In the world of cross-border e-commerce and sourcing, data is your most valuable asset. However, when quality control (QC) data and shipping logistics data live in separate silos, you only see half the picture. The HubBuyCN Spreadsheet

Why Combine QC and Shipping Analytics?

Analyzing QC and shipping data independently has limitations. You might know that Route ASupplier B

  • Identify Root Causes:
  • Calculate True Total Cost:
  • Optimize for Reliability & Speed:
  • Make Data-Driven Partner Decisions:

Building Your All-in-One Analysis Spreadsheet

The first step is to create a master spreadsheet that captures linked data points for every shipment batch or order. Essential columns should include:

Supplier Shipping Route/Courier QC Pass Rate (%) Major Defect Rate (%) Shipping Cost (USD) Avg. Transit Time (Days) Parcels Damaged in Transit Total Order Value
Supplier A Air Express - Carrier X 98% 0.5% $450 5 0 $5,000
Supplier B Sea Freight - Route Y 92% 3.0% $150 30 2 $8,000

Leveraging Pivot Tables for Multidimensional Insight

Pivot tables are the engine of this analysis. They allow you to slice, dice, and compare metrics across any dimension effortlessly. Here are key pivot table analyses to build:

1. QC Rate vs. Shipping Route Analysis

Create a pivot table with Shipping RouteAvg. of QC Pass RateAvg. of Major Defect Rate

2. Total Cost Per Route (Including QC Failures)

This advanced view calculates the effective cost. Build a pivot that sums Shipping CostQC Failure CostRouteSupplier. The route with the cheapest freight may have the highest total cost when quality failures are accounted for.

3. Transit Time Reliability Dashboard

Use a pivot table to compare Avg. Transit TimeStdDev. (Standard Deviation)

Generating Actionable Reports

From your pivot tables, create concise charts and dashboards:

  • Combined Scorecard:
  • Cost-Benefit Scatter Plot:
  • Trend Line Charts:

Conclusion

The HubBuyCN Spreadsheet