Case study · Logistics & Supply Chain
Predictive Working Capital & Multi-Node Freight Cash Flow Analytics
A freight forwarding and 3PL logistics enterprise coordinating 45,000+ container shipments annually across North American and European ports.
Engagement record
- Client
- Freight & 3PL logistics company
- Industry
- Logistics & Supply Chain
- System
- Predictive Working Capital & Freight Analytics
- Timeline
- 8 Weeks
About this write-up
This case study describes the engagement as recorded. The client is not named; figures and outcomes are as reported by the client and have not been independently audited.
The challenge
The client operated with volatile 60-to-90 day shipper payment terms against rigid 15-day carrier freight settlements. Fuel price spikes, customs demurrage fees, and fluctuating ocean shipping rates made working capital planning unpredictable, leading to expensive short-term revolving credit draws and $140K in annual interest overhead.
Objectives
- Predict multi-currency cash flow inflows and outflows 60 to 90 days in advance.
- Identify high-risk delayed invoices and automate working capital gap mitigation.
- Incorporate external port congestion and fuel index telemetry into liquidity models.
- Eliminate emergency credit line utilization through proactive liquidity rebalancing.
Discovery
Analysis of 3 years of accounts receivable data revealed that 35% of shipper delays followed identifiable seasonal cash-conservation patterns that traditional static ERP forecasts failed to capture.
What was built
- Multi-Stream Financial Pipeline. Automated ingestion of ERP invoices, bill-of-lading milestones, fuel surcharges, and historical debtor behaviors.
- Predictive Liquidity Engine. Probabilistic neural forecast model outputting 30/60/90-day cash position envelopes with confidence intervals.
- Demurrage & Detention Risk Monitor. Real-time port AIS tracking correlating maritime transit delays with anticipated invoice dispute liabilities.
- Treasury Optimization Dashboard. Actionable recommendation engine advising optimal supplier payment timing to maximize early-pay discounts.
Outcomes as reported
Reported summary: 94.2% 60-Day Cash Flow Accuracy & $1.4M Optimized.
| Figure | What it refers to |
|---|---|
| 94.2% Accuracy | On 60-day enterprise cash position forecasting |
| $1.4M Capital | In unlocked working capital optimization within 6 months |
| $140,000 Saved | In annual revolving credit interest and emergency financing fees |
| 0 Cash Shortfalls | Across 4 consecutive quarters of volatile freight rate swings |
Figures as reported in the engagement record; not independently audited.
Lessons
- Blending external operational data (port dwell times) with accounting ledgers improves financial forecast precision by over 30%.
- Showing confidence intervals alongside projections builds executive confidence in treasury decisions.
Next steps
Deploying automated dynamic supplier discount negotiations powered by real-time treasury surplus calculations.
Implementation questions
The engine models real-time FX hedging rates and currency-specific payment timing to insulate treasury forecasts from exchange fluctuations.
It integrates natively with NetSuite, SAP S/4HANA, QuickBooks Enterprise, CargoWise, and custom SQL data warehouses.
Forecasts recalculate continuously as invoices are issued, payments are settled, and shipment tracking milestones change.
Yes. Treasury officers can run instant stress-test simulations adjusting fuel prices, shipper DSO delays, and vessel dwell times.
