Credit union leaders are increasingly interested in using analytics to drive better decisions. A common question they ask is, “Once I have comprehensive access to all credit union data, how do I use it effectively?”
Thomas Davenport, co-author of Competing on Analytics, addressed the question in a recent Harvard Business Review article, Keep Up with Your Quants.
Davenport recommends decision makers need to be most active in the beginning step and ending step in the analytics process. However, awareness of the middle steps and how to keep them on track is also important.
- Recognize the problem or question - Effective problem definition is mandatory. Many times credit union leaders think they know the problem to be solved only to realize they were wrong. Not only does the “right” problem need to be identified but it is crucial that leader clearly explain the details to the analytical team.
- Review previous findings – Efforts must be made to leverage experience. High achieving credit unions take the time to document analytics efforts so future projects can easily study the processes followed and results of the processes. Leaders can help in the process to evaluate relevant historical material.
- Model the solution and select the variables – Based on the detailed problem formulation in Step 1, hypotheses are formed and appropriate data is selected to test the hypothesis. While this is the analytical team’s strength, the business leader needs to understand their thinking to avoid being surprised in the last step.
- Collect the data –This step assumes credit union data has been properly prepared in terms of integration across the organization, data quality, and ease of access. If the necessary data is not available, the prior steps are wasted. Efforts need to be taken to solve the data issues and then re-start the analytics process. Clearly, credit union leaders must take a strategic perspective on the importance of data and give the organization the opportunity to leverage important internal information.
- Analyze the data - The analytics team must be chosen wisely to ensure they have the knowledge, skills, and experience to apply the best analytical tools to the given situation. The decision maker needs to understand the capabilities of various analytical tools and be able to understand the results they yield.
- Present and act on the results – Now the decision maker takes center stage again and weaves a compelling story that moves leaders and other and stakeholders to take action and solve the problem.