Interactive Optimization of Logistic Networks out of the Cloud

Based on Google Maps, W2MO allows you to quickly create the entire network with warehouses, suppliers and final customers worldwide.

The latest detailed map data enables high geographical proximity and visualization of the customer's and supplier's base. It's always up-to-date, thus users get much faster and more precise view of their network locations, flows and cost.

With so-called "Heat maps" anyone can check the allocation and grouping of customers. Different intensity of colors stands for a certain amount of customers, e.g. red - the most "covered" area. By zooming in check clients information in detail.

W2MO offers multiple options of finding the best locations for warehouses or manufacturing sites. Depending on distances to customers and different order parameters, smart algorithms calculate optimal sites, aiming to achieve the lowest cost of entire supply chain.

logistic network optimization

The system allows you to create various flows (outbound/inbound) between manufacturing sites, warehouses and customers accordingly. It is possible to calculate the load on different flows and optimize locations of warehouses. And all this can be easily viewed with a help of W2MO's user-friendly interface.

See the immediate costs difference, define the best solution for your logistics when moving and changing the relations in your network interactively.

Take advantage of W2MO for your entire supply chain:

  • Monitor the statistics of order volume, biggest clients, flows, transports, etc.
  • Optimize logistic networks with drag and drop function directly and interactively.
  • Calculate the entire cost based on your supply chain.
  • Check various scenarios fast. Calculate cost differences immediately. Analyze best solution.
  • Extrapolation and scenario development.
  • Optimization of process allocation, articles/parts and stocks on sites or areas within the sites.
  • Optimization of supply concepts.
  • Calculation of labor costs, processing times across locations.