What is ABC Analysis?

ABC analysis is an inventory classification methodology that segments a business's entire product catalog into three categories — A, B, and C — based on each product's relative contribution to total revenue or consumption value. The technique is grounded in the Pareto principle, which in an inventory context observes that a small percentage of SKUs typically generates a disproportionately large share of total sales. A-class items are the vital few products that drive the majority of revenue, B-class items contribute moderately, and C-class items are the numerous low-value products that collectively account for a small share of sales. By categorizing inventory this way, businesses can allocate management attention, investment, and resources proportionally to each product's economic importance.

Why It Matters

Most businesses treat all inventory equally by default — applying the same purchasing rules, safety stock formulas, counting frequencies, and storage strategies to every SKU. This one-size-fits-all approach is inherently wasteful because it over-invests in managing low-value items and under-invests in protecting high-value ones. ABC analysis provides the framework for differentiated inventory management, ensuring that the products most important to your business receive the most attention and resources.

The Pareto distribution in inventory is remarkably consistent across industries. Typically, A-class items represent approximately 10 to 20 percent of SKUs but generate 70 to 80 percent of total revenue. B-class items represent about 20 to 30 percent of SKUs and contribute 15 to 20 percent of revenue. C-class items represent the remaining 50 to 70 percent of SKUs but account for only 5 to 10 percent of revenue. These ratios vary by business, but the fundamental pattern — a small number of products driving a large share of value — is nearly universal.

Understanding this distribution has profound implications for inventory management decisions. A stockout on an A-class item has a dramatically larger revenue impact than a stockout on a C-class item, so A items should carry higher safety stock and more conservative reorder points. Conversely, investing in high service levels for C-class items — which collectively contribute little revenue — wastes capital on excess inventory and warehouse space that could be better deployed elsewhere.

ABC analysis also informs warehouse layout, cycle counting schedules, supplier negotiation priorities, and markdown strategies. A items get prime warehouse locations for fast picking, frequent cycle counts for accuracy assurance, and top-priority supplier relationships. C items are stored in less accessible areas, counted less frequently, and managed with lean policies that tolerate occasional stockouts in exchange for lower carrying costs.

How It Works

Conducting an ABC analysis involves a straightforward analytical process that can be performed on any inventory dataset:

• Calculate annual consumption value: For each SKU, multiply the annual unit sales volume by the unit cost or selling price. This produces the total revenue or consumption value generated by each product over the analysis period. Using a twelve-month timeframe smooths out seasonal fluctuations.
• Rank by value: Sort all SKUs in descending order by their consumption value. The highest-value items appear at the top of the list, and the lowest-value items at the bottom.
• Calculate cumulative percentages: Working down the sorted list, calculate each SKU's percentage of total consumption value and the running cumulative percentage. Also calculate each SKU's percentage of total SKU count and the running cumulative percentage of items.
• Apply classification thresholds: Assign each SKU to a class based on where it falls in the cumulative distribution. Common thresholds define A items as those contributing the first 80 percent of cumulative value, B items as the next 15 percent, and C items as the remaining 5 percent. These thresholds can be adjusted based on business needs and the specific distribution observed in the data.
• Apply differentiated policies: Once classified, each class receives tailored management policies covering safety stock levels, reorder points, counting frequency, storage placement, and markdown triggers. These policies should be documented, implemented in inventory systems, and reviewed periodically.

Beyond Revenue: Multi-Criteria ABC Analysis

While revenue-based classification is the most common approach, sophisticated inventory management practices extend ABC analysis to incorporate multiple criteria that provide a more complete picture of each product's importance:

• Gross margin contribution: A product with high revenue but thin margins may warrant different treatment than one with moderate revenue but high margins. Margin-weighted ABC analysis prioritizes products that contribute the most to profitability rather than just the top line.
• Demand variability: Products with highly variable demand require different management strategies than those with steady, predictable sales. Combining ABC classification with demand variability analysis creates a matrix that informs both service level targets and safety stock strategies.
• Strategic importance: Some products are strategically important regardless of their revenue contribution — such as products that attract new customers, complement high-margin items, or fulfill contractual obligations with retail partners. Manual overrides to the ABC classification can account for strategic considerations that purely quantitative analysis misses.
• Customer criticality: In B2B contexts, products that key accounts depend on may warrant A-class treatment even if their aggregate volume is modest, because a stockout would jeopardize a high-value business relationship.

Maintaining and Updating Classifications

ABC classifications are not permanent. Product demand evolves due to market trends, competitive dynamics, seasonality, and product lifecycle stage. A product that was A-class during its launch year may migrate to B or C as newer products capture market share. Conversely, a slow-selling C-class product that suddenly gains popularity through social media exposure or a trend shift should be reclassified to reflect its new importance. Best practice is to rerun the ABC analysis quarterly or semi-annually to keep classifications current and policies aligned with actual performance.

How Nventory Helps

Nventory automates ABC analysis by continuously evaluating SKU-level sales data and assigning dynamic classifications that update as demand patterns change. Configurable classification thresholds let you define the boundaries between A, B, and C classes based on your business's specific distribution. Once classified, Nventory applies differentiated inventory policies automatically — higher safety stock and more frequent reorder alerts for A items, leaner buffers for C items. Cycle counting schedules, replenishment priorities, and dead stock alerts all reference the ABC classification, ensuring that your most valuable products receive the most proactive management. Dashboards provide a visual breakdown of your inventory by class, making it easy to monitor the health and balance of your catalog at a glance.