Opportunity Radar
It turns the quality-reject data you already keep into a ranked, dollar-first list of the five fixes worth chasing now. No new data collection, no new system of record.
The same quality-reject records you already track on the board today. Pulled in as a table.
Power BI / exportThe five most valuable fixes, money first, each with the reason it ranks there and where to start.
Web appMark one handled or skip it, and the next-best problem moves up. The board always shows five.
LiveThe seven marked Need are the minimum to rank opportunities. The three marked Nice just sharpen it.
| Field | Example | What the tool builds from it |
|---|---|---|
| date Need | 2026-05-14 | Trend (getting worse), recency, cost if ignored |
| part_number Need | M667233660 | Groups parts into families, concentration |
| production_line Need | 49 | Concentration, and where to go look |
| defect_type Need | Plating pits | Defines the opportunity and the grouping |
| quantity_rejected Need | 12 | Volume and frequency |
| cost_impact_usd Need | 384.00 | The money: annualized savings and the ranking |
| supplier Need | Apex Castings | Supplier signal (your sourcing lens) |
| part_description Nice | Pac R tube 36in, front | Sharper grouping by shape (front vs rear) |
| process Nice | Zinc plating | Process-level grouping and recommendations |
| disposition Nice | Rework | A more accurate cost number |
Note: geometry and exact dimensions are not needed. The tool infers part family and shape from the description and part number. If the dollar cost is not already on the board, we only need a cost-per-part (or the rework and scrap cost) to turn quantities into dollars. The sample file below is about 1,200 records over 15 months, which rolls up into roughly 30 ranked opportunities (about $592K of cost of quality).