When companies are growing they typically do not spend too much time thinking about inventory or other efficiencies, but are busy making sure they have enough products to satisfy demand. When business is slower or in transition there is more focus on cost—starting from the most visible: excess inventory.
The typical approach to improving inventory performance is to
Try to improve forecast and demand planning
Introduce a Sales and Operations Planning (S&OP) or Sales and Inventory Operations Planning (SIOP) process to better coordinate sales, marketing, finance and manufacturing
Perform ABC analysis on the products to identify fast movers and slow movers—nowadays this would more likely be a supply chain segmentation study.
Introduce supply chain visibility and planning capabilities
Offer discounts or promotions, particularly Business to Consumer (B2C) companies
All these steps are useful and can produce results. However, dealing with excess inventory without understanding the cause is taking care of the symptom instead of trying to cure the disease. Understanding the inventory drivers is the key to finding success in inventory management.
What drives inventory in the supply chain?
Service level – what is the commitment internally and to the customer? Higher service level requires more inventory than lower? What do you really need to succeed? What are the desired transportation modes? Are you expediting shipments?
Lead times – inventory is maintained to cover for the wait to replenish it.
Demand and variability – of course forecast and variability impact inventory - the higher the variability the more inventory is needed.
Reorder frequency and quantity
Transportation times and variability
Inventory positioning across the supply chain – where you keep the inventory in the supply chain can make a big difference.
Risk in the system – how much inventory do you need to maintain to mitigate the possible high financial impact of unexpected failures either internal or external?
Given the complexity of these factors and the various trade-offs it is hard to tell where to start. Therefore, modeling the end to end supply chain and using multi-echelon inventory optimization allows to quantify inventory opportunities, the drivers of these opportunities and create a common platform for management to try out new strategies that improve supply chain performance.
In addition, understanding the important risks in the system, those with a high risk exposure index can help identify where inventory needs to be used to protect the company from unforeseen events.
While multi-echelon inventory optimization can be a valuable tool for an organization, it is not without its challenges, and often it is purchased as a software solution without an understanding of what goes into it and what to do with the output from the tool. We run into this often, and the most common questions that arise are:
We will still receive some benefits of inventory reduction without all the effort of doing a complex end to end analysis. Why aren’t the local efforts we are doing to optimize inventory enough?
We have trouble with our data—both accessing it as well as trusting its quality. In addition these models require information that we may not even be tracking. Can we trust the results of studies with data that is inaccurate and incomplete?
How do we get buy-in from executives across the supply chain for this process?
The first question can be answered in two ways. First, the improvements you can achieve locally are more limited and not transformational. If you are looking to achieve significant results, you need to look at the entire supply chain. We were able to measure this when we worked with Schneider Electric and compared the results of the Single Echelon Inventory Optimization (SEIO) work to the Multi-Echelon Inventory Optimization (MEIO)
The second question is one that comes up quite often. Our approach is that you are already making important operations decisions and they will definitely improve if they are more data-driven. Therefore, alongside projects to improve data quality you should use what you have and at the same time gain better understanding of the gaps. We addressed this issue at length in Can you trust supply chain analytics with imperfect data?
Finally, buy-in from executives is crucial to the success of most initiatives, and MEIO is no different. We find that it is best to bring executives along on the journey rather than trying to conduct MEIO and then present only the output. With our clients, we conduct workshops at the beginning of a project and at key milestones along the way to be sure that executives are familiar with the process and what the output of the tool will provide them in the way of inventory reductions and risk avoidance. This is an imperative step in the process, and should not be skipped over, otherwise a lot of time and effort can end up wasted.
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