Building a business intelligence (BI) program starts with one question: Why?

“Too many people are affected by ‘shiny object syndrome,’” where they’re distracted by the latest new tool, says Anne Legg, director of market/client strategy for AdvantEdge Analytics, a CUNA Strategic Services alliance provider. “Start by asking, ‘what is your why?’ What do you want to accomplish with business intelligence?”

Legg, who addressed the 2019 CUNA Finance Council Conference Sunday in New York City, defines BI as the process of leveraging technology to analyze data with the intent to deliver actionable information that’s easy to digest.

“The primary goal of BI is to enable and empower all levels of credit union leadership to make data-driven decisions that are in the best interest of members, the credit union, and the community,” she says. “You have a lot of data and a lot of ways to leverage it.”

This data includes product use, account balances, transaction and payment histories, spending, behavior, demographics, member characteristics such as age and assets—even social media, Legg says. “You need to tell the story of what your data means.”

She offers three best practices to become a data-driven organization:

1. Be agile. Agile development is a methodology that prioritizes end-user feedback, responsiveness, and consistency. It consists of the following core elements:

• Backlog: A documented list of current and future project the BI team will complete.
• Tasks: These incremental pieces of a project are pulled from the credit union’s backlog.
• Iteration: A process of moving through your tasks.
• Sprints: Tasks broken down into small pieces that take two weeks or less.
• Stand-ups: Regular meetings during which staff identify what they did previously, what they’re working on, and what obstacles arose. “This allows cross-functional teams to create focus and solve problems,” Legg says. “Otherwise, it’s too easy to go down the rabbit hole.”
• Increments: Small, connected outputs from the agile development process.

These elements provide value more quickly, which creates business momentum, she says. “It allows for a deeper understanding of ‘why.’ And it allows departments to build products with the end user in mind.”

2. Empower end users to explore data in new and powerful ways. Different end users need to digest the same data in different ways.

The BI team must build solutions that encourage end users to discover insights and ask deeper questions by creating intuitive and controlled environments. Flexible dashboards, for example, allow users to prioritize data delivery and allow for continuous analysis even as the data targets grow and evolve over time.

3. Data governance. Developing and implementing data governance protocols is paramount, Legg says.

This entails:

• Implementing a data vision and goals. Your strategic priorities will determine the proper data governance operating model and provide a link to business value and stakeholder engagement.
• Prioritizing data based on levels of criticality and imparting a higher level of care to critical data elements.
• Documenting metadata and data lineage in an enterprise “data dictionary” to drive a common understanding and consistent use of data.
• Maintaining high data quality, with regular monitoring and reporting.
• Implementing data policies, standards, and processes outlining the oversight structure and enforcement mechanism for compliance and data management.

Taking these steps will enable credit unions to better know their members, improve allocation of resources, and create data-driven decisioning.

“Recognize data as an asset,” Legg says. “she says. “Credit union leaders often are intuitive learners—they trust their gut. But BI allows us to combine the head and the heart and move those gut decisions into something data driven.

“The fun part is when you look at the data and say, ‘who would have known?’ The magic happens when you get to ‘why.’”

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