Work began with a Data Strategy Assessment where we interviewed stakeholders across departments to understand their pain points, tool usage, and reporting needs. The assessment concluded with our recommended action plan which outlines an end-to-end data analytics solution.

We executed the recommendations from their roadmap, each phase of the solution providing more ease and insight for decision makers:

• A Data Warehouse in the Cloud: A data warehouse on Azure replaces the manual process of sourcing data from Aptify, MS Dynamics, MS Excel, and elsewhere to build reports. The new data warehouse provides a single point of access to their data and automates the data cleansing process, which alleviates data quality issues and speeds up reporting.
• A Data Visualization and Enterprising Reporting Tool: Built on Power BI, this analytics solution clearly communicates complex data that was once spread out in various systems. Visualizations and reporting in this platform are used to analyze:
  • Membership Trends: Users have a holistic view of member demographics and year-over-year membership trends, such as retention rates and the shared attributes of who left.
  • Survey Results: Cutting survey analysis down from weeks to under one hour, they can quickly analyze member feedback and easily publish results for members to view.
  • Event Feedback: Previously tracked in large flat files, attendance data from their annual convention is now seamlessly added to the application so they can perform demographic analysis and derive insights from attendee feedback.
  • Membership Dues: Instead of waiting on the monthly reconciliation process, users can now access a daily snapshot of paid vs. outstanding status.
  • Finances: Reports contain up-to-date financial metrics, including company assets and liabilities and revenue and expenses, with the ability to drill down by department.

A ground-up approach to fixing data problems resulted in an association analytics solution that will grow along with their membership count. They unified siloed data and broke down departmental decision making. Instead of worrying about data accuracy or completeness, leaders now focus on answering critical questions about their operations:

• Which types of members are being retained?
• What are the demographics of new members?
• Why are members leaving the association and then being reinstated later? What kind of members are leaving and what attributes do they share?
• Which offerings are most likely to retain members?
• Are we losing members to local associations?
• Is there a way to simplify billing at the company level if there are multiple members from the same company?