This study is based on the strategic and logistical challenges of having a complex distribution network, which can make it difficult to get a holistic view over the distribution costs. The costs are often aggregated for many products, which makes it challenging to use as decision support on a product level. Many companies lack a tool to handle this complexity, since the costs and profitability varies between the channels and intermediaries used. This makes it problematic to determine the profitability on a product level. In the different parts of the distribution chain, there are elements that drive the costs for each activity, called activity drivers. When these activity drivers have been identified, they can be used to allocate the distribution costs to the different products. The aim of this study is to develop a tool that can be used to categorize distribution costs and to determine which activity drivers that result in the fairest cost allocation. The fairest cost allocation is a complex expression, and is briefly defined as the allocation key that result in a costs allocation that represent each products level of resource consumption. This means that products that have consumed a large amount of resources should carry a larger part of the costs compared to the products that have consumed a smaller amount of resources. Sometimes it is not obvious which allocation key that represents the reality in the fairest way, and in that case, the allocated costs are compared to the products sales values. The sales value often differs between the products. The determined allocation key is the one that result in the most even allocation when comparing the allocated cost to the sales values. The case company Swedish Orphan Biovitrum (Sobi) is located in Stockholm, Sweden. They find it difficult to get a view over the costs for the different parts of the distribution chain, and to allocate the costs fair between the products. This study have investigated the distribution from Sobi’s central warehouse in the Netherlands to the end customers in France, Germany, Italy, Spain, the United Kingdom via the local storages in each country, as well as Sweden and Estonia. This was done by categorizing the costs for each activity in the invoices from the local storages, into different cost categories. After this, the costs were allocated with different allocation keys that thereafter were compared, to find the most fair allocation key per category. In the end of this study, the lessons learned and methods used have been written down, and an allocation tool has been developed. Any company that wants to make strategic decisions on a product level can use this tool. Throughout the study, the five steps that make up the allocation tool have been followed. The tool is divided into the following steps; determination of cost categories, choice of activities, selection of activity drivers, categorization of costs and analyzing activity drivers. When choosing allocation key, it is essential to find the balance between an even allocation of the costs between the products, and to make sure that the allocation represent each products level of resource consumption. If the allocation is unfair, it can make products look unprofitable, even though they actually are profitable and necessary in reality. The difficulties to find a balance show the complexity in the determination of the most fair allocation key, since it is not always obvious. If the cost categories had been divided into smaller categories with more similar activity drivers, the dilemma of choosing allocation key might have been solved. However, it is important to bear in mind that when using more cost categories, the categorization and allocation becomes more time consuming. The tool has been created as a result of this study, and is based on a complex situation, which means that assumptions and simplifications have been made to be able to draw general conclusions. It is important to bare these simplifications in mind, when applying the tool to other situations than the one investigated in this study. The allocation tool can be used to draw strategic conclusions on a product level, since it makes it possible to be aware of the profitability of the products and, if necessary, exclude unprofitable products from the product assortment.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-119402 |
| Date | January 2015 |
| Creators | Wessman, Hanna, Roos, Sara |
| Publisher | Linköpings universitet, Logistik- och kvalitetsutveckling, Linköpings universitet, Tekniska fakulteten, Linköpings universitet, Logistik- och kvalitetsutveckling, Linköpings universitet, Tekniska fakulteten |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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