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TDWI Upside - Where Data Means Business

5 Minutes with the Chairman: Venkat Viswanathan of LatentView Analytics

Venkat Viswanathan is the cofounder and chairman of LatentView Analytics. He spoke to us about what it's like to be the leader of an analytics company and about the role of the analyst.

Managing a business is certainly tough; managing one that recently passed its 10-year anniversary speaks to skill at maneuvering through tough business climates. Upside spoke to Venkat Viswanathan, founder and chairman of LatentView Analytics, to learn about his job as a business leader and the challenges analysts face.

UPSIDE: What's the one thing you wish people knew about your job?

Venkat Viswanathan: This year, LatentView is celebrating its 10th year in business, so I feel a strong sense of accomplishment. The journey has not always been smooth. No entrepreneurial journey is. At times, it has been difficult and lonely. In order to succeed, entrepreneurs need sheer willpower and determination to push past the bad times while staying attentive to further opportunities that present themselves.

Are you working on anything interesting right now? If not, what's your dream project?

We are working on building some cool ideas and technology where we combine data from different sources to get a very granular understanding of consumers. Competing on data will be a lot more common in the decade ahead and we could be a great enabler for our clients.

What's your favorite part about being an analyst/data scientist? Your least favorite part?

I have a very capable team which is a lot more adept in data analytics than I am. What I enjoy about this field is that it gives me the opportunity to work with some of the brightest minds in an industry where technology is changing so fast. It's important to build a test-and-learn environment that allows people to explore, do 'what if' analysis and question existing assumptions. The fun part is invariably the ideation and asking questions of the data that lead to the discovery of actionable insights.

My least favorite part is the more mundane processes that need to be followed to run a successful, growing business. Scale needs structure. This is necessary even if it's not exciting for everyone.

If you could go back in time, what's the one thing you would tell yourself as a new analyst/data scientist?

I would tell myself not to get caught up in the math. Too often data analysts get so consumed by the data, they fail to step back and look at it with business and human filters.

In order to deliver actionable insights, you need to understand the business context. I always say, "Business + Data + Math = Actionable Insights." As a data scientist, it is essential that you maintain a balance between all three elements.

What's a personality trait you think people need to succeed at your job?

As a data analyst: curiosity. The best insights have been uncovered by people who were not just bright, but also curious. I would add storytelling as a necessary personality trait as well.

As an entrepreneur: integrity. Teams and long-lasting client relationships are built on a deep foundation of trust, and doing business in a consistent manner and winning the right way secures our future.

What's a typical day like for you? Do you work mostly with a team or mostly alone? Which do you prefer?

No day is the same. As we are growing at a rapid pace, several new challenges that need attention crop up. As an organization, we spend time listening to concerns from various team members and understanding them before we reach a decision on the path forward.

I also spend a lot of time understanding new technologies, services, and gadgets and the changes they will have on the world we live in. I must admit, I end up buying a lot of these, too.

What's your biggest pet peeve (abused buzzword, overhyped idea, etc.) and why?

This changes from time to time. A year ago it was big data. Now it's AI. Everyone is talking about it and wants to use it, but in most industries it's only decisions at the periphery of a business that are seeing any automation. It isn't as prolific or game changing at this point as people make it seem.

Is there a tool or technique that isn't popular today but has a lot of potential? Why?

Although geolocation data is very commonly used, I'm excited about the progress we are making with it and the wide range of applications it can have for businesses. With the growth that we are seeing in mobile commerce, I see a lot more disruptive applications emerging that use geolocation data.

Whether it's the latest Python build or a 50-gallon drum of espresso, what's the one thing you can't do your job without?

LinkedIn! I find some of the key ingredients to sustain business success are enabled by a great network. This includes attracting and retaining talent that aspire to be thought leaders in our own peer group, and nurturing a strong business network that will readily "pay it forward." I wish I had more hours to learn, give, and gain from LinkedIn.

What's the most common roadblock you hit in your work? How do you deal with it?

Fear of failure. When we were younger and smaller, we approached opportunities with lots of energy and naively took on tasks without seeing gremlins everywhere. Eventually, we did find ways to succeed. As we scale, sometimes teams tend to be more cautious and become inhibited when faced with the prospect of failure. Building a culture where failure is accepted, as long as we learn from it and eventually find a way to succeed, is the key to dealing with it. Unfettered communication -- lots of it and across the organization, not just top-down -- is one way to go around this roadblock.

Where is data analytics/data science headed in the next few years?

Many large companies, especially in industries such as consumer packaged goods and retail, will see disruptions by digital, analytics-driven start-ups that sell directly to consumers via subscription models. This will, in turn, force large companies to adopt digital transformation at a scale that they were earlier not prepared for. Analytics will play a huge role in this entire transformation. Companies will increasingly automate processes that enable faster customer service through the use of AI. However, these will still remain on the fringes of the business, where the costs of mistakes are not too high.

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Venkat Viswanathan is founder and chairman of LatentView Analytics, a large and fast-growing global data analytics firms. Based in Princeton, NJ, LatentView helps companies drive digital transformation and use data to gain a competitive advantage by providing a 360-degree view of the digital consumer. Venkat is the visionary behind LatentView and has more than 18 years of experience in management consulting, technology, and global IT services management. You can contact Venkat at [email protected].

About the Author

James E. Powell is the editorial director of TDWI, including research reports, the Business Intelligence Journal, and Upside newsletter. You can contact him via email here.

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