Inventory Turnover Ratio

Inventory turnover is an efficiency ratio which calculates the number of times per period a business sells and replaces its entire batch of inventories. It is the ratio of cost of goods sold by a business during an accounting period to the average inventories of the business during the period.

Dividing the total cost of inventories sold during a period (which equals cost of goods sold) by the cost of average inventories balance maintained by a business gives us dollars of sales made per dollar of cash tied up in inventories.


Inventory turnover ratio is calculated using the following formula:

Inventory Turnover =Cost of Goods Sold
Average Inventories

Cost of goods sold = Beginning Inventories + Cost of Goods Manufactured – Ending Inventories

Cost of goods sold figure is reported on the income statement.

Average Inventories =Beginning Inventories + Ending Inventories

The values of beginning and ending inventories appear on a business’ balance sheets at the start and at the end of the accounting period.

Alternatively, inventory turnover can be calculated based on the closing inventories balance where the opening inventories balance is not available or where the inventories balance has not changed significantly over the period.

Inventory turnover ratio is also an input in calculation of days inventories outstanding (DIO).


Inventory turnover ratio is used to assess how efficiently a business is managing its inventories.

In general, a high inventory turnover indicates efficient operations. A low inventory turnover compared to the industry average and competitors means poor inventories management. It may be an indication of either a slow-down in demand or over-stocking of inventories. Overstocking poses risk of obsolescence and results in increased inventory holding costs.

However, a very high value of this ratio may result in stock-out costs, i.e. when a business is not able to meet sales demand due to non-availability of inventories.

Inventory turnover is a very industry-specific ratio. Businesses which trade perishable goods have very higher turnover compared to those dealing in durables. Hence a comparison would only be fair if made between businesses in the same industry. It is very useful in conducting a trend analysis.


Example 1: Calculate inventory turnover and days inventories outstanding for ABC, Inc. based on the information given below:

Opening inventories$25,000
Closing inventories$30,000
Cost of goods manufactured$245,000


Cost of goods sold = $25,000 + $245,000 – $30,000 = $240,000

Average inventories = ($25,000 + $30,000) ÷ 2 = $25,500

Inventory turnover ratio = $240,000 ÷ $27,500 = 8.73

Days inventories outstanding = 365 ÷ 8.73 = 41.8

Example 2: Analyze the inventories turnover ratio for Wal-Mart Stores Inc. (NYSE: WMT), Costco Wholesale Corporation (NASDAQ: COST), Caterpillar Inc. (NYSE: CAT) and Deere & Company (NYSE: DE) based on their inventory turnover ratio (as obtained from Morningstar) for the financial year 2012, 2013 and 2014.

Deere & Co.


This example illustrates the fact that ratio analysis is useful when companies’ ratios are compared with other firms in the same industry or across different periods for a single company.

Inventory turnover ratio of Walmart is comparable with Costco but not with Caterpillar or Deere. Walmart & Costco are retailers of general merchandise while Caterpillar & Deere are manufacturers of heavy machinery. Retailers are required to hold very large volume of inventories, a major portion of which is perishable, which justifies their higher inventory turnover ratio as compared to manufacturers of heavy machinery.

Walmart has been more efficient in its inventories management than Costco. However, Costco’s trend of improvement over the three-year period is more pronounced.

Caterpillar is better than Deere & Co. in inventories management as evident from their inventory turnover ratio. However, their relative trend in inventory turnover ratio corresponds with each other. Inventory turnover ratio for both decreased in 2013 and then increased again in 2014. Such trends are attributable to the overall economic growth expectations.

Written by Irfanullah Jan