flowchart LR
A[Postgres<br>Operational Data] --> D[Data Model<br>Star Schema]
B[Dataverse<br>Asset & Site Data] --> D
C[Financial Systems<br>Revenue & Cost] --> D
D --> E[DAX Measures<br>KPIs & Calculations]
E --> F[Power BI Dashboard<br>Executive Views]
F --> G[Business Unit<br>Drill-Through]
F --> H[Facility-Level<br>Detail]
F --> I[Trend & Variance<br>Analysis]
Executive Infrastructure Dashboard
A real-time operational and financial performance platform for executive decision-making across all business units
Executive Infrastructure Dashboard
Role: Lead Developer & Analyst · Organization: Select Water Services · Status: Production — Used by Executive Leadership
The Problem
Select Water Services operates across multiple business units and facilities, each generating its own stream of financial and operational data. The executive team needed a unified view to make informed, timely decisions — but what they had was fragmented:
- Scattered reporting — financial performance, operational metrics, and capacity data lived in separate systems and separate reports, requiring manual consolidation to get a full picture
- Lagging visibility — by the time data was compiled and formatted for leadership, it was often days or weeks old, limiting its usefulness for real-time decision-making
- No drill-through capability — high-level summaries existed, but executives couldn’t easily drill from a portfolio-level view down to individual business units or facilities without requesting ad-hoc reports
- Disconnected financial and operational data — revenue and margin figures were tracked separately from utilization rates, capacity, and throughput, making it difficult to see the operational drivers behind financial outcomes
The Solution
I designed and built a comprehensive, real-time executive dashboard in Power BI that consolidated financial and operational performance into a single, interactive platform.
Design Philosophy
The guiding principle was: every screen answers a decision. Rather than building a data dump with every available metric, I worked with executive stakeholders to identify the specific decisions they make weekly and monthly, then designed each dashboard view to directly support those decisions.
Architecture
What the Dashboard Delivers
Financial Performance Layer:
- Revenue by business unit and facility — with actuals vs. forecast comparison and variance highlighting so executives immediately see where results are tracking ahead or behind plan
- Gross profit and margin percentages — broken down by segment to assess the profitability mix across the portfolio and identify which units are driving margin expansion or compression
- Period-over-period trending — monthly and quarterly views that surface trajectory, not just snapshots, enabling executives to distinguish between one-time blips and emerging trends
Operational Performance Layer:
- Utilization rates — how effectively assets are being deployed across facilities, surfacing underutilized capacity that represents revenue opportunity or overutilized assets that signal risk
- Capacity and throughput metrics — real-time visibility into operational bottlenecks, enabling proactive resource allocation before constraints impact financial performance
- Operational volume tracking — activity-level metrics that provide context for the financial numbers, connecting revenue outcomes to the operational work that produces them
Executive Decision Support:
- Drill-through from portfolio to facility — executives start with a high-level view of all business units, then click through to individual facilities for granular detail without switching reports
- Variance analysis — automated flagging of actuals-to-forecast variances beyond threshold, so leadership focuses attention on the exceptions rather than reviewing every line item
- Strategic alignment views — progress tracking against strategic objectives, connecting daily operational metrics to quarterly and annual goals
Implementation Approach
Phase 1 — Stakeholder Discovery
Before touching a data model, I spent time with the executive team to understand their decision-making cadence:
- What decisions do you make weekly? Monthly? Quarterly?
- What data do you wish you had when making those decisions?
- Where do you currently go to find answers, and what’s frustrating about that process?
- What does “good” look like for each business unit?
This discovery shaped every subsequent design decision and ensured the dashboard solved real problems rather than displaying data for its own sake.
Phase 2 — Data Modeling
Built a star schema data model that unified financial and operational data into a single queryable structure:
- Designed fact tables for financial transactions, operational volumes, and capacity metrics
- Created dimension tables for business units, facilities, time periods, and asset categories
- Developed DAX measures for calculated KPIs — margin percentages, utilization rates, variance calculations, and period-over-period comparisons
Phase 3 — Dashboard Development
Built the dashboard in iterative cycles, validating each view with stakeholders before moving to the next:
- Executive Summary — portfolio-level KPIs with traffic-light status indicators
- Business Unit Views — detailed performance by segment with drill-through to facilities
- Operational Detail — utilization, capacity, and throughput metrics with trend context
- Variance & Forecasting — actuals vs. forecast with automated exception flagging
Phase 4 — Deployment & Adoption
- Configured automated data refreshes to ensure the dashboard reflected current operational reality
- Trained executive users on navigation, drill-through, and filtering
- Established a feedback loop for iterating on views based on how leadership actually used the tool in practice
Visual Walkthrough
Executive Summary View Portfolio KPIs — revenue, gross profit, margin, utilization
Business Unit Drill-Through Segment performance with actuals vs. forecast
Operational Metrics View Utilization rates, capacity, throughput by facility
Trend & Variance Analysis Period-over-period trends with variance flagging
TipScreenshots Available
Anonymized screenshots or a live walkthrough of the dashboard are available upon request during interviews. The dashboard contains proprietary financial and operational data.
Results & Impact
Real-Time
Executive visibility into all business units
Unified
Financial + operational data in one platform
Self-Service
Drill-through eliminates ad-hoc requests
Adopted
Used by executive team for weekly decisions
What Changed for Leadership
- Faster decisions — executives no longer wait for compiled reports; they open the dashboard and have current data with drill-through capability at any time
- Better decisions — connecting financial outcomes to operational drivers in a single view means leadership sees why numbers are moving, not just that they’re moving
- Proactive management — variance flagging and trend views surface problems early, enabling intervention before small issues compound
- Aligned organization — a shared dashboard creates a shared understanding of performance, reducing the “my spreadsheet says something different” problem in leadership meetings
- Reduced ad-hoc burden — the analytics team saw a significant reduction in one-off data requests because leadership could self-serve through drill-through navigation
Why This Project Matters
This wasn’t a reporting project — it was a decision-support platform. The difference matters. Reporting asks: “What happened?” Decision support asks: “What should we do about it?”
By combining financial KPIs with operational drivers, the dashboard gives executives the full picture: not just that revenue is up or down, but what’s driving it — utilization, capacity, throughput, mix. That operational context is what turns a number on a screen into an actionable insight.
The design approach — starting with stakeholder decisions, not available data — is something I bring to every project. The best dashboards aren’t the ones with the most data; they’re the ones that answer the right questions.
Technical Stack
| Component | Technology | Purpose |
|---|---|---|
| BI Platform | Power BI | Interactive dashboards, drill-through, scheduled refresh |
| Data Sources | Postgres, Dataverse, Financial Systems | Operational, asset, and financial data |
| Data Modeling | Star schema (DAX) | Unified fact/dimension model, calculated measures |
| KPI Engine | DAX measures | Margin %, utilization rates, variance calculations |
| Query Layer | SQL (Postgres) | Data extraction, validation, transformation |
| Governance | Dataverse | Asset classification, data quality enforcement |
| Refresh | Automated schedule | Near-real-time data currency |
Key Skills Demonstrated
Dashboard Architecture
End-to-end design from data model through interactive executive views with drill-through navigation
Stakeholder Discovery
Interview-driven design that starts with decisions, not data — ensuring every view has a purpose
Data Modeling
Star schema design unifying financial and operational data into a single queryable model
DAX & Calculated Measures
Complex KPI calculations including margin percentages, utilization rates, and variance analysis