Writing a resume for humans is easy and simple. Job seekers are used to it and they get a better chance to be shortlisted. But the challenges arise when they have to write a resume for machines. Applicant tracking system is one of the most useful tools that’s appreciated by almost all HR but it leaves a challenge for both the HR and the candidates due to its sensitivity to information.
Not all the tools have artificial intelligence. The tool works on a predefined rule and law which can be modified after every search but that’s not challenging! The real challenge is for the job seekers who write resumes. They have to be extra careful and cautious. The job seekers have to design a resume that’s read by the machines.
When they fail to write good resumes, they are not going to be shortlisted or filtered by ATS. Thought they have all the potential skills to excel and grab the opportunity, they would simply fail if the resume doesn’t satisfy the condition set by the resume parser.
Here are some of the laws and challenges that everyone working in resume parsing should know
The rule-based parser may fail at times
When you think you can apply a rule on the ATS, you may not win all the time. For example, let us assume that you want to set rules for a date. Imagine the possibilities. DD-MM-YY, DD-JAN-YY, MM-DD-YY, MM-DD, MM-DD-YYYY, DD-MM-YYYY and so on. If you want to sort the resume based on date, you need to specify all possibilities. Does it sound simple? It might because Date is very common but imaging some other technical terms and other skills that has numerous synonyms. If you fail to add a rule, you will not be able to find the right resume. There are a complication and the HR and the management has to work together to find out a perfect set of rules and combinations that would work flawlessly.
Even if you spend hours trying to figure out, there are chances that you might fail. You may not be able to cover all the rules and finally end up compromising the accuracy.
Machine learning might help
Machine learning solves the problem of sorting and filtering to a great level. When job seekers do not have a predefined format to write their resumes, the HR professionals have to take a leap to find out different techniques that can help them find and sort the applications. They can rely on machine learning which would help them find key points on the resume and increase the accuracy level.
However, we are not advocating the idea of learning the intricacies of Artificial Technology or Machine Learning because that is simply not feasible. The job role of an HR manager is to identify the best candidate for a particular position but the job of a new age HR Manager does not end there. An HR manager must be proactive in learning what is happening in the human resource industry so that they can employ and utilize the best available, resources to rope in the best candidates. This is the reason why it is important to familiarize one with the latest Resume parsing tools that are available in the market so that they can speed up the recruitment process.
Breaking the language barrier and social media presence
Global business leaders have to rely on multiple languages. Their ATS should be able to understand more than one language. Parsing providers should be able to serve multiple languages based on different geographical locations. This would help when the organization accepts resumes from different parts of the world. Instead of asking the jobseekers to write their resumes in English, the company must be ready to accept resumes in multiple languages.
The parser should also be able to filter resumes and profiles from various socil media platforms. Rules should be set so that the system tracks the performance of the profile/jobseeker in various social media platform and converts user information into the database.
In the process of recruitment, every resume has its own importance and it is necessary for the business to track each and every application submitted and filter them based on various criteria and rules.
Automation and its dangers
Do you think it’s okay to rely on machines and automation instead of looking at the resumes manually? A simple error can force the machine to overlook potential candidates. You must accept the fact that automation is helpful but on the other hand, it cannot be reliable if the rules are not properly set.
A poor ATS will ignore and reject all potential candidates. Technology always comes with a risk. It is important for both HR professionals and the job seekers to understand the importance of parsing and prepare a resume that’s suitable for ATS and on the other hand the HR should set the system that filters efficiently.
Sometimes you will have to take the challenges of going through each single resume and identify the candidates that are suitable for a particular position. We can all understand and can empathize with you but there is no short cut to success. If the resume parsing tool is failing to identify the ideal candidate for one reason or the other, you will have to take up responsibility on your shoulder and start scouting for the best candidate for the position available.
Parsing is a challenging task
It might sound simple and easy but everyone must believe that it is a challenging task. Especially during the initial stages, CV parsing is difficult for both the recruiters and the candidates. With proper practice and learning, you can easily customize the tool according to your requirements. If you want the tool to have full control, you need to have good knowledge in setting the rules and tracking the profiles. Once you are proficient, you can simply ignore manual intervention and trust the system to fetch proper resumes.