AI Automation Project Brief: Reporting Dashboard for Ops Visibility (Decatur)
Industry: Manufacturing / Operations · Location: Decatur, AL
Problem Overview
- Weekly reporting built manually across multiple tools
- Limited visibility into backlog, throughput, and aging
- Leadership updates requiring extra time and reformatting
AI Solution Implemented
- Lightweight KPI dashboard with stable definitions and refresh schedule
- Exception reporting (what changed and what needs attention)
- Optional narrative summaries grounded in dashboard data (not guesses)
- Data quality rules and a clear system-of-record decision per field
Tools Used
- BI tools (Looker Studio/Power BI/Metabase patterns)
- Data connectors and lightweight ETL
- LLM summaries derived from metrics (optional)
- Alerting for data pipeline failures and exceptions
Outcome (Qualitative)
Outcomes are described at a qualitative level to avoid exaggeration and to keep these briefs educational.
- More predictable weekly reporting with less manual effort
- Clearer operational visibility for leadership decisions
- Reduced time spent reconciling numbers between tools
Who This Is a Good Fit For
- Ops teams with repeated weekly reporting work
- Organizations with data split across a few systems
- Leaders who want exception-based visibility