In a real sense, I think supply chain management, at its core, is about the efficient and effective management of inventory. Logistics is about processes and skills in moving inventory; supply chain is about optimally managing supply and demand across the full plan, buy, make, move, deliver and return processes, but in the end, those processes and the skill with which they are executed largely involves having the right level of inventory where its needed – at lowest total cost.
Since I started my career, however, I think the focus on inventory has become even greater, especially for public companies. I trace this, in part, to the incredible 2001 announcement by network equipment giant Cisco that it was going to take a charge of $2.25 billion for excess inventories. That caught the Wall Street analysts completely by surprise, and ever since, most have paid a lot more attention to a company’s inventory levels than they used to.
That’s especially true in any industry with rapid product lifecycles, such as the high tech and fashion sectors, although the reality is that today that includes an increasing number of industries and companies. Even if other company had been caught with as much excess inventory versus demand as Cisco did in 2001 , it would not have had to take that type of write down.
Why? Because, to the best of my knowledge, some other products sells don’t quickly become obsoleted by the next round of new product development introductions, as they do to companies like Cisco. Time puts a more severe inventory penalty on Cisco than it does on other company.
Return on equity or return on assets , are other common way to determine the company performance ,but Companies can resort to financial strategies to artificially maintain a healthy ROE — for a while — and hide deteriorating performance in business fundamentals.
to analyze long-term profitability trends across all companies. Inventory levels avoids the potential distortions created by financial strategies like those mentioned above. As the case of Cisco demonstrated.
So, just how do we measure inventory performance?
The traditional approach for most of us has been “inventory turns.” the inventory turn metric “Measures how many times a company’s inventory has been sold (turned over) during a period of time.” It equals “the cost of goods sold, divided by the average inventory level of inventory on hand.”
So, if a company has cost of goods sold of $100 Million, and average inventory levels of $10 million, it has 10 turns of that inventory per year.
But as usual, there are complications.
First, just how is the “average inventory level” determined? Most commonly, in my experience, you take the starting and ending inventory levels for some period, add them together, and divide by two. In some cases, companies simply use the end of the period number. In either case, it can lead to issues with companies purging inventory at the end of a period, either due to sales patterns or tax efficiencies. If so, it may somewhat muddy the turn numbers.
Today WMS and ERP systems can give you a true average inventory number for a period, but I am not sure how many companies use that in their turn metrics.
Some companies may determine inventory turns using sales revenue and retail price to value inventory. I could even argue that there is merit in using “units” as the correct unit of measure, as it would remove some of the noise that can creep in as financial adjustments are made to inventory levels by the accountants. For example, back to the Cisco scenario, its current inventory level would have suddenly been reduced by $2.25 billion on the books after the write down occurred.
A related metric is “Days Inventory Outstanding” or DIO.
You calculate DIO by taking a company’s inventory levels for a period, dividing by total revenue, and then multiplying by the number of days in the period. This measures how many days of sales a company on average holds in inventory. Finance types like DIO because it is the cousin of such metrics as “Days Receivables Outstanding” (DRO) that measures how effective a company is in collecting on its invoices.
So, for example, if a company has $200 million in sales for the year, and average inventory levels of $10 million, then $10 million in inventory, divided by $200 million in sales, times 365 days in a year, equals average DIO of 18.5.
This is, in a sense (though not completely), the opposite of inventory turns. A company with a high level of turns will have a low DIO, and vice-versa.
One thing I don’t like about DIO, however, is that it mixes, in a sense, units of measures – cost for inventory and actual revenues for sales. This means that the effectiveness of the purchasing and/or manufacturing organization comes into play. If that same company was able to reduce the cost of what it paid for its goods or to make them more efficiently, its DIO would go down, not because of improved inventory management, but simply because the numerator of the equation was pushed lower by cost efficiencies.
But what none of these metrics really gets to is the real impact of inventory performance on working capital, the bottom line, and free cash flow. However those metrics as inventory levels help to analyze long-term profitability trends across all companies. Inventory levels avoids the potential distortions created by financial strategies.
