Data-driven ED-Tech and HR-Tech For University Campuses As an employer, imagine having access to the data analytics which proves that there are certain qualities in the campus talent pool that definitively represent the 'best' that they are looking for

The state of employability of college graduates in India:

• A joint report on Higher Education by FICCI (Federation of Indian Chambers of commerce an Industry) and Ernst and Young found – 93per cent of MBA's in India are unemployable.

• A report by Aspiring Minds found nearly 80per cent of engineering graduates to be unemployable, from a survey conducted on 150,000 engineering students.

This highlights the urgent need for an upgraded education and training system in our colleges.

The Problems

• There seems to be a tremendous gap between the requirements of the industry and what our education system is churning out. Surprisingly, this gap does not seem to be closing with the passage of time. One would have thought that with the availability of considerable resources at its disposal, the government would have by now figured out a way to close this gap. Or at least put a plan in place to make it happen.

Clearly, it hasn't happened. This is because in the majority of our educational institutions (and this includes the IITs, IIMs and in most of the popular colleges/universities), there are no systems in place which capture campus placements related data to generate actionable feedback that can feed into curricula design.

• Often, when recruiters visit campuses, they are bitterly disappointed with the quality of candidates who apply for the jobs on offer. As a result, most college placements feature only a handful of companies, with a high churn year-on-year as companies tend to stay away from campuses where they didn't find good talent the previous year.

This is the story of the majority of colleges in our country.

Notwithstanding the hype around 100per cent placements being achieved by almost every campus out there, it is an open secret that most colleges fall embarrassingly short of that number. Many of the students who are actually placed have to contend with a shockingly low take-home salary, which is vastly different from the one they expected when they got admitted.

While campus placements arguably remain the most advertised and followed annual event off campus, all the activity surrounding this event is rarely analysed and discussed once placements are over. The result is that, barring a couple of email threads and a few scattered excel sheets (which is what passes for record keeping and analysis in most campuses), the slate is wiped more or less clean for the next year.

As a result, thousands and millions of valuable data points are lost, along with all the insights which could have been generated from the analysis.

• Apart from helping the Training and Placement Cell to prepare the students better for next year's placements, these insights could have helped with redefining admission criteria, redesigning courses & curricula and allowed for relationships to be strengthened with the recruiters.

The challenge here is that the college management needs to have the vision to bring in these changes. Instead of Band-Aid solutions like hiring placement agencies and/or consultants to look for jobs for their students, a placement analytics platform represents a more concrete and permanent solution to the problem.

The Solutions

Importance of data-driven hiring

As a student, imagine knowing which qualities click for your favourite employers, how many of those are achievable and how many of those will require extensive training and labour.

At the same time, as an employer, imagine having access to the data analytics which proves that there are certain qualities in the campus talent pool that definitively represent the "best' that they are looking for, instead of relying on subjective analyses to arrive at these conclusions. These should be ranked parameters which have been tested over a period of time and over large amounts of data – a goldmine right?

Employability and Data

Is it actually supposed to be like that?

When it comes to making the most crucial decision in college – "your career', there is still massive uncertainty surrounding it.

Most of the activities that we perform in our jobs like making budgets, annual performance, AI modelling – all are backed by data. And yet it is shocking that there is hardly any concrete data or analysis to back our own career-related decisions. There is so little information about placements available to different stakeholders in the universities – students, the career cell, the institution and the companies - that it is almost impossible for us to be certain about anything.

Insights derived from data can help address this problem. It is more a problem of having the correct systems in place to capture the information and using analytics to derive insights. Every year's placement outcomes serve as the strongest and most concrete feedback on what the job market is willing to offer a certain level of skills/ education. It also indicates how many students are ready/ not ready for the real world. And finally comes the step of providing the right information to the right set of stakeholders.

Unemployability isn't a problem that can be solved by career cell and students by themselves. It becomes the responsibility of the entire ecosystem to help make the next generation employable – including the university and the companies. And that is why it is so important to put systems in place which help universities and companies collect the right data and share crucial insights with all stakeholders.

In 2008, Dr Kalam cited employability as a bigger problem compared to unemployment! He cited that universities should invest in producing quality human resource who meets the needs of the industry. It's time we address the elephant in the room, isn't it?