How can safety stocks be optimized?
In our interview on the topic “What can we expect in the first half of 2024?”, Dr. Dominik Hollmann talks about the development of our inventory planning solution, among other things. We talked to Katharina Klerx, Analytics Consultant, about exciting details.
Thank you for taking the time to answer a few questions about inventory management. You are involved in this exciting project as a product owner. What exactly is your role?
As a Product Owner, one of my tasks is to recognize the customer’s needs and ensure that these are implemented accordingly in the product. In other words, I am the person in the team who is closest to the customer and understands which topics are currently acute and which features we need to prioritize.
Speaking of acute topics, what are the most pressing problems in optimizing warehousing at the moment?
Determining optimal safety stocks is currently an important issue. These are often still determined on the basis of “gut instinct” or experience and are not evaluated. Since corona has caused such disruption to supply chains, this issue has become even more pressing than before. During this time, many companies have filled their warehouses out of fear of supply chain collapses and now want to know how much they really need. Although full warehouses provide security, they also tie up a lot of capital that could be better invested elsewhere.
To be honest, it doesn’t sound that complicated. As an outsider, I would expect you to be able to do it by a rule of thumb?!
Sure, if you have few materials and preliminary products, it’s actually manageable. Then you can get by quite well with empirical values. However, we are talking about companies that have to deal with over 1,000 products at 100 locations, i.e. up to 100,000 location-product combinations. Distinguishing normal demand from outliers and acting accordingly is virtually impossible. Handling such exceptional cases in particular is not easy to do manually.
We have also found that safety stocks are often increased when there are problems, for example because a delivery has failed or there has been a sudden peak in demand. Afterwards, however, it is often not analyzed what the reason for the problems was and whether the higher safety stock is necessary, but simply the higher safety stock is maintained. This means that they continue to grow over the years. In most cases, it is worth taking a critical look at the level.
That sounds like a lot of information coming together. What data do you need to be able to calculate safety stocks?
Basically, it doesn’t take much to answer this question. Firstly, we need demand forecasts and information about their reliability. After all, how much is to be produced is of course a decisive criterion for safety stocks.
The second important aspect is the desired service level, i.e. how many orders are to be fulfilled. A customer who wants to fulfill 95% of his orders naturally requires different safety stocks than a customer whose target is only 80%. The desired service level can, for example, come from contracts that guarantee a certain level of service. But production downtime can also lead to insane costs and loss of sales, which you would like to avoid.
The last thing missing is an assessment of the reliability of the supply chain. Those who can rely 100% on punctual delivery can afford to keep lower safety stocks.
This information is then fed into the model and the optimization calculates the best possible safety stock levels.
Infobox service level
With the service level, a distinction can be made between the α service level and the β service level. The α service level considers whether all orders can be fulfilled within a time interval – for example 1 week – without a stockout occurring. Only then is this week considered completed. For example, the aim is to fulfill all orders in 9 out of 10 weeks. The β service level is calculated as a percentage of how many orders are completed within a time interval. For example, the objective here is to fulfill 95% of all orders within one year.
And then you have the safety stocks issued and you’re done?
If you really only want to calculate the safety stocks, you’re already done. However, there are other exciting questions that can be answered on the basis of this data. One example would be the downsizing of the warehouse. A company has rented storage space and would like to know how many orders it could no longer fulfill if the warehouse were to be downsized in order to save on rental costs. Is it worth foregoing these orders but saving on storage costs? For this purpose, the costs of the missing quantities are quantified and compared with the costs that would be incurred if the missing quantities were to be avoided.
You can also analyze where there are weak points in the supply chain that have a major impact on the service level. Or calculate what consequences a change of supplier would have: How will my delivery readiness level change if I replace supplier A with supplier B? How will my safety stocks and therefore my storage costs change?
The data offers an incredible number of possibilities for analysis and often provides insights that were not previously expected. And if they are already available, why not use them?
Finally, a more personal question. As a product owner, what is your favorite feature of OPTANO Inventory Optimization?
Everything, of course! (laughs) But if I had to choose just one, I would say dashboards. With optimization projects in general, and not just with inventory management, you always need a lot of data, usually in the form of tables. Huge tables. And of course they are not at all clear. That’s why it’s important for us to present the findings that come out of the optimization process in a way that users can understand directly. Because only then can they be put to good use.
Thank you very much, Katharina, for taking the time for this interview.
There is potential for optimization in almost every company. But where is the best place to start? Where can the quickest or greatest savings be made? We offer a workshop to get to the bottom of precisely these questions. Find out the details in our factsheet.
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