Executive KPI Dashboard for Industrial Operations

A mid-size manufacturer with 200+ employees was running its entire operational reporting through manual spreadsheets. The finance and operations teams spent roughly 14 days each month compiling reports for leadership. By the time executives saw the numbers, the data was already stale and decisions were reactive rather than proactive.

The CEO wanted one place to see what mattered, updated in real time, without waiting for someone to pull a report.

The reporting bottleneck wasn't a people problem. It was a systems problem:

Data lived across 5+ disconnected sources (ERP, spreadsheets, production logs, financial systems, HR records)

No standardized KPI definitions existed across departments

Reports were manually assembled in Excel, with frequent copy-paste errors

Leadership meetings relied on outdated numbers and gut feeling

No alert system existed for anomalies or threshold breaches

Phase 1: Strategic Immersion (Days 1-3) I mapped the full operational data landscape: every source, every report, every decision the leadership team needed to make. Through interviews with the CEO, CFO, and operations director, I identified the 12 KPIs that actually drove decisions (out of 40+ metrics they were theoretically tracking).

Phase 2: Architecture & Build (Days 4-7) I designed a KPI hierarchy organized by decision type: financial health, production efficiency, workforce utilization, and quality control. Each metric was connected directly to its source system via Power BI data pipelines. The dashboard was built with three views: executive summary, operational deep-dive, and trend analysis.

Phase 3: Testing & Refinement (Days 8-9) I validated every data point against historical reports to ensure accuracy. Stress-tested the alert logic (threshold breaches, anomaly detection). Refined visualizations based on feedback from the leadership team to ensure the dashboard answered their actual questions, not just displayed numbers.

Phase 4: Delivery & Training (Day 10) Delivered the live dashboard with a 90-minute walkthrough session. Provided documentation covering data refresh schedules, how to interpret each metric, and troubleshooting steps. The team started using it the same day.

Reporting time cut from 14 days to 1 day (93% reduction)

12 operational KPIs tracked in real time across 4 departments

Automated alert system catching anomalies that previously went unnoticed for weeks

Leadership shifted from monthly reactive reviews to weekly data-driven decisions

Excel-based reporting eliminated entirely for executive-level metrics

Finance team reclaimed approximately 80 hours per month previously spent on manual reporting

Power BI, SQL, Excel, Google Sheets, Notion