Our blog posts

Insights: Inefficiencie in distribution
Rising customer expectations, volatile markets and growing demand are presenting distribution companies with ever greater challenges. In many organizations, the initial focus is on operational or tactical levers: transport modes are optimized, routes are rescheduled or short-term capacity bottlenecks are compensated for. These measures are important – but are often not enough to eliminate long-term inefficiencies.

Insights: Supply Chain Firefighting
Machine down. A supplier reports a delay in delivery at short notice. A plant has to close unexpectedly.
Such situations are no longer the exception, but are part of everyday life in modern supply chains. Nevertheless, many companies still react with improvised decisions based on manual planning – for example in Excel – under high time pressure and with limited transparency about the effects.

Mathematical optimization for the parcel industry
Today’s parcel service providers face a multitude of complex challenges for which mathematical optimization can be the solution. We show you how!

Insights: Transport Mode Optimization
Optimize transport mode selection to cut costs, reduce CO₂ emissions, and improve service levels with data-driven mixed-mode logistics strategies.

Insights: Flowpath Optimization
Flowpath Optimization in Tactical Distribution Planning Linkedin Twitter Youtube Flowpath Optimization in Tactical Distribution Planning Rethinking Efficiency Global uncertainties, volatile demand, and increasing sustainability requirements

Interview: Optimization Meets Modern AI
Mathematical optimization is a powerful tool for significantly and sustainably improving planning processes in companies. In existing systems, it can deliver double-digit efficiency gains without requiring compromises in other areas, such as service levels or sustainability. The downside of such systems, however, is that increasing complexity makes them harder to use, and optimization results are often difficult for humans to fully understand.