Choosing your service level to optimize inventory

Choosing your service level to optimize inventory


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Salescast determines the optimal reorder point as a function of expected demand, lead time and service level. Frequently, new users are confronted for the first time with the notion of Service Level. The following article gives a short introduction to the topic and guidance on how to set appropriate service levels.

Definition: Service Level expresses the probability of being able to service incoming orders (or demand) within a reference period without delay from stock on hand.

The implicit assumption within this statement: It is not economic to always be able to service an order from stock on hand. Deciding on the right service level for a certain product is essentially balancing inventory costs vs. the cost of a stock out. Service level is therefore an important variable for calculating the appropriate safety stock; the higher the desired service level, the more safety stock needs to be held.

Unfortunately, the cost functions describing the problem are extremely very business specific. While inventory costs can often be determined rather easily, the cost of stock outs are much more complicated to determine. A customer that does not find the product in store might either choose an alternative that is in store, postpone the purchase to a later date or buy at the competition. In grocery retail for example, out-of-shelf situations of certain must have products are known to drive customers out of the store, taking their business to a competitor.

As this example illustrates, the associated cost functions are not only business, but product specific. When considering that most manufacturers and retailers are dealing with hundreds to hundreds of thousands of products, it becomes obvious that an overly scientific approach is not advisable nor feasible.

The good news is that in practice it mostly proves fully sufficient to work with a simple framework that can be fine-tuned over time.

How to get started

Service levels are considered by many retailers as part of their core IP, and tightly guarded. Nevertheless, some ballpark figures should provide a good starting point: A typical service level in retail is 95%, with very high priority items reaching 98% or even 99%. We have seen a number of customers successfully choosing a very pragmatic approach when setting service level at a uniform 95% starting point, to subsequently improving and adjusting these to their needs.

It is important to understand the relationship between service level and safety stock. Graph 1 illustrates the relationship. Dividing by 2 the distance to 100% multiplies the safety stock by 2. For example, if an increase in service level from 95% to 97.5% will double the necessary safety stock. Service Levels approaching 100% get extremely expensive very fast, and a service level of 100% is the mathematical equivalent to infinite safety stock.

Graph 1: Relationship safety stock vs. service level

Graph 1: Relationship safety stock vs. service level


Choosing categories

It is in our experience fully sufficient to differentiate between 3-5 service level categories that cover the product portfolio from must have items to the lowest priority items. As an example, we chose a three-value system:

  • High: 98%
  • Medium: 95%
  • Low: 90%

Categorizing products

Product rankings allow a structured and sensible way to allocate products to the categories we defined previously. Rankings that are often used solely or in combination include turnover, profitability, number of orders, COGS (cost of goods sold).

Example product ranking by turnover

  • Top 80% of turnover: High service level
  • Next 15% of turnover: Medium service level
  • Next 5% of turnover: Low service level

Example product ranking by gross margin contribution

  • Top 80% of gross margin: High service level
  • Next 15% of gross margin: Medium service level
  • Next 5% of gross margin: Low service level

Once the categories have been defined and service levels have been assigned, Salescast will determine the reorder point (including safety stock levels) as a function of theses values. We often see that a lot of potential for inventory reduction is not only leveraged by the accuracy of our forecast, but also by the more sophisticated method and frequent update of the service level.

Who still feels rather insecure regarding the correct service level to be entered into Salescast should remember that it is not important, and also rather unrealistic, to have the perfectly fine-tuned service levels right out of the gates. What is important is that the new attention to this notion, in combination with Salescast forecasts and reorder point analysis, will improve the status quo with a high certainty.

Further reading


Choosing Salescast


Getting started


User guide


What people say

Classical solutions require too much manpower and don't scale correctly over hundreds of thousands of products. Lokad and Windows Azure were exactly the solution my business needed. Pierre-Noël Luiggi, CEO of Oscaro
The Lokad forecasting solution allows us to precisely forecast our sales and to optimize our inventory accordingly. The result is there: we are maintaining a 99% customer satisfaction level and deliver food that is often fresher than what can be found at local pet stores. Anthony Holloway, CEO at k9cuisine
Lokad improved the accuracy of our planning process significantly. The immediate impact was a stock reduction of almost 1 million € at a monthly cost of 150€. It was almost frightening to see our inventory levels getting so low! But what impressed me most is the ease of implementation and use. The integration was painless, and now it takes only a the click of a button and within 10 minutes I receive my forecast. The time saving for me is significant. Thomas Brémont, Head of Supply Chain Bizline

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