Interview &#8211; Mahesh Ramakrishnan, Founder CEO and MD at Nanobi Analytics
[dropcap style=”1″ size=”2″]AIM[/dropcap]Analytics India Magazine: What are some of the main tenets (philosophies, goals, attributes) of analytics approach and policies at your organization? [dropcap style=”1″ size=”2″]MR[/dropcap]Mahesh Ramakrishnan: nanobi was founded with the belief that “Business Insights is not all about Big Data, it’s about well-connected diverse small data”. With this belief nanobi has created a unique concept of self-service analytics available on an easy subscription basis at the nanobi App Store at www.theanalyticstree.com.  The technology enabler of these self-service analytics is nanobi’s “liquidData” platform. nanobi’s analytics app store is theanalyticstree™ which contains predefined, domain and content rich analytic apps built for specific industry verticals that businesses can choose from, subscribe for and connect with their concerned internal enterprise apps. nanobi partners can also use the liquidData platform to design analytics and publish the developed analytics applications to theanalyticstree™ for subscription by customers. nanobi believes in enabling every organization to take informed decisions, using business intelligence, and must be able to do so using high impact and low cost analytics. Our goal is to provide users the capability to build and design analytics in an easy manner and deliver, as it is to use. We also thought that end users must experience analytics with “zero training”.  This will enable creation of decision makers at all levels in the hierarchy who will then be able to leverage analytics and feel empowered to take smart decisions using data. There are also a large number of organizations that are yet to embrace analytics, to take informed decisions, in many areas. Most of them still rely on reports, and static MIS, simply because of the time and cost involved in building and maintaining analytics within their organizations. For all of these, we believe the nanobi analytics liquidData platform offers a simple agile process of building business intelligence, with several pioneering ideas.  These ideas enable those who have and those do not have investments in data, to realize significant ROI in their investments in analytics. AIM: Please brief us about some business solutions you work on and how you derive value out of it. MR: A QSR (Quick Service Restaurant) chain took on the problem of calculating profitability of its cafes and the items on the menu. This had been an intractable problem so far. However, the problem was solved in days using nanobi analytics.  A healthcare services company was able to get complete financial analytics using nanobi’s Tally Adapter in under 30 minutes. An education services organization has been able the use the nanobi platform to analyze the effectiveness of its mentoring programs. Quick time to delivery and no upfront capital investments are big quantifiable benefits to businesses opting to subscribe to the analytics at theanalyticstree™. AIM: How does a typical requirement gathering to delivery cycle looks like for you? MR: The entire concept of an analytics App Store is unique in itself. Now businesses can subscribe to readily available analytics at theanalyticstree™ on a pay-as-you-use model, and be up and running with analytics in a few hours. The analytics App Store is a one stop store for analytics developed not just by nanobi but also by nanobi partners. theanalyticstree™ contains predefined, domain and content rich analytic apps built for specific industry verticals that businesses can choose from. nanobi removes the plumbing efforts required for companies to consume analytics. Just plug in your data sources using nanobi adapters and consume instant analytics as a service, delivered on the cloud. No coding necessary! By providing content rich analytics on a simple subscription model, we aim to democratize the usage of analytics across spectrum of enterprises ranging from small neighborhood stores to large enterprises without asking for huge upfront investments or evoking any fear of failure. Added to this low skill requirement, quick time to value and low infrastructure needs of the analytics apps help SMBs achieve a faster ROI. AIM: Please brief us about the size of your analytics division and what is hierarchal alignment, both depth and breadth. MR: nanobi is a team of 25 professionals. The founding team has more than 100 years in domain experience, analytics and product development. We were probably the first team to introduce pre-packaged analytics to the world as a concept. The Organisation structure has been crafted based on the skill sets that each of the founding member brings in. We have Sumant Sarkar, heading the Product Development, Abhishek Purohit heading the Sales & Partner Enablement, Dr. S Jayaprakash managing the Apps development for Insurance and Education verticals, Vinod C V managing the Apps development for Financial Services Industry, Restaurants and other industries as well as taking care of the Financials, Human Resources of the company. Mahesh provides us the direction and the vision for the product. Further, to bring an independent oversight and outlook, we are supported by; Independent directors on our Board Specialist advisors on our Advisory Board Independent Financial Advisor for compliance and corporate governance AIM: Would you like to share any example of an Insight that generated a huge positive impact for your clients? MR: Our entire philosophy is to enable organisations gain insights into their performance in a simple and agile manner. And this must be able to do so using high impact and low cost analytics. This approach we feel brings in a faster ROI to an Organisation that has subscribed to analytics provided by nanobi. The other big differentiator is the ability to gain insights into Organisation’s performance by mashing up data with external data which helps in unraveling never thought of or imagined correlations that may exists between the organizations data and the external data. We have had almost all our Customers gaining a huge positive impact either in terms of their ability to deliver analytics to its users, manage its profitability better or reduce costs. As an illustration, we have listed below couple of customer success stories; India’s leading coffee shop chain The coffee shop chain leverages the nanobi liquidData platform to analyze sales for items sold across all their cafes. The platform helps them in doing a detailed profitability analysis for each and every café and for each of the items sold in these cafes. In addition to this the coffee chain uses the platform to analyze key sales performance metrics like ASPD, APC, Best/Worst performing cafes etc. at various granular time intervals and to get a view of how the performance changes across time intervals. Given the complexity of data requirement and acquisition the nanobi concept of nanoMarts helps in building these analytics incrementally independent of each other while at the same time giving the management a unified view of information. The platform has helped this chain to easily implement a system driven approach to analytics and moving out of an error prone and time consuming manual way of doing the same. NGO in the Educational Sector This NGO is working to promote English Language among the students studying in the government schools in Maharashtra.  They were much in need of analytics for two key reasons. One being, the mentors who regularly visited various schools had to rate the students and teachers on monthly basis and to do this they wanted to complete analytics for the students, teachers and mentors.  The insights from the analytics were useful for them to reach out to the patrons and sponsors to show them the live statistics of the student, teacher, and mentor participation status. AIM: What are the next steps/ road ahead for analytics at your organizations? MR: In terms of Product strategy / roadmap nanobi has a two pronged approach, one focusing on the analytical applications available on theanalyticstree and the second focusing on the liquidData platform that powers theanalyticstree. nanobi intends to have analytical applications spanning industry verticals like BFSI, Healthcare, Retail, Automotive, Manufacturing (specific business use cases), Restaurants, Software startups etc. We are actively working with partners for developing analytical apps for some of these industry verticals. On the liquidData platforms some of the features that are on the roadmap include full support for hadoop, expanding the support for predictive analytics, expanding the repository of pre-built adapters to market standard applications etc. Our goal is to be “world’s largest analytical app store” over the next few years. AIM: What are a few things that organizations should be doing with their analytics efforts that most don’t do today? MR: Organizations should treat analytics as a core business area and not an afterthought that needs to be looked at later. Most of the organizations require guidance on the value that analytics can bring in running their businesses efficiently and effectively. We feel that Organizations can take one step at a time on the analytical journey to see the benefit themselves and this is best done using nanobi’s low effort and low cost approach. AIM: What are the most significant challenges you face being in the forefront of analytics space? MR: The analytics infrastructure needs to keep pace with the constantly evolving business realities and ever growing data. Analytics is taking on harder and harder problems of the world. It’s one thing to sift through machine production data to predict parts failure. But mining through CCTV footages and match faces/actions against a known database in real time, is a different challenge altogether. We have been seeing such requests of late. AIM: What do you think are your key differentiators? MR: Our differentiation comes from the fact that we offer “analytic apps” for SME’s on a subscription basis, at a very low cost, on the cloud. So today, any SME business that requires analytics can come and subscribe and use analytics. We also enable business insights not just from your own organization data, but from external data as well, which are seamlessly blended with the organisation’s data to provide different insights of the business. A sophisticated underlying technology powers all of this and is isolated to the end user thus making the experience richer and easier. We are probably the FIRST analytics App store in India, and we want to grow first in India, and then go Global. And the same philosophy is what is being offered to Large Enterprises that are seeking to increase their ROI on their existing investments in DWHs by providing them with a technology that helps in integrating data across multiple sources to delivery high impact analytics at a low cost. [divider top=”1″] [spoiler title=”Biography of Mahesh Ramakrishnan” open=”0″ style=”2″] Over 25 years of experience in the area of Product and Process Innovation, New Product development, Product Engineering and Solution Architecture, on a range of technology platforms. Recognized as a thought leader and pioneer in Business Analytics, Business Intelligence and Data warehousing, across the industry by peers and customers. Inventor, Innovator and Architect of many pioneering ideas, concepts and products in the areas of data warehousing and business analytics. Mahesh holds BE from Mysore University and MBA from IIM Bangalore.[/spoiler]
[dropcap style=”1″ size=”2″]AIM[/dropcap]Analytics India Magazine: What are some of the main tenets (philosophies, goals, attributes) of analytics approach and policies at your organization? [dropcap style=”1″ size=”2″]MR[/dropcap]Mahesh Ramakrishnan: nanobi was founded with the belief that “Business Insights is not all about Big Data, it’s about well-connected diverse small data”. With this belief nanobi has created a […]
AIMAnalytics India Magazine: What are some of the main tenets (philosophies, goals, attributes) of analytics approach and policies at your organization?
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["AI", "ML", "analytics", "Aim", "RAG", "predictive analytics", "R", "Go", "API", "big data"]
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