The Decision Maker

Big Data Success Principles

Posted by Aaron Wang on Apr 1, 2013 10:05:31 AM

Aberdeen Research identified four Big Data success principles in a report earlier this year.

  • Support a data-driven culture
  • Develop or hire skilled staff
  • Build a flexible, high-speed data infrastructure
  • Enable self-service analytics

These came out of an analysis of survey results from 125 organizations world-wide at various levels of Big Data sophistication. Yet, how do these principles apply in the credit union industry?

Support a data-driven culture

What is a “data-driven culture? First and foremost, it is a culture that values decisions based on reliable data. Second, it is a culture that can deliver reliable data in a timely fashion. For most credit unions this will require a “top down” effort to educate, enable, and motivate the organization. The desired behavior change will take time because changing even a small slice of the organizational culture is a long-term prospect.

Senior management needs to be committed to the task, set concrete objectives, and firmly execute a carefully considered plan. This is an evolutionary process so the plan should focus on winning many small victories that build on each other.

Develop or hire skilled staff

The needed cultural change requires not only internal champions at the top but also skillsets that did not previously exist in the organization. The question of whether to “build or buy” these skillsets need not force a black/white answer. In fact, many credit unions start by retaining an expert vendor who assumes a mentoring role as a part of the engagement. This way, the organization starts to quickly accumulate small analytical victories while at the same time internal personnel increasingly acquire the knowledge to do more on their own.

Build a flexible, high-speed data infrastructure

An important concept in developing a successful data-dependent decision making culture is “don’t scrimp on the hardware”. Many credit unions are wary of overspending on technology. Yet, hard won shifts in organizational thinking and behavior should not be jeopardized by slow and/or difficult to use technology. Luckily, the necessary components for a successful program have become progressively more affordable for credit unions.

Enable self-service analytics

Eventually, the credit union will mature to the point where team members can do more analytics on their own. Yet, it is a mistake not to build self-service applications from the start. Even though some system capabilities may be underutilized at the outset, it is better to have tools already in place when users are ready.

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Topics: Data Analytics