Optimizing cash at a Managed ATM Services company

Finance

A close integration of Operational Improvement, Supply Chain Optimization, Advanced Statistical techniques and Machine Learning was used to generate substantial financial savings that greatly exceeded targets.

Client

  • ATM turn-key solutions company
  • 60,000+ ATMs across US, UK and Canada
  • $1B in revenue

Business Challenge

  • Client provides turn-key ATM solutions. Manages over 45,000 units in the US and is responsible for stocking, maintaining and servicing ATMs
  • Machines were stocked at fixed frequency (daily, weekly or monthly) using third-party Armored carriers
  • In case of ATM out-of-cash, emergency cash-order is placed
  • Client pays daily interest on cash borrowed from banks
  • Total spend was over $50M per year in interest
  • Armored carrier costs (for scheduled and emergency fills) were on the rise
  • Our team was faced with the problem of reducing stock-outs and reducing costs at the same time
 

Our Approach

  • Reduced outstanding cash (and interest) through safety stock optimization - used forecast error in addition to historical data to compute safety stock
  • Reduced safety stock by reducing overall forecast error using machine learning algorithms to capture demand patterns across groups of machines
  • Optimized ATM Fill Frequency using linear programming model comprising interest vs fill cost using exponential smoothing and probabilistic demand modeling
  • Reduced Emergency cash-orders using probabilistic demand model and Executive Management Control System

Results

  • Reduced outstanding cash by nearly $270M while reducing stockouts by 18%
  • Reduced interest spend and armored carrier costs by approx. $5.8M annualized in less than six months
 

Key Takeaways

Our team used a blend of traditional operational improvement techniques, supply chain optimization, advanced statistics and machine learning to rapidly drive operational improvements. These improvements generated substantial financial savings in less than six months.

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