Research on Monitoring and Quality Improvement Measures of Cnfans Purchased Products in Spreadsheets-OK Spreadsheet-The best and new spreadsheet

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Introduction

With the rapid development of cross-border e-commerce, Cnfans, as a purchasing agent platform, plays a significant role in connecting global consumers with Chinese products. However, ensuring consistent product quality remains a critical challenge. This study explores the establishment of a quality monitoring system within spreadsheets to track product inspection data, user feedback, and other metrics. Through data analysis, we aim to identify root causes of quality issues and implement targeted improvement strategies to enhance overall product quality.

1. Building a Quality Monitoring System in Spreadsheets

Spreadsheets serve as an efficient tool for tracking multidimensional quality data due to their flexibility and accessibility. The proposed system includes:

Product Inspection Records:
User Feedback Database:
Supplier Scorecards:

Figure 1 illustrates the data framework integrating automatic COUNTIF/VLOOKUP
=IF(DefectRate!B2>0.05, "Escalate", "Normal")

2. Data Analysis for Root Cause Identification Pivot tables and conditional formatting enable rapid identification of patterns: Product Category Defect Rate (%) Top Issue Electronics 8.2 Battery lifespan Apparel 3.1 Size discrepancy Statistical functions (CORREL, regression) help correlate defects with variables like shipping methods or supplier tiers. 3. Targeted Quality Improvement Measures 3.1 Supplier Management Enhancements Implement quarterly audits triggered by spreadsheet alerts when defect rates exceed thresholds. Establish a dynamic supplier blacklist using FILTER 3.2 Inspection Process Optimization Develop standardized checklists integrated as dropdown menus in spreadsheets. Introduce barcode scanning to automate data entry and reduce human error. Conclusion This spreadsheet-based system provides real-time visibility into product quality metrics, enabling data-driven decision making. Future work includes connecting Google Sheets with ERP APIs for live data synchronization and implementing Python scripts for advanced predictive analytics beyond native spreadsheet functions. References: Deming, W.E. (1986). Out of the Crisis. MIT Press. Microsoft Excel Business Intelligence (2023). "Dynamic Dashboards".

Product Category	Defect Rate (%)	Top Issue
Electronics	8.2	Battery lifespan
Apparel	3.1	Size discrepancy

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