Name an instance where you wanted something and went out of your comfort zone to achieve it OR Tell us the biggest risk you have taken so far in your life.
During my final year major project in engineering, I worked on a wheelchair prototype guided by eyes. The idea was to use digital image processing to track eye movements and guide the wheelchair prototype in the direction of the eyes. It was tailored for quadriplegics, a person affected by paralysis of all four limbs.
Initially, we (my team) fared well. We decided on algorithms and processors for the hardware unit. But as we progressed, we found it exceedingly tough to integrate the wheelchair prototype. Even the faculty and friends suggested using some tactical/physical cue to guide the wheelchair and later suggested to drop the project altogether. That would have defeated the purpose. We decided to give ourselves a week to see any substantial progress.
Eventually, perseverance paid. Not only we successfully integrated the hardware, but we also brought down the response time of the prototype. The same year, our college had applied for course accreditation to NBA (National Board of Accreditation). Our project was one of the few projects demonstrated to the NBA team. Also, a proposal was sent to the Government of India for funding worth INR 1.5 Crores for further developments.
When was the last time someone relied on you? OR What did you do which was purely for someone else - a truly selfless act.
It was vacation after a tough semester and equally grueling exams. Most of us were heading to home and relatives for the rest of the winters. Rows of bags lined the hostel entrance with frequent arrivals of cabs, happily ferrying students to airports and railway stations. I was available for an extra day and my friend, heading an NGO, suggested that I accompany him for a field visit to a slum nearby. I had no plans for the day. Hence I agreed.
I had read about the contrast of haves and have nots in society and was unaware that a similar situation existed roughly two miles from my college. The slum consisted of rag pickers and their families. Due to low/nil primary education and hygiene issues, most schools nearby didn't accept them. Throughout the day, we profiled students to make a strong case for their admission to schools nearby.
I left for home the next day. While traveling, I came up with a plan to train these kids on soft and hard skills. My friend and I worked through the month. We designed the curriculum, arranged stationary, recruited volunteers, and sourced funds. End of vacations - both of us started implementing the program. With 25 volunteers, over eight weeks, we trained 45 unprivileged children in the Bawana slum area. The ratio of volunteers and students was capped at 1:2 for better learning outcomes. At the end of the program, we mapped students' skills and prepared a dossier for pitching to local schools. The acceptance rate for admission to schools increased by 40% year over year in the next season.
It was not a selfless act. My college, Delhi College of Engineering, is built on the land acquired from these people who had to shift to slums nearby. I was driven by the nagging sense of giving something back and was bullish on the outcomes. I still remember the glint in the children's eyes when we donated a laptop; probably, they had it for the first time.
Tell us about a time when you disagreed with an opinion/idea/decision. What did you do about it?
Before the start of the MBA session 2020-22, a bunch of us at IIM Kozhikode decided to create an informal group to guide incoming juniors with their CV and profile building process. Given depressed economic conditions, we expected the summer internship process to be challenging; hence the group was aptly named ‘Head Start.’ It was based on our experiences during summer internships, where some of our batchmates faced difficulties and had less time to build their CVs and profile before interviews.
My senior at work once told me there is no free lunch, and even if it seems so, then there is someone paying for it. I proposed charging a nominal fee to keep both the team and students serious about commitments. The group agreed on donating whatever amount we collected to the social service cell in our college, which was to be further contributed to the orphanages in Calicut. All of us agreed on the plan and posted our initiative on social media.
First 10 minutes, we had more than 150+ sign-ups across the colleges. We were ecstatic. However, it was short-lived. We were contacted by the student committees at college and were asked to pull down the post. Despite insisting that the initiative was not related to IIM Kozhikode, there was a massive outcry with some of our batchmates accusing us of siphoning the expected funds from the initiative. The social service cell decided not to continue with us, and seeing the response across quarters, the rest of the team members decided that we close the initiative.
I disagreed. I knew the upcoming summer internship process could be overwhelming for students. A nominal fee (we proposed INR 100 per session for three sessions) wouldn’t hurt anyone, given that we had decided to donate the entire amount collected from the initiative. After discussing for more than 4 hours with committees, seniors, and batchmates, the group decided to proceed with the idea. Instead of the social service cell, we requested the participants voluntarily donate to the Akshay Patra Foundation.
Through three phases, we reviewed and guided over 400 students across multiple colleges. I am sure our suggestions must have helped students, possibly prepare them better for the expected process. We sent regular reminders for donations if they were satisfied with our work and collectively decided not to track the contributions as it might have put pressure on the rest. However, even if someone donated a single meal, that would have fulfilled the purpose.
What is the one thing you can claim to have some level of expertise or depth of knowledge in - it could be anything - a subject, a sport, a hobby, a venture, an initiative which has led you to do deep work in that field?
I have some level of comfort in Statistics. I took econometrics in the last semester of my under graduation. There I first encountered statistics and its application in economics. After graduation, I joined ZS Associates in a business consulting role. There I worked extensively with applied statistics, not just the theoretical part but executed projects for Fortune 500 clients.
While working, I realized how numbers could be used to craft a story. Understanding statistics gives the ability to interpret figures often quoted at multiple places. You start questioning the metrics, often enquiring more on sample sizes, base effect, etc. And this quantitative outlook has benefited me. I could answer questions in interviews, had less difficulty in data analysis and operations courses in MBA, and also help my batchmates. Knowledge of statistics helped me implement Machine Learning models in my internship at Uber.
I keep improving my skills in the area. I regularly sign up for MOOCs and positively complete those. Given the nature of rapidly changing business with algorithms guiding our decisions, I hope this skill will keep me in good stead in the future.
If 10 Million Dollars (approximately INR 75 Crores) is given to you to use it any way you deem fit what would you do with this corpus?
A believer in charity begins at home; I will divide the corpus into five tranches:
Tranche 1:
I will pay for my education loan.
Tranche 2:
I belong to a small village near Samastipur, Bihar. The majority of the poor in my village were pushed into poverty due to two significant reasons:
- A loan from loan sharks
- One time expenditure on a disease
The local loan shark charges 35% interest, compounded annually. The interest payment takes a massive chunk of families' income, and they usually refinance by taking another loan, often from the same shark. Due to high-interest charges, they also have to compromise on food, education, and necessities. I would repay the loan shark and then spread the payments for these families over a more extended period. A team would be formed for recollection, and the investment would be recovered at a nominal interest rate, equivalent to the savings account rate.
Tranche 3:
Sulabh sauchalaya model for village health emergency services :
The government under Ayushman Bharat covers health-related expenditures for low-income families. However, emergency services are in shambles in impoverished areas. Local PHCs are either existent on paper or are in dire need of resources. The third tranche would include training individuals in villages for emergency services. These individuals would be kept on payroll and would respond to emergency services in the area.
Tranche 4:
My grandfather was a headmaster at a government primary school, and my mother teaches at a government middle school in a village. Hence, I was privy to the pitfalls of the system from an early age.
Most parents enroll their children in schools in villages for government benefits: free food, clothes, bicycles in case of girl child or scholarships. However, similar benefits aren't available for higher education. The loss of labor (children working in fields after school hours) and the inability to pay the fees force them to drop out. Loss of labor is hard to substitute, but any financial help for higher education can sway the decision. The fourth trance would be invested in a low yield, low-risk fund (similar to pension funds), the returns on which can be used to sponsor the higher education fees and needs of these children.
Tranche 5:
Personal Investments:
This tranche would be further split into two. The first will be used to invest in alternative investment funds as with the corpus I would be counted as a high net worth individual. I would keep the remaining money in a fixed deposit for my higher education in the future. With the pace of change, the skills I learn today may be obsolete in the future.
I would conduct a pilot first for tranches 2,3, and 4 to determine the tranche's size and feasibility. There would be multiple pitfalls and loopholes in the models, which can be iteratively improved before scaling to mass.
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