Answering the ‘Whys’ with ‘Whys’: Data in Development

When I booked the cab to commute to office earlier that morning in August, it felt unsettling knowing that I wouldn’t be entering the same address ever again. It was my last day at work and, starting the next day, life would be different. “How do you feel?” my colleague asked me excitedly and to answer her I simply replied, “I am trying not to think over it”.

And that was exactly my state of mind! Blank! My job was one of the best things that had happened to me after college: a reputed organisation, an amazing set of people and all the perks that came along with it. And here I was leaving behind all that I had worked towards to charter into unknown territories. “Why?” was the question everyone around me asked. “Why?” was the question I asked myself.

I have been a techie for a good portion of my life now. Being a software engineer was never a conscious goal that I had but a number of small and big decisions cumulated to bring me down this path. Programs and codes have always interested and awed me, by their sheer power to deconstruct and simplify things, by their ability to automate the mundane and create the new. And it was this fascination that finally culminated into a profession. But when it came to the question of what next, I would always draw up a blank. I was looking for excitement, fulfilment and for myself.

While in the search for these answers, I tapped into my interest in the socio-economic sector and chanced upon a world of data-driven policies, randomized controlled trials and scientific research in the domain of development economics. The questions on why the poor continue to be bridled in poverty, why they struggle to make ends meet across generations, why the vicious cycle of hunger, debts and diseases is all-consuming for a certain part of our society has been of the greatest mysteries of the world. Billions of dollars in charity, countless hours of volunteering, and the tremendous work done by organizations for the betterment of this sector has hardly got us any closer to a more equitable society. The slums still border the high-rises, dengue and malaria continue to threaten our very existence and an empty stomach is what a majority of the developing world sleeps on.

Why do these people with the limited resources that they have – make the decisions they make? Why do they borrow from the money-lender offering exorbitant interest rates? Why do they not use the toilets built for them? Why do they not get their children immunised from something that could potentially kill them? Why do they continue to expand their family knowing that they lack the resources to sustain it? Why do the streets flood on a rainy night, and the polluted air chokes on a busy day and still people make their peace with it? The crumbling infrastructure, unaccountable institutions, the uneducated masses – who ultimately shares the blame?

As we transcend towards the age of self-driving cars and colonies on mars, these pertinent questions still remain largely unanswered. Artificial intelligence has given us talking assistants guiding us through our day, maps that direct us, apps that know us better than we know ourselves and yet the divide between the “haves” and “have-nots” is nowhere getting thinner.

And hence, it was with the realisation of these facets of the world around me, that I decided to take out one year out of my career to explore the tenets of these daunting problems. No, I am not making tall claims to find out the solution to world hunger or a way to eradicate malaria, but simply to understand what would take us to move towards that direction. And how do I plan to go about it? By using the gold of today – data.

Illustration of networks that connect people across the world via Facebook. Photo courtesy of Facebook. Source:!v1zfE

Every step you take is lodged in a server in some part of the world, every click on the internet is tracked, every phone call that you make, every bill that you pay gives a sneak-peek into your life. And all of these data points join together like a jigsaw puzzle to define the person that you are. The most efficient algorithms use this data of yours to tell you what movie you would like, or how late you are for work, or how much traffic you might encounter on your way today. Along with these amazing applications, what if the data could tell us the migration patterns of the people in rural India? What if the call records could help us predict the potential default rate of rural entrepreneurs looking for loans[1]? What if GIS data could be used leverage to gauge the impact of drought on weather conditions and settle insurance claims of poor farmers[2]?

These and many more approaches to designing data-driven policies can not only help in formulating solutions, but can also go a long way in understanding the crux of the problem itself. And it was with an aspiration to explore these ideas and possibilities towards a more informed policy making approach, that I undertook the AIF Clinton Fellowship with IFMR LEAD (Leveraging Evidence through Access and Development).

IFMR LEAD is a non-profit research organization based in India conducting high-quality scalable research and outreach in development economics and finance. It collaborates with leading professors and economists, development specialists, and industry experts on research design and implementation, and data analysis and dissemination.

Seeking to complement the traditional statistical research methods with data science and machine learning techniques to unearth deep seated patterns, the organisation is aiming at setting up an Analytics team. The aim of the Analytics project is to contribute to the innovation, usage and promotion of knowledge in advanced analytics for research, policy and practice in socio-economics and development. With my prior academic and work experience in computer sciences and data engineering, I aspire to be part of the Analytics initiative at IFMR LEAD to drive innovation and produce impactful research during the tenure of my Fellowship. Looking forward to “Serve, Learn & Lead”!


[1] Bjorkegren, Daniel, and Darrell Grissen. “Behavior Revealed in Mobile Phone Usage Predicts Loan Repayment”. SSRN, 13 July 2015. Available at:

[2] European Space Agency. “Sentinel-1 Speeds Up Crop Insurance Payouts”. 17 Aug. 2017. Web.



An Indian by nationality, an engineer by profession and a tinkerer by habit, Asra aspires to explore the world beyond its confines and come up with solutions that can drive change, thereby promoting better quality of life for all. A Bachelors in Technology specializing in Computer Science & Engineering, Asra has worked for a leading Bay Area company for two years before taking up the AIF Clinton Fellowship. With the goal of applying technology and analytics to the field of developmental policy, Asra is seeking to answer some of the pertinent challenges faced by India's development sector. During her tenure as a Fellow, Asra will be working with IFMR LEAD in the domain of data science for public policy. When she is not mulling over life and its intricacies, you might find her engrossed in a book or enjoying an engaging conversation.

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