Case Study

Logistics major transforms billing process with robotic automation


A diversified, truck rental and leasing company

  • Facebook
  • Twitter
  • Linkedin
  • Email

Business need addressed:

  • High operating cost due to manual data collection from many sources
  • Low customer satisfaction due to inaccurate and delayed billing


  • Effective data management to improve accuracy and speed-of-billing forecasts
  • Automated revenue collection and reporting process for greater visibility and reduced operating cost

Business impact:

  • Greater customer satisfaction through process optimization, accurate billing, and precise forecasting 
  • Additional $3 million revenue growth over five years 
  • Potential to bring down the operating cost by ~40%
  • Further opportunities identified within order to cash to save another $2 million in the next four years

Large transport and logistics companies struggle to collect accurate data, such as mileage, fuel consumption, and driving hours, as it is typically held by different sources. Timely availability of accurate data can help logistics companies control costs, estimate the correct billing amount, and speed up billing to improve cash flow. Using accurate data management processes and applying robotic automation helped this logistics leader bring analytics insights into its billing operations at scale, leading to revenue growth, customer satisfaction, and improved efficiency.

Business challenge​

The company is a leading service provider of transportation and logistics services in the US, serving customers across North America, South America, Europe, and Asia. With more than 1,000 locations and 200,000 vehicles, it addresses the transportation and logistics challenges faced by individuals, small companies, and complex multinational organizations. 

The company faced two major challenges in mileage billing:

A fragmented data-collection process: The existing process depended on the manual calculation of mileage data from trucks using input from multiple legacy systems to estimate the billing amount for end customers

Inaccurate data capture: Incorrect data feeds from the field on the consumption of fuel and manual calculations resulted in inaccurate and delayed billing, which not only led to disputes, but also negatively impacted customer satisfaction and cash flows

Take a copy for yourself

Genpact solution

Having worked with the organization for over a decade, Genpact had deep operational expertise and insights into the company’s order to cash, record to report, and analytical processes. A detailed diagnostic study helped pinpoint improvement areas in billing and cash application processes. The solution involved:

Process redesign for effective data management: Genpact integrated data from multiple sources and legacy systems into a new single master database. Genpact conducted a deep-dive analysis of the existing process and historical billing data. Based on the results, dynamic business rules were built for faster data processing and analysis. 

Improved visibility through Trend Finder: Deploying Trend Finder, a visualization and analytics tool, across the existing systems helped to analyze historical data (such as fuel tickets and repair orders), and applied predetermined rules to calculate the final mileage to bill the end customer. 

Forecasting through rapid automation: Robotic process automation (RPA) was then configured to input the forecasted miles into the system of record to generate the billing amount for the next billing cycle. Timely and accurate data entry left little scope of billing errors. Unlike most automation initiatives that struggle to take off due to the complexity of the underlying processes, workflow, and legacy IT architecture, RPA allowed for practical implementation, rapid deployment, and minimum disruption to existing systems.

Business impact

The blend of technology and enhanced process design, supported by a feedback loop for continuous learning and improvements, helped the client to calculate and forecast mileage readings faster and with greater accuracy. This led to:

  • Greater customer satisfaction through process optimization, accurate billing, and precise forecasting 
  • $3 million revenue growth over a period of five years 
  • Potential to bring down the operating cost by ~40% 
  • Additional opportunities identified within order to cash processes to save $2 million in the next four years

Visit our digital transformation page

Learn More