ABC Analysis for Inventory: The 80/20 Method Explained (UK Guide)

What is ABC analysis?

ABC analysis classifies your inventory into three groups by how much value each product contributes to your business. It is a direct application of the Pareto principle — the observation that a small share of causes usually produces most of the effect. In inventory terms: a minority of your SKUs generate the majority of your revenue.

• A items — the vital few. Typically around 20% of your SKUs producing roughly 80% of your consumption value. These deserve tight stock control, accurate forecasting, frequent counting, and priority when cash is limited.
• B items — the middle tier. Roughly the next 30% of SKUs producing about 15% of value. Standard controls, reviewed on a normal cycle.
• C items — the trivial many. Often 50% or more of your SKUs producing the last 5% of value. Light-touch management: simple reorder rules, infrequent counts, and honest conversations about whether some should be discontinued.

The percentages are conventions, not laws. Your catalogue might split 70/20/10 or 85/10/5. What matters is the principle: match the management effort to the value at stake. Spending an hour a week forecasting a product that sells two units a month is a waste of your time; failing to forecast the product that pays your rent is a business risk.

The calculation, step by step

You need two numbers per SKU: annual units sold and unit value (most sellers use cost price; some use sale price — pick one and be consistent). Then:

1. Calculate annual consumption value for each SKU: units sold × unit value.
2. Sort all SKUs by consumption value, highest first.
3. Total the consumption value across all SKUs.
4. Compute the cumulative percentage as you walk down the sorted list.
5. Assign classes: SKUs up to ~80% cumulative value are A; from 80% to ~95% are B; the rest are C.

Worked example

A candle seller with ten SKUs. Consumption value is annual units × unit cost:

Two SKUs — 20% of the catalogue — account for 75% of the value. That is the Pareto principle showing up in real data, and it shows up in almost every catalogue we see. The practical conclusion is immediate: if the lavender candle stocks out, the business has a problem. If the brass snuffer stocks out, nobody will notice for a month.

What to actually do with each class

Classification is only useful if it changes behaviour. Here is what different treatment looks like in practice:

A items: protect them

Your A items should never stock out. Every day an A item is unavailable costs you meaningful revenue and — on marketplaces like eBay and Amazon — search ranking that takes weeks to recover. Hold more safety stockthan the formula strictly suggests, count them frequently so recorded stock matches reality, and know your supplier's lead time to the day. If cash is tight, cut C-item orders before touching A-item cover.

B items: systematise them

B items are where automated rules earn their keep. Set a reorder point, let your software alert you when it's hit, and don't think about them otherwise. The danger with B items is drift: a B item trending up deserves promotion to A-level attention, and one trending down is on its way to becoming dead stock.

C items: question them

C items are where dead stock hides. Each one looks harmless — a few pounds of stock, a sale every few weeks — but collectively they can tie up a third of your cash and most of your shelf space while contributing 5% of revenue. Review them quarterly and ask: would I reorder this today? If not, run it down and clear it. The best C-item strategy is often to have fewer C items.

Useful variations

ABC by margin, not revenue

Revenue-based ABC can flatter high-turnover, low-margin products. A product doing £20,000 of revenue at 8% margin contributes less profit than one doing £6,000 at 45%. Running the same calculation on gross profit contribution instead of consumption value often reshuffles the classes in ways that change your decisions — particularly around which products deserve marketing spend.

XYZ analysis: adding demand variability

ABC tells you how much a product matters; XYZ tells you how predictable it is. X items sell steadily (easy to forecast), Y items fluctuate (seasonal or trend-driven), Z items are erratic. Combining both gives a two-dimensional grid: an AX item (high value, steady demand) can run with lean safety stock because forecasting is reliable, while an AZ item (high value, erratic demand) needs generous buffers precisely because you cannot predict it. For most small sellers, the full grid is overkill — but the intuition matters: value determines how much attention a product gets; variability determines how much buffer it gets.

Seasonal catalogues

If you sell seasonally (Christmas, garden, back-to-school), run ABC on a rolling 12-month window rather than calendar-year data, and interpret classes with the calendar in mind — your Christmas A item is a C item in June, and that is fine. What you want to avoid is the October mistake of treating it like a C item when its season is about to start. See our guide to managing seasonal inventory.

Where ABC analysis misleads

ABC is a blunt instrument, and it is worth knowing its blind spots:

• New products have no history. A product launched last month will land in C purely for lack of data. Exclude recent launches from the analysis or judge them separately.
• Complementary products. The brass snuffer might be a C item that A-item customers expect you to stock. Cutting it could dent A-item sales. Look at basket data before discontinuing.
• Strategic items. Some low-value products exist to win the customer relationship — samples, entry-price items, replacement parts. Classify them, but exempt them from the cut list.
• Stale classifications. An ABC snapshot from January is fiction by June. Demand moves; the analysis has to move with it. This is the strongest argument for automating it.

Spreadsheet vs software

The calculation is easy in a spreadsheet — export sales, multiply, sort, cumulative sum. The problem is not the maths, it's the maintenance. The spreadsheet is out of date the day after you build it, and in our experience almost nobody rebuilds it quarterly by hand.

Salync runs ABC analysis continuously from live sales data across every connected channel — eBay, Shopify, Amazon and the rest — so classes update as demand shifts. The reports flag class movements (a C item trending toward B, an A item losing momentum) and pair the classification with dead stock detection, so the "question your C items" review comes ready-made. It's available on the Growth plan, with a 14-day free trial.