Home / Case Studies / Trend Analysis & Early Warning
Trend Analysis & Early Warning
Analytics
Trend charts and leading indicators in Power BI; alerts when parameters drift. Earlier detection and preventive action.
Executive Summary
Quality issues were often discovered only after defects had occurred. This project implemented trend analysis and leading indicators (e.g., parameter drift, near-miss counts) in Power BI, with alerts when trends crossed thresholds. Outcomes: earlier detection of process drift, fewer customer-impacting defects, and a shift from reactive to preventive action.
- Earlier detection of process drift via trend alerts
- Fewer customer-impacting defects
- Preventive rather than reactive quality actions
Context & Problem
By the time SPC or final inspection caught an issue, bad product had often already been made. The organization wanted to use trend analysis and leading indicators to act before defects occurred.
Methodology & Frameworks
Trend charts for key parameters and defect rates in Power BI. Leading indicators (parameters that tended to drift before failure). Alert thresholds and response procedures when a trend crossed a threshold.
Implementation
Historical data was analyzed to identify parameters that correlated with future defects. Dashboards were built in Power BI with trend charts and alert logic. Recipients were trained on how to respond to alerts. Thresholds were refined over time.
Outcomes
- Earlier detection—drift was often caught before defects reached the customer.
- Fewer defects—preventive action reduced customer-impacting issues.
- Culture shift—teams began to act on trends rather than waiting for failures.
Lessons Learned
Leading indicators must be validated with data. Alerts need clear ownership and response procedures. Tuning thresholds reduced noise while keeping sensitivity. Trend analysis complemented SPC by adding a time-series view.