Risk Control in Second-Hand Watch Purchasing: BBDBuy Spreadsheet's Movement Longevity Prediction Model
2025-07-20
Introduction
In the booming market of second-hand luxury watches, risk mitigation is critical for both buyers and resellers. BBDBuy, a leading player in the pre-owned watch industry, has developed an innovative spreadsheet-based movement longevity prediction model
The Challenge: Identifying Timebomb Movements
Key risks in second-hand watch purchasing include:
- Hidden mechanical wear in movements
- Undocumented servicing history
- Frankenstein watches with incompatible parts
- Counterfeit or modified calibers
The BBDBuy model specifically targets these pain points through data-driven analysis.
Core Algorithm Components
| Parameter | Weighting | Data Source |
|---|---|---|
| Service Records | 35% | Original paperwork/EDI data |
| Amplitude Variance | 25% | Timegrapher measurements |
| Power Reserve Efficiency | 20% | Bench testing |
| Producing Year | 10% | Serial number decoding |
| User Reviews | 10% | Platform transaction history |
The proprietary scoring system generates a LOPS (Longevity Prediction Score)Excellent (80+), Moderate (50-79), and High Risk (below 50).
Actuarial Validation
Sample size of 2,137 Rolex Caliber 3135 movements demonstrated:
+----------------------+---------------+----------------+ | LOPS Classification | 3-Year Claims | Mean Repair Cost| +----------------------+---------------+----------------+ | Excellent | 8.5% | $420 | | Moderate | 34.1% | $780 | | High Risk | 61.7% | $1,220 | +----------------------+---------------+----------------+
Implementation in Purchase Workflow
BBDBuy integrated this model directly into Google Sheets used by purchasing agents:
- Field input tab
- Validation dashboard
- Dynamic pricing adjustment
- Validation dashboard
"The spreadsheet interface allows real-time decision making during watch sourcing" - BBDBuy quality control lead