Stef Optimizes its Transportation and CO2 Emissions with DCbrain
STEF uses DCbrain to make its transportation plans dynamic and efficient.
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As the European leader in temperature-controlled food logistics, STEF pursues optimization of its transportation plans. Before DCbrain, each branch devised its own transportation plan, which made it difficult to identify the global optimum.
To continue to grow at constant resource levels, STEF needed to reduce its transportation costs. The leverage identified: Optimization of delivery vehicle loading and distances travelled.
The updating of transportation plans at STEF was done annually, manually and locally. There was a huge number of possible combinations, of the order of 10 to the power of 12. Significant requirements needed to be met, including reduction of the carbon footprint, contractual obligations with clients, limited resources and improvement of the load factor.
It was humanly impossible for us to find the required leverage for optimization, given the environmental challenges.
Damien Chapotot
Deputy CEO
Context
Why ?
The group needs to absorb significant growth and activity spikes at constant resource levels, while following its strategic plan ‘Moving Green’ (30% reduction of its CO2 emissions by 2030).
Who For ?
The tool is used by the design team at national level to identify and suggest avenues for optimization to local managers.
Before DCbrain
Given the complexity involved, manual updating of the transportation plans was done annually and left little room for maneuver. There were few synergies in the construction of these plans between the branches and regions.
With DCbrain
- Decision between direct and indirect flows to streamline or remove routes
- Organization of loops to simplify flows
- Deployment of new cross-docking procedures to put forward optimized routing rules
- Creation of several versions of standard transportation plans, for days with low and high activity levels
- Analysis of impacts of unforeseen events on the network.
Data Used
- Distance and transportation cost matrixes.
- More than 100 management rules and 50 variable parameters
- Information on products transported with data on departure and arrival
- Past transportation plan for comparison
Gains projetés
- Optimization of the transportation plan in a complex network
- Savings achieved (>€M)
- CO2 emissions reduction
- Flexibility and integration of new clients/resources.
- Digitalization of operations
The number-one thing we expect, which we found at DCbrain, is the ability to have a super-fast decision-making process.
Damien Chapotot
Deputy CEO
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