The client is a leading player in logistic and supply chain solutions provider in India. The company was founded in 1958 and has headquarters in Gurugram. They have 6000+ employees with a network of 1500+ branches. They cater various segments like Automotive, Retail, Chemical, Pharma, Renewables, etc.
Logistics
India
The client faced significant challenges in managing their extensive and diverse fleet, which included inefficiencies in fleet management, escalating costs, and delays in shipping times. The complexity of coordinating a large number of vehicles, including trucks, ships, and flights, made it difficult to optimize fleet usage.
Additionally, maintaining 12 million square feet of warehouse space across multiple locations added to the operational challenges. These issues led to increased shipping costs and hindered the client's ability to plan and execute logistics efficiently, ultimately impacting their service delivery in both Indian and international markets.
The Datamatics team began by analyzing various data sources, including demand volume, vehicle availability, route options, and delivery times. Leveraging this data, they developed a hybrid model approach using advanced analytics techniques.
By employing methods like Ant Colony Optimization and Genetic Algorithms, they identified optimal routes and fleet usage strategies. This approach not only improved the efficiency of fleet management but also resulted in significant cost optimization and enhanced the client's overall bottom line.
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