Varun Aggarwal completed his Bachelors of Engineering from NSIT, University of Delhi and holds a Master’s degree in Electrical Engineering and Computer Science from MIT. He co-founded Aspiring Minds with his brother Himanshu Aggarwal in 2008 and together the two have built it into the world’s leading job credentialing company. As CTO, Varun oversees delivery, operations, product design, research and new initiatives. Under his guidance, the research group at aspiring Minds has developed the world’s first machine learning based programming assessment, the world’s first automated test of motor skills and the only scalable way of spoken English assessment.
Varun is a recognized expert on developing and applying statistical learning and optimization techniques to real world problems, including circuit modeling and design, parallel processing and network coding. His work has been published in more than 20 technical publications and he has five US patents pending, including his work for the algorithms he developed for Aspiring Minds. He is the founder of the MIT India Reading Group, a platform for collaborative research on socio economic issues in India. He is also the co-founder of CURE, an organization working against hazing (ragging) in India.
Varun was awarded the HUMIES award in 2006 for developing algorithms that mimic human intelligence and the AWA award for his article on Bose’s contribution to the invention of radio. He has been a prominent speaker and panelist at Harvard University, MIT, INSEAD and IBM Research Center (NYC). In an attempt to understand the value proposition created by Aspiring Minds and to paint a more vivid picture about the recruitment analytics landscape in India, Analytics India Magazine interacted exclusively with Varun Aggarwal. We present to you the detailed interview as follows.
Analytics India Magazine: Enlist the factors that spurred the conception of Aspiring minds. Elaborate about your journey in the recruitment analytics space.
Varun Aggarwal: The emphasis on rote learning and theoretical education in schools/colleges is often one of the primary reasons for poor job readiness among
students. In such a scenario, regular certifications in the form of college grades/GPAs cannot be relied upon to accurately validate skills or competencies of students. Also, with the job landscape changing drastically, higher education is no longer a credible indicator to employability. Aspiring Minds is a global job skills credentialing leader and has developed some of the world’s most advanced assessments backed by state–of–the-art, adaptive assessment technology and machine learning algorithms.
Our flagship product AMCAT allows adaptive, standardized and reliable measurement of generic employability skills (language, cognitive, behavior) as well as a wide range of functional skills. This enables students to get a scientific job readiness feedback and earn industry recognized credentials to find appropriate career opportunities. While, on the other hand companies are able to get predictive analytics on the suitability of a candidate helping them improve their recruitment efficiency and bringing on board the ‘right’ talent. The pre-employment tests become even more critical in the blue collar segment where there are no real indicators of qualification or job readiness. This is where innovative technology driven assessment solutions are playing a significant role in the hiring mechanisms of organizations by helping them identify the ‘right’ talent.
AIM: What are the key impediments in the recruitment analytics space? What are the strategies employed to make the space more efficient?
VA: Organizations, especially ones with 500+ employees, often receive hundreds of applications against job roles and manual screening of such large applicant volumes is bound to be error-prone, long-winding and costly. In fact, a study suggests that human recruiters spend an average six seconds reviewing an individual resume and 80% of this time is spent on name, current title/company, current position start and end date, previous title/company, previous position start and end date, and education. This process can leave out an optimal pool of potential employees from the race.
While effective recruitment is at the heart of HR responsibilities, hiring the right candidate for the right job in a cost and time effective manner is one of the key challenges faced by modern day HR. Finding the right talent is critical for business success. That is why we should make the right decisions while hiring. When it comes to decision making in any part of a business structure, it is better to put data and analytics to use.
Streamlining the hiring process along with improving its quality takes more than just a good hiring team. That is where recruitment analytics help companies evaluate candidates in a holistic way. While our technology ensures reliable and precise evaluation, the adaptive and standardized nature of our tools ensure their use for making the right talent decisions. All our assessments imbibe the latest science in evaluation & matching excelling and setting global standards of quality. Our tools powered by state of art machine learning, statistics and simulations use a wide range of technologies to ensure you get the best.
AIM: What is state of analytics in India? How is Aspiring Minds making difference with its analytics-dedicated offerings?
VA: Technology is advancing in an ever-evolving world, and our lives are changing just as rapidly. The recruitment domain is undergoing a technological churn as well. The overall process of hiring today is undergoing substantial changes and we at Aspiring Minds are developing advanced assessments backed by state–of–the-art, adaptive assessment technology and machine learning algorithms to contribute to the recruitment analytics story in India and abroad. Our flagship product AMCAT allows adaptive, standardized and reliable measurement of generic employability skills (language, cognitive, behaviour) as well as a wide range of functional skills. This enables students to get a scientific job readiness feedback and earn industry recognized credentials to find appropriate career opportunities. While, on the other hand companies are able to get predictive analytics on the suitability of a candidate helping them improve their recruitment efficiency and bringing on board the ‘right’ talent.
The pre-employment tests become even more critical in the blue collar segment where there are no real indicators of qualification or job readiness. Powered by Aspiring Minds’ TESLA technology, the assessments are reliable, standardised, valid and ensure high integrity results. This is where innovative technology driven assessment solutions are playing a significant role in the hiring mechanisms of organizations by helping them identify the ‘right’ talent.
AIM: Walk us through your solutions which make use of analytics? How are these solutions helping your clients find the right talent?
VA: At Aspiring Minds, our vision is to create a merit driven talent ecosystem and enable efficient job skills matching by crafting credible recruitment analytics and assessments. Our flagship product AMCAT is the world’s most widely-taken employability test helping over 2 million candidates find the right jobs every year. Backed by state–of–the-art, adaptive assessment technology and machine learning algorithms – it allows adaptive, standardized and reliable measurement of generic employability skills (language, cognitive, behavior) and a wide range of functional skills using simulated assessments.
We also help companies dramatically improve their quality and efficiency of hiring and are today associated with more than 3500 corporations. Some of our other products include Automata – Machine Learning powered programming assessment; SVAR – Voice recognition and synthesis to automatically evaluate spoken language skills; TESLA – A versatile simulation platform for vocational evaluations; AM Situations – A situation judgment psychometric test to reliably evaluate soft skills and practical intelligence. Lastly, we have Simulations test – to assess Contact Center Skills for Voice and Chat Support roles.
AIM: How is your recruitment analytics customized to find the right talent for the right people across various industries?
VA: We’ve helped a variety of industries in locating high quality & credentialed talent. We help deploy benchmarked talent across branches and our tools leverage cloud, device & streaming to ensure best in class reliability, scalability and reach. Our assessment tools are powered by state-of-the-art IRT, Machine Learning and Simulation technology. We have a comprehensive portfolio of assessment tools that can measure a candidate’s knowledge, skills and abilities. The various industries we cater to include Banking Finance & Insurance, Automotive, Business Process Management and Analytics, Information Technology, Hospitality, Retail Industry, and Telecom, among others. To understand industry-wise solutions, better click here.
AIM: Any advice for the startups and other organizations in India who are striving ahead in the recruitment analytics space.
VA: Startups have been competing with bigger corporations to get the best talent on board, but the war for talent has grown more severe in the past months. Startups don’t have the luxury to invest in training unlike large organizations. Startups are looking for people who are ‘job-ready’ and can learn quickly on-the-job. Most young startups today are faced with scarce resources and funding. In this scenario, setting up an elaborate recruitment mechanism not just becomes impossible but HR as a function invariably takes a backseat. Startups need to address this lacuna by leveraging recruitment analytics to build the right set of assessments that can accurately and objectively assess skills and better predict a candidate’s job performance. The assessments can offer dramatic insights into the skill set of candidates for over hundreds of job roles and competencies. The scientific assessment tools already available today can play a significant in talent filtering and in helping startups hire the right people for the right job.
Try deep learning using MATLAB