Inventory Turnover

Inventory turnover is the number of times average inventory (typically stated in dollars) is sold and replace over a specified period of time (typically one year).

 

For example, if your firm has $11 million in average on-hand inventory, and average inventory-related costs of sales is $2.66 million per month, then inventory turnover would be calculated as $11 million / $2.66 million, or 4.1 times per year.

 

While this number has some value in terms of financial averages and, typically, a higher inventory turnover ratio is better, it provides supply chain managers with almost no guidance for individual SKU management.

 

Inventory turnover ratios can be calculated on a SKU-location basis, however, and this provides additional information. It is likely that some items will have very high turnover ratios, while others will have very low turnover ratios.

 

Glenday sieve analyses over a large number of enterprises strongly suggest high inventory turnover ratios will be found on only about six percent (6%) of SKUs in any location. On the other end of the spectrum, nearly 50 percent of SKUs will have relatively low turnover ratios and together account for only five percent (5%) of unit sales. The average inventory turnover ratio, therefore, provides very little guidance to the inventory or supply chain manager.

 

SKU velocity

While inventory turnover ratios are intended to provide guidance on SKU velocity, it is of little practical use because it provides no clear way to connect SKU management decisions and parameters with the resulting velocity.

 

Demand-driven supply chain theory suggests that there is a better way. In the DDOM (demand drive operating model), SKU velocity is linked directly to SKU-specific management profile decisions through a metric called the flow index.

 

The flow index for any SKU-location (stocking position) is calculated within the DDOM as the size of the GREEN ZONE divided by the ADU (average daily usage). For example, a SKU-location with a GREEN ZONE of 70 units and an ADU of 10 would have a flow index of 7.0 (70 / 10).

 

Calculating the size of the GREEN ZONE

Going into the full details of how to calculate the full DDOM (or DDMRP) buffer size--with its RED ZONE, YELLOW ZONE and GREEN ZONE--is beyond the scope of this article. (If you'd like the full details, please read DDMRP - Demand Driven Requirements Planning by Ptak and Smith.) However, we will talk about the three typical options for sizing the GREEN ZONE in a stock buffer. They are:

 

  1. Using a fixed order cycle - Sometimes the expected number of days between replenishment orders is fixed. This may be due to a repetitive production cycle (read: Lean RFS - Repetitive Flexible Supply by Ian Glenday and Rick Sather, but don't confuse the RFS "green stream" with the DDOM "green zone"), or for any number of other valid reasons. When the order cycle is fixed, then the size of the GREEN ZONE is calculated simply as ADU * Order Cycle Days.

    For example, if Order Cycle Days = 7, and ADU = 10, then the size of the GREEN ZONE = 10 * 7 = 70.

  2. Applying a Lead Time Factor - For a SKU-location with an ADU of 7, a decoupled lead-time (LT) of 12 days, and a Lead Time Factor (LTF) of 50 percent (indicating coverage of 50 percent of lead-time), the size of the GREEN ZONE would be calculated as ADU * LT * LTF = 10.0 * 12 * 0.50 = 60 units.

  3. Use of a Minimum Order Quantity - If a minimum order quantity (MOQ) is imposed for any reason, then calculation of the GREEN ZONE is always determined by the maximum of any other method or the MOQ. For example, if the MOQ for our SKU-location is 85, then the GREEN ZONE would be set to 85, regardless of the 60 units calculated using a Lead Time Factor, or the 70 units calculated by the imposed order cycle.

    However, if the MOQ were 50 units, then either of the other methods might be applied, leading to a GREEN ZONE of 70 or 60 units instead.

 

Back to the FLOW INDEX

So, for the SKU-location used in our example above, the FLOW INDEX would be calculated as

  1. 70 / 10 = 7.0 for the fixed order cycle method
  2. 60 / 10 = 6.0 for the LTF method
  3. 85 / 10 = 8.5 for the MOQ method (where MOQ = 85 units)

 

Unlike the turnover ratio where higher is better, with the FLOW INDEX a lower value is better.

 

Therefore, if you can serve a higher ADU with the same amount of inventory, your FLOW INDEX improves (goes down). For example, if your ADU increases from 10 to 11.3 units, the FLOW INDEX calculations above change to

  1. 70/11.3 = 6.2
  2. 60 / 11.3 = 5.3
  3. 85 / 11.3 = 7.5

 

With these calculations, supply chain managers can immediately see the working relationships between their stocking calculations and FLOW. If order cycles can be reduced, or if lead times and lead time risk factors can be reduced, or if minimum order quantities can be reduced, FLOW INDEXES decline. And, provided the net flow is meeting customer demand, improvement is the result.

 

By the way, you might have noticed that the FLOW INDEX is actual "days" and represents the frequency of replenishment orders (not lead-time). Without going into the DDOM details, with a GREEN ZONE of 60 and ADU of 11.3, you should be placing a replenishment order about every 5.3 days. However, with a GREEN ZONE of 85 (MOQ) and an ADU of 11.3, you would be placing a replenishment supply order about every 7.5 days.

 

Linking actions with metrics

I think you can see that linking specific actions to the metrics is easier using the DDOM's FLOW INDEX method, than when using the inventory turnover ratio method.

 

While the inventory turnover ratio is linked to accounting measures and controls (dollars in inventory and cost of goods sold), the FLOW INDEX is linked directly to decisions the supply chain manager considers every day: order cycles, average daily usage, minimum order quantities, and lead times. The supply chain manager or inventory manager is working in familiar territory to drive daily improvement actions.

 

If you'd like to experience the difference of supply chain management in the demand-driven operating model, we can help.

 

We would be delighted to have you leave your comments below. However, if you'd prefer, feel free to contact us directly, as well.

 

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