontinued or improved.
- The product has just been released, is at the stage of introduction to the market, its sales have a positive sales trend.
- The sales that the product shows are maximum, but it is strategically important for the campaign, since it satisfies the needs of a separate market (possibly a smaller one), does not cannibalize the main assortment, emphasizes the positioning of the brand, etc.
Ready solutions
We have a ready-made template with which you can easily apply the theoretical knowledge of this article in practice. You can download an example example for conducting ABC analysis of the assortment in the section.
ABC analysis (or the Pareto principle) is a very simple and at the same time quite effective tool that allows companies to focus their attention on what is really important to them. Moreover, companies can use this method very widely. For example, to analyze product range, identify key customers, optimize warehouse orders and budget expenses. The idea of ABC analysis is based on the Pareto principle. This Italian economist and sociologist analyzed the number of rich and poor people in different countries and came to the conclusion that 80% of all wealth is concentrated in the hands of 20% of the world's population. Therefore, this principle is also called the “80/20” principle. Applicable to trading, this method can be expressed as follows: “80% of income comes from 20% of customers”, “80% of sales will give you 20% of goods / services”, “80% of the company’s income comes from 20% of employees”, etc.
Each store must analyze each group itself and make the appropriate decision
The result of ABC analysis is the grouping of objects according to the degree of influence on the overall result. Depending on the purposes of the analysis, an arbitrary number of groups can be identified. Most often there are 3 groups.
Applicable to product analysis, ABC analysis is the division of a product range into groups according to their contribution to achieving the result. As a rule, the following parameters are taken as the result:
- sales frequency (how often a specific item is sold),
- turnover (how much sales of this item amounted to),
- profit (what is the contribution of this position to the total profit).
Obviously, the same product can belong to different categories. For example, it can generate a small turnover and profit, but have a fairly high frequency of sales, that is, have a high demand. Most likely, this is a so-called “indicator” or “locomotive” product (a product with a small markup that ensures an influx of buyers). If you analyze this position only by profit or only by turnover, then you can decide that this position should be excluded from the assortment. But this would be a mistake, because... Products in this group are designed to ensure a flow of customers, and not to “make money.”
Multivariate ABC analysis
To expand the capabilities of classical ABC analysis, multivariate ABC analysis is used. In this analysis, three (or more) parameters are assigned to each position. As a result, for each position we receive a rating in the form of a combination of groups: AAA, ABB, CCC, etc.
Let's consider as an example the result of a multidimensional ABC analysis of the products of a tool store, which we did on the instructions of one of our clients. To the classic parameters of sales frequency, turnover and profit, we added a valuation of the remaining goods in the warehouse. This will help to see the situation when a product of group AAA (or one of the “high” groups) will be out of stock or, conversely, there will be too much product of group C in stock.
Let's look at some positions:
- “Welding equipment” is included in the AAA category. It sells well, generates high turnover and high profit margins. Such products need maximum attention. Monitor their quantities, quality, ensure uninterrupted supply, etc. As we can see, the product “Cult” also belongs to the AAA category. 5.5l”, however, in terms of the total balance it belongs to category C - it is not available at all. It is necessary to find out why this product is out of stock: maybe due to a lack of information, they simply forgot to order it.
- "Electric hoist" - category ABB. It sells well, but generates average turnover and average profit margin. In this case, actions are applied to goods of this group, the purpose of which is to increase the markup. For example, increasing prices or reducing costs.
- “Hydraulic trolley roller” is included in the BBB category. The product has its own audience, not too large, and brings average income and profit. Typically, no action is required in such situations.
- “Tachka Zubr” is included in the problematic category of the CCC: low number of sales, low turnover, low profit. In such cases, they usually look at two indicators: the number of sales and the markup percentage. If a product is sold less than once in a certain period (for a grocery store, for example, a day) and has a small markup, then you should think about excluding this product from the assortment. In this example, this product still has a relatively large share of inventory. We need to analyze how this situation happened. For example, a product is regularly ordered from a supplier (some suppliers do not sell the product below a certain quantity, or offer a discount for a large order volume), despite its low profitability. In this case, it is recommended to further stimulate the product - arrange promotions, assign discounts, etc.
A tool for the job, not a magic wand
Successful use of ABC analysis allows you to reduce and free up a huge amount of time and labor resources. This is achieved by concentrating work on the most important elements and, conversely, saving resources on less priority components. However, ABC analysis, like any other statistical method, is a tool in the hands of the analyst. Analytical methods, like any tool, need to be able to use.
Here are a number of notes that the analyst should keep in mind.
The result of multidimensional ABC analysis is the sorting of goods into groups. For a three-dimensional analysis there will be 27 such groups, for a two-dimensional analysis there will be 9. The analyst must be well versed in this variety of groups, identify important groups, and know what needs to be applied to each of them. It should be noted that among the goods there may be not only those that sell poorly, but also those that are not sold 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. Also, more than 50% of the assortment may fall into group A - in this case, it may be useful to select subgroup A+ from group A (Carry out an ABC analysis for group A). It should also be remembered that the analysis is carried out for a certain period, and based on the data of this period, a forecast for the future is made. Here you should take into account seasonal products that sold well, for example in winter, and do not take them into account when ordering for the summer seasons. It also happens that some items fall out of sales. This happens for various reasons: the supplier does not have it, 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.
Thus, ABC analysis is a simple, universal analysis tool. But it should be remembered that, like any statistical tool, it cannot recognize the quality and nature of the data; this must be done by the analyst before making calculations.
Analysis of ABC XYZ First of all, you need to know: what is it? To begin with, it is worth noting that these two analyzes are used in various business structures, for example, restaurants, shopping centers, alcohol companies, etc.
These two computing assistants help identify problem areas of the enterprise, plan actions, promptly raise the cost of goods that are in demand, and protect the company from future mistakes. So, ABC XYZ?
ABC analysis is the process of classifying goods and resources of an enterprise into groups according to their level of significance. This analysis uses the famous Pareto principle. This principle is based on the axiom: 20% of the total product produces 80% of the turnover. In particular, this rule can be applied to ABC analysis as follows: qualitative control of 20% of an enterprise’s resources brings 80% of the control of the entire system, in general, these can be products, equipment, raw materials, etc. What is this analysis method needed for and how is it applied? ?
Let’s say in a restaurant or fast food cafe, ABC analysis is most often used; it is needed to “sort everything out” and determine the share of the product in the turnover of the enterprise and calculate the percentage of the share of the product in the profit of the restaurant. A special table is displayed in which you must enter: the number of sales of the product per month (six months, year), the cost of the product and the selling price. Using a certain formula, it is necessary to order the products on a scale from min to max. Then, using this formula, determine the share of the product in the turnover and the percentage of the share of the product in the profit of the enterprise. After this, the table will give us the data of each product and the scale of their importance in terms of turnover and profit participation. The scale is called “Cumulative Total”, built from 1 to 100. If the assortment group on this scale falls in the range from 1 to 50, then it is group A, if in the range from 50-80, then the product is in group B, but in group C are products located in the range from 80 to 100. Products that are in group A and B have a large turnover and bring a good percentage of profit to the company, but those categories that are in group C should be worked on, to increase demand and turnover, or withdraw them from sale. According to statistics, categories that have been in group C for more than six months are eliminated.
XYZ analysis is a classification of inventory. Forecasts consumption, patterns of change and inventory requirements. A specific analysis algorithm is built, which includes calculating the coefficient of variation, grouping from min to max, distribution into XYZ groups, and displaying the result on a graph.
Most often, this method is used in large enterprises where there are warehouses and a logistics center, which XYZ conducts research and evaluates the company’s logistics and clients.
What is included in the groupsX, Y, Z?
Group X includes the main stock items with a coefficient of variation of statistical sequences of shipments of 25%. These are resources that are consistent with a stable amount of consumption and require an accurate forecast of consumption.
In group Y there are the same product items with and have a statistical range of shipments of 25-50%. In this group of resources, it is necessary to determine the need for them; these could be seasonal products (beer, water).
Group Z carries the reserves of the statistical series with more than 50%. This group is characterized by irregular resource consumption and inaccurate forecasting. If you combine ABC XYZ analysis, it will show a more accurate table of consumption rates and shipment rates.
ABC XYZ analysis works best in pairs for a more accurate assessment of the enterprise's efficiency. This is the most powerful internal weapon of the company; by installing it at the core of the business, you can identify key points, save important resources of the enterprise and capture the lion's
