The Decision Maker

Moving Toward Big Data Breakaway

Posted by Aaron Wang on Apr 28, 2013 9:35:42 AM

Credit unions considering Big Data initiatives often don’t know where to begin. There is a lot being written about the subject yet it is difficult to gain a perspective how exactly to begin a Big Data initiative.

A first step is to understand where the credit union is in terms of analytics maturity. Arvind Sathi’s book, Big Data Analytics: Disruptive Technologies for Changing the Game provides five benchmarks for progressive levels of maturity. Using these benchmarks, a credit union can assess its current standing and use it as a point of departure for further Big Data and analytics development.

Ad hoc

This is the lowest level of maturity. Organizations at this level are mired in inefficient manual processes that provide rudimentary reporting. While some of the information generated is helpful, the organization’s competitors are advancing faster.


Information quantity and timeliness is improving on a department by department basis. However, uniformity in quality and distribution across the enterprise is lacking. Automation is more prevalent but the organization is still too dependent on manual information processes. Competitors continue to have an advantage.


At this stage the organization about equivalent to its industry peers allowing it to start using information to make effective competitive decisions. Information is collected and analyzed more uniformly and company-wide standards for analysis are forming.


Information is now used with greater effect in the marketplace. The organization is one of the few in the industry to create ongoing competitive advantage. Management has greater confidence in its ability to get accurate information more quickly and reliably than ever before. Key metrics have been established and are acted upon across the organization.


Now generally judged to be the industry forerunner, the company has mastered the management of information to drive its business strategy, optimize its processes, and dominate its market. Excelling in both descriptive and predictive analytics, the organization can create compelling visualization of its past, present, and future environments.

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Topics: Data Analytics