4 Amazing HR Solutions To Automate Your Manual Data Entry Process
November 23, 2021 by Rohini Sood
Manual data entry in recruitment is a crucial everyday task for organizations across hundreds of industries, including real estate, education, medical, architecture, retail, and many more. But let’s accept that it is certainly not the most productive use of time.
Let’s get straight to the point - why do you need to put an end to manual data entry?
Globally, numerous ATS, job boards, and staffing agencies continue to use manual data entry as an economical way of processing resumes. But it limits the growth and hinders the progress due to the following reasons:
Expensive and time-consuming
Human error leads to inaccurate information
Slow turnaround time
4 Common Recruiting Challenges and How to Overcome Them?
One way to reduce manual data entry is to automate your processes.
Challenge #1: Lengthy job application form
Generally, candidates quit a long or complicated application process. They don’t want to answer a heap of questions seeking information that can be found on their resumes.
Applicants often complain about:
Irrelevant data fields and re-entering the state and country, even after providing the address and zip code.
Manual data filling and seeking the same information again, which is there in the resume. Repetitive questions that are too personal or biased, like questions relating to marital status, gender, or age.
Solution: A simple application form that can be filled in a few seconds. RChilli resume parser permits candidates to submit their applications with a single click by simply uploading their resumes. They do not need to fill in repetitive information again and again as the parser automatically populates the data fields. Isn’t that interesting!
By making the form and recruitment process more straightforward, you enhance the candidate experience. Happy candidates are sure to announce their experience via social channels, thus, strengthening the employer brand. To sum up, there are enough reasons to simplify the application form.
Challenge #2: Manual resume data entry to your database/ATS
If you are a recruiter, you may have found yourself in this situation where you are collecting data of prospective candidates and entering these details manually into your ATS.
Several recruiters perform manual data entry more than other recruitment activities like relationship building, calling candidates, follow-ups, etc.
But why are the recruiters still doing manual work?
Well, below are the reasons behind this:
Lack of automation tools
Resumes are not in a proper format, and they find it time-consuming to scroll down to collect the candidate’s information.
Several organizations utilize the ATS as a centralized database for candidates’ profiles and recruiters to fill in the necessary details.
Solution: Recruiters can use resume parsing technology to streamline the resume and applicant screening process.
RChilli’s cv parsing technology allows recruiters to gather, store, and organize many resumes in a structured format.
The resume parser extracts candidate data from resumes in 140+ data fields through REST API. It analyzes resumes created in any document format, such as DOC, DOCX, PDF, RTF, TXT, ODT, HTM and HTML, DOCM, DOTM, DOT, DOTX.
Challenge #3: Manual data entry of jobs/resumes lying in email
At a recently concluded Job Fair, numerous candidates forwarded you their resumes, some scanned as well. What methodology do you adopt to screen all the resumes in your email inbox to find the ideal candidate? Will you manually review the resumes and enter data in your ATS?
Solution: Our advanced Email Inbox Integration feature allows the users to parse resumes or jobs from single or multiple email inboxes. Within less than 2 seconds, get resume/job data in your database.
Challenge #4: Jobs data entry
Extracting data from job descriptions manually is a daunting task. Recruiters need a solution that can give them the details of a job description in a structured format.
Solution: The advanced RChilli JD parser extracts the parameters from a job description and gets all the job information from the job feeds in a structured format.
RChilli uses AI/ML trusted technologies to parse a job description into the JSON output format lexically.
With the correct approach and automation tools, manual data can be processed with contemporary automation solutions.
Are you looking to automate your manual data entry process? Try our products for greater accuracy, easy implementation, and quick integration.