3 Keys to Leveraging the Power of Big Data

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May 7, 2012 0

Technology deployments are creating an ever-increasing volume of data, but as discussed in our big data article last month, it is not solely about volume. The velocity, variety and complexity of data are equally challenging, and offer a wealth of insight. In this article, we will see how some enterprises are leveraging the power of big data to their advantage and some use cases of big data in the enterprise.

A successful approach to the handling of big data will be a critical business capability in today’s data-rich environment. It will be the key to delivering significant competitive advantage to organizations that invest not only in analytics, but also adapt their business model and decision-making processes to take advantage of new insights from big data.

  1. Competitive Differentiation
    First, mass customization, constant experimentation, and novel business models are becoming hallmarks of competition as companies analyze large volumes of data. Big data may well become a new type of corporate asset that cuts across business units and functions much as a powerful brand does, thus helping differentiate a company from competitors.
  2. Innovation
    To improve the development of next-generation products and to offer innovative after-sales services, manufacturers are leveraging data obtained from the use of products. For example, stitching together real-time location data with buyer’s persona has created an advertising boom for the mobile platform. There are many examples that illustrate this point further. For example, a transport company recognized that in the course of doing business, it was collecting vast amounts of information on global product shipments. A consumer packaged goods manufacturer analyzed point-of-sale data to gain insight into customer’s buying patterns. Such comparisons can be a disruptive force from a business perspective and have created substantial value for consumers.
  3. Process Automation
    Third, big data and automated algorithms are increasingly being used to replace and support human decision making. There is no doubt sophisticated analytics can substantially improve decision making, minimize risks, and unearth valuable insights that would otherwise remain hidden.

As far as use cases, there are several common big data uses that have emerged from various industry verticals:

  • In financial services the ability to model portfolio risk is dependent on analyzing reams of historical transaction data from different sources. There is heightened scrutiny on risk management to guard against flash crashes and impact of “rogue traders” these days.
  • Utility companies and aviation manufacturers are turning to big data to take proactive steps to prevent failures in their products and services. By understanding load patterns and analyzing sensor data these companies can predict failures of component devices with accuracy.
  • Customer churn analysis in the telecom sector is also an example of how big data can solve a real business problem. By analyzing customer’s usage pattern, customer service data and correlating with data from their social graph, telecom companies can piece together what causes customers to drift away from their service, and thereby optimize their spend in areas that matter.
  • In the world of online businesses, behavioral targeting based on customer preferences, transactional data, social interactions and sentiment analysis have led to a revolution in the ad targeting, recommendation engine and in the field of marketing.

As illustrated above, big data offers tremendous opportunity to cost-effectively marry traditional transactional data with large amounts of customer intelligence derived from modern sources such as Twitter, Facebook, and blogs to help the company’s top line or bottom line in very tangible ways. It is no wonder that Big Data is now being dubbed the “new oil”, whose serendipitous insights are leading to major gains for businesses and public sector alike.

Issue May 2012
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