Neelesh Bora
Interactions with faculty and industry experts help you understand the power of data-based decision making, how the markets may evolve and where the opportunities could be.
Could you tell us a little about your background?
After a successful stint of 3 years at Jones Lang LaSalle – an International property consulting firm, I decided to move on to set up my own company – Bora Housing Limited – a start up real estate company which specialising in development of Holiday Homes & Residential Homes in Chennai. I handle the Sales & Marketing and also focus on planning & feasibility of new projects. Today, technology has got a huge role to play in the construction industry but is not in effective practice due to lack of professional approach. And I wanted to implement analytics in real estate to change the way projects are being sold, planned and executed. The aim was to apply analytics to understand the way real estate market is evolving and change the way projects are planned, sold and executed.
Why did you choose PGP-BABI at Great Lakes?
I enrolled myself in the Business Analytics program and in hindsight, this was a highly rewarding experience. What Great Lakes faculty bring on the floor is brilliant and peer interactions add a lot of insight to your thought process. There are lots of on ground examples shared which encourage you to learn more.
Please describe your experience at Great Lakes
Simultaneously, when you have the industry stalwarts talk about the projects of the past and future; it certainly gives you a good idea of market knowledge. This especially helps when you are a young startup company. Most of these faculty and industry lecturers have exposure to developed markets and they give you good knowledge on how the market is evolving. These interactions helps you understand the power of data based decision making in understanding how markets may evolve and where the opportunities could be. Thanks to my learnings in the Business Analytics program, I use analytics at work to understand the evolving customer behaviour, predicting the curve in sales volume and the factors around it.