- Like Post
Meet The Smart Cube’s Data Scientists: Ravi Bagiya
“There’s an expression: ‘The job of a scientist is to ask the right questions’. I firmly believe this applies as much to data scientists today.”
Ravi Bagiya has spent the best part of a decade working in analytics, helping major retailers to drive efficiencies and realise new possibilities. He talks to us about the industries making the best use of data – and what amazing things the future of analytics could entail.
A fork in the road
Ravi’s journey into data science came from a moment of decision. After graduating with a degree in engineering from Gujarat University, he had to make a choice between a career in IT and a career in the then relatively new world of analytics. One of those options was far more appealing than the other.
“I like maths and I’m good at logic, but I wasn’t particularly interested in just applying that to coding,” he says. “I thought, you know what, I’m going to try data science. And if it doesn’t work out, I can always get an IT job later down the line.”
Eight years and counting, that moment hasn’t arrived. Ravi now specialises in helping The Smart Cube’s major clients, including one of the UK’s biggest supermarkets, find new ways to succeed in an increasingly difficult industry. “In retail right now, everyone’s scared of Amazon,” he says. “Customers want to shop online, and Amazon entering the grocery market is giving supermarkets a lot of food for thought.”
Driving efficiencies with data
In his role supporting the implementation of The Smart Cube’s analytics solutions for clients, Ravi works directly with in-house analytics teams, and acts as a liaison with other business teams and their senior stakeholders, to embed data-driven best practices and processes.
“This is a lot more interesting to me than just looking at data in a silo,” he says. “It gives me really good exposure to how things work on the ground, and how business strategies are actually formed. In turn, that helps me to ask the right questions and really help our clients find the answers they need.”
And clearly understanding the question you are seeking to answer is absolutely key, according to Ravi: “French philosopher Claude Lévi-Strauss once said: ‘The scientist is not a person who gives the right answers, he is one who asks the right questions.’ I firmly believe this applies as much to data scientists today.”
So far, Ravi’s work in the retail space has involved executing projects designed to increase customer engagement, optimise pricing, and identify the promotions most likely to provide the highest returns, to name but a few.
These are the kinds of projects retailers are increasingly undertaking to help overcome the industry’s growing challenges. When you’re operating at scale, small improvements can have a big impact, but these areas for improvement aren’t things that can be seen with the naked eye.
However, Ravi notes: “Even though a lot of analytics solutions use real time data, the implementation is nowhere near real time, be it customer targeting, market mix modelling or attribution, and I think that is going to change in near future.”
In fact, as data science goes, retail is by no means leading the charge.
The industries nailing the numbers game
“As you might expect, the most ground-breaking things are being done in the tech space,” Ravi says. “These are the companies who capture customer data at every touchpoint, and use this information to expand the landscape of their products.”
Gaming companies for example are going to the next level – they know everything about you, how many times you log in, how active you are, everything. Whereas once a game would be a one-off, physical purchase, we now have a huge influx of casual, mobile titles full of in-game micro-purchases.
These games create veritable treasure troves of user data, which is used to deploy the promotions and must-have content that keep players wanting more.
“There are traditional industries doing some advanced work too,” Ravi continues. “Telecoms, insurance and advertising are the ones I see implementing data-based decision making to the greatest extent.”
Get ready for growth
Although some industries are showing more maturity than others, Ravi thinks it won’t be long before the rest catch up – especially with analytics tools becoming cheaper and more accessible.
“I’ve seen an increase in awareness of the power of data in all markets,” he says. “In a couple of years, I think even small companies will be using analytics in some way.”
Ravi believes a big factor in this change is technological progress, particularly with open source and cloud computing. Where SAS was once the industry standard, open source big data technology means that more capabilities are now available at a much lower cost. Cloud computing ensures everything is scalable, and removes constraints to expanding storage infrastructure, enabling data to be stored at highly granular levels.
“The thing about open source, is that it evolves so quickly,” Ravi says. “The power of the community informs product design, which means one major feature is its user friendliness. This kind of collaborative development is what will really drive the industry forward.”
The grand masters of analytics
So, what kind of future will this create? What will tomorrow’s analytics look like?
Ravi believes the theory is already all there, citing DeepMind’s AI algorithms beating computer brute force engines at chess as an example. But chess is a perfect information and closed system game. AI has now been extended to algorithms like Pluribus, which beat WSOP professional players at poker, which is not an objectifiable game and there is no one right move.
“Everything’s getting more sophisticated, and it’s happening at an incredible rate. We are certainly going to see more cutting-edge applications of AI in big data that will change the entire landscape in the next decade,” Ravi says. “I’m very excited to see what the future holds.”
Want to meet more of The Smart Cube’s data scientists? Keep an eye out on our blog over the coming weeks and months!