Venkat Viswanathan
Chairman at LatentView Analytics

Almost to the day, 10 years ago, on a summer afternoon, I recall an interesting conversation with a friend about the potential of Analytics, sitting in an empty coffee shop on the beach. Having spent much of the previous decade helping clients derive value from traditional Business Intelligence and other IT implementations, we were conjecturing that the next wave might be business teams enhancing their decision making with better data and more detailed analysis, sometimes adopting advanced math. We spent hours talking about our collective experience, and the more we spoke, the more it piqued my curiosity. The next few weeks were a blur with many conversations and research reaffirming our initial hunch, and I decided to act on exploring that market. Within a year, LatentView was off the block on an exciting journey.

At that time, the emphasis on Analytics was primarily on its predictive capabilities.Mainstream media played this up with cover stories on BusinessWeek (“Math will Rock Your World”, Jan 2005, by Stephen Baker) and in popular business books like Freakonomics, Steven Levitt & Co., 2005 and Super Crunchers, Ian Ayres, 2007.However, within a couple of years, we realized that the vast majority of businesses were still not convinced about the quality of data they collected, (many still aren’t!)and the fundamental need was to create organizational change. Companies needed to understand there was a better way to derive actionable business insights that would result in better decisions on the ground. More than just help with solving tough math problems, large enterprises seemed to need a Trusted Analytics Partner, who could work with them in the trenches, in long term partnerships and help them create a centre of excellence that address the gaps in knowledge, talent availability and problem solving skills essential to realize the analytics potential. We have made that our core focus and over the last 9 years, and have strived to be the most reputed name in that space.

Along the way, changes in the business environment, innovations in the technology ecosystem, and the successes of data driven business models creating digital role models like Google AdWords, and Facebook early on and Uber and AirBnB more recently, have redefined the Analytics opportunities for businesses. Around late 2009, consumer brands started warming up to “social listening”. Decoding social media conversations and other unstructured data became an important part of their analytics needs. Knowledge of semantic analysis, platform APIs, and client business context proved crucial in combining machine intelligence with human intelligence and delivering digital business insights.

Another wave of Analytics for enterprises was around data visualization. I love saying “visualization is to analytics what email was to the Internet”. A simple, engaging and dynamic application that is used every day that helps with managing a business. The pioneering work and books of Edward Tufte and Stephen Few were already an inspiration when we realized that our clients needed help with data visualization. Tableau’s meteoric rise and ever expanding footprint meant that by 2012 most of our clients had already invested in it and were looking for knowledge and expertise in embedding it within their business or were receptive when we showcased the potential. The visual medium is crucial to democratising access to data and allowing business users to quickly navigate to actionable insights.

Fast forward to 2015, and peering ahead, the future is bright with the advent of multiple iterations of drones, intelligent machines, connected devices and wearables - from watches to activity trackers to devices that infer your state of mind from your breath (http://www.spire.io/), and the increasing buzz around the potential for IoT (Internet of Things), we are at the cusp of some fundamental breakthroughs. In less than a decade, machine generated data and algorithm driven interactions would far outnumber the traditional data sources and applications. Analytics would gain all new interpretations, and business applications.