Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/20748
Title: Safety stock optimization at AAA
Authors: Ranjan, Sanjeev 
Sahoo, Soumya Ranjan 
Keywords: Supply chain management;Logistics;Logistics disruptions;Risk management
Issue Date: 2016
Publisher: Indian Institute of Management Bangalore
Series/Report no.: PGP_CCS_P16_184
Abstract: Logistics disruptions, local strikes, suppliers’ inefficiency and incapability, natural disasters, labor disputes, documentation inefficiencies and more mundane risks can seriously upset or delay the flow of material, information and cash and hence would lead to higher storage at each point throughout an organizations’ supply chain. This would lead to not only higher cost but also lost sales and lost relations with downstream customers. This report discusses about a number of supply chain risks pertaining to AAA Automotive Limited, Bangalore (India). Various risks and inefficiencies at different ends of the supply chain led AAA to hold higher than theoretical safety stock. This report has analyzed the problem of higher safety stock using three loops – Procurement loop, Production loop and Demand loop. Under these three loops, synchronization in each loop has been quantified using the retrospective data and theoretical understanding of the supply chain management. The problem of erratic and high safety stock of inbound components is not only due to suppliers and logistics inefficiencies but also disruptions and lack of synchronization in the production and outbound planning. To mitigate risks related to upstream (suppliers and logistics), geographical location of suppliers, local political situation and past performances of suppliers have been analyzed. To analyze production loop, synchronization between actual and planned production is analyzed to quantify a factor which can be included in the final calculation of required safety stock. Similar thing is done for demand loop part also. In the end, safety stock calculation was quantified using delay factors, synchronization factors and volatility in delays.
URI: https://repository.iimb.ac.in/handle/2074/20748
Appears in Collections:2016

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