Most businesses would put high customer service as one of their top business priorities. While there are many different things that make up the overall customer experience, one of the key performance indicators (KPIs) that companies measure is the timely delivery of goods to the customer. In safety stock calculations, this is typically an input called the service level. In this blog post, I will explore this a bit.

Imagine a B2C business such as a retailer. The store shelves at this business are re-stocked every night without fail. They are never re-stocked during the day. The customers can walk into the store any time, walk up to the appropriate shelf and pick up the products that they want. Every night, delivery trucks from the original manufacturers show up to re-stock the shelf in what is often described as a direct store delivery (DSD) model.

In this situation, the product is unavailable to a customer whenever a shelf is empty. This is also called a stock out. When this happens, the customer either:

  • Buys a substitute product and all other products on his wish list.
  • Buys all the other products on his wish list and then goes to another store to buy the item that was not in stock
  • Goes home to return another day
  • Goes to another store with his entire order

All of the above are examples of customers’ action in response to one fact: the business failed to meet his needs.

In terms of a customer service metric, that is a negative score. However, in a retail situation, the retailer might not even know that this had happened or whether this happened to one or two or ten customers on that day. It would also not know how much of the demand was not satisfied; after all, each buyer might have been looking for more than one unit of that item. They would also not know exactly when the stock out happened. Even if they know by walking the aisles, the only time this will be recorded in a system is when the person doing the restocking notices the empty shelf and records the stock out. If in a year, this happens 30 times, then the percent of days with a stock out is 30/365 = 8%.

In this type of business, the service level should be measured as cycle service level, i.e., the percent of time a stock out happened for a particular product. In this case, the business should deploy safety stock techniques that try to reduce the occurrence of these stock outs. Here is a link to a Wikipedia post on how to calculate cycle service level based safety stocks. This method calculates safety stock based on demand and supply variability.

As one can imagine, this type of service level calculation is quite severe. For example, a product might have emptied five minutes before the restocking operation and it would still get a stock out for that day, even if no customer walked up to that shelf in those five minutes but in the absence of a continuous review system there really is no other choice.

Next post, I will talk about a different way to think of service level: the fill rate service level. (Update: Click the link to read part 2: Cycle Service Level Versus Fill Rate Service Level – Part Two)

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