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Identifying Main Drivers on Inventory using Regression Analysis

In: Operational Excellence in Logistics and Supply Chains: Optimization Methods, Data-driven Approaches and Security Insights. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 22

Author

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  • Hoppenheit, Steffi
  • Günthner, Willibald A.

Abstract

Inventory management is essential for satisfying customer demands and reducing logistics costs. Extensive material portfolios, balancing inventory costs versus customer service levels as well as fluctuating demand are factors that influence inventory levels. Inventory management is often considered as inventory reduction; quick reduction activities are carried out without knowing the exact root causes of nontarget inventory levels. A sustainable and comprehensive approach could be, to consider those factors which have a strong impact on inventory and to use this information for further inventory optimization activities. This paper therefore gives an answer to the question, how to systematically identify main drivers on inventory, using multiple linear regression analysis and how to quantify their impact considering company-specific data and structures. The described approach is applied in a case study at a company in the commercial vehicle industry. Data sets from different locations are analyzed and compared. It will be shown in a methodical way that few factors have a strong linear influence on inventory level and differ depending on the characteristics of the respective location. Companies can thereby analyze main drivers on inventories e.g. per location, region, sales channel or company-wide, depending on the chosen data set. The results can be used to identify root-causes for nontarget inventory levels and form the basis for company-specific inventory optimization activities.

Suggested Citation

  • Hoppenheit, Steffi & Günthner, Willibald A., 2015. "Identifying Main Drivers on Inventory using Regression Analysis," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Blecker, Thorsten & Kersten, Wolfgang & Ringle, Christian M. (ed.), Operational Excellence in Logistics and Supply Chains: Optimization Methods, Data-driven Approaches and Security Insights. Proceedings of the Hamburg , volume 22, pages 141-169, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:209284
    DOI: 10.15480/882.1265
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    References listed on IDEAS

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    1. Panagiotis Kouvelis & Genaro J. Gutierrez, 1997. "The Newsvendor Problem in a Global Market: Optimal Centralized and Decentralized Control Policies for a Two-Market Stochastic Inventory System," Management Science, INFORMS, vol. 43(5), pages 571-585, May.
    2. Kakabadse, Andrew & Kakabadse, Nada, 2002. "Trends in Outsourcing:: Contrasting USA and Europe," European Management Journal, Elsevier, vol. 20(2), pages 189-198, April.
    3. Golini, Ruggero & Kalchschmidt, Matteo, 2015. "Managing inventories in global sourcing contexts: A contingency perspective," International Journal of Production Economics, Elsevier, vol. 165(C), pages 64-78.
    4. Demeter, Krisztina & Matyusz, Zsolt, 2011. "The impact of lean practices on inventory turnover," International Journal of Production Economics, Elsevier, vol. 133(1), pages 154-163, September.
    5. Beamon, Benita M., 1998. "Supply chain design and analysis:: Models and methods," International Journal of Production Economics, Elsevier, vol. 55(3), pages 281-294, August.
    6. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    7. Golini, Ruggero & Kalchschmidt, Matteo, 2011. "Moderating the impact of global sourcing on inventories through supply chain management," International Journal of Production Economics, Elsevier, vol. 133(1), pages 86-94, September.
    8. Ben Naylor, J. & Naim, Mohamed M & Berry, Danny, 1999. "Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain," International Journal of Production Economics, Elsevier, vol. 62(1-2), pages 107-118, May.
    9. Stratton, Roy & Warburton, Roger D.H., 2006. "Managing the trade-off implications of global supply," International Journal of Production Economics, Elsevier, vol. 103(2), pages 667-679, October.
    10. Demeter, Krisztina & Golini, Ruggero, 2014. "Inventory configurations and drivers: An international study of assembling industries," International Journal of Production Economics, Elsevier, vol. 157(C), pages 62-73.
    11. Pfohl, Hans-Christian, 2010. "Logistiksysteme. Betriebswirtschaftliche Grundlagen," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 57571, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Gérard P. Cachon & Marshall Fisher, 2000. "Supply Chain Inventory Management and the Value of Shared Information," Management Science, INFORMS, vol. 46(8), pages 1032-1048, August.
    13. Olhager, Jan, 2003. "Strategic positioning of the order penetration point," International Journal of Production Economics, Elsevier, vol. 85(3), pages 319-329, September.
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