The Process: Turning Data into Insight

1. Data Consolidation

   Gather all historical QC reportsshipping documentation. Create a unified database or spreadsheet where each order is linked to its seller, product SKU, QC outcome, and shipping timeline.

2. Key Metric Definition

   Establish the metrics that define "accuracy" for your business. Common ones include:

   • QC Pass Rate (%): (Number of QC-passed units / Total units inspected) * 100.
   • Defect Rate by Category: Frequency of specific issues (e.g., color mismatch, material flaw, functionality).
   • On-Time Shipping Rate (%): Orders shipped by the seller's promised date.
   • Documentation Accuracy: Accuracy of invoices, packing lists, and customs declarations.

3. Seller-Specific Timeline Analysis

   Filter the data for each seller and analyze performance over quarterly or semi-annual periods. This reveals trends—not just snapshots. Look for:

   • Improvement or decline in QC Pass Rate.
   • Consistency in shipping speed and communication.
   • Recurring vs. resolved defect patterns.

4. Comparative Visualization

   Use charts (line graphs for trends, bar charts for side-by-side comparison) to visualize seller performance against your defined metrics over the selected time frames. This makes differences starkly clear.

5. Reliability Scoring

   Assign weighted scores to your key metrics (e.g., QC Pass Rate might be 50% of the total score, On-Time Shipping 30%, Documentation Accuracy 20%). Calculate a Consistent Reliability Score