Risk-Pooling Essentials: Reducing Demand and Lead Time Uncertainty (SpringerBriefs in Business)

Language: English

Pages: 91

ISBN: 3319141562

Format: PDF / Kindle (mobi) / ePub


This book provides comprehensive and concise definitions of risk pooling and risk-pooling methods, a straightforward statistical explanation, and a value-chain oriented framework for analyzing risk-pooling methods. Risk pooling mitigates demand and lead time uncertainty in logistics and supply chain management. The author also provides readers with a downloadable computerized decision support tool to compare and choose appropriate risk-pooling methods and to apply them in companies. Students and practitioners of logistics and supply chain management will find this book particularly useful.

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production as well. This not mutually exclusive and exhaustive classification of risk-pooling methods according to value activities is reflected in Fig. 2.3 and shows the ­versatility of risk pooling in tackling demand and lead-time uncertainty. Risk pooling helps a company to cope with demand and/or lead-time uncertainty and thus to carry out these value activities at a lower cost for a given service level, a higher service level for a given cost, or a combination of both.156 Thus it may

influencing factors that led to recommending a certain risk-pooling method, so that a sensitivity analysis can be conducted afterwards. They do not indicate an order in which the flowchart is to be passed through. For a detailed derivation of the RPDST please refer to Oeser (2011, pp. 57ff.). To ease the usability of this RPDST it was implemented in a software that can be downloaded from “SpringerExtras” (http://extras.springer.com/). You will find a version that was compiled for Microsoft

39 115,000 110,000 Total Sales (t) 105,000 100,000 95,000 2012 2013 2014 90,000 85,000 80,000 75,000 70,000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months Fig. 4.1  Our company’s total fine paper sales in Germany in tons per month Total demand for fine paper in Germany is seasonal: It is higher in January, February, and March, lower from April till July, then increases up to November in order to decrease again in December (see Fig. 4.1). Total customer demand depends on

individual variabilities (measured with the standard deviation) of demand and/or lead time. These individual variabilities are © The Author(s) 2015 G. Oeser, Risk-Pooling Essentials, SpringerBriefs in Business, DOI 10.1007/978-3-319-14157-2_6 69 70 6 Conclusion consolidated by aggregating demands (demand pooling) and/or lead times (leadtime pooling). This reduction in uncertainty allows to reduce inventory without reducing the customer service level (product availability) or to increase the

FMCG and industrial products in Italy: practices and the advantage of postponement. Int J Phys Distrib Logistics Manage 30(5):413–424 Bauer H (1974) Wahrscheinlichkeitstheorie und Grundzüge der Maßtheorie. de Gruyter, Berlin Benjaafar S, Kim J-S (2001) When does higher demand variability lead to lower safety stocks? Technical report. Department of Mechanical Engineering, University of Minnesota, Minneapolis Benjaafar S, ElHafsi M, De Véricourt F (2004) Demand allocation in multiple-product,

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