The distribution planning process is one of the phases of the broader logistics and production planning process for almost every company, and plays a pivotal role in the overall performances (Lee and Kim, 2002; Bard and Nananukul, 2008). According to Chandra and Fisher (1994), companies can treat this stage in a dual approach. In the first one the overall planning process is considered as an indivisible entity: according to this way several researchers (Glover et al., 1979; Cohen et al., 1988) proposed models in order to coordinate production and distribution activities. In the second approach, the company considers the distribution policy as an independent stage of the entire planning process (for details, see Thomas and Griffin, 1996). Such an approach is more frequently adopted in industry (Chandra and Fisher, 1994). According to the “independent approach”, this paper illustrates the results of an empirical study involving a relevant food company operating in Italy. The aim of the study is to investigate the distribution planning process, in order to identify the main parameters that govern it, to analyse their impact on the company’s performances and, finally, to propose some improvements, in terms of costs reduction. According to these objectives, the study addressed, through an intensive case study, two main aspects: (i) the analysis of the company as-is context, encompassing the order process management and the supply chain structure, and (ii) the development of a simulation model that replicates the as-is context and proposes alternative scenarios (to-be), following some ad-hoc optimization rules. Thanks to the simulations, we carried out an optimal configuration for the process parameters, which guarantee, along with the standardization of the order process management, significant economics savings and increased effectiveness for the overall distribution planning process.

Reviewing the distribution planning process: an empirical case study in the food&beverage industry

BACCHETTI, Andrea;ZANARDINI, Massimo
2014-01-01

Abstract

The distribution planning process is one of the phases of the broader logistics and production planning process for almost every company, and plays a pivotal role in the overall performances (Lee and Kim, 2002; Bard and Nananukul, 2008). According to Chandra and Fisher (1994), companies can treat this stage in a dual approach. In the first one the overall planning process is considered as an indivisible entity: according to this way several researchers (Glover et al., 1979; Cohen et al., 1988) proposed models in order to coordinate production and distribution activities. In the second approach, the company considers the distribution policy as an independent stage of the entire planning process (for details, see Thomas and Griffin, 1996). Such an approach is more frequently adopted in industry (Chandra and Fisher, 1994). According to the “independent approach”, this paper illustrates the results of an empirical study involving a relevant food company operating in Italy. The aim of the study is to investigate the distribution planning process, in order to identify the main parameters that govern it, to analyse their impact on the company’s performances and, finally, to propose some improvements, in terms of costs reduction. According to these objectives, the study addressed, through an intensive case study, two main aspects: (i) the analysis of the company as-is context, encompassing the order process management and the supply chain structure, and (ii) the development of a simulation model that replicates the as-is context and proposes alternative scenarios (to-be), following some ad-hoc optimization rules. Thanks to the simulations, we carried out an optimal configuration for the process parameters, which guarantee, along with the standardization of the order process management, significant economics savings and increased effectiveness for the overall distribution planning process.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/488180
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