LatentView's Venkat Viswanathan: Getting the Signal from the NoisePublished January 08, 2013 in Arabic Knowledge@Wharton
The negative aspect of the information age is that the world is too much with us. Data was generated in earlier periods, too. But very little of it was captured for posterity. Today, big data is getting bigger all the time.
But this unwieldy mass hides many a gem: Enter analytics, which many businesses are using as a way to make sense of the noise. From an organizational standpoint, analytics is defined as the application of advanced quantitative techniques on enterprise and third-party data to help managers make the best possible decision in a given situation.
LatentView Analytics, which has offices in Princeton, N.J. and San Jose, Calif., and a global delivery center in Chennai, India, is one of the cutting-edge companies in the business. CEO Venkat Viswanathan tells India Knowledge@Wharton in an interview that the consumer insights that come from analytics give a competitive advantage to firms that use them strategically.
An edited version of the transcript follows:
India Knowledge@Wharton: After the recent presidential election, many commentators noted that in addition to Barack Obama, the real winner was Nate Silver, the New York Times blogger who predicted the results with stunning accuracy. Why did Silver's model work so well and what does the success say about analytics -- to take data and crunch those numbers to predict outcomes?
Venkat Viswanathan: If you look at what Nate Silver is talking about, it's this ability to tease out the signals from all the noise. I think analytics as a discipline is really coming [into its own] now as the technology, the ability to store data, the ability to meld together radio signals and come up with the insights are improving each year with changes in technology. We are able to apply this to various disciplines; the application for the elections is just a very recent one.
India Knowledge@Wharton: In addition to Nate Silver's success, the Obama campaign itself also analyzed massive volumes of data and they did it to enormous effect. In fact, Time magazine recently wrote about how the clever use of analytics enabled Obama's number crunchers, headed by Ravid Ghani, to do everything from raising one billion dollars in campaign funds to developing persuasive messages to get people to vote. What are some of the important lessons that business people can learn from such experiences?
Viswanathan: In analytics, the number one ingredient that you need is vision from the top and sponsorship from the top. I think the Obama campaign probably had the belief that they could really compete using data and they had sponsorship right from the top. In fact, I remember having conversations with some of the members of the Obama campaign more than two-and-a-half years back. They were starting the preparations for the campaign and were collecting all the data sources. They were trying to understand where they should focus energies. What they have done is something that was doable even earlier. But no one had taken an organized approach to doing this. And they did it in a very systematic manner in terms of collecting all the data, ensuring they prioritized where they put limited funds to use, and getting the sponsorship that they needed. So, they had the right data, the right organization, the right process and the right vision. That made the difference.
India Knowledge@Wharton: What would you say this means for businesses that want to use analytics for equally effective outcomes?
Viswanathan: I think the biggest lesson that we keep discussing with our clients is that we need the self-belief that has to come from the top. The organization needs sponsorship from the management that [focusing on analytics] is a direction that [the firm] wants to go. Look at how Amazon is using data as compared to others. Look at innovations like the Elastic Cloud. The biggest difference is that Amazon is proactive and aggressive in leveraging all the data assets. This comes from the vision they are laying out -- this is the direction we want to take the business. So, I think from a business perspective the number one thing leaders can take away is the need to have a significant vision. Then build the infrastructure that is needed, which will allow you to collect all the data. And have a plan to find the talent.
India Knowledge@Wharton: For those who don't know the Elastic Cloud, can you explain that?
Viswanathan: Sure. What Amazon has done is create a platform that allows you to access computing capacity in a very flexible way in a business model that is pay-per-use. Small businesses as well as large enterprises can assemble computing power at short notice. This allows them to run very complex calculations for short periods of time without incurring the capital expenditure they would traditionally have had to do. This has dramatically reshaped them. The interesting thing is that Amazon always had this capacity, built for peak usage [of its own site]. They have built a billion-dollar market [by leveraging it].
India Knowledge@Wharton: What's an example of a way in which a small company uses this Elastic Cloud?
Viswanathan: There are many examples where businesses are built on top of the Elastic Cloud. Take Foursquare, which is a consumer service that allows you to make your presence noticed in retail locations. Their entire product is built on top of the Amazon Cloud. Even our own product innovation initiatives tend to rely on Amazon. It gives us the opportunity to build very scalable solutions. As we gather more and more data, we don't need to scramble to find the hardware or software support. We already have it. We just need to turn on the tap. We are able to do calculations that used to take us weeks in a matter of minutes. That's a significant productivity saver as well.
India Knowledge@Wharton: That's great. I hear a lot of buzz these days -- and perhaps a little bit of hype -- about big data and this is often in conjunction with trends like social networking, cloud computing and mobility. These are all described as forces that are, in many ways, reshaping the business world. Do you think these forces are converging? What are the challenges that companies face as a result of these forces?
Viswanathan: I agree with you, there is a certain amount of hype to all the buzz that we hear around big data, but it is a very real trend. When you [look at] the sources that have created this data, you can see the dramatic change that is happening in the business landscape. Mobility, for instance -- the number of smartphones that are available and being used today. Each of these smartphones is a computer creating real-time data with location information as well, which is a potential goldmine for multiple businesses that want to understand consumers. In five years, the social networks have gone from 100 million users to over a billion users. And each of them creates significant content, the user-generated content that [serve as] signals that businesses need to glean insights from. So, I think there is certainly a trend. The biggest difference this time is the speed at which things are changing. It used to take 10 years to reshape a particular sector; we are now seeing it being reshaped in three to four years. And with that, there is also the falling cost of data storage, the ability to compute that we just discussed, the access to talent ... all of this leads to an opportunity where the pioneering companies can actually create business models. This gives them an advantage over other companies that are slow to adopt it.
India Knowledge@Wharton: More and more, companies are trying to figure out how to become social enterprises in the sense that they use their social networks to get their employees to share knowledge with one another or to engage with the customers and so on. And, predictably, this generates large volumes of data. Can you offer any specific suggestions on how companies can mine this data and put it to good use?
Viswanathan: I think there is certainly a lot of opportunity, but I would say the opportunity is different for different types of businesses. There are consumer businesses, which have a lot to gain because they have direct access to consumer insights in terms of what consumers are talking about. The part that you're talking about is more relevant for large corporations where they can tap into the collective wisdom of their own employees and they can make the connections internally within their organizations and create this ability to trade knowledge very quickly within their organizations. So, systems like Yammer, which Microsoft has recently acquired, have created a platform where employees can share content in a format. I think more than the content itself, the beauty of these applications is that the relative ease and familiarity that people have with a platform like Facebook is replicated in enterprise space. If an organization creates certain incentive mechanisms where you are incentivized to share more of your knowledge and become an expert in a particular field, it is certainly possible for companies to tap into this.
India Knowledge@Wharton: When companies use social media, they often focus on metrics like Facebook friends or likes, Twitter followers and so on to track their success. What value do such metrics have? And what metrics should companies use to determine the effectiveness of their efforts?
Viswanathan: The metrics that you mentioned are what I would call first generation metrics.... The absolute numbers themselves may have limited value. It depends on the sectors you operate in, the kind of consumers you have access to and the type of brand power that you have. So, I think it's very important for companies to have benchmarks. One of our partners is a company called Unmetric and they've developed a social media benchmarking platform, where every brand can benchmark itself against four other selected brands.
India Knowledge@Wharton: But isn't it possible to easily gain these metrics in the sense that aren't there companies that will even sell services like increasing the number of likes? It skews the picture, doesn't it?
Viswanathan: Sure, which is why the absolute numbers don't necessarily convey what is happening out there. What is important is to try and see how these metrics change over time and what is happening in the real world when this is happening? The other aspect is you need to go beyond basic metrics into what I call "engagement metrics," because that's when you understand whether the followers and "likers" of your brand are actually engaging with your brand. Do they have a point of view? Are they communicating that point of view in an articulate manner, which will then become an opportunity for us to derive insights? So, a lot of the work that we are doing today for some of our clients focuses on what I call the influencer analysis, where we are trying to identify whether it is a consumer world or a business-to-business world. Who are those influencers who shape opinion about our products and about our competitors' products? We can engage with them and provide them all the content that is needed so that they make a more informed judgment.
India Knowledge@Wharton: Once you have identified the influencers, how do you work with them?
Viswanathan: I think it's no different from how companies have been engaging with influencers in the real world or the offline world over the past 50 years of marketing. So, you still need to give them all the inputs that are needed about your brand -- maybe be proactive in addressing all the questions that they are raising about it. And then try and give them enough input so that they can potentially see your point of view in terms of what are the benefits and values that your product brings. And if they do buy into it, you create a virtuous cycle, which is going to lead to more opportunity for you and a better metric for your brand.
India Knowledge@Wharton: What are some of the most common mistakes that companies make with regard to analytics and how do you help them correct those?
Viswanathan: I think an overemphasis on math and techniques is sometimes a bias that certain people have because of the backgrounds they come from and because of all the hype that is being created around predictive analysis. And this is something we need to hold back people on. We are saying it's not about the math, that we need to go beyond the math. We need to keep the analysis grounded on what can be actionable and how we can take it to market. So, that's one aspect we have looked at. Maybe ignoring external sources of data is another bias that we have seen. Companies seem to go after the low-hanging fruit, which is data that they have already collected within their business. But in reality, in such a complex world that we operate in today, it is very important to pick signals from other sources as well. They may have a lot to tell you in terms of what is happening in your business. The third aspect is analytics being run as a kind of technology or data initiative. It then tends to sit in a silo and is not integrated within an organization. It has to become mainstream for it to have an impact. So, it almost should not be called analytics if it has to have impact.
India Knowledge@Wharton: That's interesting. In fact, the point you mentioned about the weak signals is something that goes back to Nate Silver. He also makes the point that as the volume of data increases, it creates a lot of confusion. And as confusion increases, people sort of tend to gravitate toward their own biases.
India Knowledge@Wharton: And they find people around them who share those biases.
Viswanathan: Reinforce those biases.
India Knowledge@Wharton: You have facilities based in the U.S. -- in the Princeton, N.J., area and on the West Coast -- and also in India. India has often been recognized as a destination for IT outsourcing. What's the role for big data analytics in terms of capabilities within India for this kind of work?
Viswanathan: Over the past 20 to 25 years, the infrastructure needed to attract talent, train talent and manage a set of knowledge workers has been put in place by the pioneering knowledge-oriented companies from India. All we are doing is essentially replicating a lot of that for a new segment. I think there is a potential talent shortfall in the big data space. This could potentially disrupt the opportunity we are creating with the technology breakthroughs that are happening. And India is a potential supplier of talent to fill this gap.
India Knowledge@Wharton: Who are the biggest competitors India faces? And what are some of the pros and cons that India has relative to those other countries?
Viswanathan: I think China is probably the number one alternative to India, which many of our clients already harness. We have clients who tend to leverage China as a potential center of quantitative analytics. And China has probably done a much better job in terms of stepping up to this opportunity, as compared to what it had done in the earlier wave of IT services. Some of the Eastern European countries are far ahead. What goes in India's favor as compared to these countries is the entrepreneurial spirit. India also has established role models in terms of attracting capital and then building businesses using that external capital. And then knowing how to do business with international clients and building the softer engagement management layers, as well, in addition to the quantitative project delivery layers.
India Knowledge@Wharton: Since you were referring to the entrepreneurial spirit in India, let's turn now to your own entrepreneurial journey. You previously worked for Cognizant. What inspired you to start LatentView?
Viswanathan: While I was at Cognizant, which is a great organization, I could see some of our clients starting to ask business questions in terms of how do we leverage all these investments into marketing campaigns and how do we then understand the consumer insights? When I started looking at this space, I realized that there was need or potential for applying the same global services delivery model, which a lot of the Indian organizations have perfected, to functions like marketing research and potentially serve the chief marketing officer. That was the germ of an idea. So I took a six-month sabbatical after I left Cognizant to research this a lot more and get comfortable with all the pros and cons. I always had this ambition of doing something on my own. I guess I just happened to be at the right time in the right place and it looks like we caught onto the right wave.
India Knowledge@Wharton: What have been some of the major milestones along your journey and, also, some of the major challenges?
Viswanathan: For any young company, the biggest milestone right at the early stages is attracting the right talent and putting together the team. One of the entrepreneurs I met had this nice way of explaining what entrepreneurship is all about. He told me, "As long as you figure out how to hire five people whom you have never met and how to win business from five people who, again, you have never met, or raise money from five people who don't know you at all, you know how to run a business and you'll be a successful entrepreneur." And so, the first step for me was finding those five people who didn't know me at all and who believed in the vision that I was laying out.
Then, we move onto the clients. Each large American client that we win is a significant milestone and increases our credibility. When they start making us enterprise analytics partners or the partner of choice, it's a very big milestone.
India Knowledge@Wharton: Of all the different projects that you have handled for your clients, which one are you the most proud of?
Viswanathan: It's almost like asking a parent which of your children you are most proud of. There are multiple things we are doing. Each of them pushes the envelope in a different direction.
India Knowledge@Wharton: In any entrepreneurial journey, you have both successes and failures. Which has been your most instructive failure?
Viswanathan: Very early on, when we were still relatively young as a company, we made a choice, which in hindsight we could have made differently: we spent a lot of time focusing on servicing a shallow market. We spent maybe the first two years -- an enormous amount of time -- focusing on India as a marketplace. I believe India has a lot of opportunity as a marketplace in the future. But maybe we got our timing wrong.
India Knowledge@Wharton: Since you have been the CEO of LatentView, what is the biggest leadership challenge you have had to face?
Viswanathan: I think leadership primarily comes down to selling my vision to the team and setting a direction for the company. I think one of the issues I have faced at different points of our growth is picking markets that we need to focus on. And we have made choices where sometimes the rest of the team needs to be convinced that this is the right choice. And so, I have been challenged at different points in explaining why we are making this choice. Another area is in terms of accessing external capital. There are enough investors focused on this area and we have made the conscious choice to manage this growth ourselves and run it as a private company. This does get questioned at different points in time.
India Knowledge@Wharton: One last question: How do you define success?
Viswanathan: In my view, success is very happy clients, very happy individuals working for us, and a very strong reputation. By those measures, we are already fairly successful and I want to ensure we continue to maintain that, especially the reputation part.