Businesses to succeed faster in fact-driven economy: Sudheesh Nair, ThoughtSpot

Sudheesh Nair has a new role at ThoughtSpot, the fast growing unicorn in the Silicon Valley. As the Nutanix president in his previous role, he was responsible for leading the sales organization and help the enterprise cloud infra company reach over USD 1 billion in revenue and over USD 9 billion in market cap. And now, he leads a company that provides solutions in the niche domain of augmented AI, and empowers C-suite executives and front-line employees with the ability to instantly uncover data-driven insights. 

IDG Media had an interaction with Sudheesh Nair, CEO, ThoughtSpot about his new stint, pertinent challenges and future GTM to help business users analyze tons of data and leverage AI to get trusted, relevant insights.

It’s been a little over nine months for you at ThoughtSpot. After an illustrious tenure as Nutanix president, was the switch related to the seven year itch?

It was honestly somewhat of an itch. I never knew how to create GTM when I joined the then new company Nutanix in 2010. I am at my best when I don’t know what I am doing. I like being uncomfortable because that’s when you always learn. Secondly, you are very easy on yourself when you make mistakes. 

After an 8-and-a-half year tenure at Nutanix, that market was becoming comfortable. The product, sales and GTM were working comfortably, and I wanted to make myself a little more uncomfortable. Also, the process of selling software has changed fundamentally with SaaS, subscriptions. I thought of moving up the value chain towards analytics and AI. Another big reason to join ThoughtSpot was its founder, Ajeet Singh, who is a tremendous force in the industry, though he left Nutanix (as co-founder) very early.

What have you added or tweaked in the company’s GTM that has worked well? And any ‘not so good’ moves?

If all goes well, disruptive changes in tech world won’t happen. Let’s start with the not so good. Many Silicon Valley companies make a similar mistake of getting excited and talk to their customers about their amazing technology. Some will buy for sake of technology but then you hit that slate. Majority of people (companies) have their own problems. Unless you take the tech and boil it down to a problem that connects with customers and solves it in a unique way and sell it compellingly, it will not fly. ThoughSpot went through interesting premise of BI, AI, Search, (Google-like). But a financial bank CEO wants insurance claim rate needs adjusted, or manufacturing IT leader needs better inventory churn rate, AR needs to be better - these problems needed inside out tweaking from us.

From GTM perspective, ThoughtSpot sale is very complex. It’s not fixed budget but a discretionary budget at customer end because of the solutions approach as a transformational sale from cloud. It is not BI sale but analytics sale. Combined with the fact that we are a young company with no reference customers and brand recall. We had unique skillsets (people), but GTM had to be redone at scale.  

Talking on good points, architecturally there is nothing in the market similar to what ThoughtSpot offers. There is no way customers will deal with the level of data they are collecting from transformation of IoT, cloud, SaaS by directly giving to human beings and deal with charts and dashboards. There has to be AI involved, natural language search involved. Search is about accuracy and speed that is sufficed by ThoughtSpot’s new architecture. 

Secondly, I love the culture of ThoughtSpot and the humble environment that emanates from the founders Ajeet, Amit and Abhishek. ThoughSpot has good product market fit, great culture, and GTM issues have been ironed out.

What exactly is the correct definition of ThoughtSpot? It’s been known as a BI company, Google of Enterprise, analytics AI platform at different times of its inception.

What we are is probably best defined by Gartner as augmented analytics, which is data analytics that is helped by massive scale AI-driven machine learning. At the core of ThoughSpot, we allow everyone with the need to ask the question to structured data that is sitting without learning how it happens. There are complex questions where data needs to come in visual format without going through the filter of a data scientist. We want to democratize access to insights – no matter where the insights come from. We want to be the company that makes the world fact driven.

Fact driven and not data driven. 

Facts and opinions are at conflict today. Data is the raw material which can be made to look like fact if you are smart. The lack of context and details of the data set means it’s incorrect, and data driven is not the end. You can make your opinion but you cannot make your fact. We want to make the world a bit more fact driven and the problem is that fact is not accessible to all in real time. 

Would you feel uncomfortable if I compare ThoughtSpot to Tableau or Qlik? What is ThoughtSpot’s real value proposition? 

Not at all. Tableau is an amazing company with over USD 10 billion market cap and its good they created this market. A decade ago, AI did not mature like today. There was no cloud, IoT, as the world was dominated by excel. Tableau had a good ride of 15 years, but it will not be easy for them to completely wipe everything and start afresh in the new tech world. 

We have an unprecedented advantage that stems from being incepted nearly half a decade ago. IoT will create lot of data and there has to be better way of doing things. The BI team will look at data and give insights to the business units. This data increase with the rate of change makes human the bottle neck. As a result, insight is not enough as customers want personalized services. Data turned insights with algorithms is needed wherein the human experience is combined with design to turn insight into knowledge.

AI and data science doesn’t mean that you don’t need people. The new tool we are building is about harmonizing relationship between human experience and data science. We are hiring the best talent in data science, algorithms, AI, but also design. So, ThoughtSpot is a very different company than Tableau. 

Does that mean AI translates to assisted intelligence wherein humans and machines will co-exist? 

The term AI has been somewhat bastardized. Someone can put a chatbot and claim they are an AI company. There is so much fad around AI because it fundamentally changes on how business is being done. I believe AI is another transformation, not unlike the one where human species has gotten better. 

For instance, automobile revolution created fear amongst a bunch of farmers who were harvesting hay and they thought automation will kill jobs. But cars gave rise to petrol exploration, transportation, distribution, roads to be built, parking lots, engineering plants to make cars, repair jobs etc. Same fear arose when computers came, but people learnt new languages like Fortran, and there were more jobs in last fifty years. It is possible some jobs will be gone. But, AI will lead to more productivity, expand the economy, lift more people out of poverty, create new jobs and make lives better. We are trying to focus on one thing. With more data created, don’t give raw data to humans, give the raw data to AI.

Is it easy to sell augmented AI than plain vanilla analytics in the market? Who’s your chief buying influencer at the customer end – CIO, CFO, LOB, CDO or a mix of all?

It’s harder because it’s easy to do the same thing or nothing. Change is always tough. There’s no better time to sell ThoughtSpot than now because the cost of standing still is hard for businesses and most of them know this. 

We have to sell to three different personas - the first being business user - sales, marketing, finance, customer support folks. The second persona is data people as we need to have access to data warehouse– data scientist, BI people. But we have to carefully position to sell directly to them the value of automation through ThoughSpot because some of them will feel that complexity is job security and they will be a problem. But, most fast moving digital transformation companies know that. The third persona is CIOs and CEOs as they get charts and dashboards from competition like Tableau and they would look at us as an option. This is high level transformation if they can reduce AR by 3 percent and inventory by 3 percent. This means saving hundreds and millions of dollars, and hence CIOS, CEOs, CXOs will always be involved.  

Selling to different personas at customer end means longer sales cycle. 

We have taken a 4 by 3 approach – three verticals, three use cases, three personas, and three personas – in the market. The verticals are financial sector, healthcare, and third one is manufacturing, telco and retail together because it is mostly around customer 360 use case. Within those verticals we will have use cases like fraud detection, inventory management, customer churn management. 

What pitfalls should CIOs and business leaders dodge on their ‘augmented AI’ blueprint versus vanilla analytics of the past? 

Just saying we need to have a data driven business without any context makes little sense. More than the tools, it is the organization’s culture that needs to be prepared for digital transformation. Having a mobile app or adopting cloud doesn’t make you digital unless you fundamentally change.

Customer delight will trump everything else more than ever before. If you don’t deliver bespoke experiences, personalized choices to customers, you cannot lock them in and believe that they will with you because you have been in business for a long time. Creating a fully compliance feedback loop that extends all the way from the business to customers and back to your business will become very critical. And all these things are related to data analytics that can help businesses.

Your ‘top-of-the-line’ priorities as CEO of ThoughtSpot for 2019 and 2020?

In the short term, ramp up our sales and marketing GTM. In the near term, the product needs to fundamentally transform on three axis - cloud, mobile and universal search. Defining cloud native and context of the augmented AI experience needs more innovation at our end.

With people passively consuming data on mobile, we need to enable people for conversational experiences with their data as opposed to the human-computer interaction. We continue to innovate mobile and cloud with our best of breed ‘search experience’ tools and enable AI at scale that truly uses power of cloud.

Lastly, what emerging trends you foresee if you were to gaze into a crystal ball? Sell ThoughtSpot to me in a short phrase. 

Not a crystal ball perhaps but data security is continuing to be an issue with our product that gives insight access to everyone.  We are not a system of record, but a tremendous system of engagement. The quality of search and insight, and the way we deliver delight on mobile – there is a lot of work there. Cloud is important because customers want consumption-based pricing. 

ThoughtSpot empowers your business users with insight and when you do that, they will serve your customers better and your customers will be more delightful.

Fast Facts on ThoughtSpot

• Date founded: 2012
• Headquarters: Sunnyvale, CA, USA
• Offices: Seattle, USA; Dallas, USA; London, UK; Dusseldorf, Germany; Singapore; Bangalore, India
• Sample customers: Hulu, Daimler, BT, 7-11, RollsRoyce, PetCo, Metropolitan Police
• Founders: Ajeet Singh and Amit Prakash
• CEO: Sudheesh Nair

4 Mantras for ‘Augmented AI’ Journey: ThoughSpot CEO

1. Better communication amongst C suite peers on ‘why not’ than just the ‘what’ just the what.
2. More than the tools, the organization’s culture needs to be prepared for digital transformation.
3. Customer delight including bespoke experiences, personalized choices will trump everything else
4. Creating the full compliance feedback loop extending from business to customer and back to business.

Sudheesh Nair and his key take-aways on AI

- AI has been bastardised as a chatbot responding to hello; this isn’t AI.

- Much Fad with AI as it fundamentally changes business paradigm.

- AI and data science doesn’t mean that you don’t need people.

- With data explosion, don’t give raw data to humans, but to AI.

- AI will lead to more productivity, expand the economy, lift more people out of poverty, create new jobs and make lives better.