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Five Success Factors for Generating Big Data ROI

Kevin Cusack |

You’ve undoubtedly read enough about big data and data analytics. But I’m going to bet you haven’t read enough about the ROI of analytics. Here’s a basic question: “What has been the financial impact of our investment in analytics?”

The truth is that most corporations are unable to answer this seemingly basic question. Yet, according to Gartner Inc., by 2020 50 percent of all companies will not only ask it but demand an answer.

Throughout any large organization there are a variety of systems, each with its own purpose and internal “owner”. As a result, only a fraction of companies are able to fully realize the business value of their investments in analytics: The siloed nature of analytics implementations prevents systems from communicating effectively with each other, depriving the organization of the analytics-driven insights that would otherwise be possible. Instead, most executives rely on subjective, nonscientific approaches, such as “intuition” and “personal experience” to make key business decisions, over data, information and analysis.

Integrating analytics into normal performance management processes is a critical first step on the journey to ROI. This tactic alone can move the organization from a piecemeal, tactical use of analytics to more of a strategic, cross functional, integrated adoption of it. To achieve this level of adoption and integration of analytics into day-to-day business, we have identified five success factors:

  1. Test-and-learn culture. The organization must foster a natural curiosity about the marketplace whereby hypotheses can be generated and tested as a result of analysis related to key performance indicators in the business.
  2. Data management expertise. It is essential to develop the capability to integrate data from disparate sources—both internal and external—to support the analysis and execution of different promotion strategies.
  3. Insight generation. Advanced analytics capabilities across the spectrum of standard reporting, ad hoc query, comparative and relative analysis, forecasting, what-if analysis, predictive analytics and optimization can help the business answer basic questions.
  4. Execution capabilities. The ability for the organization to move from generating an insight to taking action requires tight integration with operational systems.
  5. Measurement: Closing the loop on the execution of a business tactic driven from analytic insights requires a measurement and tracking capability to be in place (e.g., to measure the lift generated in sales). Once this measurement capability becomes part of the normal performance management set of metrics, the business can monitor the effectiveness of its business tactic execution and ultimately the effectiveness of its analytic environment.

This is blog is an abridged version from the Compendium. Go here to read the unabridged version.

Topics: Big Data, Inclusion, Payments Strategy

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