Every minute of unplanned production downtime is a minute of lost profit. For too many manufacturers, “downtime” is just a high number on a summary report, not an actionable metric.
If you are treating every machine failure or sensor trip with the same priority, you are likely wasting resources. To fix your bottlenecks, you need a targeted, data-driven strategy.
Introducing the Power BI Downtime Pareto Analysis report.

📊 Stop the Leak and Optimize Your Output:
The 80/20 Rule Applied: Automatically identify the 20% of critical failure points causing 80% of your total downtime duration.
Visualize Unplanned Causes: Stop guessing why machines are down. Drill down from ‘Plant Level’ to ‘Equipment ID’ to pinpoint the main culprits (Sensor Trips, Changeover Jamming, etc.).
Target Maintenance Efforts: Shift your maintenance team from reactive firefighting to predictive optimization by tackling the highest-impact issues.
Track Cumulative Savings: Visualize how targeting top Pareto causes significantly improves your overall line efficiency (OEE).

💡 The Business Case:
Moving to a data-driven downtime strategy typically helps manufacturers reduce unplanned downtime by 15-25% within the first six months.
Is your production floor still managing millions in assets using static Excel sheets? Let’s build a smarter factory.

👇 Drop a “DEMO” in the contact us form or send me a DM, and let’s discuss how we can tail or this Power BI dashboard for your operation.