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Building and Organization-Wide Reporting Infrastructure for Legal Services Nonprofit
A nonprofit legal services organization managed all case and client data across multiple program areas through a case management system (CMS). Reports on program performance, case trends and grant/funder compliance were being produced manually, upon request.
Developing a suite of Power BI dashboards, connected to the CMS through an API, around the distinct data needs of each of the programs focus areas allowed leadership access to consistent, real-time and reliable performance data for the first time — supporting operational and long-term strategic planning decision making, while reducing manual reporting time by approximately 40% through automation of recurring reports.
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This dashboard was created to look at the distribution of federal contract awards in FY25 through a specific contracting medium. The first page is looking at all department contract awards and the second is looking at awards for one departmnt in particular and then broken out by component within that department
Most dashboards don’t have a visualization problem.
They have a KPI problem.
I’ve reviewed dozens of reporting systems recently and the pattern is consistent:
Metrics are defined differently across sheets
“Revenue” means one thing in finance and another in marketing
KPIs are tracked… but not tied to decisions
Dashboards look clean but don’t answer operational questions
When metric logic isn’t aligned, teams don’t have a data problem.
They have a decision problem.
That’s why I’ve started offering a structured KPI & Revenue Diagnostic Audit — focused on:
• Metric consistency
• Reporting logic
• Revenue driver alignment
• Decision-readiness
If you're building dashboards or scaling reporting systems, this layer matters more than design.
Data VisualizationData AnalysisProduct Data AnalyticsMicrosoft ExcelMicrosoft WordGoogle Sheetsexceldashboardexceldataanalytics
Completely agree. Most dashboards optimize for visuals, not decision velocity. If KPIs aren’t standardized across teams, you’re basically scaling confusion. The real leverage is in metric governance before visualization.
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