ATM Replenishment Optimization
- A large retail bank with a network of 200 ATMs across a metropolitan area sought to optimize its ATM replenishment logistics
- The bank aimed to reduce operational costs and improve service efficiency by optimizing routes for its fleet of cash replenishment vans
- The objective was to create a dynamic routing plan for ATM replenishment vans, ensuring efficient cash management and balanced workload, considering drive time, traffic, and cash demand
- Collected data on ATM locations, cash withdrawal patterns, and replenishment schedules
- Compiled details of the fleet, including 10 vans with 8-9 hours of drive time per day. Analyzed traffic data for peak congestion and road conditions
- Used geospatial clustering to group ATMs by proximity and demand
- Developed a dynamic routing algorithm considering ATM priority, cash levels, and traffic
- Created dynamic weekly and monthly schedules, adjusting for demand and traffic
- Conducted pilot tests and set up a monitoring system to track van movements, cash levels, and schedule adherence
- Optimized routes reduced total drive time by 20%, allowing vans to cover more ATMs
- – Efficient routes cut fuel costs by 10%
- Even workload distribution reduced overloading and underutilization
- Timely ATM replenishments increased customer satisfaction and reduced cash shortages
- Real-time route adjustments improved responsiveness to unexpected demands and traffic
