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Three blueprint shelf blocks labeled A, B, and C holding real cardboard boxes — a few large boxes under A marked with a cyan pin, a moderate amount under B, and many small boxes under C — beneath a blueprint Pareto bar chart on pale-blue grid paper

What Is ABC Analysis in Inventory Management?

Binlogic Team 4 min read
TL;DR

ABC analysis sorts SKUs into three tiers by value or velocity: A items are the vital few that drive most of your activity, C items are the trivial many. It tells you where to slot stock, how often to count it, and where tight control actually pays off.

Not every SKU deserves the same attention. The dish soap that sells forty units a day and the novelty mug that sells one a month should not get counted on the same schedule, slotted with the same priority, or watched with the same care. ABC analysis is the simple framework that sorts the two apart so you spend your effort where it pays off.

It comes from an old observation: a small share of your items drives most of your activity. Roughly 20% of SKUs often account for around 80% of sales or picks. ABC analysis turns that pattern into three buckets you can actually manage.

The three tiers

The letters are tiers, not acronyms. They rank importance, nothing more.

  • A items are the vital few. The fast movers, the high-margin lines, the SKUs your business runs on. Often about 20% of SKUs driving the bulk of value or pick volume.
  • B items are the moderate middle. Steady, worth attention, not where you spend your best hours.
  • C items are the trivial many. The long tail. Lots of SKUs, small individual impact, easy to over-manage if you're not careful.

The point isn't the exact cutoffs. It's the principle: concentrate control where the impact is, and stop spending equal energy on items that don't move.

Revenue or velocity — which lens?

This trips people up. Should you rank by how much money a SKU makes or by how often it gets picked? The honest answer is: depends on the decision you're about to make.

Decision

Classify by

Why

Purchasing, stock investment

Revenue or margin

You care about dollars tied up and earned

Slotting, pick-path design

Pick velocity

You care about labor and travel time

Cycle count frequency

Pick velocity (and value)

Count what moves and what's expensive

A SKU can be a revenue A and a velocity C at the same time. Think of a high-priced item that sells rarely. It matters a lot to finance and very little to your pickers. Plenty of mature operations run both lenses side by side and accept that a SKU lands in different tiers depending on the question.

How to classify your SKUs

You don't need software to start. You need a spreadsheet and a few months of data.

  1. Pull every SKU with its annual sales value (units sold × cost or price) or its pick count over the period.
  2. Sort the list from highest to lowest.
  3. Calculate each SKU's share of the total, then the running cumulative share.
  4. Draw the lines. A common split: the SKUs making up the top ~80% of value are A, the next ~15% are B, the final ~5% are C. Adjust to fit your catalog.

That's it. The first time you do this, the result is usually a little jarring, because you find a cluster of C items you've been treating like A items out of habit.

What ABC analysis is actually for

Classification on its own does nothing. It pays off when it drives real decisions.

Slotting. Your A items belong in the easiest-to-reach locations, close to packing, in the golden zone where a picker doesn't bend or stretch. C items can live in the back. This single move cuts travel time on the picks you do most.

Cycle counting. Count A items often — monthly, sometimes weekly for the high-value ones. Count B items quarterly. Count C items a couple of times a year. You audit where errors hurt most and stop wasting labor recounting slow movers.

Purchasing focus. A items get tight reorder points, real demand forecasting, and a closer eye on supplier reliability. C items can run on simpler rules because a stockout costs less.

A worked example

Say you stock 1,000 SKUs. You run the numbers and find:

  • 180 SKUs (18%) drive 79% of your sales value. Those are your A items.
  • 320 SKUs (32%) drive the next 16%. Your B items.
  • 500 SKUs (50%) drive the last 5%. Your C items.

Now the schedule writes itself. The 180 A items go in your best locations and get counted monthly. The 500 C items go in the back and get counted in spring and fall. You just aimed the majority of your operational attention at 18% of the catalog — the 18% that actually pays the bills.

Keep it current

Demand drifts. A seasonal item climbs from C to A in November and slides back in January. A discontinued line that used to be an A is now dead stock. If your classification is a year old, you're slotting and counting last year's business.

Rerun ABC analysis quarterly for most operations, and always after a big seasonal swing or a product launch. It takes an hour with the spreadsheet you already built, and it keeps every decision downstream pointed at the right SKUs.

Frequently asked questions

What do A, B, and C stand for in ABC analysis?

They're tiers, not acronyms. A items are your highest-impact SKUs (often the top ~20% that drive ~80% of value or picks). B items are the moderate middle. C items are the long tail of low-impact SKUs. The letters just rank importance.

Should I classify by revenue or by pick velocity?

Depends on the decision. Classify by revenue or margin for purchasing and stock-investment decisions. Classify by pick velocity for slotting and cycle-count frequency, because that's what drives warehouse labor. Many operations run both lenses.

How often should I redo ABC analysis?

Quarterly is a reasonable default for most operations, and after any major seasonal shift or product launch. SKUs migrate between tiers as demand changes, and a classification that's a year stale will slot and count the wrong items.

Plan the route. We deliver the rest.

See how Binlogic powers last-mile logistics — routing, tracking, and the platform that turns the plan into the package on the doorstep.

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