ABC Inventory Analysis: How to Prioritize Your Products

In most shops, a small number of products account for a large share of the money flowing through inventory. ABC inventory analysis makes that visible, so you can spend your limited time controlling the products that matter most — and stop over-managing the ones that do not.

This guide explains the ABC method step by step, shows a complete worked example with ten products, and turns the result into concrete policies for ordering, counting and pricing.

What is ABC inventory analysis?

ABC analysis ranks products by their annual consumption value — how much money moves through each product in a year — and groups them into three classes:

Class	Typical share of SKUs	Typical share of value	Management attention
A	about 10–20%	about 70–80%	High — tight control
B	about 20–30%	about 15–25%	Medium
C	about 50–70%	about 5–10%	Low — simple rules

The idea follows the Pareto principle (“80/20 rule”). The percentages are conventions, not laws: practitioners use slightly different thresholds, and your own data decides where the natural breaks are.

Annual consumption value

Use cost rather than selling price when the goal is inventory investment and control. Some retailers rank by gross profit or revenue instead when the goal is commercial focus; the method is the same, but be consistent and state which basis you used.

You need two data points per SKU: the unit cost (from your purchase records) and the number of units sold in the last twelve months (from your sales reports). See purchase management and reports.

How to do an ABC analysis in five steps

1. Export each SKU’s unit cost and units sold over the last 12 months.
2. Calculate ACV for each SKU: unit cost × annual units.
3. Sort SKUs from highest to lowest ACV.
4. Calculate each SKU’s share of total ACV and the cumulative percentage down the list.
5. Classify: SKUs up to roughly 70–80% cumulative value are A, the next band up to roughly 90–95% are B, and the rest are C. Adjust the cut-offs to the natural breaks in your data.

A spreadsheet is enough. Sort by ACV, add a running total column and divide by the grand total.

Worked example: a coffee equipment shop

A small specialty coffee shop sells beans, equipment and accessories. Here are its ten SKUs, ranked by annual consumption value (unit cost × annual units). All figures are calculated and rounded to one decimal place.

Rank	SKU	Unit cost	Annual units	ACV	Share	Cumulative	Class
1	Premium beans 1 kg	$14.00	2,600	$36,400	32.2%	32.2%	A
2	Espresso machine	$420.00	60	$25,200	22.3%	54.6%	A
3	Coffee grinder	$95.00	180	$17,100	15.2%	69.7%	A
4	Milk frother	$38.00	320	$12,160	10.8%	80.5%	B
5	Paper cups (box of 1,000)	$22.00	410	$9,020	8.0%	88.5%	B
6	Ceramic mug	$6.50	900	$5,850	5.2%	93.7%	B
7	Descaler	$5.20	600	$3,120	2.8%	96.4%	C
8	Filter papers	$1.80	1,500	$2,700	2.4%	98.8%	C
9	Cleaning brush	$2.40	350	$840	0.7%	99.6%	C
10	Gift card sleeves	$0.60	800	$480	0.4%	100.0%	C

Total annual consumption value: $112,870.

Reading the result

• Class A — 3 SKUs (30% of items) carry 69.7% of value. Two of them — the espresso machine (60 units) and the grinder (180 units) — are the two least frequently sold items in the whole range, yet they rank second and third by value.
• Class B — 3 SKUs (30% of items) carry 24.0% of value (93.7% − 69.7%).
• Class C — 4 SKUs (40% of items) carry just 6.3% of value. Filter papers sell 1,500 units a year but matter little financially.

With only ten SKUs the split is less extreme than in a real shop with hundreds or thousands of products, where the long tail of C items is usually much larger.

Turning classes into management policies

Policy	Class A	Class B	Class C
Reorder method	Calculated reorder point with safety stock	Reorder point, reviewed quarterly	Simple min/max or periodic top-up
Service level target	Highest (e.g. 97–99%)	Medium (e.g. 95%)	Lower (e.g. 90%)
Cycle count frequency	Monthly or more	Quarterly	Once or twice a year
Count tolerance	Exact match	Small tolerance	Wider tolerance
Supplier management	Track lead time; second source	Regular review	Consolidate orders
Shelf position / security	Prime, visible, protected	Standard	Standard
Review frequency	Weekly	Monthly	Quarterly

The service-level and frequency figures are starting points, not standards. Adjust them to your margins, space and staffing. For counting schedules, see inventory cycle counting.

ABC analysis in a spreadsheet

Column	Formula (Excel / Google Sheets)
C: Annual consumption value	=A2*B2 (unit cost × annual units)
Sort	Sort the whole table by column C, largest to smallest
D: Share of total	=C2/SUM($C$2:$C$1001)
E: Cumulative share	=SUM($D$2:D2)
F: Class	=IF(E2<=0.7,”A”,IF(E2<=0.95,”B”,”C”))

Change 0.7 and 0.95 to the cut-offs you choose. In the worked example above, these thresholds give three A items, three B items and four C items.

Using ABC to manage cash and purchasing

ABC is not only a counting tool. Because A items hold most of the money moving through inventory, small improvements on them have the biggest effect on cash flow:

• Order A items more often in smaller quantities where suppliers allow, so less cash sits in stock.
• Negotiate on A items: a few percent on a high-value line is worth more than large discounts on C items.
• Order C items less often in larger quantities to reduce ordering effort; the cash impact is small.
• Review slow-moving B and C items for discontinuation when space is tight.

Illustrative scenario

The following is a hypothetical illustration, not a customer case. A hardware store with 4,000 SKUs runs its first ABC analysis and finds that roughly 400 items make up most of its annual consumption value. It moves those items to weekly reorder reviews and monthly counts, sets reorder points for them, and switches thousands of low-value fasteners and accessories to a simple monthly top-up. The owner spends less total time on stock — but now spends it where the money is.

Refinements: XYZ, criticality and new products

• XYZ analysis adds demand variability: X items sell steadily, Z items sell erratically. An “AZ” item (valuable and unpredictable) needs more safety stock than an “AX” item.
• Criticality overrides: a low-value C item can still be essential — the paper cups a café cannot trade without. Flag such items manually.
• New products lack a year of history. Classify them provisionally on expected sales and revisit after three months.
• Seasonality: a seasonal product may be A in December and C in March. Run the analysis on the relevant period.

What ABC changes in a store’s daily routine

Classification only pays off when it changes what people do. In practice, a retailer using ABC typically ends up with three different rhythms:

Routine	Class A	Class B	Class C
Low-stock check	Every day	Twice a week	Weekly
Ordering	Per reorder point, possibly several times a week	Weekly order	Monthly top-up
Counting	Rolling monthly counts	Quarterly	Once or twice a year
Price checks vs. suppliers	Every delivery	Quarterly	Yearly

These rhythms are examples to adapt, not rules. The point is that the shop owner’s limited attention follows the money. Keep the class visible — for example as a prefix in an internal note or category tag — so staff know which products deserve extra care when stock is low or a delivery is short.

Where the data comes from

Everything ABC needs is already produced by a POS that records sales by product and purchases with cost prices: units sold per product over twelve months, and the latest unit cost. Export both, run the spreadsheet steps above, and repeat twice a year. Accurate inputs depend on accurate stock and cost records — another reason to keep up regular cycle counts and to record every delivery.

Common ABC analysis mistakes

• Ranking by units instead of value. High-volume, low-cost items look important when they are not.
• Never updating the classes. Review at least twice a year; product ranges and prices change.
• Ignoring gross margin entirely. For buying decisions, also look at profit contribution, not just cost.
• Using inaccurate stock or cost data. The analysis is only as good as your records — keep them clean with regular counts and recorded purchase prices.
• Treating C items as unimportant to customers. Missing small items still frustrates shoppers; keep simple, reliable rules for them.

ABC analysis checklist

• Export 12 months of units sold and current unit cost for every SKU.
• Calculate ACV, sort, compute cumulative percentages.
• Set cut-offs at natural breaks (around 70–80% and 90–95%).
• Apply different reorder, count and review policies by class.
• Flag critical C items manually.
• Schedule the next review date (every six months, or before peak season).

For the overall framework, see the retail inventory management guide. Product categories, brands and cost prices are managed in inventory management.

Frequently asked questions

Related guides

• Reorder point formula
• Inventory cycle counting
• Retail inventory management guide
• Retail shrinkage prevention

Sources and further reading

• Zoho Inventory — ABC analysis in inventory management
• DCL Logistics — ABC analysis: meaning, advantages and challenges
• Cleverence — What is ABC analysis of inventory?