Home / [RPA] Enhancing Purchase Invoices Data Entry in the Retail Industry with RPA Solution
[RPA] Enhancing Purchase Invoices Data Entry in the Retail Industry with RPA Solution
77%
of manual data entry time saved
75%
of operating costs reduced in 2nd year
85%
accuracy rate
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Client Overview

Our client is a Korean company operating in the retail industry.

Business Challenges

Managing and processing purchase invoices can be a demanding task for any business. In the case of a supermarket with millions of invoices from retail buyers and suppliers, manually entering all the data into the management system can take up to 8 hours a day for the warehouse management department. This not only impacts employee productivity but also leads to low levels of accuracy, which can affect the overall billing process. An efficient solution to automate this process could go a long way in improving productivity and accuracy.

Our Solutions

Facing this problem, our client decided to transform their manual data entry process by using an RPA solution to save effort and operating costs. We have discussed directly, provided appropriate advice to the actual situation, and implemented digitalization and automation according to the following steps:

  • Use OCR to read PDF documents or scan purchase invoices from different suppliers and convert them to text.
  • Collect necessary information such as product name, quantity, selling price, and some information required for invoice processing.
  • Automatically input entry data into the invoice management system.

Using OCR and RPA integration enables customers to automate the entire data entry process, which not only improves work productivity and saves costs significantly, but also contributes to a happier working environment.

Key results

  • Reducing manual data entry time by about 77% from 8 hours per day to 12 minutes per day, increasing employee’s working capacity 
  • Saving nearly 45% of operating costs in the first year and 75% in the second year
  • Increasing accuracy by up to 85% compared to manual data entry processes

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