A large PE-backed US retail conglomerate

Requirement
 

• The Retail chain, spanning 4 islands, wanted to optimize their ordering process across their 30+ stores, to guarantee a consistent supply of fresh inventory and ultimately boost their margins through data-driven sales planning and forecasting
  

Challenges faced by the client
 

• There were complexities in managing large number of products across departments, selective availability of suppliers at specific locations and varying lead times
• Lack of a standard ordering system for stores which led to wastages, markdowns and loss of sales due to over/under ordering
  

CRISIL solution

Database creation
 

• Created a centralized database of products store-wise for each department and mapped the vendor, minimum order quantity, shelf life, order/delivery schedule, safety stock level and other required parameters
  

Semi-Automated Ordering Framework
 

• Used the collected data to create an order management framework to efficiently place orders at warehouse and store level, incorporating sales forecasting based on recent trends and historical sales
• Automated the manual processes in sales planning, warehouse, inventory and order management for departments like Bakery, Service Deli, Produce and their in-house kitchen
  

Interactive Inventory Dashboard
 

• Leveraged Python to create an inventory management dashboard considering various lead times at different locations and adjusted orders for existing inventory at the time of ordering
  

CRISIL impact

Benefits to the client
 

• Automated ordering reduced manual errors, enhanced supply chain efficiency, reduced wastages and improved stock availability
• Reduced manual efforts of store managers, which helped them focus more on customer relationship management
• Implementation of the ordering system helped the client to increase operating margins by 4-5% 
  

Questions

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