ABC analysis is a valuable inventory management technique that can help businesses prioritize their products based on their importance and sales performance. By categorizing items into different groups, companies can optimize their inventory levels and increase profitability.

This article will provide a detailed introduction to ABC analysis and give an example of how it can be applied in business, especially in inventory management. Additionally, we will explore how business intelligence tools can be used to simplify and enhance the ABC analysis process.

The ABC analysis is a method used to categorize inventory items by considering their consumption values, which refers to the total value of an item consumed within a specific period, typically a year. This approach, which relies on the Pareto principle, aims to prioritize the management of critical items.

Item A represents the products that have the highest consumption value on an annual basis. According to the Pareto principle, a small fraction of these items, typically around 20%, accounts for a large proportion of the total consumption value, often around 80%. Consequently, it is reasonable to subject this class of items to scrutiny, to minimize costs and losses. This is because there is a significant opportunity to achieve cost savings or loss reduction through the analysis and control of these items.

Item B has lower consumption values than A items but higher values than C items. This class is important because it includes items that are close to A or C, and a slight shift in their consumption values may lead to changes in stock management policies. Since stock management incurs costs, it is necessary to balance controls that protect the asset class and the value at risk of loss against the cost of analysis and the potential value gained from reducing class costs. As a result, the scope of this class and inventory management policies are determined by the cost-benefit analysis of class cost reduction and loss control systems and processes.

Item C has the lowest consumption values, and although they account for a high proportion of total items, their consumption values are relatively low. It is not usually cost-effective to implement tight inventory controls for this class, as the value at risk of significant loss is low, and the cost of analysis is likely to yield low returns.

The thresholds that define the upper and lower limits of each class cannot be defined because businesses differ in their risk appetites and needs. The upper and lower limits may also vary over time or across different locations. For instance, a business may have a higher proportion of A items in a high-crime area, or a less secure facility may classify more items as A. Thus, management accountants should perform risk and stock management cost-benefit analyses by location to determine the optimal overall cost-benefit balance and establish the ABC ranges.

Optimizing inventory investment presents a challenge for all businesses. Determining which products to procure to satisfy future demand while avoiding an excess of unsold inventory is a formidable task. Additionally, purchasing blindly or relying solely on intuition makes it nearly impossible to identify products that should be avoided. A unity dashboard can significantly aid in this process, providing real-time, comprehensive data visualizations that help businesses track inventory levels, forecast demand, and make more informed purchasing decisions.

Effective inventory management involves striking a balance between having enough products available and minimizing inventory costs. Failing to meet customer demand for popular products may result in lost sales opportunities and dissatisfied customers who may seek out competitors and become repeat buyers elsewhere, resulting in an estimated $1 trillion in lost revenue for retailers annually due to stockouts.

On the other hand, over-purchasing can result in storing dead or slow-moving inventory, which can be a financial burden. With storage fees on the rise, it's crucial to optimize inventory management to avoid unnecessary holding costs such as warehousing, insurance, and labor expenses. Moreover, perishable products that expire cannot be salvaged even at discounted rates.

To secure long-term success, businesses must routinely evaluate their inventory. The ABC method is an effective approach for this task. FineBI, a premier business intelligence tool developed by FanRuan, excels in facilitating this analysis. With FineBI, you can seamlessly create comprehensive ABC analysis dashboards and perform detailed evaluations. This advanced tool empowers you to gain critical insights, ensuring data-driven decision-making that enhances inventory management and drives overall business performance.

Next, we will show you an ABC analysis example dashboard of how to use a professional BI tool FineBI to quickly conduct ABC analysis.

FineBI is a modern BI software specialized in big data analytics and BI, catering to those who require data analysis. It is user-friendly and accessible to all regardless of skill level, enabling the effortless establishment of professional BI dashboards, self-service data analysis, and valuable insights to advance your business.

Through simple operations like drag-and-drop, creating professional business reports and dashboards has never been easier!

FineBI provides a hassle-free data processing experience through its convenient features such as filtering and merging calculation. Users can process data rapidly without having to write SQL statements or other codes.

Moreover, FineBI supports over 50 chart styles, including basic and high-level charts, and offers dynamic effects and powerful interactive experiences. The software allows for customization of features according to the user's needs and can also be easily displayed on mobile terminals and large LED screens.

Using FineBI makes it easy to build various classic data analysis models, such as the ABC analysis model discussed in this article, as well as other models like the BCG Matrix (Growth Share Matrix), RFM Model, DuPont Analysis Model, etc., to help businesses gain insights.

FineBI offers business theme analysis scenarios for different industries, including manufacturing, pharmaceuticals, retail, finance, and more. By analyzing and displaying business indicator data, relevant managers can easily grasp business dynamics.

FineBI can liberate business professionals from the quagmire of data processing and visualization, allowing them to focus more on data analysis, management, and business communication.

Let's now demonstrate how to use FineBI for a quick ABC analysis example.

For the existing data, use the self-service dataset for data processing, or use the formula to add calculation indicators when making components to calculate the proportion of cumulative sales indicators. When making components, divide the objects into ABC proportion according to the proportion of cumulative sales (2-8 analysis will divide the objects into 2-8 proportion). Finally, reflect the analysis results through column charts of different colors. The data processing idea is shown in the figure below:

The key to achieve the division of ABC proportions is to calculate the "Proportion of cumulative sales" indicator, and then divide it according to the proportion of cumulative sales indicator. This article introduces two methods for calculating the proportion of cumulative sales.

The indicator of "Proportion of cumulative sales" is obtained by data processing in the self-service dataset. The obtained indicator can be used repeatedly in multiple components.

Take the "Sales schedule" and "Brand dimension table" under the "Retail industry" business package as examples to conduct a Pareto analysis of the sales of major brands and get the company's most important brands. Realize analysis effect by making self-service dataset.

1. Create a self-service dataset

1.1 Add field

1) Click "Add table", add a self-service dataset, as shown in the figure below:

1.2 Group summary

Click on "+", Select "Group Summary", drag "Category description" into the "Group" box, and drag "Sales" into the "Summary" box.

1.3 Sort

Click onClick "+", choose "Sort". Click "Add a sort",choose "Sales" Field and select "Descending" as shown in the figure below:

1.4 Calculating total sales

1) Click "+", choose "New column".

2) Name the newly added column "Total sales", select "all values/within group". The value rule is "all values", the value comes from "Sales", and the statistical method is "SUM":

1.5 Calculte the cumulative total

1) Name the new column "Cumulative total" and select cumulative value/within group. The value rule is "cumulative value", the value is from "Sales", click "OK".

2) Get the "Cumulative total" field:

1.6 Calculate the cumulative proportion

1) Add a new column, name it "Cumulative proportion", enter the formula Cumulative total / Total sales.Click "OK".

Note: The cumulative total and total sales in the formula cannot be entered manually, you need to click on the field name of the numeric field.

2) Get the "Cumulative proportion" field:

1.7 Effect view

Name the self-service dataset "Pareto Analysis Table" and click "OK". Enter the data preparation interface, click "update data". 

2. Making components

2.1 Create components

Select "Pareto data analysis" and "Create component", enter the dashboard information, and click "OK".

2.2 Add proportion of cumulative sales indicator

Click "+" to add a calculation indicator, name it "Proportion of cumulative sales", and enter the formula ACC_SUM(SUM_AGG(Sales)/TOTAL(SUM_AGG(Sales),0,"SUM")). Click "OK", as shown in the figure below:

The formula description is shown in the following table:

In addition, the effect can also be achieved by calculating the cumulative sales first and then calculating the proportion. The formula is as follows: ACC_SUM(SUM_AGG(Sales),0)/TOTAL(SUM_AGG(Sales),0,"SUM")

2.3 Making components

Drag the field of the area to be analyzed into the corresponding horizontal and vertical axis, select "Custom Chart", and set "Sales" as a column chart, and "Proportion of cumulative sales" as a line chart.

2.4 Set value axis

Set the value axis for the "Proportion of cumulative sales" field.

Select "right-value axis" for the shared axis, check the "Axis Scale Customization", and set the "maximum value" and "minimum value".

2.5 Sort

Arrange "Brand description" in "Descending" according to "Sales(Sum)".

2.6 Add "ABC Classification" indicator

1) Add a calculation indicator, name it "ABC Classification", and enter the formula IF (Proportion of cumulative sales<0.8,1, IF (Proportion of cumulative sales>0.9,3,2)) , where "1" represents category A commodities, "2" represents category B commodities, and "3" represents category C commodities.

2) Divide different types of "Brand descriptions" by color. Drag the "ABC Classification" field into the "color" box under "Graphic Properties> Sales", and select "Custom" for the gradient interval. Select the number of color intervals according to the type of division. Since there are three types of products, select "3" for the number of intervals and set the corresponding color.

2.7 Set cordon

Set the cordon on the Pareto chart as shown in the figure below:

At the same time, you can set up a dynamic Pareto chart, add filter components and other required component types. 

3. Expected effect

In the dashboard, you can view the sales of each brand's merchandise and the corresponding cumulative proportion of sales. According to ABC analysis method, brand goods are arranged in descending order according to sales volume, and are divided into three categories: Class A, class B and class C, with sales accounting for 80%, 10% and 10%, which are displayed in column charts of different colors, as shown in the following figure:

We can come to the following conclusions based on the analysis of the dashboard of ABC analysis example:

Predicting demand accurately is a challenging task. Without a crystal ballto see the future , relying on historical data is the next best option. To optimize your inventory, consider conducting an ABC analysis to determine your top-performing products. Investing your open-to-buy budget on those products can generate significant profits for your business, while minimizing storage fees by avoiding overstocking of poorly performing products.

Customers expect stores to have the items they want in stock. Identifying your top-performing inventory, and ensuring processes are in place to maintain those stocks can prevent potential customers from leaving empty-handed.

Investing in products that generate maximum revenue is a logical decision for any store. An ABC analysis is a useful tool to determine which products yield the highest value and usage. By categorizing products based on their value, you can identify slow-moving products that result in a loss and make informed pricing decisions such as offering discounts to clear out stock and create room for more profitable products.

The rate at which your products are being sold to customers, known as the sell-through rate (STR), is crucial to your business success. A desirable STR is above 80% as it reduces storage costs and provides valuable customer feedback. A high STR indicates that your customers are satisfied with your products and are willing to purchase them.

By conducting an ABC analysis, you can identify which products are most popular and use this information to improve your store's overall STR. Prioritize replenishing your stock of grade A inventory and reduce your investment in grade C products to minimize the amount of unsold stock in storage.

Store owners understand the challenges of managing limited resources. In an ideal situation, ample shelving space would be available to accommodate all inventory items. However, this is not always practical, as the cost of leasing a large enough space for total inventory can be exorbitant. It is necessary to make the most of the available resources.

Conducting an ABC analysis will help you identify your grade A inventory, which includes the top 80% of items. Allocating more shelving space to these high-priority items will ensure that your resources are not wasted and are utilized effectively.

Although an ABC analysis is an uncomplicated technique to identify the most and least successful items in your inventory, there are some drawbacks to consider when conducting such an assessment. Here are a few factors to keep in mind while performing an ABC inventory analysis.

Since this method relies on data from a specific time frame, it may misclassify and undervalue such items. For instance, a toy product may be classified as a C grade product during the summer and autumn months, but its demand typically spikes during the holiday season, making it an A or B grade product.

The ABC analysis relies on standardization and calculates the revenue generated by each item within a particular time frame, often a month. As a result, it's recommended to exclude any seasonal products from the ABC analysis. If seasonal products are included, there's a risk of selling off most of the inventory during the period when they're categorized as C grade products, leading to a frenzied rush to restock during the period when they're in high demand.

These factors can influence what and how consumers purchase products during a particular period. For instance, costumes related to a popular movie may experience a surge in demand when the film is released, leading to the product being classified as A-grade inventory. However, once the initial hype dies down, the same product may end up on the back shelf and become a rare purchase, resulting in its reclassification as C-grade inventory.

As trends change with time, it's challenging to predict whether a product categorized as A-grade inventory will continue to generate high demand. Moreover, relying on historical data for forecasting may not always be dependable, making the ABC analysis a less reliable method for predicting future performance.

While ABC analysis is useful for identifying products that generate the most revenue, it's important to also analyze other performance indicators like inventory turnover rate, days on hand, stock to sales ratio, sell-through rate, rate of return, and profit margin. A comprehensive analysis of these metrics can help businesses make informed decisions regarding their inventory management strategies.

It is recommended to use BI tool like FineBI to create a dashboard which can contain multiple performance indicators like the one shown in the picture:

Consistency and regular reviews are key to the success of ABC analysis. To conduct ABC analysis effectively in your business, here are some recommended approaches:

To streamline inventory management, it's best to keep the classifications for ABC analysis simple. Your teams should be able to quickly identify which products belong to each class. Common classification methods include categorizing products by price or sales frequency.

Each classification should have its own designated labor level, which determines the number of hours dedicated to managing that inventory class. The higher the value or impact of the class on the business, the more labor should be allocated to it.

Measure each classification against its own set of rules established during the initial ABC analysis. This involves using different key performance indicators (KPIs), performance reviews, and approaches to reorder or sell any overstock.

As inventory and markets change, it's essential to review existing classifications and reclassify products if necessary. Factors to consider include consumer trends, new industry competitors, and changes in sales per class and product.

Inventory software can help track product turnover and sales changes. By establishing a set of rules and actions, an inventory management system can automatically track and generate reports to highlight areas for improvement.

ABC analysis is a valuable inventory management technique that can help businesses prioritize their inventory management efforts. FineBI is an excellent tool for conducting an ABC analysis, as it provides advanced data analysis and visualization capabilities. By using FineBI to perform an ABC analysis, businesses can gain valuable insights into their inventory and develop a more effective inventory management strategy.

FineBI is free without time or feature limits for personal use. For enterprises, it offers a quote-based plan that charges according to different situations. In a word, FineBI is price-friendly to all customers.

Feel free to make an appointment for a live demo with our product experts. We will be more clear about your needs and see how FineBI can help you and your organization to transform data into value.