INFORM shares how it can support operators to optimise hauler assignment in aggregates logistics.
In the aggregates industry, logistics planners face the constant challenge of selecting the right hauler for each shipment. While many producers rely on third-party haulers or use the spot market, this selection process is far from straightforward. The range of available providers is often long, with each offering different capabilities, costs, and service levels.
The Challenge of Hauler Selection
At first glance, it might appear sensible to simply award each job to the cheapest available hauler. However, freight rates are not static. They vary significantly depending on factors such as distance, backhaul opportunities, or fleet availability. Choosing solely on the basis of the lowest immediate cost can quickly lead to inefficiencies, higher total costs, and reduced service quality.
Effective hauler assignment requires logistics planners to weigh multiple variables under time-critical conditions. Decisions made in isolation (shipment by shipment) rarely yield the best results. Instead, planners must adopt a holistic approach that considers the full cost implications of every choice across the network.
Understanding the Key Variables
Each hauler brings a unique profile of strengths and limitations. Important factors that logistics teams must consider include:
- Fleet size and equipment types: Availability of suitable trucks and trailers.
- Technology capabilities: Tracking, communication systems, and integration options.
- Reliability and responsiveness: Proven ability to deliver on time and handle urgent jobs.
- Financial stability: Ensuring long-term viability and reducing risk.
- Reputation and integrity: Built through consistent performance.
- Freight rates: Often the decisive factor, but highly variable across routes and loads.
Particularly complex is the influence of backhauls. When a hauler can secure a return load, they may offer highly competitive or even below-market rates for specific lanes. While this can lead to significant savings in certain cases, it adds complexity to rate structures and complicates straightforward comparisons.
Figure one shows an example of a planner’s hauler/rate matrix covering 20 haulers across 33 different distances, resulting into a decision landscape of 660 possible assignments. The colors indicate the relative price of a hauler within a distance class, from red (most expensive) to light green (least expensive). The size of a dot represents the absolute price of hauler within that distance class. Distance classes start at 10km (left) and end at 330km (right), with a width of 10km each. Within a distance class, the costs between the least and most expensive hauler differs on average by roughly 30 per cent.
Why Manual Planning Falls Short
In practice, planners frequently work under pressure, managing dozens of shipments and dozens of haulers simultaneously. When relying on manual processes, they must make fast choices with incomplete information. The result is often suboptimal, as decisions that seem cost-efficient for one shipment may inadvertently drive up total daily costs.
The Role of Algorithms and AI
Algorithms excel in environments where many variables must be processed simultaneously to deliver an optimised result. For hauler selection, they enable planners to:
- Evaluate all potential hauler-shipment combinations instantly.
- Optimise not just individual moves but the overall transport plan.
- Balance competing priorities (cost, service quality, responsiveness, and availability).
- Reduce the risk of costly errors made under time pressure.
Rather than replacing the planner, AI tools act as decision-support systems. The logistics professional retains control, while algorithms ensure the options presented are already optimised for both cost efficiency and operational reliability.
To illustrate, INFORM recently carried out a simulation study for a customer using the above hauler/rate matrix. Manual planning resulted in average daily transport costs of around $50,000. By contrast, algorithmic optimisation reduced those costs to $46,000 per day.
That difference of $4,000 per day highlights the limits of human decision-making under pressure and the potential for advanced optimisation to unlock significant savings.
Strategic Benefits Beyond Cost
While direct savings are compelling, optimised hauler assignment delivers broader benefits to aggregates producers:
- Improved customer service: More reliable transport execution and reduced delays.
- Sustainability gains: Better utilisation of fleets reduces empty miles and emissions.
- Stronger hauler relationships: Consistent, data-driven assignments foster trust and fairness.
- Scalability: The ability to manage more shipments and more haulers without proportional increases in planning workload.
In a sector where margins are often tight and supply chains face rising volatility, these advantages can provide a decisive competitive edge.
Making the Right Move
The logistics of aggregates is characterised by high complexity, fluctuating rates, and demanding time pressures. Relying on manual decision-making leaves planners vulnerable to inefficiency and unnecessary costs.
By adopting algorithmic and AI-driven assignment tools, producers can transform hauler selection from a reactive, tactical task into a strategic lever for cost reduction and performance improvement. The message is clear: make the right move and let optimisation guide your hauler assignment.
