ABC Analysis and Its Role in Optimal Inventory Management

While inventory management is a crucial component of a company's financial stability, determining inventory levels and advancing them according to the production plan also determines the future of the business. Just as low inventory levels are critical, so too is high inventory levels. While low levels directly impact production and output, high levels increase holding costs and, in a sense, divert large amounts from cash flow. Maintaining an optimal supply chain is the solution to eliminate both of these risks. Optimum inventory levels prevent production contractions by being used efficiently and support the company in terms of cost and satisfaction.

Inventory Value, Inventory Quantity, and Inventory Duration are guides to achieving optimal levels. The way to control branched inventory items is to classify them. ABC analysis is one of the most widely used methods for classifying inventory in inventory management.

ABC analysis is a method based on grouping inventory items according to their cumulative percentage of the total value. Inventories are generally divided into three classes: A, B, and C. While products in Group A account for only 20% of the total in terms of quantity, they account for approximately 80% of the total in terms of sales value. Group B stocks range from 20–30% in terms of quantity and account for 15% of the sales value. Group C stocks, on the other hand, account for the largest share in terms of quantity (50–60%) but contribute only 5% to the sales value. This classification is essentially consistent with the Pareto principle (80/20 rule). In other words, a small number of critical stock items (Class A) account for the majority (80%) of the total sales value, while a large number of low-value items (Class C) contribute only limitedly to sales.

The classic ABC approach, introduced by Dickie (1951), classifies stocks solely based on annual usage value. However, recent research has focused on multi-criteria stock classification, which considers multiple criteria, as it is more suitable for the current needs of the business world.

Group A stocks:

· Should be checked more frequently, with daily/weekly monitoring.

· Purchasing processes should be managed more meticulously.

· It should be reported at the board level.

Group B Inventories:

· Between A and C, monthly control may be sufficient.

· The policy can be kept more flexible.

Group C Inventories:

· Less important, requiring bulk purchasing or longer periodic control.

· Can be automated without much effort.

ABC Analysis in Real-Life Applications

To better illustrate the value added to a business, consider an example of a retail company with a total of 10,000 inventory items and an annual material consumption of $30 million.

Applying ABC analysis:

· Group A: 2,000 items (20%) - $24 million (80%)

· Group B: 3,000 items (30%) - $4.5 million (15%)

· Group C: 5,000 items (50%) - $1.5 million (5%)

With this classification method, weekly inventory control is sufficient for Group A, monthly for Group B, and quarterly for Group C. This significantly reduces inventory control workload and directs management resources to the highest-value product groups, resulting in both cash flow flexibility and operational efficiency.

Today, classification based solely on monetary value is often insufficient. Modern businesses consider the following criteria to make ABC analysis more realistic:

· Supply risk - Products dependent on a single supplier carry a high risk.

· Criticality - Major components that could halt production receive priority.

· Lead time - Products with long lead times require different stocking policies.

· Demand variability - Products with regular demand are predictable, while products with variable demand are more risky.

When these criteria are considered, ABC analysis becomes a decision-making tool that reflects not only cost but also strategic importance.

Technology Integration and Future Inventory Management

With Industry 4.0, ABC analysis is also becoming digital. AI-powered systems can analyze historical data, market trends, supplier reliability, and customer demand patterns, dynamically updating the classification.

Inventory levels are monitored in real time via IoT sensors, and these structures, integrated with automated ordering systems, minimize human error. This greatly simplifies the management of low-value but numerous Group C items, allowing managers to focus their attention on critical Group A items.

Proper inventory management in the retail industry is a critical factor not only in increasing profitability but also in maintaining customer loyalty and competitiveness. ABC analysis, combined with the Pareto principle, clearly identifies the products that create the most value for companies.

Through multi-criteria approaches and AI-powered solutions, ABC analysis helps retailers reduce costs, accelerate cash flow, and increase customer satisfaction.