ABC Analysis
ABC analysis is a classification method that divides a set of items, such as stock-keeping units, customers or suppliers, into three groups according to their relative importance, usually measured by value or consumption. The aim is to focus management attention where it matters most: a small number of high-value A items typically account for the bulk of total value, while a large number of low-value C items contribute comparatively little. The technique rests on the Pareto principle and is widely embedded in material management and inventory functions of ERP systems, where it supports differentiated control and prioritisation.
- Term
- ABC Analysis
- Entity type
- Method / planning logic
- Domain
- Inventory management and prioritisation in materials planning
- Canonical definition
- ABC analysis is a classification technique that groups items into A, B and C categories by their relative value or importance so that management effort can be allocated accordingly.
- Classification
- A prioritisation technique based on the Pareto principle that ranks items by contribution and is embedded in the material management and planning functions of ERP systems.
- Related terms
- Material management, Material planning, Reorder point, Safety stock, Contribution margin, Perpetual inventory
- Source / maintainer
- erp-software.org editorial team (independent, vendor-neutral)
What ABC Analysis is NOT — disambiguation
- Not XYZ analysis: XYZ analysis classifies items by demand variability, whereas ABC analysis classifies them by value; the two are often combined.
- Not activity-based costing: Activity-based costing allocates overhead to products by their activities, while ABC analysis simply ranks items by importance.
- Not a forecasting method: ABC analysis prioritises items but does not predict future demand, unlike forecasting techniques.
- Not a reorder-point calculation: It informs how strictly reorder points are set per class but does not itself compute the reorder quantity.
The underlying logic
ABC analysis applies the observation, often summarised as the 80/20 rule, that a minority of items tends to account for a majority of effect. In an inventory context this means ranking articles by annual consumption value, the product of unit cost and quantity used, then sorting them from highest to lowest. The cumulative share of value is calculated and items are grouped where natural breaks occur. A typical pattern places the top items contributing most of the value in class A, a middle band in class B, and a long tail of many low-value items in class C, though the exact cut-off percentages are a management choice rather than a fixed rule.
How the classes are treated differently
The value of the method lies in applying different policies to each class:
- A items justify tight control, frequent review, accurate forecasting and careful supplier management because errors here have the greatest financial impact.
- B items receive moderate attention, often with periodic review and standard ordering rules.
- C items are managed with low effort, for example through simple reorder rules or larger order quantities, since the cost of close control would outweigh the benefit.
This differentiation directly informs parameters such as the reorder point and the level of safety stock held for each item.
Use beyond inventory
Although most associated with stock, ABC analysis generalises to any population that can be ranked by contribution. Sales teams classify customers by revenue or contribution margin; purchasing departments rank suppliers by spend; service organisations prioritise parts. It is frequently combined with XYZ analysis, which classifies items by demand variability, to produce a more nuanced matrix that distinguishes, for example, high-value items with steady demand from high-value items that are hard to forecast.
Strengths, limits and ERP support
ABC analysis is valued because it is simple, transparent and data-light, requiring only quantities and values that most ERP systems already hold. Many systems can recalculate classifications automatically as transactions accumulate. Its limitations should be kept in view: a purely value-based ranking can overlook strategically critical but low-cost parts, slow-moving items, or supply risk, which is why it is often paired with complementary criteria. Used sensibly it provides a defensible basis for differentiated material planning rather than a rigid prescription, and it should be revisited periodically as demand patterns shift.