Freight Spend Intelligence — Chibuike Dialaekwe

// spend overview

Freight Spend Summary

// optimization potential

Identified Savings Opportunities

// analytics

Freight Cost Analysis

Freight Spend by Lane — Actual vs Benchmark (€)

Top 12 lanes by spend volume. Red bars indicate lanes where actual cost exceeds market benchmark — priority renegotiation targets

Spend by Carrier (€)

Total freight spend distribution across 8 carrier partners — concentration risk and renegotiation leverage

Spend by Transport Mode (€)

Modal split of freight spend — identifies modal shift opportunities from high-cost air to road or sea

Cost Per Kg by Carrier (€/kg)

Efficiency benchmark — carriers with high cost/kg on similar routes signal contract renegotiation opportunity

Variance from Benchmark by Mode (%)

How far actual cost deviates from market rate per transport mode — positive = overpaying vs benchmark

// raw data

📊 Raw Dataset

Freight invoice data aggregated across 8 carriers — 50 rows shown. Red rows = overcharge flagged (>15% above benchmark).

#	Shipment ID	Origin	Destination	Carrier	Mode	Weight (kg)	Distance (km)	Freight Cost (€)	€/kg	Benchmark (€)	Variance %	⚠ Flagged

// methodology

Problem → Solution → Findings

🔴▶ PROBLEM

Freight invoices from 8 carriers arrived in different formats — PDFs, Excel files, EDI messages — with no single consolidated view of total spend, making cross-carrier benchmarking impossible
Lane-level cost visibility did not exist: the company knew total freight spend but had no idea which origin-destination pairs were overpriced versus market rates
Carrier contracts were renegotiated based on general volume arguments, with no lane-level data to challenge specific rate line items — leaving significant negotiation leverage unused
Air freight was being used for shipments within 800km of road distance purely from habit — no one had quantified the modal shift saving available by switching to express road services

🔵▶ SOLUTION

SQL pipeline extracting and normalising freight invoice data from 8 carrier portals into a unified freight_invoice_fact table with standardised lane, weight, mode, and cost fields
Python benchmarking script pulls market rate indices (Freightos Baltic Index for sea, Xeneta benchmarks for road/air) and calculates variance per lane — flags any lane >15% above benchmark as overcharge
Power BI dashboard visualising spend by carrier, lane, mode, and month — with drill-through from overcharge alerts directly to invoice-level detail for dispute resolution
Modal shift analyser calculates CO₂ and cost saving from switching flagged air shipments to road or rail, linking freight optimisation to ESG reporting requirements

🟢▶ FINDINGS

27% of lanes were priced above the market benchmark — with the Hamburg→Warsaw road lane overcharged by 34%, representing €48,000 in addressable annual savings from a single route renegotiation
Air freight accounted for 38% of total spend but only 12% of shipment volume — analysis revealed 41% of air shipments could have moved by express road at 65% lower cost per kg
DB Schenker showed the highest cost/kg variance at +21% above benchmark on Central European lanes — direct renegotiation using this data secured a 17% rate reduction within 6 weeks
Consolidating 3 partially-loaded sea freight shipments per month into 1 full FCL container would reduce sea freight cost by €31,000 annually while also reducing Scope 3 emissions
Total identified savings across all flagged lanes: €214,000/year — representing 12.4% of total freight spend

// outlook

📈 Forecast & Projections

Annual Freight Spend Forecast with Lane Optimization Potential (€)

Historical monthly spend (solid) vs 12-month forward projection — shaded area shows savings achievable if flagged lanes are renegotiated

// strategic guidance

💡 Advice for Companies with Similar Challenges

Freight Cost Control — Key Recommendations

Before renegotiating carrier contracts, build a lane-level spend database first. Carriers set rates knowing shippers lack visibility. Even 3 months of clean freight data gives you the negotiating leverage to reduce rates 10–20% — far more than general volume arguments achieve.
Benchmark every lane separately, not just total contract value. A carrier can give you a 3% overall rate reduction while quietly raising rates on your highest-volume lanes by 8%. Lane-by-lane benchmarking closes this loophole entirely.
Audit your modal split quarterly. Air freight usage drifts upward over time as operations teams default to speed — often unnecessarily. A simple rule: any shipment under 800km and non-urgent should be road. Any >5,000km and non-urgent should be sea. Apply it systematically and you will find 10–20% of your air spend is avoidable.
Connect freight optimisation to your ESG reporting from day one. The same analysis that finds cost savings also identifies Scope 3 emission reductions. Presenting freight savings alongside CO₂ reduction numbers gives the project dual business justification and is increasingly expected by sustainability-conscious customers.

// KEY TAKEAWAY

Companies that invest in freight data infrastructure consistently outperform those that rely on relationship-based carrier management. One analyst with 3 months of clean invoice data and a benchmarking model will deliver more freight savings than a procurement director with 10 years of carrier relationships but no lane-level visibility. Data always wins in freight negotiations.

Freight SpendIntelligence

Freight Spend
Intelligence