Reducing processing time in product scope assessment for electrical appliances using RPA software technology at a government agency

Abstract

The research objective was to investigate the development of a product-scope assessment process for electrical appliances within a government agency to enhance assessment efficiency for customs clearance by at least 50%, reduce operational delays, identify bottleneck factors, and determine optimal stages for automation via the National Single Window (NSW) system. The proposed framework integrated Robotic Process Automation (RPA) with Artificial Intelligence (AI). Utilizing a one-group pretest–posttest experimental design, the study evaluated a dataset of 350 product applications. The methodology incorporated RPA, AI models for document and product image analysis, and a Cause-and-Effect Diagram to comprehensively analyze the root causes of operational inefficiencies. The findings revealed that after implementing RPA and AI, the processing time decreased to 2 days from 6 days per request, representing a 66.67% reduction. Processing capacity increased from 355 to 575 requests per day, while the backlog declined by 90%. The system achieved data extraction accuracy of 88–92% for text-based PDF documents and 80–85% for scanned documents. An economic feasibility analysis using Cost-Benefit Analysis (CBA) showed a Return on Investment (ROI) of 716% and a payback period of 2.2 months. The results demonstrate that the application of RPA and AI can significantly improve the efficiency of public service delivery and serve as a practical model for adoption by other government agencies.