ABC FSN XYZ Inventory Classification Tool | Free Calculator

80% of your revenues are generated by less than 30% of your products. If your team doesn't have that accurately mapped out, it's making blind inventory decisions.

Managing all the SKUs with the same stock policy is not a neutral stance. It's an active decision: overinvesting where you shouldn't and understocking where it hurts the most. The combined ABC XYZ FSN classification exists to correct just that: segment the portfolio according to what each product actually represents in revenue, how predictable its demand is and how often it moves.

We created this tool so that you can do this classification in minutes, with any dataset, without manual formulas and with specific action recommendations for each SKU.

What each methodology measures and why the combination matters

Each of the three methodologies answers a different question about your inventory.

• ABC → How much money does this product make? Apply the Pareto principle to your income. Class A products are the core of the business. C's are portfolio queues that often consume more resources than they justify.
• XYZ → How predictable is your demand? It measures the Variation Coefficient of sales by period. An X product has stable demand and is easy to plan. A Z product is erratic: the forecast fails, the safety stock is systematically underestimated and the stockouts arrive without warning.
• FSN → How often do you receive orders? Evaluate intermittency. A product F is constantly moving. One N has not generated a single order for periods and takes up warehouse space that could be financing profitable products.

Cross-classification (AXF, BZN, CZN) is where the real insight is. A product A with stable demand and high turnover has nothing to do operationally with an A with erratic demand and low frequency. Stock decisions, ROP, and restocking policy should be completely different for everyone, and rarely are when this segmentation doesn't exist.

How to use the tool in four steps

The flow is designed so that you don't need to be a data analyst to execute it. If you have your sales data in Excel or Google Sheets, you can have the complete ranking in less than ten minutes.

Step 1: Upload your data

The tool accepts .xlsx, .xls, or .csv files. You can also copy a range directly from Excel or Google Sheets and paste it with the “Paste table” button, without having to export the file.

If you want to explore the tool before loading real data, there's an integrated sample data option.

The minimum dataset you need includes three items:

• SKU_ID: identifier for each product
• Total revenue: sales in the analysis period
• Demand by period: monthly columns (or whatever time window you use) with units sold

The tool accepts as many demand columns as your file has. We have tested it with 6 and 12 periods without any problem.

Step 2: Map the columns

The tool automatically detects key fields and labels them as “Auto”. In practice, if your headings are reasonably descriptive, you won't have to do anything manually.

Mappable fields include: SKU ID, product name, total revenue, demand columns by period, periods with orders, and total periods. If you already have pre-calculated the periods with orders in your file, the tool accepts them directly. If not, it calculates them based on the demand columns.

Step 3: Configure the thresholds

Here is the only decision that requires business judgment. The default thresholds are industry standards, but you can adjust them if your operation has peculiarities.

XYZ Thresholds (Coefficient of Variation):

• X: CV ≤ 0.33 → stable demand
• Y: CV between 0.33 and 0.66 → moderate variability
• Z: CV > 0.66 → high variability (automatic)

FSN (Intermittency) Thresholds:

• F: Intermittance ≤ 0.25 → fast moving product
• S: between 0.25 and 0.50 → slow movement
• N: > 0.50 → no movement (automatic)

The ABC classification has no manual thresholds. Use the Pareto principle automatically to distribute the SKUs in A, B and C based on their cumulative income contribution.

Before calculating, the tool shows a preview of the ABC × XYZ matrix in 3×3 format so that you can see the cross distribution before confirming.

Step 4: Analyze the results and export

The results panel provides the full classification by SKU with all the metrics calculated automatically.

What does the tool deliver for each SKU:

The three key metrics — CV, intermittency and cumulative% of revenue — are calculated by the tool internally. You don't need to pre-calculate them in your file.

From classification to decision: what the tool does with each profile

Each SKU doesn't just receive its combined label. Get a recommended action with a priority level and specific strategies. When you click on the popup for each product, the full detail is displayed.

• High Stock Intensive Management (High Priority) AXF profile: critical product, stable demand, high turnover. The strategy includes 20-30% security stock, daily review, automatic reorder, and proactive negotiation with suppliers. These are the products that cannot fail.
• Variable Intensive Stock Management (High Priority) AZF profile: same level of income as the previous one, but with erratic demand. It requires larger security stock (25-35%), predictive analysis and multiple vendors to absorb variability.
• Moderate Stock Standard Management (Medium Priority) BXF or BYF profiles: average value, predictable demand. Weekly or biweekly review, periodic reorder. The operational risk is low.
• Basic Low Stock Management (Low Priority) Profiles such as BZS or CXF: low value or low turnover. Minimum stock to reduce maintenance costs. They don't justify intensive resources.
• Evaluate Discontinuation (Medium Priority) BZN Profile: medium or low value, without movement. Do not make new purchases. Liquidate existing stock and evaluate if it's a real niche product or simply dead cargo in the warehouse.
• Review Classification (Medium Priority) AZS Profile: an atypical combination that may indicate a problem with the data or a product that deserves further analysis before making any stock decision.
• DISCONTINUE Delete from catalog (Low Priority) CZN profile: low value, no movement, erratic demand. Remove from the catalog, liquidate all stock and free up warehouse space for profitable products.

An example with real data: distributor of cleaning products

We tested the tool with a dataset of ten SKUs from a distribution company to show exactly what type of output it generates. Revenues per product range from $285,000 to $18,000.

Summary of the classification:

• ABC → A: 4 SKUs (40%) | B: 3 SKUs (30%) | C: 3 SKUs (30%)
• XYZ → X: 5 SKUs (50%) | Z: 5 SKUs (50%)
• FSN → F: 5 SKUs (50%) | S: 2 SKUs (20%) | N: 3 SKUs (30%)

Three observations that come out of this analysis and that are worth breaking down:

The first four SKUs account for 71.6% of revenues. The 5L Industrial Detergent and the 1L Concentrated Degreaser alone represent the accumulated 43.6%. If either of those two has a stockout, the impact on revenue is immediate. And both have CVs of 0.03 and 0.04 respectively: almost perfectly stable demand. With that combination of critical and predictability, there's no valid argument for not having the stock covered loosely.

Professional Bleach 10L is the case that deserves the most attention. Third product by income, class A, but with a CV of 0.71 and intermittency of 0.33, giving it the AZS combination. The tool correctly marks it as “Review Rating”. Before defining any stock policy, the team needs to understand why a high-value product is in such erratic demand. Seasonality? Orders by project? A customer who concentrates the bulk of the volume and orders irregularly? The tool signals the anomaly; the equipment interprets it.

The Industrial Air Freshener and Stain Remover have a CV of 2.24 with an intermittency of 0.83. In almost 83% of the periods there were no orders, and when there are, the quantity is completely erratic. With combined revenues of $41,000 out of a total of $1,108,000, less than 4% of the portfolio, the decision to discontinue should not generate debate.

What the tool does and what you should contribute

The ABC XYZ FSN ranking is only as good as the track record you give it. That's not a disclaimer: it's something that changes the quality of the result.

The analysis period matters. With only three months of data on a product with marked seasonality, the CV may be inflated by normal seasonal variation and the product would end up rated Z when in reality it is perfectly predictable within each season. For portfolios with seasonality, work with at least twelve months.

The granularity of the period also matters. Weekly data give a finer picture of the variability than monthly data. If your operation has short replenishment cycles, working with weeks significantly improves XYZ accuracy.

The combined classification is the starting point. An AZS such as the Professional Bleach in the example requires additional qualitative analysis. And before executing any discontinuation, validate that the SKU does not respond to a strategic customer who buys low volume but is important for business reasons that do not appear in the sales data. The tool doesn't have that context. Your planning team does.

From this classification to a complete planning system

With a well-segmented portfolio, security stock decisions, ROP and review frequency are no longer opinion and are methodologically based. That is already an important leap.

The problem is that demand behavior changes. A product that today is AXF can become AZF in high season. If that reclassification doesn't automatically update the stock policy, the diagnosis loses value quickly. For operations with hundreds or thousands of SKUs, multiple locations, and data distributed in an ERP, keeping that classification up to date with manual work doesn't scale.

That's exactly what the Datup platform does: it connects portfolio diagnostics with forecasting, inventory optimization and purchasing workflows in a single environment, integrating directly into your ERP without additional manual work from your team.

If you want to see how it would be applied to the real data of your trade, you can schedule a personalized demo with the team.