Importance of Placement Data in Choosing College

Placement is one thing that I have written a lot about over the last 10-15 years. Most of the time, I have pointed out that it is impossible to get trustworthy information about placement from universities and hence this should not be a criteria for selection of college.

Why parents love to hear about placement. Two things. One, it is seen as a proxy for quality of education. Two, every parent assume that their ward will get the highest package when s/he comes to final year.

First, the proxy for quality thing. Everyone would agree that they want high quality of education (in whichever way they define quality - whether narrow or broad, for example). The problem is that they don't know how to evaluate faculty quality, the quality of curriculum, the importance of flexibility and so on. But everyone understands money, and hence higher the money, the better must have been the quality of the institute.

Let us compare two colleges. In both colleges, there are 100 students, same discipline, etc. In one college, everyone gets a job of Rs. 6 lakhs, while in the other college, two students get a package of Rs. 1 crore each, and the other 98 students get a job of Rs. 4.5 lakhs each. Which one is more likely to provide a higher quality of education. Notice that the first college has a median and average of Rs. 6 lakhs. The second college has a median of Rs. 4.5 lakhs and an average of 6.41 lakhs. If you consider the highest or the average, the second college has better numbers, but one should think if they just got lucky with those two students. If the quality of education was really good, shouldn't they have a greater number of students with higher packages.

In my opinion, if  you want to consider placement as a proxy for quality, you should look at the median package. And, of course, that is difficult to get. Most colleges do not reveal that since average is almost always higher than median in placement data. Most colleges may not even understand what is median and may tell you average when you ask for median. But if it is possible to get median, take that as a more valuable information than any other placement stats.

The second thing was about the assumption that every parent has that their ward will get the highest package. Can we really say that if you work very hard for four years, you will get the highest package. One can easily say that students working hard to acquire knowledge and skills in the college will get a good job. But getting the highest job requires a bit of luck during the interview process and it also depends on what knowledge/skills are in the highest demand that year, which you may not be able to predict when you were in first or second year. And in any case, if you really care for money, you should care for money that you will earn in your career and not just the money you will earn in the first month.

The last point about placement is that the correct data is not easily available and what is interesting is that often even the students who have gone through this exercise do not have any clue about the data of their batch. I have many stories about colleges perceived among the best but have poor placements (I happened to have seen data), but if you ask anyone on the campus - student or faculty - they have the perception that their placements are great. Now, if the students who are going through the placements do not know about their own batch, how can you hope to get realistic data from anywhere. This perception of good placement happens because in a typical college, students who get good jobs host a dinner or a treat for their batchmates and hence everyone knows about them, and those who get poor jobs don't talk about it as much. So if we keep hearing good stories, we will assume that everyone is getting those good jobs.

If you have junk data and you take decisions based on this junk data, you are playing into a model which is based on Garbage In Garbage Out (GIGO).

A very large number of engineering colleges today are dependent upon software services industry (TCS, Infosys, Wipro, HCL and so on) for placing their students, and most of these companies pay a salary of around Rs. 3.5 lakhs, and hence a large number of colleges (including some of the very reputed ones) have a median job offer of Rs. 3.5 lakhs. Of course, they will always talk about the average which could be substantially higher. But remember, median is the closest proxy to quality.

At JKLU, the B.Tech. batch that graduated in 2022 had a median of Rs. 7.0 lakhs (double of a typical engineering college), and the initial indication about the 2023 graduating batch is that their median will also be Rs. 7.0 lakhs despite economy not doing too well, and many companies not recruiting or even letting employees go. (But still, I advise people to consider JKLU as their higher education destination only if they are convinced of the quality of its faculty, flexibility in curriculum, ability to spend a semester in an IIT or IIIT, and many other such things, and not focus on placements.)

Parents will now ask how they should decide for their wards, if they can't ask or depend on placement data. They don't feel comfortable taking a call based on other parameters like faculty, curriculum, pedagogy, etc. And my advice for the last couple of decades has been to visit the potential colleges. This is one of the most important career decision. They must invest some time and effort in understanding their options and no better way to do that than to visit the campuses that you are considering. If you talk to random students and faculty on the campus (and not just the admissions office folks), you will get a good insight into the college and that would help you decide.

 

What does Industry Readiness Mean for a College Student?

Educational institutions are not what they used to be. They no longer produce graduates that are "industry ready." This is something all of us in academia have heard often. But what is meant by "industry readiness?"

We are often told that we must update our curriculum regularly, to include technologies that the industry is currently working on. Since our faculty may not be able to update themselves so quickly, we should invite working professionals in our classrooms. Students should be encouraged to work on "live projects" (whatever that means). All this is supposed to ensure that the graduate when joins some company would hit the ground running. Currently, there is a lot of cost that companies incur on training and if that cost can be saved, our industry would be able to compete better in the global market.

But I still don't understand what will make students "industry ready."

In various industry forums, I ask a simple question. Will top 50 companies who generally hire graduates of the same discipline (say, Computer Science or Information Technology) come together and tell academia what programming language they want the graduates to know, and promise that 4 years later when these students graduate knowing that programming language, they will recruit them and assign them projects where they are required to work on programs in that particular language. (And programming language is just the most basic skill. We can ask the question about other knowledge elements and skills.)

I don't think any company can promise today that four years from now they will need only these technologies and not others. In such a situation, does it make sense to chase the dream of graduate being ready to contribute to a project on the day of joining.

When I pose such questions, some experienced industry veterans would point out that the industry readiness is not about removing the training requirement completely, but is about reducing the training requirement substantially. Can the graduate learn on the job, picking up a new skill or a new technology in a couple of weeks. Industry readiness, as per these experts is about having the skills to learn oneself.

This revised definition makes sense to me. And thankfully, it is possible to train students to be industry ready as per this definition. But, the folks visiting colleges for campus placements and those who attend these industry-academia workshops don't seem to be articulating this definition and therefore, there is utter confusion in academia.

The usual reply to this is that we ask for the graduate to be ready on day 1 in the hope that academia would provide graduates who are ready within a month of joining. So the day 1 thing is a negotiating position and they are willing to settle for day 31.

And herein lies the problem of lack of understanding of academia by industry. If an academic institution has to make its graduate ready for day 1, the curriculum and pedagogy will be very different than if the academic institution has to make its graduate ready for quick learning. So it is not a matter of negotiation since the two situations are very far apart. To make a student ready for day 1, an academic institution will have to select a few roles that it wants to prepare students for and have a curriculum that includes all technologies and skills needed for that role. But to make students ready for quick learning, an academic institution will have to have a deeper focus on basics, they will have to ensure that the student can apply knowledge from multiple courses (so do large projects), that the student can learn somethings on its own (through online or whatever) and after this, one can be reasonably sure that the student is ready for self-learning and will pick up any new knowledge/skills in 30 days.

So day 1 readiness means a narrower focus of education which is not good for either industry or for the career of the student. If industry really needs people who can learn things quickly, why not articulate that need clearly.

I am seeing some changes in industry already. For the last few years, it has become common for the job interviewers to ask what have students learn outside the curriculum. This is to see whether students have tried to do self-learning which is an indication of whether they will be able to pick up new knowledge/skills quickly.

If a company really wants the academic institution to prepare their graduates with specific skills and knowledge, they should recruit students very early on (say after 2 years or even earlier), start paying that student a salary (treat them as employees), ask them to take specific electives, do projects and internships as desired by the employer (since the student is now an employee), even ask them to take a semester off from academics and work and then come back and complete the degree, and if some student is willing to sign up for it, that would be fine. But demanding that all academic institutions teach a specific technology to all its students is not in the long term interest of students or even industry.

Of course, all this discussion is only about 20 percent of academic institutions. Eighty percent of academic institutions would not be able to prepare its graduates for day 1 or day 31 or day 101 irrespective of what definition of industry readiness is used.