The role of C-products in providing customer service—refining the inventory policy according to customer-specific factors |
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| Affiliation: | 1. Shanghai Municipal Center for Disease Control and Prevention, 1380 Zhongshan West Road, Shanghai 200336, China;2. California Department of Public Health, Richmond, CA 94804, USA;3. School of Life Science, Shanghai University, Shanghai 200444, China;1. Faculty of Chemistry, Kharazmi (Tarbiat Moalem) University, Tehran, Iran;2. Department of Chemistry, Faculty of Science, Payam Noor University, Marand, Iran;1. Department of Hygiene, Social and Environmental Medicine, Ruhr-University Bochum, Universitätsstraße 150, D-44801 Bochum, Germany;2. Instrumental Analytical Chemistry, University Duisburg-Essen, Universitätsstraße 5, D-45141 Essen, Germany;3. Department of Analytical Chemistry, Ruhr-University Bochum, Universitätsstraße 150, D-44801 Bochum, Germany;1. Discipline of Business Analytics, The University of Sydney, Room 490, Merewether Building (H04), Sydney, NSW 2006, Australia;2. Department of Industrial & Systems Engineering, Rensselaer Polytechnic Institute, ISE, RPI, 110 8th St., CII, Suite 5015, Troy, NY 12180, United States;3. Department of Management, University of Notre Dame, Room 359, Mendoza CoB, Notre Dame, IN 46556, United States;1. Department of Automation, Tsinghua University, Beijing, China;2. Department of Management Sciences, College of Business, City University of Hong Kong, Hong Kong;3. Department of Management Science, College of Management, Shenzhen University, Shenzhen, China |
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| Abstract: | An approach is provided for categorizing C-products on the basis of their significance for the business through their customer service effects. In the approach, C-products are considered significant for two types of service reasons: (1) C-products, which are mainly sold to the most important customers, and (2) C-products, which are mainly sold in connection with A-products and are necessary for making a complete order. These customer service-related aspects are combined with product-related variables such as demand volume and variation to categorize the products into distinct clusters for which different service policies can be exercised. A self-organizing map, which is a flexible tool for clustering problems, is used for creating product groups. The approach is illustrated with an application of a wholesale company in a constructing business. As a result of the analysis, the C-products are categorized as service products (with local availability policy), slow response products (centralized stock policy), and non-important products (potential ones to be discarded). |
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