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Client case – Dynamic safety stock adjustments

Our client is a pharmaceutical company with several billion Euros of inventory. They already use GenLots on one of their sites to do a dynamic lot sizing in their supply planning. This got them a large benefit. But there was the feeling that the current supply planning was dependent on a correct parametrization of safety stock levels. To optimize those as well and leverage GenLots further, they have approached us.

The challenge

The service level is best explained with an example. If you have a 90% service level, this means that your client (or in supply planning the production) will be out of requested material 10% of the time. As pharma is a very high value-add activity, production stops are extremely costly and therefore unacceptable. That means that the target service level of our customer is a very high 99.9%.

This service level needs very high safety stocks to absorb delayed suppliers, forecast inaccuracies, batches which don’t pass quality inspection and many more unforeseen events. The following factors added to the problem at our client:

  • Forecasts from sales and consequently production vary considerably in a bi-weekly rhythm
  • As suppliers have to first produce the specialized ingredients and then ship them around the world, lead times can be up to 18 months. This means that an out-of-stock event takes a long time to fix
  • The company direction has given strict instructions to lower inventory levels, which were identified as an important cost driver. That means that high safety stocks run counter to one of the Key KPIs of the planner
  • Safety stock levels are set by hand in a manual process and analysed/modified infrequently. Often only after a problem has occurred already

Our approach

GenLots has leveraged its existing safety stock optimizer and simulator to create a new offering to our client at no additional cost.

Our approach has been the following:

  1. Agree on a custom formula for the calculation of safety stocks based on target service level, lead time variability and demand variability
  2. Use this to calculate the service levels that the current safety stocks imply and display this key number to the planner in our dashboard
  3. Leverage our simulator to check how to change safety stocks to guarantee a 99.9% service level and the projected impact on inventories. Show what trade-offs have to be made on the service level, in order to keep inventories constant or lower them
  4. Send a weekly email with the products where safety stocks should be adapted to the planners


Thanks to the approach above, planners now can identify the risk of too low safety stocks or the savings opportunity of too high safety stocks easily and early. This leads to a significant reduction in stock outs while lowering inventory at the same time. The financial impact of a decision is immediately visible.

What’s next

Next steps are to further automate the process. The customer is switching the SAP system to the more modern S4/HANA. As we are a certified SAP partner, we will therefore have more possibilities of writing back recommendations directly into the ERP. This will change our interface for faster decision-making by the planner and help our client to react even more quickly to changes in demand and supply.

Client cases