Leader Talk: In Conversation with Mr. Atul Batra, Manthan


NASSCOM staff writer in conversation with Mr. Atul Batra, CTO, Manthan and Chair, NASSCOM Product Council.

AI is going to be the biggest disruption in the history of mankind. We are fast approaching the era of autonomous decision making where the machine will be increasingly making most decisions in our personal and professional lives

If you look up the company’s website you will find a line on the word “manthan”. It is a metaphor for deep contemplation; churning facts to arrive at a conclusion. Artificial Intelligence is arguably the most disruptive force today and is also the technology with which Manthan Systems is powering its future. We managed to eke out some time from the CTO’s busy schedule and were privy to much deep contemplation indeed.    

1. About Manthan – how the journey started. He weaved in his journey alongside.

The company would like to see itself as an evangelist of the new world. It was started 13 years back by Atul Jalan, a lifelong entrepreneur, with an inventive mind and track record of creating disruptive products and solutions . Right at the beginning by focusing on Analytics, the company made its intent very clear – to be ahead of the curve.  Back then, analytics had yet to capture popular mindshare and be considered mainstream which it did eventually. They were the pioneers in Pure Play Analytics being offered on the cloud. The steps they took earlier held them in good stead. Like, investing in domain expertise such as in retail and consumer industries coupled with a strong focus on technologies of the future such as cloud, big data, AI, married to mathematics, statistics and data sciences. The growth has been strong and steady and today the company has made its presence felt in 23 some countries.  Today Manthan is leading the race to be the provider of choice for AI on the cloud for retail and consumer industries.

Atul Batra has an extensive background in tech having worked for stellar names like Yahoo, Motorola and Sun Microsystems, before he joined Manthan 5 years back.          


2. The philosophy of “analyze, decide, do” at the core of Manthan’s innovation philosophy.

Expertly, he traced the journey of Analytics – from descriptive to predictive and now prescriptive. How it has evolved to help leaders arrive at better decision-making which is data-driven. He explained some of the solutions that reside on the cloud which help businesses perform better – the merchandizing decisions powered in Retail, through popular Manthan products like Retail Analytics. But it just doesn’t stop here and goes a step further. It also recommends on implementation of decisions and help businesses close the loop applying those actions. The philosophy is powered by the constant need for optimization of results by a continuous prescribe, act, measure and learn framework.


3. Tracing the journey of decision-support system to decision-making system to decision-execution system.

Tech has always been harnessed to understand business better. The early moorings can be found in Decision Support Systems (DSS), and today, Analytics & AI are at the forefront of intelligent and accurate business decision making. It’s prescriptive in nature and to give an example, he cited Customer Analytics, another Manthan product, recently benchmarked by leading analysts as one of the top ones globally, which helps understand customer behavior and target them better intelligently. Products like these are personalized and real-time and can accurately guide the marketer on optimized personalized targeting through multiple channels using sophisticated AI based recommendation algorithms. Manthan has developed an AI platform called Maya which is the World’s first cognitive platform for complex business analytics. It is able to discern conversations in natural language and activate all kinds of analytics including AI models for business decision making.  


4. The Product ecosystem in India – which are some of the specific areas that companies should focus & what kind of govt. interventions would be desirable?

It would be most encouraging to witness more participation in the B2B segment, beyond consumer internet which has had the most focus in the past. There are some hard problems to be solved and there is a huge global market for it.  Good news is that we are seeing some of that shift in the ecosystem particularly in the context of the Digital opportunity in India amongst businesses, big and small. He contrasted and spoke briefly on the startup ecosystem of Israel and the kind of focus that is required in India. India has established itself as a leader in IT Services, and, taking cue, for example, can we achieve something similar for business automation? He was particularly emphatic about verticalized AI-powered solutions made available through the SaaS model.

In Silicon Valley and Israel, top educational institutions and the industry work very closely – marked by the spirit of collaboration. Infact Silicon Valley was born out of a handful of universities largely Stanford. In India, somehow this has not happened. Focus on deep technology is yet another area that India should try and learn from Israel. In these countries, the startup founders often incubate technology even while studying – in their final years for instance. Here, top-tier institutions in India can have a strong role to play: formalize the process of IP building so that students can carve out startup ideas eventually which are commercially viable. These are also some areas of focus for the N­­asscom Product Council that he is Chair for.


5. A whole lot of digital technologies are doing rounds. The ones that are likely to work for India.s

AI, Cloud & IoT are some of technologies which have very high potential to disrupt many industries – healthcare, agri, retail etc. Given the sheer size of the market, the country can come up with incredible used cases which can be showcased to the world. Natural Language processing, Machine Learning / AR / VR are enhancing capabilities at a very rapid pace. Wide scale adoptions are likely to come by in the next 18 – 24 mths. 

6. The talent landscape in India. The entire process of re-skilling? What are some specific things that companies should do?

These technologies have no precedence and skills will have to be built ground-up. Not too many trained people are available in the market so the onus is on companies (large and small) to invest in re-skilling. For example there are estimated less than 30-40K data scientists the world over but the demand is multifold owing to the AI era. There are a few companies which allow a certain percentage of employees’ time to pursue innovative ideas / skilling etc. Such initiatives should be encouraged right across. Incubating in-house takes time and commitment from senior leadership. People should be allowed to fail. Not every idea is likely to yield results but that should not dither people from trying something new. And, be able to work with domestic and global research institutions closely. In Technology, things are happening much faster than we could have imagined. It is imperative that we break down silos and learn to collaborate better as an ecosystem. 

7. Pivots for Manthan for future.

They are pushing hard for AI. Like autonomous cars, the world is moving to an autonomous state. Initially machines will augment human decisions, ultimate they will be making most decisions. We are fast approaching a state where complex business problems too can be solved with AI in an autonomous manner.  He believes in “Singularity” and that the machine will one day exceed man.

8. His leadership mantra.

  • Empathy, trust. Don’t ask for permission, only forgiveness if needed. Culture at the heart of it so that people can be groomed / mentored to take up innovation, ownership & responsibilities.
  • The spirit of collaboration always kept alive and a win-win situation sought at all times.
  • Have a vision for the future and set up people for success accordingly, having prepared them with the right mindset and collective objectives and skills.
  • Building things is easier than scaling them which is amongst the hardest things to do on a continuous basis.

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