CubeCold is a European logistics provider specialising in temperature-controlled distribution. Operating a multi-depot set-up and serving a wide geographic footprint, the company manages a complex network of inbound and outbound flows across several countries and hundreds of delivery locations.
Challenge
4Supplychain was asked for a clear, data-driven view of optimisation opportunities within CubeCold’s transport network. With multiple depots, partially overlapping service areas, and datasets of varying quality, the organisation sought structured insight into consolidation potential, routing efficiency, and network synergies.
Deliverables
We analysed CubeCold’s distribution network through a structured, multi-phase approach:
- Harmonised and validated data from different depots to create a unified, analysis-ready dataset
- Built a consistent modelling framework with standardised routing, capacity, and time-window assumptions
- Ran scenario-based simulations to explore milk-run efficiencies and consolidation opportunities across various regions
- Identified address overlap and synergy potential using geocoding and detailed location matching
- Compared alternative routing and depot strategies to support strategic network discussions
The project provided CubeCold with a clear and structured view of its combined distribution network. By consolidating fragmented datasets into one reliable foundation and applying a uniform modelling approach, CubeCold now has full transparency into the structure of its delivery footprint, the degree of overlap between depots, and the factors that drive route efficiency. This improved clarity enables more confident operational planning today and supports broader strategic decisions around depot roles, consolidation opportunities, and future network design.
