Data science helps to solve complex supply chain management challenges. In our Data2Move Research Stories, you can find out how our students tackle these challenges. This time, we feature Lisa van Lierop’s Master thesis research at Hilti AG in Liechtenstein. Hilti AG is a multinational company that develops, manufactures, and markets products and services for the construction, building maintenance and energy sector.
Where it started – challenge
When inventory is optimized locally, inventory control is often based on a single-echelon approach. But a single-echelon approach might not be optimal from a broader supply chain perspective. In order to optimize stock levels over multiple supply chain stages and still ensure a high service level to end customers, Van Lierop focused on the potential of multi-echelon inventory control. More precisely, she studied the potential of centralized inventory control under different settings. This should help to strive for optimized stock levels throughout the entire Hilti network, and in the meantime ensure a high service to end customers.
Van Lierop addresses this challenge in her Master thesis ‘Quantifying the benefits of multi-echelon inventory control’.
Technical and organizational challenges
“Changing to a multi-echelon control policy is not easy”, Van Lierop states. “The main technical challenge is that you need to collect, and simultaneously process, a large amount of data. You also have to consider that in most supply chains, data needs to be exchanged between different firms.” On top of these technical challenges, organizational challenges pop up. When you optimize your inventory throughout the whole chain, local control is no longer necessary. Inventory should be managed centrally. However, this change requires someone, or some department, to take responsibility for the centralized inventory control. Another organizational challenge regards benefit sharing: ‘How are the benefits of the new inventory control approach shared or divided between the different supply chain stages?’
Multinationals such as Hilti AG who look for answers to these important questions might benefit from software tools to support these answers. Still, considering the complex inventory landscape and organizational responsibilities, according to Van Lierop “it is no surprise that the number of published real-world applications of multi-echelon inventory control are scarce.”
‘When does a multi-echelon inventory control policy pay off?’
Before a company decides to switch to a multi-echelon approach, they need to have a good indication of the potential for their product portfolio, according to Van Lierop. For some products, the benefits of a multi-echelon approach might be higher than for others. That is why the aim of Van Lierop’s research was to identify the product/supply chain characteristics for which a multi-echelon inventory control policy pays off. More concretely, she studied scenarios based on combinations of the following five dimensions: demand, demand variability, lead-time, lead-time variability and holding costs.
Van Lierop used a software program designed by Prof. Dr. Ton de Kok (ChainScope) for the multi-echelon safety stock optimization. By using simulation, she was able to model and compare different safety stock procedures and multi-echelon distribution networks. In her research approach, Van Lierop also used a MRP-based replenishment policy with forecasted demand, because many companies replenish their stock based on forecasts.
Results revealed that the benefits of a multi-echelon inventory control approach are the highest for items with a high lead-time to the first location in the distribution network, a high demand rate and high inventory holding costs. Van Lierop: “Furthermore, the savings for low demand, low cost items were relatively low. Especially when the first location in the distribution network can be quickly resupplied. So when companies consider a pilot for a centralized safety stock procedure in their distribution networks, they should focus on ‘high-potential’ items first.”