Starting point Starting point: High dynamics, low transparency
Imagine a logistics company that coordinates hundreds of trucks across Europe every day. On paper, everything is well planned: routes, loading times, delivery schedules. Reality, however, rarely sticks to the plan. A sudden traffic jam near Lyon, unexpected weather in the Alps, or fluctuating diesel prices – and calculations start to wobble.
Dispatchers know the situation all too well. “When will the delivery actually arrive?” or “How much will the transport ultimately cost?” are questions that often receive only rough estimates. The result: uncertainty for customers, inefficiencies in planning, and unnecessary manual work behind the scenes.
Arrival times and transport costs are frequently estimated using static tables, averages, or manual experience. The result: forecasts that are simply unreliable in many cases. Dynamic factors such as weather, traffic conditions, or short-term price changes barely play a role.
The consequences:
- Lack of transparency: Customers and internal teams have to work with rough estimates.
- High manual effort: Dispatchers spend a lot of time collecting data and recalculating scenarios in Excel.
- Low interactivity: Static dashboards don’t allow quick, alternative scenario checks.
What to do Solution: Intelligent ETA and transport cost calculation
What helps here is a predictive model that reliably forecasts transport costs and ETA (Estimated Time of Arrival) in real time. What’s special: by combining forecasting with generative AI, usage becomes as simple as chatting.
The model can tap into a wide range of data sources: historical transport data, live traffic reports, weather information, fuel prices, and more. Based on this, it produces forecasts that are not only more precise, but also continuously adapt as conditions change.
How it works in practice
Example 1 (transport costs): A dispatcher wants to know how an additional partial load of 100 kg affects the transport cost for a trip from Berlin to Paris. Instead of browsing tables, they simply type the question into a chat interface:
“How do transport costs change if I ship an extra 100 kg from Berlin to Paris?”
Within seconds, the model returns a precise answer – including an explanation of which factors have the greatest influence.
Example 2 (transport costs): Diesel prices rise by 15%. The planner enters this assumption in the chat and immediately sees the impact on the total costs of the planned transports.
Example 3 (ETA): A customer asks whether a shipment from Hamburg will still arrive in Cologne by the next morning despite forecasted heavy rain in the Ruhr area. The dispatcher forwards the question to the chat. The model considers current weather, traffic reports, and historical patterns. Within seconds it provides an updated ETA – including hints on how strongly the weather is likely to affect timing.
Key features at a glance
- Predictive model: Uses historical and real-time data to forecast costs and ETA.
- Natural interaction: Ask questions in everyday language instead of applying complex queries or Excel formulas.
- Scenario simulation: Interactively run “what-if” situations to assess risks.
- Explainability: Surfaces the factors driving a prediction – a key trust enabler.
- Seamless integration: Existing systems like ERP or TMS remain the central workspace.
Your benefits Benefits: From blind spots to data-driven operations
This approach brings several advantages:
- Better decisions: Planners act based on reliable forecasts and can test alternatives instantly.
- More efficiency: Manual calculations drop significantly; planning accelerates.
- Everyday agility: New information, e.g. a traffic jam or price hike, flows directly into forecasts.
- Happier customers: Reliable ETAs and costs build trust and improve service.
The result is a new level of quality in transport logistics: instead of flying blind, companies gain an intelligent assistant powered by forecasting and generative AI – delivering precise answers at any time, in natural language, and on equal footing.
For dispatchers, planners, and customers this means: less uncertainty, less effort, more clarity. And for the company: a decisive competitive edge in a market where reliability and transparency matter more than ever.