Sramana Mitra: If you put yourself at a 30,000-foot level, what do you see? What are the open problems in the industry? What are the white spaces in the industry?
Ashish Sharma: If I were to focus on these two industries, there is a strong need that is getting defined and driven by business. Businesses are now saying, “We are buying certain datasets and making investments into acquiring data, but I have difficulty including them into my studies unless you focus on data infrastructure being modernized.”
The investment for the whole inclusion of these diverse datasets cannot be justified. One thing that is driving it is huge investments in data infrastructure. Both finance and pharma are heavily focusing on that. Hence you see more and more Chief Data Officers being created in both pharmaceuticals and finance. That’s one. If a company is investing on data, they’re asking for ROI. That was being hampered by not having the right infrastructure.
The second change that I’m seeing is that in this whole scenario of having three different types of customers, every company is fighting to be more effective and efficient. With increased focus on efficiency, they’re forced to focus on reducing the cost of care and increase the efficiency of the analysts. How can I compete in the market by reducing the cost of competition and maintain a certain level of margin? Those are the general competing trends that I’m seeing.
Competing on data and insight is another. Businesses are pushing these organizations saying, “To deliver those kinds of efficiencies, I need to have a robust underlying infrastructure to leverage these data assets.” At the end of the day, it’s data that is driving the decision, which is driving the insights.
Sramana Mitra: Given all that, if you were starting a company today, what open problem would you go after?
Ashish Sharma: If you look at my short background, I’ve dabbled in leveraging unstructured data in many different ways from providing insights for security organizations to corporates, to experimenting with hypothesis on how to produce a feature film using social media data or by crowdfunding. What interests me the most is, I see a lot of value in publicly available data that is sitting outside the firewall. I see a huge opportunity in combining the data that sits outside the firewall and data that sits inside the firewall. How can you combine the two and start to see a pattern that one is actually influencing the other?
In one of the recent conferences at Pharmaceutical Management Science Association, I was co-presenting with a data scientist from Axtria. We both took social media data for some of the leading brands and we were able to demonstrate causality between their brand perception and how it is influencing sales. If I were to do something at this time, I would do something with the publicly available data by combining it inside the firewall data.
Sramana Mitra: Great. Thank you for your time.