A strategic focus is a necessity for any credit union seeking improvement. To set attainable goals requires a planning process that relies on learning from experience and accurate projections for the future. There are two ways to understand this history and set direction: one is to talk about what you think happened and will happen; the other is to let the data tell you what happened and extrapolate that knowledge into the future.
When you are in your planning session, how often do you hear, “I think…” or “My gut tells me…” Comments like these are an indication of whether you are planning from intuition or knowledge. To move from this “I think” to fact-based planning requires data.
Credit unions hold a significant amount of data, so much data that a marketing company would trade their first-born child for the insights within the credit union’s core and other applications the credit union uses. The challenge that credit unions face is this data is tough to access. It is often in proprietary programs that require professional services, consultants, or costly APIs to access. The other challenge is, to make sense of these insights, requires connecting the dots from two or more applications or systems. Too often, the linking of dots needs someone to “cut and paste” or key-enter data from one or more applications into an Excel spreadsheet. This methodology is time-consuming and prone to human error. The time to collect and organize the data take so much time; the organization doesn’t have time to understand what the data is telling them.
Credit unions that are successful in making sure they have the data to make, not only to understand the rear view mirror view of data, but also the front windshield view of data for forecasting, need to build a strategy and strategic plan to harvest, aggregate, store and then bring data to the point it is normalized, cleansed, accessible, and provides single source of truth for the credit union.
So, in preparation for strategic planning, how does a credit union transition from intuition to data-driven?
- Identify all of the critical data sources. A vital data source is one that holds member balance and engagement. This critical data is in just a few sources: core, online banking, mobile banking, and the loan origination systems.
- Identify where to collect or aggregated this data. A word of caution, don’t just go out and spend a pile of money on a “data warehouse solution” before you know how system/core agnostic the solution is.
- Agree on data definitions. Terms that need to be defined are a member, household, member, active member, inactive member, active account, inactive account, new member, etc.
- Identify projects to bring all of these “critical data sources” into the data warehouse and set time to complete goals, budget allocations, and resource allocations for these projects.
- Develop the organizational structure and skills to mine the data for critical decision-making information and build reports that are easily understood and made actionable.
This process is not a magic wand. It takes time, money, resources, skill re-alignment or FTE adds, discipline, and to agree that the data, once cleansed and normalized, will “tell the truth, the whole truth, and nothing but the truth.”
Written for Synergent by Rich Jones, President and Principal at Leading2Leadership LLC, a strategic planning consultancy that specializes in helping credit unions prepare and transform to better compete in digital and data-driven competitive business environment. Rich has been a frequent speaker at Synergent events, including our Technology Workshop.