Case Study - Using Machine Learning and Robotic Process Automation to Improve Regulatory Compliance While Reducing Staffing Time Spent by 95%

Overview

The logistics industry has increasingly faced stricter environmental sanctions and regulations imposed by both federal and local governments. The costs associated with compliance management and the evolution of business processes have made it difficult for logistics providers to maximize profits.

Challenge

The client needed to automate a manual process that prevents the shipment of materials that are federally prohibited. The manual process involved a dedicated FTE cross-referencing and reformatting two cumbersome spreadsheets to identify the requested information and generate a Daily Material Receipt Report.

Solution

NITCO worked to implement preemptive measures within the client’s current business processes. NITCO designed and developed an enterprise solution using RPA with machine learning algorithms.

Benefits

• 100% accuracy in data identification
• Increased business compliance with federal and local regulations
• Reduction in human error, maximizing profits
• 95% FTE Savings (3 FTEs at 30 minutes manual per FTE; 5 minutes for the complete automated process)