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Emerging Trends in Predictive Analytics

By Vivek Agarwal
SVP & Business Head-Analytics & Technology Solutions in Middle East, Africa and South Asia-Dun & Bradstreet
Friday, January 10, 2014
By Vivek Agarwal
Headquartered in New Jersey, Dun & Bradstreet (NYSE:DNB), a leading source of commercial information and insights on business, is serving the global customers for more than 171 years with over 225 million business records in their global commercial database.


In the last two decades, investments made in digitalization and transaction automation have enabled organizations to evolve significantly in their ability to capture raw customer behaviour data. Now we find organizations looking to exploit this data through analytics to improve business performance.

The massive increase in computing power, cheap cost of data storage and integrated data supply chains cutting across traditional boundaries are expanding the universe of problems that could be addressed by using analytics and optimization solutions. Key areas where analytics can make a significant impact are: efficient capital deployment, improved speed & accuracy of customer decisions, development of differentiated products based on customers' needs & risk profiles and reduction in operational costs through enhanced automation in routine decisions; thereby allowing businesses to become more consistent, competitive and customer centric. Therefore, in 2014, we expect the interest and investments in analytics to further grow with the following key trends across demand and supply side.

Evolution of Emerging Markets
In my work with several banks in emerging markets of South Asia, Middle East and Africa, I find that adoption of analytics is less significant compared to those in more mature markets. Availability of sufficient data of acceptable quality and appetite for investments in analytics infrastructure has been the traditional hurdles. A fundamental belief that analytics can produce the right answers, even if such answers are counter intuitive, is sometimes absent in the higher levels of management. This may be because a generation ago, most organizations lived in a data starved environment which resulted in most successful managers of the time relying on experience and intuition to take decisions.


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