This session we will use Little's law to define a new variable that we will call inventory turns. Inventory turns is based on a somewhat funny view to an operation. Think about an operation as a big, black box, where you have individual dollar bills go into the operation. And then with some delays kind of being spit out of the operation. We can then for every individual dollar bill compute a really odd number, and with the amount of time that, that dollar bill has spent inside the operation. This is really the intuition behind the concept of inventory turns. Once we have defined inventory turns, we can also compute a cost advantage, that a company has if it's turning its inventory faster than its competitors. Here's a comparison between computer companies, Dell and Compaq. I know that Compaq is long gone from the landscape, But for the sake of comparison, I've picked the data for Dell and Compaq in the year that Compaq ended up merging with HP. And we'll give you some updated data about Dell in just a moment. Now, look at these computations. We want to look at how many dollar bills flow throw Dell per unit of time, in this case, per year, And then apply [inaudible]. The number of dollar bills in the organization is simply 391 million dollars. The flow of dollar bills through the operation is the cost. The cost of goods sold, which is twenty billion. 20,000 million. This suggests that, if we solve for t, the average dollar bill spent, 391 divided by 20,000. And they're just expressed in years in the operation. If we multiply this with 365 days in a year, we're gonna get roughly seven days as the time that a dollar bill spends within Dell. Now, do the similar calculation for the case of Compaq. The inventory here, is $2,000,000,000. The flow rate is slightly larger, 25. 263 times T. And if you solve for T, you would get roughly 29 days. So while a dollar has to only spend 7 days at Dell, it will spend four times longer, 29 days at Compaq. Instead of saying that they are, keeps your dollar bills for 7 days inside the operation, we can refer to one over T as the inventory turns. If you're keeping your dollar bills for 7 days, given that there are 52 times 7 days In the year, you're turning your inventory 52 times in the year. This is the concept of inventory turns, one over T in the above equation is simply COST divided by INVENTORY. We see that Dell turns its inventory roughly 51 times in the year, but Compaq is turning it roughly twelve and a little bit, 12.6 times in the year. Now when you do these calculations, be careful. Use cost NOT revenue to do these flow unit analysis because the margins that the companies make have really no impact on these calculations. How did the inventory returns change over the years at Dell? In the early years you saw that Dell is roughly making 10 inventory turns per year. Over the late 90s Dell perfected its business model, And together with a strong tech bubble was able to turn its inventory way faster than 50 times per year. In their best state, they're almost actually getting their money from the customers before they even had to pay their suppliers, leading to negative working capital. Here in the 2001 phase, you see the birth of the tech problem. You see the big decrease in inventory turns as the bubble bursts at around 2001. They are restored in inventory level subsequently. The more recent downfall of the inventory turns has to change, has to do with the change in Dell's business model. More recently, Dell has emphasized making many other things than made-to-order computers, including televisions, PDAs and other things. These things oftentimes are held at Dell's inventory, which has hurt Dell's inventory turns. To see the economic importance of inventory turns, consider the following data. This is data compiled by my colleagues, Gowell, Fisher and Ramon which shows the gross margin and the inventory turns for large, publicly traded US retailers. To understand the economic implications of inventory turns, you have to first understand the concept of inventory cost. Ask yourself how much does it cost a retailer to hold one item. In inventory for an entire year. At a minimum we have to finance that item, and most large public companies are incurring capital costs of roughly 10 percent. But you have to also store the inventory, and especially if it's a computer or a fast-living item, you also have to adjust the cost of in, obsolescence. Say, for the sake of arguments, these costs Capital, storage, and obsolescence together are 30 percent for the players to show in here in this data. Now let's pick two retailers that are competing head-to-head in roughly the same retail segment, Retailer B and Retailer A. Now, notice that neither of these retailers is holding its inventory for an entire year, so neither of them is having to pay for 30%. But, you notice that retailer A, which is turning its inventory 4 times per year. We have to divide the 30 percent by the four turns, and we see that for everything that they sell, they incur a 75.5 percent as an inventory cost. You can think of this as l-, something like a tax rate that we have to pay to the gods of inventory. You combine, compare this with the data from retailer B. Retailer B turns its inventory faster. And it allows them to only pay 3.75%. Now this difference between retailer A and retailer B, 3.75 percent, is the difference between the two of them, is a dramatic number. This is an industry where typically net variance range between 1 percent and 2 percent. So simply by turning the inventory faster we are gaining a dramatic competitive advantage. Holding inventory is expensive. Unless you're holding French red wine in inventory, that might gain in value as it gets older, most of the things lose value. At the same time, you have to finance the inventory, which takes working capital. For this reason, inventory transit is a powerful metric to capture how well you're using your working capital. The margin advantage that you might get from faster transit looks initially small. However, if you compare it to the net margin of a business. In most businesses, fast returns has a very significant impact on the bottom
