Optical character recognition (OCR) is one of the most effective methods used for automated data capture to convert data like text and images into digital data. As it totally eliminates manual data entry the chances of errors are almost nil. As per a Transparency Market Research (TMR) report, the global OCR market is expected to increase by 14.8% during the forecast period 2017-2025 and will be worth US$25.1 billion by the end of 2025.

best practices for ocr based data capture

OCR enhances accuracy and cut down on the operational overheads considerably. This technology can be effectively used to capture data in a quick and efficient way from different sources of information in any type of electronic or typewritten or handwritten paper format and convert them into digital format to ensure easy access and editing in future. Availing the services of an experienced OCR outsourcing service provider can reduce the amount of time required for carrying out data entry and help businesses focus on their core processes.

OCR technology helps business organizations in better organization of their data and increase the efficiency of the work. This technology is particularly useful to deal with voluminous data inflow and scanning. OCR will help to reduce costs and enhance accuracy, storage space and data security even during emergency situations like a flood.

5 Best Practices for OCR Based Data Capture

1. Analyze the data

Before getting started it is important to take a detailed look at the original data that needs to be digitalized. From the paper quality to the font and type of text, everything can play an important role in determining whether the data capture process will be easy or not. An experienced data entry outsourcing service provider will be able to provide the necessary expertise in this regard.

2. Project objectives

The specific goals of the OCR project must be clearly defined along with the timelines to complete the data capture process successfully. Chart out a well planned OCR process workflow to ensure that everything turns out as per the expectations. Depending on the purpose of the project, the data entry team must find the best method that matches their requirement and deliver the type of data capture output required.

Consider the following key factors to make sure that the OCR data capture project goals are met.

• The type of output required and its purpose
• Level of the accuracy of data capture
• Does the data capture include only text or other elements like images?
• The acceptable error range of the user
• Whether the OCR text files would have to be displayed to users

3. Quality check

A foolproof quality check process will make sure that the project is on track and will be completed on time. Either a full project review or partial