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The Analytics Advantage

The Analytics Advantage
Digital Transformation is a double-edged sword, predictive analytics is an important piece in the digital transformation journey.

Digital transformation is more than a buzzword today. It’s the new imperative. Organizations are launching numerous initiatives in their march towards digitalization. Disruptive technologies viz. Social media, Mobility, Analytics, Cloud and the Internet of things (SMACI) are leading the way. Of these, analytics plays a pivotal role as it supplements the other four. And at the same time, it is getting ever more useful in addressing day to day organizational requirements. Social Media has expanded beyond sharing of personal updates to including career interests, product promotions, customer surveys, and identifying new business avenues. With the huge volume of data, it generates, it is essential to pick what is relevant and use analytics to draw meaningful inferences.


Similarly, IOT devices are exploding in number, coupled with which is the volume of data collected from associated devices. Again, analytics is essential to identify usage patterns, failure patterns, and so on. Within the organization, analytics is no longer restricted to pretty dashboards. Users are examining the same data in real-time from several perspectives, to gain deeper insights that support smart business decisions. So, while SMACI is driving digital transformation, it also generates large volumes of data, commonly referred to as Big Data. Several technologies and platforms have emerged, to handle and manage this large volume of data, and it is analytics that eventually delivers meaning to big data. In order to make sense of huge mounds of data, it is essential to evolve intelligent data models that combine several dimensions of the data to permit different perspectives. This provides new insights into the functioning of organizations, permitting executives to chart better growth paths confidently.


Thus far, those using analytics for organizational control are using forecasting, simulation, and other predictive approaches to confidently assess the future state. Predictive analytics deals with mining the data for predicting trends, demand, behavior patterns, etc. It combines techniques such as data mining, statistics, machine learning, data modeling among others, to deliver results that are within reasonable limits of tolerance. With the increased number of aspects being built into the data models and with better application of statistical methods, the results are getting further refined and businesses can make more accurate predictions. From YouTube and Netflix predicting your entertainment requirements to advertising based on your interests to data-driven talent acquisition by organizations, analytics is helping marketing and decision making like never.

At the same time, more sophisticated tools are showing up on the horizon. In-memory devices such as HANA are making the onerous task of managing big data appear simple. Tools like Fiori, Lumira enable the accurate and user-friendly representation of the data analyzed to ease decision making. Predictive analytics is also being deployed in areas of customer behavior, spend analysis, operational improvement, enterprise performance management, financial planning among others. Predictive Analytics is indeed a strategic tool as well as tactical guidance.


As for the business potential, multiple global reports estimate the predictive analytics market to reach $8-10 billion by 2020. The relevance of India in the overall value chain of delivery of predictive analytics services is very high, particularly because of supplying talent such as data scientists. Among the sectors expected to be early adopters of predictive analytics, BFSI, Government, Public Administration & Utilities, Telecom, and IT, Transportation & Logistics, and Healthcare rank among the top. The future vehicle of business growth will be driven by the advancement of technologies. Predictive Analytics is one critical pillar supporting future growth in organizations.