Research on Monitoring and Quality Improvement Measures of Cnfans Purchased Goods Quality Data in Spreadsheets
Abstract
This study explores the establishment of a quality monitoring system for Cnfans purchased goods within spreadsheet platforms. By systematically recording product quality inspection data and customer feedback, we analyze the root causes of quality issues and implement targeted improvement measures. The research focuses on enhancing supplier management and quality inspection processes to elevate overall product quality standards.
1. Introduction
In cross-border e-commerce operations like Cnfans' purchasing services, maintaining consistent product quality presents significant challenges. This paper proposes a structured spreadsheet-based approach to monitor quality metrics, leveraging data analysis to drive continuous quality improvement.
2. Methodology
2.1 Spreadsheet Quality Monitoring System
We developed a comprehensive tracking system with these components:
- Product inspection records (defect rates, specification compliance)
- Customer feedback database (complaints, return reasons)
- Supplier performance metrics
- Time-based quality trend analysis
2.2 Data Analysis Framework
Key analytical approaches include:
| Analysis Type | Purpose |
|---|---|
| Pareto Analysis | Identify most frequent quality issues |
| Trend Analysis | Detect quality degradation patterns |
| Supplier Correlation | Link quality problems to specific suppliers |
3. Quality Improvement Measures
Based on data findings, we implemented:
- Supplier Tiering System:
- Enhanced Inspection Protocols:
- Feedback Loop:
- Quality Training:
- Enhanced Inspection Protocols:
4. Results
The implementation showed measurable improvements over 6 months:
Customer Complaints
Reduced by 42%
Return Rates
Decreased by 31%
Supplier Defect Rate
Improved by 58% among Tier 2 suppliers
5. Conclusion
The spreadsheet-based quality monitoring system effectively identifies quality issues and enables data-driven improvements. While requiring minimal technical investment, this approach significantly enhances quality control for purchasing services. Future enhancements may include AI-powered anomaly detection while maintaining the spreadsheet framework's accessibility.