Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/19489
Title: Supplier health scorecard and demand supply correction factor development
Authors: Niranjan, S Karthik 
Gajawada, Mounika 
Keywords: Purchasing strategy;Supply chain;Health scorecard;Tractors and generators
Issue Date: 2020
Publisher: Indian Institute of Management Bangalore
Series/Report no.: PGP_CCS_P20_100
Abstract: The project involves analyzing the purchasing strategy concerning the selection of suppliers for Bosch and arrive at a correction factor for forecasted demand for the component A-pump which is used in Tractors and Generators. A-Pump is one of the largest components by volume and manufacturing is localized in India. The study involves solutions for the following problems in the Purchasing strategy of Bosch: • The suppliers are decided based on several parameters that involve the product quality delivered, capability available, and cost of service offered. In addition to the above parameters, the financials of the Supplier play a significant role in enhancing their capability as it enables investment in resources such as Inventory, additional machinery etc. Analyzing the customers of the individual supplier and the value attributed to Bosch provides insights on the willingness of suppliers to invest in other resources. The objective is to develop a Supplier Health Scorecard for the suppliers incorporating Financial data, which will zero in on the required Suppliers. • A-pump demand is subject to the demand for tractors and generators. Variation in the schedules and inward is attributed to variation in the market demand, which necessitates a correction factor to predict the demand for the components accurately. Suppliers hold stock of raw materials and finished goods to supply to Bosch and the quantities are planned in accordance with the schedules prepared by Bosch. The correction factor for the demand predicted helps in minimizing the inventory of the suppliers, thereby mobilizing more resources in manufacturing and improves the accuracy of costing.
URI: https://repository.iimb.ac.in/handle/2074/19489
Appears in Collections:2020

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