What Drives Inventory in Your Supply Chain?

To fully realize inventory savings you also need to analyze the interplay between the location where the inventory is maintained as you may be losing on risk pooling and other potential savings by looking at inventory in one location.


One of the largest, if not the largest, investment of many businesses is inventory.

This includes raw material, components, finished goods and spare parts. Inventory protects the business from fluctuations related to the order cycle, called cycle stock and changes in expected demand and lead times called safety stock.

Maintaining the right inventory levels and understanding the tradeoffs requires knowledge of what drives inventory.

In the following, we will go into the details of how cycle stock and safety stock are calculated and therefore what drives the levels of inventory required.

Cycle Stock
The portion of an inventory which companies cycle through to satisfy market demand for a specific replenishment period is called cycle stock.

Cycle stock level depends on a product’s order frequency and demand profile.

The equation for calculating average cycle stock is as follows:

Where

  • RP = Replenishment Period
  • D = Average Demand
  • RP(D) = Average Demand during Reorder Period

It is not difficult to see that cycle stock is driven by demand and replenishment period. Cycle stock will rise when the demand and reorder period increase.

For example, if a product has an average demand of 10 units per business day and is replenished every 5 business days, then the average cycle stock level is 25 units, half of the average demand during the reorder period.

If product is replenished every business day, then the average cycle stock level is reduced to 5 units. The key to cycle stock reduction is to reduce the replenishment period.

Safety Stock
Safety stock, as the name suggests, is the buffer inventory kept to prevent stock outs arising due to misalignment of actual and forecasted demand, utilization and delivery time shortfalls.

In order to understand the proper levels of safety stock, it is important to understand the drivers.

The general equation for safety stock, assuming both lead time and demand are normally distributed, is as follows:

Where

  • D = Average Demand
  • StdD = Standard Deviation of the Demand
  • LT=Average Lead time
  • StdLT = Standard Deviation of the Lead Time

 

  1. Demand Variability - occurs when actual demand deviates from forecast demand. Naturally, the way to combat fluctuations is to hold more inventory. The first factor affecting that amount of inventory is demand variability. The amount of inventory needed due to demand variability is the product of square root of the average lead-time and the standard deviation of demand. This portion of the equation covers the demand fluctuations between the order date and receipt date considering the lead time and the demand that might occur.
  2. Lead time Variability - drives the safety stock similar to the demand variability where in the amount of inventory needed to mitigate the effect of variation of time between order date and ship date is calculated by the product of Average demand during that period and lead time standard variation.
  3. Service Level - defined as the probability of not having stock-outs. It is used in the safety stock equation in terms of its Z score. In statistical terms, the Z score refers to the number of standard deviations above mean that a parameter can fluctuate. Here, with respect to safety stock, Z(service level) is the number of standard deviations above mean demand needed to protect you from having stock-outs.


Safety stock is not needed when the fluctuations are happening below the mean demand. That is because the fluctuations will be taken care of by cycle stock when the demand moves between zero and mean demand. After the mean demand, safety stock is needed to combat fluctuations

To understand this, we need to look at how service level based on the Z-Score drives inventory. Service levels and Z-scores have a non-linear relationship. Hence, higher service levels incur highly disproportionate safety stock. Imagine that no safety stock is carried.

In this situation, the Z score is zero. Even then based on the Safety Stock equation, there will be enough inventory to meet demand in 50 percent of the time. If the Z-score equals 1, the safety stock will protect against one standard deviation; there will be enough inventory 84 percent of the time. But if you want to have a service level of 98%,Then you have to hold two times the safety stock as in the case of 84% Service Level.

It is always a managerial decision to balance between prevention of stock outs and customer service. Based on the organization’s culture, optimum safety stock is calculated using the above mentioned equation by choosing a proper service level so as to balance inventory costs and customer service. However, it is also possible using advanced optimization techniques to move the tradeoff curve and improve both inventory levels and service levels.

As you can see, calculating inventory for one product on one level is already quite complex. But to fully realize inventory savings you also need to analyze the interplay between the location where the inventory is maintained as you may be losing on risk pooling and other potential savings by looking at inventory in one location.

In fact, we recently worked with Schneider Electric on calculating the difference, With traditional single location methods they could save 11% but with multi-echelon inventory optimization they could save 30%. These savings are achieved while still maintaining the same service levels.

Related: Inventory Management - Four Common Pitfalls of Safety Stock


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OPS Rules is a consulting practice begun by a team of specialists who have created lasting improvement and increased value at top global enterprises and government operations. From this vantage point OPS Rules sees operational processes that have been leaned out to a point where they are fragile and cannot perform well in situations that require subject matter expertise. Continued emphasis on lean, six-sigma and other traditional continuous improvement methodologies won’t create or even maintain a competitive advantage.



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