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Business Problem: A FMCG company has entered into the instant noodles business two years back

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Business Problem: A FMCG company has entered into the instant noodles business two years back. Their higher management has notices that there is a miss match in the demand and supply. Where the demand is high, supply is pretty low and where the demand is low, supply is pretty high. In both the ways it is an inventory cost loss to the company; hence, the higher management wants to optimize the supply quantity in each and every warehouse in entire country. Goal & Objective: The objective of this exercise is to build a model, using historical data that will determine an optimum weight of the product to be shipped each time to the warehouse. Also try to analysis the demand pattern in different pockets of the country so management can drive the advertisement campaign particular in those pockets. This is the first phase of the agreement; hence, company has shared very limited information. Once you are able to showcase a tangible impact with this much of information then company will open the 360 degree data lake for your consulting company to build a more robust model. File: Data.csv Target variable: product_wg_ton Data dictionary: Variable Business Definition Ware_house_ID Product warehouse ID WH_Manager_ID Employee ID of warehouse manager Location_type Location of warehouse like in city or village WH_capacity_size Storage capacity size of the warehouse zone Zone of the warehouse WH_regional_zone Regional zone of the warehouse under each zone num_refill_req_l3m Number of times refilling has been done in last 3 months transport_issue_l1y Any transport issue like accident or goods stolen reported in last one year Competitor_in_mkt Number of instant noodles competitor in the market retail_shop_num Number of retails shop who sell the product under the warehouse area wh_owner_type Company is owning the warehouse or they have get the warehouse on rent distributor_num Number of distributer works in between warehouse and retail shops flood_impacted Warehouse is in the Flood impacted area indicator flood_proof Warehouse is flood proof indicators. Like storage is at some height not directly on the ground electric_supply Warehouse have electric back up like generator, so they can run the warehouse in load shedding dist_from_hub Distance between warehouse to the production hub in Kms workers_num Number of workers working in the warehouse wh_est_year Warehouse established year storage_issue_reported_l3m Warehouse reported storage issue to corporate office in last 3 months. Like rat, fungus because of moisture etc. temp_reg_mach Warehouse have temperature regulating machine indicator Proprietary content. ©Great Learning. All Rights Reserved. Unauthorized use or distribution prohibited. approved_wh_govt_certificate What kind of standard certificate has been issued to the warehouse from government regulatory body wh_breakdown_l3m Number of time warehouse face a breakdown in last 3 months. Like strike from worker, flood, or electrical failure govt_check_l3m Number of time government Officers have been visited the warehouse to check the quality and expire of stored food in last 3 months product_wg_ton Product has been shipped in last 3 months. Weight is in tons