INVILENT’S next venture is to develop talent data research algorithms. Sorting out portfolios and choosing a blissful personality from them is daunting and tedious. It takes ages before a company digs out its ideal candidate.
A quick fix to the problem is integrating talent research algorithms into the recruitment policy. Talent data algorithms are a complex set of instructions designed to narrow down a candidate’s job portfolio. The advanced codes cross out contenders who are not suitable for the position.
The recruitment process in the world needs improvements. The problem with many recruiters is that they scout out graduates or candidates only from the best universities. Their primary activity consists of filtering those from renowned universities or don’t have a Big Name to back them up.
This is a massive understatement to graduates from technical walks. These students have all the required potential and qualities. However, they are deprived of fundamental recruitment equality as they don’t have mere mentions of reputed universities in their resumes.
What INVILENT believes is, there are hidden talents everywhere. Everyone deserves an equal opportunity to be recruited. It is where we think of implementing algorithms in the hiring process. Talent research algorithms remove all kinds of subjective biases from a recruitment process. So the possibility of missing out on high-quality candidates significantly decreases.
Moving With the Dream
To realize our target, we appointed Universiti Sains Malaysia as practicum host. The university will organize and train master’s students with classified courses for six months. The structure is designed according to the Masters’ curriculum of Data Science and Analytics.
Here’s what we expect from the talent data research program:
- Refining hiring accuracy
- Reducing employee turnover rate
- Accelerating the development speed for research projects
- Escalating the income rate for marketing and sales departments via employment clarity
- Improving the employment productivity for operation staff
I would like to address the symbiotic relationship between INVILENT and Universiti Sains Malaysia. USM is regulating and monitoring the steps behind the algorithm development on their premises. On the other hand, INVILENT is providing a robust ground for USM’s master’s level students. We are supporting the thesis and final year projects of the students with lucrative opportunities. Having INVILENT’S name linked to their projects can help the students stand out among the overly competitive market.
The algorithms will be designed to look for precise characteristics and qualities. We hope this little technological upscale will eliminate hiring biases from the industry. It’s our dream to eventually convert talent data research algorithms as a crucial tool for every hiring industry.
Decades ago, a first-rate academic degree was all students needed for their dream job. But in today’s reality, only good grades do not quite fit in the picture. The earlier you have gained the experience, the better! Most hiring companies want to ensure they are hiring experts in specific niches.
But students who have only gained academic lessons in these niches do not have any practical work experience. As a result, they are lagging on both labor markets and personal development.
That’s where practicum comes into the picture. These courses guarantee students are receiving real-time experiences instead of a clean piece of paper. It is what motivates them to break their limits and participate in some real work. I think practicum courses are the perfect foundation to design our talent data research algorithms. The skills students will obtain are colossal additions to their CVs. It will also give us some metrics to perceive our algorithm.
Masters students from technical sectors are invited to join our program. The program ensures practical skills development for the participants. It will help students discover their capabilities and inherent skills.
INVILENT is currently working with three students on this research project. The mission of this study is to observe student profiles from their interview sessions closely. Due to the pandemic, we are allowing Work From Home opportunities.
From the recorded sessions, we will try to identify the strengths and weaknesses of the participants. Gradually we will integrate our findings to devise resume screening, interview methodology, voice algorithms, and face identification.
I believe this will be a revolution to establish a modern recruiting process. Corporate companies engage qualified HRs to conduct the hiring process. But for SMEs, it’s an entirely different story. They cannot afford to appoint such distinguished HRs. So instead, they just pass on the responsibility to the admins or clerks. This is a time-consuming process since they don’t have the option to skim out candidates.
What I think is, clerks are not the appropriate interviewers. Recruitment is a sensitive topic, especially when we have to hire managers and executives. Only the authority knows which candidates are the best fit for their company. So, it’s always clever for the owner or administration to directly conduct the interview. I know they are the busybodies of an institution. However, having a picture-perfect team for a company is a blessing. To expedite the lengthy recruiting process, they can easily opt for the talent data research algorithm.
Since technology is the present and future, joining hands with such a program is wholesome for everyone. These talent research algorithms promise an effective screening process, reduced hiring duration, and improved employment structure. The talent data research algorithm will target developing an elite recruitment process.