We have previously discussed how many businesses today are struggling to reach desired customer service levels without extensive use of express or emergency deliveries. In many cases, this leads to an unnecessary loss of supply chain efficiency. However, when implemented correctly an express delivery system can offer opportunities for improved supply chain operations, both from an environmental and monetary viewpoint. Hence, finding optimal strategies regarding these deliveries is of high importance for many companies. One such company is Volvo Parts Corporation, a spare parts service provider with headquarters in Sweden. Volvo Parts is responsible for the distribution and stock keeping of spare parts for vehicles and engines made by the Volvo Group, including:
Volvo Trucks, Mack, Renault Trucks, Volvo Busses, Volvo Construction Equipment, Volvo Penta, and Volvo Aero. They have distribution points in over 120 different countries and over 600,000 different articles are stocked globally. Focusing on the European market, the Öresund region is of high strategic importance for Volvo Parts.
Firstly, the company has dealers (that are responsible for service and sales to the end
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customer) situated in the region. Secondly, a large part of the shipments between the Swedish and the remaining European market pass through the region by truck and air. For the worldwide distribution of spare parts, Volvo Parts uses a mixture of truck, boat, and airfreight. Needless to say, the strategies used for transportation and stock keeping have a major impact on their environmental footprint.
Looking more closely at Volvo Parts’ distribution system, it consists of a number of central warehouses, positioned around the world, each one responsible for supplying spare parts to several local markets. On each local market, they have a number of dealers that, in turn, serve the end customers. As mentioned above, this includes both service and repairs of the customers’ vehicles, as well as direct ‘over the counter’ sales of spare parts.
Most local markets also have what is referred to as a support warehouse. The purpose of the support warehouse is to provide transshipments or express deliveries in the event of a stock-out at a dealer. That is, the dealers place regular replenishment orders with the central warehouse, but if extra items are needed quickly, an express transshipment order is instead placed with the support warehouse. The support warehouse also replenishes its stock at the central warehouse. The system is illustrated schematically in Figure 3.
Figure 3: The considered distribution system for one local market
An express delivery from the support warehouse is more resource consuming and costly than a regular delivery from the central warehouse. This is because of the extra handling and transportation involved, that is, the transportation of items from the central warehouse to the support warehouse, and then on to the dealers, compared to direct transportation from the central warehouse to the dealers for the regular orders. On the other hand, express deliveries from the support warehouse (typically by truck) are generally much cheaper and environmentally attractive than the alternative of express deliveries from the central warehouse directly to a retailer (typically by air). Hence, there is an economic and environmental rational for using a support warehouse structure.
For placing regular orders, all stock points use reorder point policies with fixed batch quantities (so-called (R,Q) policies). This means that when the stock level reaches or drops below the reorder point, R, a batch of Q units is ordered. It follows that the choice of reorder points (at the support warehouse and at the different dealers) greatly affects supply chain performance. For instance, a low reorder point at a dealer implies a low inventory holding cost at that location, but requires frequent use of the support warehouse
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to maintain a sufficient service level to the end customers, and vice versa. Therefore, developing a method for jointly determining the optimal values of these reorder points, and thereby improving current operations, has been the aim of the first part of our collaboration project at Volvo Parts. The second part of our project involves potential changes in supply chain design and the use of extended information.
Currently, Volvo Parts determines reorder points at each inventory location separately;
using tables based on price and forecasted demand. These tables are constructed based on achieving target service levels set by management (for more information on current operations at Volvo Parts see Borowiec and Liedberg, 2009; Alfredsson and Hansson, 2010). However, several shortcomings can be identified with the current method used.
The most obvious problem is that there is no coordination between the choice of reorder points at support warehouses and the dealers. That is, inventory decisions are made at one location without regards to how it affects other locations. In particular, the extra amount of resources needed when ordering from the support warehouse, compared to a regular replenishment, is not taken into account when determining reorder points at the dealers.
This makes it impossible to weigh the potential benefits of using express deliveries against the potential downsides. Other problems identified are that the current method tends to result in rather large over-investments in stock, and that the price/demand tables cannot be updated automatically (see Borowiec and Liedberg, 2009; Alfredsson and Hansson, 2010).
In the first part of the project, a mathematical optimisation model of the described distribution system was developed, the purpose being to determine the best possible reorder points for the support warehouse and all dealers on any given local market. The model considers the extra resources needed for express deliveries along with other input data (for instance demand variability) that are not reflected in the current approach used by Volvo Parts. The modeling technique used is based on concepts within probability theory, statistics, inventory control, and optimisation theory (see Axsäter et al. 2009, and Axsäter, Howard and Marklund, 2011 for further details). For effortless implementation in the company’s current IT system the model was developed in Excel®, which is a software used at all installations in Volvo Parts’ supply chain. In combination with the optimisation algorithms that were developed, this means that new reorder points can be automatically generated for a large number of articles in a matter of seconds. This also holds true for high demand articles, a class of articles for which solution times can be quite long in general.
Given the nature of spare parts inventories, it usually takes several years to evaluate changes in inventory policies. In order to provide Volvo Parts with a tool for faster (and less costly) evaluation of the reorder points proposed by the optimisation model, a computer based simulation model was also constructed. Designed in the simulation software Extend®, the model mimics the real systems in greater detail than the optimisation model. A simulation study of representative articles revealed that the optimisation model outperforms the current method used by Volvo Parts (see Axsäter et al. 2009, Borowiec and Liedberg 2009, Alfredsson and Hansson 2010, and Axsäter, Howard and Marklund 2011 for details). On average, the new solutions reduce costs of keeping and distributing inventories by 29 per cent, while staying above the required end customer service levels. The average inventory reduction was 43 per cent, but through better coordination between the support warehouse and the dealers, this can actually be combined with high customer service and 30 per cent fewer express deliveries from the
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support warehouse. Consequently, by using the new optimisation model Volvo Parts has the opportunity to reduce their environmental impact, reduce costs and still provide their customers with competitive service.
The second part of our project was aimed at investigating how Volvo Parts can benefit from investment in more advanced IT systems and inventory control policies. We focused particularly on expensive low demand articles, which are notoriously difficult to manage.
In this case, our model also includes the option of requesting express deliveries by airfreight from the central warehouse; a service currently provided for expensive articles if both the dealer and the support warehouse are out of stock. As in the first part of the project, new optimisation and simulation software was developed, this time to evaluate a new type of inventory control policy (see Howard et al. 2010 for details). The new policy utilises information about the exact geographical position of incoming orders, and the time until they arrive, before determining whether to place a regular order or an express order. Such real-time information can for instance be obtained by use of RFID technology. A second simulation study, encompassing 70 representative articles, discovered a large potential for cost reductions. Results indicate that using real-time information can lower stock keeping and distribution costs by 12 per cent, on average.
The study also revealed that, if the new policy was implemented, the expensive and environmentally taxing express deliveries from the central warehouse could be avoided altogether for most articles.
In summary, the current project has resulted in optimisation and evaluation models that can be directly implemented into Volvo Parts’ systems. The developed software tools can be used to determine how much stock there should be at each inventory location and when it is best to use express deliveries. Two different simulation studies show that there is a large potential for Volvo Parts to optimise its current operations, as well as to invest in new technology that will give them additional competitive advantages in the future.
This will be of direct benefit for the Öresund region, because of the shipments passing through and the dealers situated in the area. Furthermore, although the software was developed based on the specific conditions at Volvo Parts, the modeling assumptions are quite general. This means that it is relatively easy for other companies within the Öresund region to use the developed models and software and achieve more efficient and sustainable supply chain operations.