Big data is enabling organizations to gain insights into their businesses letting them to harness all aspects of their business. Dataquest quizzed Amit Sanyal, Assistant VP & Head of Consumer Value Solutions Business at Mahindra Comviva to understand how big data is changing the way businesses work. Excerpts:
Q. In what ways does big data rid organizations from stagnancy and growth challenges?
In today’s competitive landscape, the challenge before organizations is to increase the pace of innovations without letting costs to get out of control. Big data helps organizations to unlock various business competencies and avoid stagnancy and growth challenges. By evaluating and analyzing data closer to its point of origin businesses can take timely action and unlock new revenue opportunities. For big data evangelists, what’s really alluring is the capability of big data to deliver actionable insights that lead to better—and more profitable—business decisions. However, delivering these value-added insights requires IT systems that allow users to ask a much more varied set of questions than that they can ask today. Questions that can help in unlocking trends and patterns from terra-bytes of data generated during the course of customer interactions. With better understanding, businesses can design sharper outcomes by designing faster go to market strategies, efficient executing and better results.
Q. What sets big data/analytics apart from traditional BI solutions?
The problem with traditional BI is that it is prejudiced right from the very beginning. Traditional BI is used to run a predetermined query on data to justify outcomes (or user assumptions). Since query is always defined by the user, it is not able dig deeper into the data. Big data analytics works the other way around. It allows data to make the correlations. Algorithms are unleashed on data subsets to find patterns matching with interesting outcomes. Once the user has narrowed down to an algorithm, it is applied to other sets of data to predict outcomes.
Q. How can CIOs justify their investments on big data/analytics?
Most IT investments are undertaken with one of the two objectives in mind – reduce costs, increase revenues. Big data analytics kills several birds with one stone. In terms of costs, predictive modelling helps organizations to understand the various consequences of their actions and avoid costly mistakes. On the revenue front, big data analytics not only gives a competitive advantage to businesses but also helps in augmenting speed and accuracy of actions helping businesses to drive profitability. Considering the various advantages given above, CIOs must push big data as a scientifically proven and forward looking decision making approach to their internal as well as external stakeholders.
Q. How easy or difficult is to get insights from data using modern big data/analytics tools? Do organizations need to dedicate in-house specialists to do this?
In future businesses will run at zero latency and zero downtime. This will require a robust architecture as well as infrastructure to collect as well as analyze huge amounts of real time data. This is where Big Data proves its usefulness as it uses machine learning algorithm to recognize patterns in data and thus helps in providing business clarity. Big data refines organization approach from one that is based on “hit and trial” to one that is based on a “well- defined” actionable plan. Organizations have intuitively realized the importance of big data and the role of the Chief Data Officer is only going to grow in importance in the future.
Q. In what ways has big data/analytics begun to transform telecom operators globally with whom Mahindra Comviva is closely linked?
The significant cost of customer acquisition and slim margins have put a huge amount of pressure on operators to maximize customer life time value. Big data analytics platform has shown great results initially which has led to many operators betting big on the platform. In today’s customer centric environment, big data analytics provides the tools to engage customers in a proactive manner which helps in creating a positive image of the operator in the minds of the customer. Operators using big data analytics platform have seen a sharp improvement in take up rate of new services (as they are contextually relevant to customer needs) and adoption of new services and engagement of customers have gone up manifold. This along with timely intervention has helped to bring down the churn rate helping operators get a significant competitive advantage in the market.
Q. Can you briefly run us through one of the cases from your customers where big data has brought significant change?
With increasing competition disrupting the status quo, one South East telecom operator faced a sharp increase in churn rates, which eroded its market base and revenues. With the increasing penetration of affordable, dual SIM smart-phones, the incumbent operator realized the need to stop customers from churning. The operator deployed Mahindra Comviva’s churn prediction modelling, leading to significant results. The system was designed to predict churn with a high degree of accuracy (> 60%) resulting in timely retention actions. The churn modelling was combined with a pool of customer retention offers for different churn reasons and customer behavior for value and volume retention.