The Trellance Data Blog

Is Your Credit Union Ready for Big Data & Analytics?

Posted by Paul Ablack on Oct 27, 2014 1:58:00 PM

I recently attended a seminar at which John Best, CEO of Best Innovation Group, presented on the topic of mobile technology and payments. A key takeaway from the presentation was his explanation of why many technology implementations fail.


It is the case with most technology implementations that the IT department initiates a project and measures success by their ability to stand up the application. Unfortunately, it is also often the case that business users fail to adopt the application. What results are two different perspectives on the success of the application. Users complain, “Yeah, IT installed this new application but no one is using it”. Yet, from the IT perspective, they are being criticized for fulfilling the user’s requirements!

In his presentation John said the root cause of the issues is the failure of the organization to look at every project from three perspectives: (1) People (2) Process and (3) Technology. This holistic approach, which has been used extensively in the manufacturing sector, applies to any organizational initiative. It always comes down to answering three questions:

  1. What are the implications for our people?
  2. What are the implications for our processes?
  3. What are the implications for our technology?

When it comes to Big Data & Analytics (BD/A), the “HOW” of implementing BD/A matters as much as the “WHAT”. I have been in the business intelligence space since 1998 and, in my opinion, credit unions and retail banks significantly lag other industries in the area of analytics. For example, retail, manufacturing, and Wall Street invest heavily in analytics because they understand the competitive advantage analytics can provide.

I think most credit union CEOs now have a limited window of time to take action and re-define themselves as “Analytic Competitors”. Take a look at what UBER is doing. It caught the taxi industry asleep at the wheel just like Amazon did to Borders and Barnes & Noble. Now, the taxi industry is struggling to come up with a competitive response.

A few credit union CEOs have embraced analytics as a key foundational element of their competitive strategy and are aggressively moving their organizations in that direction. However, most CUs are far behind the adoption curve and need to catch up fast.

As credit union leaders think about how BD/A fits into their strategic plan for 2015, it will be important to evaluate this initiative along the three critical dimensions of People, Process, and Technology. To help with this, I have provided a table below that provides that summarizes the Key Success Factors for each of these dimensions, which is based on over 10 years of implementation experience.


Key Success Factors


  1. The CEO is engaged and sees analytics as a core component of the strategic plan.
  2. There is a named executive sponsor that is constantly engaged in supporting the team.
  3. There is an Analytics Governance (AG) team that includes Subject Matter Experts from different areas of the CU (e.g. - Lending, Marketing).
  4. The AG team leader shares the CEO’s vison.



  1. Develop an Analytics Road Map that is tied to the CU’s strategic plan. Set up quarterly review meetings between the AG Team and the Executive Sponsor to review progress against this plan.
  2. Develop a phased implementation plan for the data warehouse. Start with Core then stage the ancillary systems based on the Analytics Roadmap.
  3. Promote the integration of analytics into every day decision making.
  4. Encourage active, scheduled, participation by IT and the business in (a) Implementation and (b) the AG teams
  5. Establish that the AG team makes the final decisions on data questions like, “How do we define a Member?”
  6. Focus on standing up one analytics “application” at a time. This will build excitement and confidence.

Set the expectation that Big Data & Analytics is a journey not a destination; the data warehouse will always be in a state of expansion (e.g. - new data sources) and improvement (e.g. - better user interfaces).


  1. Implement an Enterprise Data Warehouse Architecture that is:
    • System Agnostic
    • Scalable
    • Provides granularity to the atomic level of the data
    • Uses conformed dimensions
    • Emphasized flexibility
    • Employs an open user interface (UI) that supports any data visualization software
  2. Data Visualization Software (e.g. - iDashboards, SSRS, other…)
  3. Data Integration Technology (e.g. - SSIS, Informatica)
  4. Access to Data Scientists to run advanced analytic models (e.g. - R, SAS, SPSS)

 Are you ready for a Big Data/Analytics initiative?  Find out now with the Credit Union Big Data/Analytics Readiness Assessment:

Assess Your Big Data/Analytics Readiness

Topics: Business Intelligence, Big Data, Credit Unions, Data Analytics