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Ultima descărcare din IBN: 2024-04-03 09:37 |
SM ISO690:2012 STAVER (CONDRATCHI), Liliana. Supply chain: key performance indicators analysis. In: Simpozion Ştiinţific Internaţional al Tinerilor Cercetători : Culegere de articole selective, Ed. Ediţia a XVII-a, 24-25 aprilie 2019, Chişinău. Chişinău Republica Moldova: Departamentul Editorial-Poligrafic al ASEM, 2019, Ediţia 17, pp. 109-114. ISBN 978-9975-75-962-5. |
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Simpozion Ştiinţific Internaţional al Tinerilor Cercetători Ediţia 17, 2019 |
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Conferința "Simpozion Ştiinţific Internaţional al Tinerilor Cercetători" Ediţia a XVII-a, Chişinău, Moldova, 24-25 aprilie 2019 | ||||||
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JEL: Q 23 | ||||||
Pag. 109-114 | ||||||
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Rezumat | ||||||
Supply chains are fluid and are continuously adjusting to changes in supply and demand for the products they handle. To get the performance desired from supply chains requires a company to monitor and control its operations continuously. That is done through continuous measuring and monitoring their supply chain Key Performance Indicators (KPIs). Most organizations are ignoring the importance of analyzing their KPIs, and they stop at measuring and reporting them. That is not helping senior management to address root causes and understand what went wrong. We show here, how to transfer the quantitative into qualitative measures. So this paper is discussing some of supply chain KPIs, which are used in our practical case, what types of analysis are done on them, in which forums or meetings they are discussed, and the improved results. We started this concept as part of supply chain reengineering process in industrial international Fast Moving Consumer Goods (FMCG) Company by initiating Sales and Operational Planning Process (S&OP), and get use of much raw data and transforming it to meaningful analysis which helped the organization to improve their decisions. This process is being developed and implemented and after one year, results started to come. |
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Cuvinte-cheie Supply Chain Management, Performance Measurement, Inventory Management, Quality Data Analysis |
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