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ABC Analysis Definition

ABC Analysis Definition

ABC analysis is a system of inventory classification that separates products into different categories based on priority and value. This system enables managers to easily identify important data, so they can react to trends and make merchandising adjustments more intuitively. The most important items are designated as “A” products; the second-most valued items are category “B”, and category “C” consists of low-priority goods.

A Little More on What is ABC Analysis

The idea of ABC Analysis was first conceptualized by an Italian economist and sociologist, Wilfredo Pareto in 1987. He developed the system after realizing that demand is not distributed across inventory equally. Inventory addresses this issue by designating the items with the highest demand as “article A”, to illustrate their importance to revenues and denote the higher demand for these goods.

There are several ways of determining which inventory items are classified into which category. The following classifications reflect Pareto’s original principles and, while sales volume and revenue are the primary concerns of this system, all factors should be taken into consideration to determine what works best for individual practitioners

  • Article A: These are the most important items, and strict inventory control procedures should be in place for these products. Items should always be maintained in stock, and enhanced security procedures should be employed when storing these items.
  • Article B: Products in this category lay between A and C items. This category often serves as a transitional point as demand fluctuates and items are reclassified.
  • Article C: This category is for low-demand items that constitute only a small part of sales volume.

Each item will be afforded different treatment according to its classification. For example, article A items are placed in high-traffic areas of the store to make them more accessible to customers and the stock is maintained at all times. Article C items, conversely, are low-volume items and it’s common for businesses that employ the system to keep only one unit of article C items in stock at a time.

This system allows managers to better employ their inventories for maximum revenues. There are obvious benefits to both merchandising and inventory management, as managers can easily determine which products need their foremost attention. Focussing on the more important, article-A items will funnel sales traffic and volume to your most in-demand inventory items. This enables a business to play to its strengths, nourishing the most successful parts of their business while wasting little time and effort on small-ticket or low-demand items. The system gives managers the ability to objectively make decisions regarding merchandising and demand.

Classifying inventory in an ABC system also makes it easier to assess sales performance for your key items without diluting your sales figures with low-revenue, article-C sales. Managers can find their article-A sales figures when perusing reports and give those particular figures the majority of their attention.

References for ABC Analysis

  • https://www.cleverism.com/complete-guide-abc-analysis-customer-segmentation-inventory/
  • https://en.wikipedia.org/wiki/ABC_analysis
  • https://whatis.techtarget.com/definition/ABC-analysis-Pareto-analysis

Academic Research for ABC Analysis

  • •    ABC inventory classification with multiple-criteria using weighted linear optimization, Ramanathan, R. (2006). Computers & Operations Research, 33(3), 695-700.  This article discusses the uses of weighted linear optimization as a method of employing the ABC classification system to inventory. The article goes on to propose a simple ABC-related classification scheme employing weighted linear optimization.
  • •    A note on multi-criteria ABC inventory classification using weighted linear optimization, Zhou, P., & Fan, L. (2007). European journal of operational research, 182(3), 1488-1491. The model discusses in this paper is an expansion of the Ramanathan’s model (R-model), which uses weighted, linear scales to classify inventory. This model differs from the R-model in that it uses two different weight to give each item a correct and effective classification.
  • •    An improvement to multiple criteria ABC inventory classification, Hadi-Vencheh, A. (2010). European Journal of Operational Research, 201(3), 962-965. The inventory model mentioned here uses a weighted, non-linear means of classifying items. This model uses both weighted criteria and multi-criteria ABC to determine a more accurate system for managing inventories.
  • •    ABC inventory classification in the presence of both quantitative and qualitative criteria, Torabi, S. A., Hatefi, S. M., & Pay, B. S. (2012). While ABC inventory systems have traditionally focussed on one sole criterion for classifying inventory, such as annual dollar usage, recent studies have demonstrated the effectiveness of using other important information to categorize items with DEA models. The multi-criteria inventory classification (MCIC) system described here is the result of modifying the DEA approach in order to better illustrate qualitative attributes.
  • •    ABC classification: service levels and inventory costs, Teunter, R. H., Babai, M. Z., & Syntetos, A. A. (2010). Production and Operations Management, 19(3), 343-352. The downfall of ABC inventory applications is that there are often inefficiencies estimating costs due to the generalized approach taken to each SKU. A new system that can take into account the attributes of every individual SKU has proven to be a much more effective system that can provide better managerial insights.
  • •    Classifying ABC inventory with multicriteria using a data envelopment analysis approach, Liu, Q., & Huang, D. (2006, October). In order to make the ABC system more quantifiable, a system was developed that rated all inventory items between 0 and 1 to determine their nominal value. The model uses data envelopment analysis (DEA) to make categorization systems more rational.
  • •    Multi-criteria ABC inventory classification: With exponential smoothing weights., Jamshidi, H., & Jain, A. (2008). Journal of Global Business Issues, 2(1). Traditional ABC inventory analysis uses dollar usage as its primary benchmark for classifying inventory. However, recent studies have demonstrated the advantages of using other criteria for classification, such as lead time, ordering cost, commonality, scarcity, etc.
  • •    Optimizing ABC inventory grouping decisions, Millstein, M. A., Yang, L., & Li, H. (2014). International Journal of Production Economics, 148, 71-80. The basic ABC system is a framework upon which customized inventory solutions can be developed that will truly fit a business’s operation. A system that optimizes inventory groups based off their respective services costs and assigns SKUs accordingly was shown to be more effective than ABC when applied to company inventory reports, so businesses should adjust the system to fit their operations during implementation.
  • •    Towards a normative model for inventory cost management in a generalized ABC classification system, Stanford, R. E., & Martin, W. (2007). Journal of the Operational Research Society, 58(7), 922-928. The ABC system can be implemented as the foundation for a system that effectively calculates maintenance costs and inventory turnovers. Accurately estimating inventory costs and adapting to them quickly is extremely important to profitable business, and the ABC system can play a significant role in efficiently estimating those costs.
  • •    Inventory control system design by integrating inventory classification and policy selection, Mohammaditabar, D., Ghodsypour, S. H., & O’Brien, C. (2012). International Journal of Production Economics, 140(2), 655-659. Businesses with very large inventories or inventories with a large amount of SKU numbers may find that categorical inventory systems can be cumbersome and hard to implement due to a large number of categories and policy groupings. The best solution to address the problem of complexity is using an integrated model that designates the items by both item and policy at the time of categorization.

Research into the merits of the ABC inventory system continues to this day, and it is widely-agreed that implementing an inventory system that takes into account both quantitative and qualitative attributes can be a highly effective means of improving inventory management. While there is no one-size-fits-all solution, this model can be highly effective for businesses with inventory operations that are conducive to this type of classification system.

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