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MANUAL, SEMI-AUTOMATED OR FULLY AUTOMATED?

Route Planning Comparison

Tourenplanung im Vergleich

The three approaches to route planning in TMS

Differences between manual, semi-automated and fully automated planning

Simple or highly complex: The requirements placed on dispatchers for daily route planning vary significantly. The level of complexity depends on the specific business area, such as local distribution, long-haul transport, less-than-truckload (LTL), or full truckload (FTL) operations.

It also depends on whether fixed routes are used or fully dynamic planning is required, and whether returns and pickups need to be integrated into the process.

Increasing Pressure on Companies

Planning efficient routes is one of the key tasks in logistics and supply chain management. Rising transport costs, limited driver availability, volatile shipment volumes, and increasing sustainability requirements are putting growing pressure on companies to optimize their transport processes.

A transport management system (TMS) plays a central role in this. It offers solutions for manual, semi-automated, and fully automated route planning. But how are routes actually created—and which planning approach is best suited for your business?

One thing is clear: fully automated route planning is not always the best solution. Each approach has its own strengths and limitations.

Route Planning as a core function of the TMS

Route planning describes the process of consolidating transport orders into economically and operationally efficient routes. The goal is to maximize vehicle utilization, meet delivery deadlines, and minimize costs and emissions.

To achieve this, a modern TMS processes a wide range of information, including shipment orders with quantities, weights, and volumes, delivery addresses and time windows, vehicle types and capacities, as well as freight costs, tariffs, and surcharges. It also considers constraints such as tolls, driving bans, and driver working and rest time regulations.

The extent to which this information is used automatically depends largely on the planning mode of the TMS. This is where manual, semi-automated, and fully automated route planning come into play.

A modern TMS processes a wide range of data:

  • Shipment orders with quantities, weights, and volumes
  • Delivery addresses and time windows
  • Vehicle types and capacities
  • Freight costs, tariffs, and surcharges
  • Constraints such as tolls, driving bans, and driver working hours

pLG Route Planning

BENEFIT FROM PLG SOLUTIONS

Manual Route Planning

In manual route planning, the TMS primarily serves as an information and documentation tool. The actual decision of which orders are assigned to which routes is made by the dispatcher.

Experience Matters

Orders are selected manually and assigned to routes. The dispatcher relies on experience, regional knowledge, and personal preferences. The TMS typically only checks basic constraints such as vehicle capacities.

The key advantage of manual planning is its high flexibility, especially in handling special cases and exceptions. It allows companies to leverage the expertise of experienced dispatchers and requires only minimal master data and rule definitions.

  • Orders are selected and assigned manually
  • Dispatcher relies on experience and local knowledge
  • TMS checks only basic constraints (e.g., capacity)
Manuelle Tourenplanung

No Systematic Optimization

However, this approach is time-consuming as shipment volumes increase and creates a strong dependency on individual employees. Transparency is limited, and decisions are not always fully traceable. In addition, manual route planning offers little potential for systematic cost or CO₂ optimization.

Advantages

✅ High flexibility for special cases

✅ Utilization of dispatcher expertise

✅ Low requirements for master data and rules

Disadvantages

❌ Time-consuming with increasing volumes

❌ Strong dependency on individuals

❌ Limited transparency and traceability

❌ Little systematic cost or CO₂ optimization

Conclusion

Semi-Automated Route Planning

Semi-automated route planning combines algorithmic support with human decision-making. The TMS generates route suggestions based on defined rules and parameters, which are then reviewed, adjusted, and approved by the dispatcher.

Human Oversight Remains Key

Route proposals are created automatically, taking into account time windows, capacities, distances, and costs. The dispatcher can intervene and make adjustments when necessary.

The main advantage is significant time savings compared to manual planning, combined with improved planning quality and consistency. At the same time, dispatcher expertise remains an integral part of the process, leading to high acceptance among employees.

  • Automatic generation of route proposals
  • Consideration of time windows, capacities, distances, and costs
  • Manual adjustments possible

Optimization Potential Not Always Fully Utilized

A drawback is the strong dependency on high-quality master data. In addition, dispatchers may override algorithmic suggestions, meaning that the full optimization potential is not always realized.

Advantages

✅ Significant time savings

✅ Higher planning quality and consistency

✅ Continued use of dispatcher expertise

✅ High user acceptance

Disadvantages

❌ Dependency on high-quality master data

❌ Optimization potential not always fully utilized

❌ Algorithmic suggestions can be overridden

Conclusion

Fully Automated Route Planning

In fully automated route planning, the TMS takes over the entire planning process. Routes are generated automatically based on defined objectives, constraints, and optimization criteria, and are directly transferred to downstream systems or carriers.

Complete Algorithmic Optimization

Fully automated planning is characterized by comprehensive algorithmic optimization and the consideration of numerous constraints in real time. Companies benefit from optimized costs, service levels, utilization, and CO₂ emissions. The system can also automatically respond to changes such as order cancellations or delays.

This approach offers maximum efficiency and scalability, as well as reproducible and transparent decisions. Disruptions can be handled quickly, significantly reducing the workload of dispatchers.

  • Full algorithmic optimization
  • Real-time consideration of multiple constraints
  • Goal-oriented optimization (costs, service level, CO₂, utilization)
  • Automatic response to changes

Implementation Effort is High

However, fully automated planning requires very high data quality and clearly defined rules. Special cases must be properly modeled, and implementation—including change management—is complex. Without early involvement of the team, acceptance may be limited.

Advantages

✅ Maximale Effizienz und Skalierbarkeit 

✅ Reproduzierbare, transparente Entscheidungen 

✅ Schnelle Reaktionsfähigkeit bei Störungen 

✅ Entlastung des Dispositionspersonals 

Disadvantages

❌ Hohe Anforderungen an Datenqualität und Regeldefinition 

❌ Aufwändige Einführung und Change Management 

❌ Geringere Akzeptanz bei unzureichender Transparenz 

❌ Sonderfälle müssen klar modelliert sein 

Conclusion

Key Criteria for Choosing the Right Level of Automation

The right planning approach depends on several factors. First, shipment volume and process dynamics: the higher and more volatile they are, the more beneficial automation becomes.

No Automation Without Clean Data

Network complexity also plays a major role. A high number of constraints makes manual planning inefficient and favors algorithmic support. Data quality is another critical factor—without clean master data, automation is not possible.

Organizational readiness and team acceptance are equally important. Resistance to change must be addressed early. Finally, strategic goals also influence the decision. If service quality is a priority, human involvement remains essential.

Not Opposites, but Stages of Development

Manual, semi-automated, and fully automated route planning are not opposing concepts—they represent different stages of maturity.

In practice, many companies evolve step by step: from manual planning to hybrid approaches and ultimately to highly automated processes. The key is to consciously choose the right level of automation—aligned with processes, data, and people.

Key Decision Criteria

Shipment volume and dynamics:

higher volatility favors automation

Network complexity:

more constraints require algorithmic support

Data quality:

no automation without clean master data

Organization and culture:

dispatcher acceptance is critical

Strategic goals:

cost leadership, service quality, or sustainability

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FAQ – The three approaches to route planning in TMS

MANUAL, SEMI-AUTOMATED AND FULLY AUTOMATED PLANNING

Route planning is the process of consolidating transport orders into efficient routes. The goal is to optimize vehicle utilization, meet delivery deadlines, and reduce both costs and CO₂ emissions.

Manual planning is particularly suitable for:

  • small shipment volumes
  • stable and manageable structures
  • individual or complex special cases

Here, the dispatcher’s experience plays a central role.

Semi-automated planning combines efficiency and control:

  • significant time savings
  • improved planning quality through algorithms
  • continued flexibility for dispatchers

It is especially suitable for companies with medium complexity.

Automated planning relies on data. Only when master data such as addresses, time windows, or capacities are accurate and complete can optimal routes be calculated.

Yes – and this is actually the typical path. Many companies evolve step by step:

  • Manual planning
  • Semi-automated support
  • Fully automated processes

This allows systems, data, and teams to be aligned effectively.

Optimized route planning can:

  • improve vehicle utilization
  • significantly reduce transport costs
  • minimize empty runs
  • lower CO₂ emissions

The decision depends on several factors:

  • strategic goals (e.g. cost, service, sustainability)
  • shipment volume and dynamics
  • network complexity data quality
  • team acceptance
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