How OCR is shaping the future of performance review documentation in HR

We all know that the performance review is an assessment through which HR determines the working performance of an employee. After the assessment, the manager may have to extract useful information (name, date, score, feedback, etc.) from the physical employ-performance document, so that he/she can update it into the company’s database as a record.

Obviously, this will definitely require time and effort, but that was before the introduction of Optical Character Recognition (OCR) technology. This technology has totally transformed the performance review documentation in HR management. Want to know how? Keep reading this article till the end.

Optical Character Recognition (OCR) Technology – What it is?

ORC with magnifying glass

OCR is basically a character recognition /pattern-matching technology that quickly scans the given picture or document to extract all the textual information from it. This technology has totally eliminated the need for HRs to devote time and effort to manually performing data or text extraction processes from employee performance review documents.

Instead, Optical character recognition will get the job done within seconds without compromising on the accuracy. And the best thing is its extracted data will be editable, reviewable, searchable, indexable, etc.

Working Mechanism of OCR


It is important to note that OCR is just a technology that will only become useful when paired with some online tools. These tools are commonly known as OCR or image-to-text converters. So, the work discussed below is in the context of online tools.

1.      First Stage:

This first stage is referred to as pre-processing in which the OCR will eliminate any kind of blurriness, noises, etc. from the input so that it can easily differentiate between the letters and words the input image or document contains.

2.      Second Stage:

After removing noises and distortions, the OCR will then start recognizing the text by matching the characters and words of the input with its database of words and phrases. The technology then extracts the ones that have a successful match with the database. Due to this reason, this stage is called the “Text or feature recognition” stage.

3.      Third Stage:

This stage is known as “Post-processing” in which the OCR ensures the extracted text is free from any kind of grammatical errors and is totally accurate or not.

To provide you with a better idea about the working, I have provided an image of a performance review document to a picture to text converter. The output I got from it can be seen in the attachment below:

Performance review

How OCR is Transforming Performance Review Documentation for HR’s

There are numerous ways through which Optical character recognition is transforming the performance review documentation.

1.      Automating Data Extraction:

As we have already mentioned earlier, extracting useful information from the employee performance review document manually will definitely require a lot of time and effort.

Because HR first has to look at the document to understand the information i.e., name, score, designation of the employee, etc., and then has to enter the info into the company’s database. Fortunately, the introduction of OCR technology has solved this issue.

This technology can automatically translate all the data from a given picture or document into a machine-readable form (editable form). Searching, indexing, and archiving becomes easier for such data, and that speeds up the HR-related processes.

2.      Making Hiring Process Easier:

I could have discussed this point in the above one but thought it would be better for your understanding. When a job is posted, the HR manager gets hundreds of CVs and resumes for the published job post. Viewing each resume and extracting relevant information from them can be a hectic task. But thanks to OCR technology which has enabled developers to develop tools that can automatically scan hundreds of CVs and extra data from them. This magic has made the hiring process quite an easy thing for HR managers.

3.      Eliminating Human Errors:

Manually extracting important information from employee performance review documents will have a strong chance that HR may accidentally make mistakes (like grammar or spelling errors). This will greatly damage the reputation and will also raise questions about the professionalism of HR.

Thankfully, that’s not the case with Optical character recognition technology powered up by Artificial Intelligence. It makes use of advanced pattern-matching algorithms that efficiently analyze the text that a given image or document contains, and then extract it with 100% accuracy.

So, by utilizing OCR technology HR can totally eliminate the chances of making human errors in the extracted text from the performance review document.

4.      Offering Maximum Accessibility Or Searchability

Optical character recognition offers maximum accessibility and searchability to HR’s. Let me explain how.

By converting physical documents into editable ones through OCR, HR can easily find a specific piece of information in them through search. This will save ample time and effort, allowing them to take care of other essential tasks as well.

5.      Reduceding Chance Of Data Breach:

This is yet another way through which OCR is shaping the future of performance review documentation in HR. We all know that performance review documents that are in physical form will always have a chance that someone get unauthorized access, ending up stealing or damaging them.

So, by converting physical performance review documents into digital ones with the OCR, HR can greatly reduce the chances of data loss or breaches.

Final Thoughts

OCR has transformed the way of performance review documentation in HR by automatically extracting useful information with 100% accuracy. In this article, I have explained what this technology is along with its working, and also some ways through which it is changing the future of the performance review documentation process for HR.

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