Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/21357
Title: Application of analytics for assortment optimization in apparel industry
Authors: Sharma, Jyotsna 
Keywords: Business analytics;Apparel industry;Fashion indistry;Artificial intelligence;Manufacturing
Issue Date: 2021
Publisher: Indian Institute of Management Bangalore
Series/Report no.: PGP_CCS_P21_147
Abstract: And when users are generating enormous amount of data at every moment, the pressure on the industries is more than ever to make use of this data to provide a better customer experience. Data analytics is at the core of human brain, just like sapiens intake millions of bits of information, filter out the essential information to draw insights and then take a suitable decision, industries intake the collected data and try to extract any helpful information or insight that can help the company take a data backed decision. Each company can have a different objective at a given point of time and analytics can help us optimize processes, target audience, enhance topline and bottom line etc. In this project, we will primarily focus on fashion industry. Inventory management is one of the crucial aspects of apparel industry when the seasons are short and turnaround is quick, the cost of overstocking and understocking both are very high. Managing the inventory close to the precisely forecasted demand not just saves money but also keeps the firm relevant to the customers in a rapidly changing fashion landscape. This project analyzes various assortment optimization techniques to deal with stocking problems, and to take statistically supported decisions for purchasing, stocking, and marketing products to give customers a wholesome experience.
URI: https://repository.iimb.ac.in/handle/2074/21357
Appears in Collections:2021

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