In the complex world of global logistics, controlling freight costs is a constant challenge. For businesses leveraging services like CNFANS Shipping, data-driven decision-making is no longer optional—it's essential. By systematically analyzing historical spreadsheet data, companies can uncover significant savings and enhance supply chain efficiency.
The Power of Your Historical Shipping Data
Every shipment generates a data point. Collected over time in spreadsheets or databases, this information forms a treasure trove of insights. Key data points to track include:
- Freight Charges:
- Route Details:
- Carrier/Service:
- Performance Metrics:
- Shipment Specifications:
- Route Details:
A Step-by-Step Guide to Data Analysis for Cost Optimization
Follow this actionable process to transform raw data into actionable intelligence.
Step 1: Data Consolidation & Cleaning
Gather historical freight invoices and logs into a single, structured spreadsheet (e.g., Microsoft Excel or Google Sheets). Ensure consistency in format, currency, and units of measurement. Clean the data by removing duplicates and correcting errors.
Step 2: Comparative Analysis by Route and Carrier
Use pivot tables and charts to compare average costs for identical or similar routes over the past 6-12 months. Group data by:
=AVERAGEIFS(Cost_Column, Route_Column, "Specific Route", Carrier_Column, "Carrier A")
This reveals which lanes are most expensive and identifies consistently high or low-performing carriers for specific trade routes.
Step 3: Performance vs. Cost Trade-off Evaluation
Create a scatter plot with Average CostAverage Transit TimeOn-Time Percentage
Step 4: Identifying Inconsistencies and Anomalies
Sort data by cost per unit (e.g., cost per kilogram or per container) to spot outliers. Investigate sudden price spikes—were they due to peak season surcharges, a specific carrier, or a change in route? Use conditional formatting to highlight these anomalies automatically.
Step 5: Building a "Best-Option" Decision Matrix
Synthesize your findings into a simple reference table. For your most frequent lanes, list the top 2-3 economical options alongside their performance profile.
| Route (Origin-Destination) | Recommended Carrier/Service | Avg. Cost | Avg. Transit Days | Best For |
|---|---|---|---|---|
| Shenzhen to Hamburg | CNFANS Standard Ocean | $1,850 (FCL) | 32 | Cost-sensitive, non-urgent cargo |
| Shenzhen to Hamburg | CNFANS Express Rail | $3,200 (FCL) | 18 | Urgent shipments balancing cost & speed |
Implementing Findings with CNFANS Shipping
Armed with this analysis, your negotiations and bookings become strategic. When preparing a new shipment:
- Consult your decision matrix
- Quote with Purpose:
- Leverage Historical Data in Negotiations:
- Continual Update:
- Quote with Purpose:
Conclusion
Optimizing freight costs is not about always choosing the absolute lowest price, but about selecting the most economical valueCNFANS Shipping