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Inventory · February 26, 2026 · 8 min read

ABC inventory analysis: find your top 20% SKUs

You cannot give every SKU equal attention. The top 20% of your catalog deserves daily care; the bottom 50% deserves to be left alone. ABC analysis is the discipline of treating different SKUs differently, on purpose.

The pareto reality of any catalog.

Take any retail or wholesale SKU list of meaningful size — say 5,000 SKUs in a hardware distributor — and rank by trailing 12-month sales value. Plot cumulative sales against cumulative SKU count. You will get a curve where the top 20% of SKUs (1,000 items) account for roughly 80% of sales, the next 30% (1,500 items) account for another 15%, and the bottom 50% (2,500 items) account for 5%.

The numbers vary — sometimes it is 70/20/10, sometimes 85/12/3 — but the shape is universal. Half your catalog is producing almost no value. The opposite is also true: a small core is producing most of your business. Treating these as equally important is operational malpractice.

How abc actually classifies.

A items: top 20% of SKUs by value, producing roughly 80% of sales or COGS. These are your bread and butter. Stock them deeply, count them frequently, never run out, get the best supplier terms on them.

B items: next 30% by value, producing roughly 15% of sales. These get standard treatment — adequate stock, quarterly cycle counts, normal reorder discipline.

C items: bottom 50% by value, producing roughly 5% of sales. These get the lightest treatment — minimum stock, semi-annual counts, and a hard look every 6 months at whether they belong in the catalog at all.

  • Classify by value (price × quantity sold), not just price
  • Re-classify quarterly — SKUs migrate between classes
  • New SKUs default to B until they have 3 months of sales history
  • Some SKUs are A despite low value (insulin, regulator-mandated, key brand)

A worked example for a hardware shop.

A hardware distributor in Chicago has 4,200 active SKUs. Trailing 12 months of sales total USD 1.8 million. Running ABC: top 840 SKUs (20%) produce USD 1.44 million (80%) — these are A. Next 1,260 SKUs produce USD 270,000 (15%) — B. Bottom 2,100 produce USD 90,000 (5%) — C.

Operational implications. A items: target 30 days of cover, count monthly, supplier review quarterly, reorder triggered by min/max not just visual. B items: target 21 days of cover, count quarterly, supplier review annually. C items: target 14 days of cover or less, count semi-annually, candidates for delisting if they sit stale for two consecutive quarters. Same warehouse, three different operating disciplines.

A · 840 SKUs (20%) · 1,440 k revenueB · 1,260 SKUs (30%) · 270 k revenueC · 2,100 SKUs (50%) · 90 k revenue
Half the catalogue produces 5% of revenue. Treat the three tiers differently or pay for the inattention.

Why c items are dangerous.

C items look harmless individually — each one moves slowly and ties up little cash. The problem is volume. A 4,200 SKU catalog with 2,100 C items means half your shelves, half your bin counts, half your receiving complexity is producing 5% of value. You are paying for warehouse space, staff time, and tax-on-stock for inventory that is barely earning its keep.

The right answer is ruthless C-class management. Set a rule: any C item with under 4 turns per year for two consecutive quarters goes on the kill list. Either order it only on customer request (no stock), find a substitute that already exists in the catalog, or delist entirely. Most businesses find they can cut catalog by 15-25% with no revenue impact, freeing meaningful working capital.

C item flagged< 4 turns 2 quartersOrder on requestNo stock heldFind substituteExisting A/B itemDelistRemove from catalog
Four-option triage. Most chains cut 15-25% of SKUs with zero revenue impact and meaningful working-capital release.

When abc gets refined into abcd or abc-xyz.

Standard ABC classifies by value alone. A second axis classifies by demand variability: X items have very stable demand (low coefficient of variation), Y items have moderate variability, Z items are erratic. Crossing the two gives 9 cells: AX through CZ. The interesting cells are AZ (high value, erratic demand — needs safety stock and forecasting attention) and CX (low value, stable demand — automate the reorder, ignore otherwise).

For most growing businesses, plain ABC is enough. ABC-XYZ becomes valuable past mid-market revenue or 10,000 SKUs, where the catalog is too complex to manage by value alone. Below that, plain ABC drives 80% of the benefit.

How nonari runs abc automatically.

Nonari computes ABC quarterly based on trailing 12-month sales value per SKU. The classification feeds three downstream systems: cycle count scheduling (A monthly, B quarterly, C semi-annual), reorder point calculations (A items get tighter safety stock), and dead stock alerts (C items with low turns flagged for review).

You can also override the auto-classification for specific SKUs — a high-margin loss leader, a regulatory-required item that must be in stock regardless of velocity, a key brand item that sets the tone of your shop. Override reasons are logged so the next manager understands why a SKU is treated as A despite low value.

Frequently asked

Common questions.

How often should I re-run ABC?

Quarterly is the right cadence for most businesses. Monthly is overkill and creates classification thrash. Annual is too slow — seasonality and trend shifts get missed.

Should I classify by sales value or by gross profit?

Either works. Sales value is simpler and adequate for most. Gross profit is more accurate but requires reliable item-level margin, which not every business has clean. Start with sales value and upgrade later if needed.

What about new items with no history?

Default to B for the first 90 days, then re-classify based on actual sales. Avoid the temptation to call new launches "A" without data — it leads to over-stocking flops.

Can I use ABC across all branches together or per branch?

Both. Chain-level ABC drives catalog and supplier strategy. Branch-level ABC drives stock levels and cycle count schedules per location. Nonari runs both automatically.

Are there industries where ABC does not apply?

Boutique single-SKU manufacturers, rare. Almost any retail, wholesale, distribution, or multi-SKU manufacturing business benefits. The Pareto effect is empirical, not theoretical.

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