Increasing the workforce for organizational requirements is a constant hassle for the HR department because of the long and complicated reference check process. Make it efficient using AI tech that can optimize the process, and reduce complexity.
Reference checking is a critical step in the hiring process because it is crucial to learn about a potential employee’s past, work experience, and workplace interactions; however, reference checking can result in wasting countless hours and manpower. Frustrating rounds of manual work often result in wasting valuable time. Hence, organizations need to look towards AI and its potential for addressing problems related to reference checks.
But before we dig deep into how AI can aid companies involved in reference checks, let's first understand the meaning of a reference check and its importance.
A reference check is when an employer reaches out to a job applicant's previous employers, educational contacts, and other sources to learn about the applicant’s history, work habits, and other qualifications.
The evaluation of an applicant’s skills, character, and work habits is the primary focus of a reference check. It is important to perform a reference check before a person is hired as an interview can only reveal a limited amount of information about a person and it is important to learn what other people have to say about the candidate. A reference check can cover aspects such as leadership skills, adaptability, decision making, etc. It can even ask for examples of how the candidate demonstrated specific skills in the past.
Reference checks are important as they provide an opportunity for important final validation, or warning, about a candidate. Moreover, reference check proponents argue that reference checks are less about acquiring a thumbs up or thumbs down vote from previous employers, and more about learning about a candidate’s strengths and limitations in order to best support them once they are on the job.
Additionally, reference checks provide employers a chance to hear what a candidate has achieved historically and traits in their behavioral patterns as described through the eyes of a previous manager, peers, and direct reports. Depending upon the caliber of questions asked and if conducted insightfully, speaking with someone who has worked with a candidate in the past can reinforce observations or alternatively can bring new information to the table.
The traditional methods of reference checks are associated with a lot of drawbacks. Some common disadvantages of traditional reference check methods include-
We all know that reference checking is by far, one of the most time consuming and tedious processes of recruitment. Now, if we look at traditional ways of reference checks, only a small portion of the references who are contacted give you all the information you are looking for. Most are simply too busy or just not willing to go through with answering the questions. This hence leaves you with an inefficient system. Hence, automated reference checking with the help of AI can work wonders to help you streamline the entire data collection process.
The fact that AI enabled reference checking gives you more complete information, means that you have the data to make better decisions in a short time. An AI powered reference check system does the hard part for you, so you can continue to focus on the other business critical aspects.
Here’s how AI works for reference checks-
AI based reference checks can provide quality data along with offering a level of convenience that cannot be matched by traditional ways such as phone interviews or requests for letters of recommendation.
They are faster and more accurate than traditional reference checks because they don't require the time-consuming back-and-forth between many people or various departments. And unlike traditional reference checks, automated reference checks have no bias because they are objective algorithms that do not rely on human judgment or input from past stakeholders.
Some more benefits of AI based reference checks include:
AI powered reference checks can allow you to customize questions to elicit the exact information you need. This means you can plan your questions, and you won’t be derailed when the referee says that they are short of time. An AI based reference check can also help organizations flesh out competency based surveys that can make organizational processes more streamlined.
Catching someone on the fly is never the best way to find out about your prospects. With AI based reference checking, the referee can complete the reference when and where it suits them. This means you are getting the referee’s full attention, which will ultimately lead to more detailed and considered answers. Exactly what you need to make the best decision.
AI based reference checking also helps companies remain compliant, while safeguarding data. Organizations using AI based reference checks can eliminate messy notes, and tons of phone call records. This means they get the required data at one place-at the click of a button.
The reference check process for any business is a difficult and time-consuming exercise that involves interviewing and gathering information from previous stakeholders, managers, co-workers, and acquaintances. It is also costly and time consuming and can often be inaccurate, biased or misleading; even if they're conducted correctly they often take longer than necessary to complete.
But now all these problems can be solved, thanks to the introduction of AI powered reference checking tools, it is possible to automate the process. Automated checking will help cut down on time and mistakes, making the whole process a lot faster. They can also be used for multiple reference checking.
VisionERA IDP platform can help organizations involved in reference checks automate this time consuming process by combining advanced AI technologies with complimentary technologies such as RPA or API integration. From taking care of mundane tasks such as verifying a candidate's educational background to assessing job qualifications, VisionERA's intuitive IDP capabilities can help you with so much more.
Designed by our experts, VisionERA IDP undertakes auto correction of scanned documents to eliminate the noise and enhance image quality for better data extraction accuracy. It then applies machine learning to identity and classify various documents . Post this, our smart, smart state of the art IDP platform leverages OCR and extracts relevant fields from the identified documents based on document type. NLP is then applied to validate correctness of information from these data laden documents. We even use triangulation logic to validate information from different sources and documents. All this is finally integrated with all downstream applications including cloud and local databases. This makes exporting data easier to business processes workflows and hence makes the entire boring paperwork workflow easy and accurate.
Sounds interesting right? Well book a demo with us to see it live in action.
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