When most of us think about data, we think about numbers, charts, graphs, and reports. However, we need to talk about CULTURE.

Collecting, aggregating, normalizing, manipulating, and presenting data seems to consume the conversation. However, here is the question we need to ask ourselves, “Is our culture ready to become truly data-driven?” Too often organizations spend lots of money on software, tools, and expertise, only to learn the culture was not ready to be data-driven.

How do I get the culture ready?

1. Remove the data silos. Too often I see data owned by departments. Lending owns lending and collection data, marketing owns marketing data, finance owns finance data, and call center owns call center data. The problem data silos bring to the organization is the loss of data integrity. If the Chief Lending Officer is responsible for making lending and collection goals and they own the data in a silo, there is a risk that the data can be manipulated to tell the story lending wants to show. The only way to wean the credit union from silos is to have the data centrally collected, managed, cleansed, and normalized, to have the definitions of commonly used data terms standardized, and to have the data report queries standardized. Centralizing data is a painful process because some of these silo owners may not like this neutral party controlling the story the data is telling the organization.
2. Make all data accessible to the organization. Data is an organizational asset and needs to be available for all to see. This accessibility and availability of data will allow anyone in the organization to see what is happening and to even ask questions of the silo owner or the data for clarification or understanding.
3. Create a Business Intelligence (BI) unit in your organization. Their job is to collect, aggregate, store, cleanse, and manage all data. The BI staff does not write reports but are the data experts. With accessibility, tools and training are available to the subject matter experts, whether they are marketers, lenders, operational staff, or finance staff, to run their reports. However, the queries, definitions, and timing of reports are understood so variances in reports can be easily explained. This method of data management is called centrally managed, widely distributed or the “hub and spoke model.”
4. Install a Data Governance process. Only when the organization has clean, normalized data can it be successful in aligning reports and rolling out accurate AI and machine learning tactics.

The organization needs to see Business Intelligence the same way they see Human Resources, IT, or Marketing. It is an independent business unit that makes data available to the entire organization in a way they can access and query the data. The organization structure needs to include a strategic owner, usually an SVP or EVP, and a tactical owner. The strategic owner keeps data projects, software, and tools visible in the planning and budgeting process the tactical owner owns the work of collecting, aggregating, normalizing, cleansing, and monitoring of the data, definitions, and queries.

Data is the credit unions most valuable asset; it needs to be right and has a strategic focus.