“Secure it cheap now, rather than buying dear later” – those days are over! Increasing trade barriers such as tariffs, geopolitical tensions disrupting central trade routes, energy price shocks impacting transport costs and fluctuating demand cycles are driving global supply chain uncertainty to new heights. When long-term predictability becomes the exception, traditional procurement logic no longer holds. Conventional tenders are based on historical data and supposedly stable conditions – while demand, routes and capacities have long been changing in much shorter cycles.
Ghost Lanes or Uncertain Capacities?
Traditional freight procurement systematically leads to misallocations. So-called Ghost Lanes are a particular problem: on average, 70% of secured FTL (Full Truckload) capacities are not utilized. Ultimately, these cost shippers dearly. While pre-secured capacities are intended to ensure predictable and low costs, they achieve the opposite if they aren't called up. Because they block capacity for carriers and lead to inefficient route planning, carriers compensate for these costs with higher prices in future contracts.
The alternative is the short-term procurement of freight capacity on the spot market. The downsides: operational effort increases significantly, as tenders are short-term and often manual. Simultaneously, there is often a lack of price transparency, making comparability difficult. Add to this the fluctuating availability of capacity, which further restricts predictability.
AI Shifts Proposal Generation
AI-supported Autonomous Procurement addresses exactly these issues. Increased efficiency compensates for the disadvantages of labor-intensive spot offers. At the same time, this tool transforms procurement from a periodic task into a continuous process where situations are constantly re-evaluated, allowing for flexible reactions to deviations.
The core of the solution: Shippers, not carriers, create the offers with the help of Artificial Intelligence. Algorithms independently calculate market-driven offer prices based on historical and current freight and spot rates, defined price ranges and logistical and sustainability criteria. Furthermore, AI and behavioral science models consider the individual booking behavior of carriers, allowing for targeted differentiation of offers.
These offers are published in real-time on our platform. If an order remains unbooked, the system independently manages further rounds of tendering – including the selection of the next carriers and adjusted conditions. The entire process runs autonomously, scalably and 24/7, within defined guardrails.
Measurable Efficiency and Cost Advantages
We can clearly measure the effects:
-
Match Rate: Up to 90% of FTL transport orders are matched automatically across the network.
-
Match Time: Average matching times drop to around 70 minutes.
-
Cost Savings: Shippers achieve spot prices that are, on average, 8% to 12% lower than traditional methods – even while continuing to work with their proven freight forwarders.
-
Productivity: Feedback indicates that the solution increases the productivity of dispatch teams by about 20% per year, enabling even inexperienced team members to efficiently tender spot freight.
New solutions only gain traction when everyone benefits: carriers no longer have to invest resources into time-consuming calculations with uncertain outcomes. Instead, a single click is enough to accept an order and receive all necessary shipment details. This simplifies dispatching and helps avoid empty runs.
Flexibility is Key
The future of freight procurement does not primarily lie in even more precise or longer-term tenders for capacity assurance. Today, flexibility is paramount to continuously adapting decisions without increasing complexity or costs.
AI-powered Autonomous Procurement offers exactly this possibility, benefiting shippers and carriers alike. The decisive prerequisite remains a solid data basis: the more structured historical data available on freight, routes and carriers, the more precise and efficient the system becomes. Platform-based Transport Management Systems (TMS) provide the best foundation for this, especially when they offer access to a broad network and reliable market data.
At a Glance: Starting with Autonomous Procurement
-
Harmonize Master Data: Integrate freight and spot rates, carrier performance, telematics and ERP data.
-
Identify Spot Needs: Pinpoint time-consuming ad-hoc routes.
-
Define Rules: Set price limits, service levels, sustainability criteria and preferred carriers within the system.
-
Launch Pilot: Start a trial run with 2–3 fixed relations (routes).
-
Go-Live: Activate automated allocation.
-
Scale Gradually: Successively integrate further relations.
-
Measure KPIs: Track match rate, match time, and price levels via dashboards.
-
Manage Roles: Shift the focus of dispatchers toward strategic management and exception handling; actively manage the internal transition.