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Bertani

1,100,000 vehicles a year, zero waste: Decision Intelligence for automotive logistics

When loading a car-carrier stops being an art and becomes an algorithm, without losing the planners’ expertise.

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The challenge

Moving cars and industrial vehicles is one of the toughest challenges in distribution logistics. For Bertani Trasporti, which handles around 1,100,000 vehicles a year with peaks of 6,000 orders a day, efficiency is measured in centimetres.

The complexity lies in building optimal loads (batches) onto car-carriers, starting from three-dimensional constraints (length, height, weight) and geographical and time constraints tied to strict delivery penalties. On top of this, Bertani manages a mixed fleet of over 600 vehicles, company-owned trucks and owner-operators, while coordinating the migration from the legacy AS400 system to the in-house web application “Easy TMS”.

Before Optit stepped in, load planning relied solely on planners’ hands-on experience, limiting fleet optimisation and risking an increase in empty-running kilometres.

How we create value

Optit integrated its proprietary decision-making platform, OptiLogistics, with Bertani’s TMS, introducing advanced mathematical models to support operational decisions. The solution is built on two modules tailored specifically to Bertani’s business:

  • The Planning module automates load creation through a custom algorithm that clusters vehicles into classes, calculates a predictive load index (trained using machine learning models) and applies geometric constraints and single-unit extensions to maximise vehicle fill rate.
  • The Dispatching module optimises resource allocation, matching trips, car-carriers and drivers.

The algorithm solves a standard cost function that minimises empty-running kilometres, transfer times and waiting times, integrating real-time telematics data (GPS and remaining driving hours) fed in from the TMS. The system combines algorithmic automation with the flexibility of manual editing.

Impact

Putting this operating model into practice has delivered measurable gains in logistics performance:

  • Higher vehicle fill rates and lower overall operating costs.
  • More efficient collections and a structural reduction in empty-running kilometres across the national network.
  • Human-algorithm synergy, putting dispatchers’ expertise to work through real-time alerts.
1,100,000 vehicles a year, zero waste: Decision Intelligence for automotive logistics