CNFANS Spreadsheet: How to Monitor Delivery Speed by Courier Line
Automatically rank shipping lines by average delivery time using your historical data.
For e-commerce sellers and logistics managers, consistent delivery speed is a key factor in customer satisfaction and operational planning. Manually tracking multiple courier lines is time-consuming and prone to errors. The CNFANS Spreadsheet
The Core Concept: Data-Driven Courier Assessment
Instead of relying on couriers' advertised speeds or subjective impressions, you build a system that uses your own historical shipment data
Step-by-Step Setup in Your Spreadsheet
Step 1: Data Collection Structure
Create the following columns in your main data sheet (e.g., "Raw Data"):
- Order ID
- Shipping Line
- Ship Date
- Delivery Date
- Delivery Days
- Destination Country/Region
Step 2: Calculate Average Delivery Time Automatically
On a separate analysis sheet (e.g., "Performance Dashboard"), use spreadsheet functions to compute key metrics.
To calculate the average delivery days for Carrier A:
=AVERAGEIF('Raw Data'!B:B, "Carrier A", 'Raw Data'!E:E)This formula averages the "Delivery Days" (column E) for all rows where "Shipping Line" (column B) is "Carrier A".
Step 3: Rank Courier Lines by Performance
Create a table that lists all your courier lines, their average delivery time, and their rank.
Example table structure:
| Courier Line | Avg. Delivery Days | Rank (Fastest to Slowest) | Number of Shipments |
|---|---|---|---|
| Carrier A | 12.5 | 2 | 150 |
| Carrier B | 10.2 | 1 | 200 |
| Carrier C | 14.7 | 3 | 80 |
Use the The RANK.EQ
=RANK.EQ(B2, $B$2:$B$10, 1)1
Tips for Full Automation
- Dynamic Data Ranges:
- PivotTable Reports:
- Conditional Formatting:
- Regular Refresh:
- PivotTable Reports:
Key Benefits of This System
Objective Decision Making
Choose couriers based on hard data from your own operations, not marketing claims.
Identify Trends & Issues
Spot if a courier's performance is improving or deteriorating over time.
Negotiation Power
Use performance data as leverage in contract or rate discussions with providers.
Manage Customer Expectations
Provide more accurate delivery estimates based on historical averages for each line.