Intelligent and efficient use of data

easy to use and powerful

Consistent database with data collection, verification and consolidation in one tool

phenomenal google geographic data

Efficient handling of big data with modern database architecture

easy to use and powerful

Sustainable setup by extrapolation and scenario calculation

easy to use and powerful

Extensive statistics for an in-depth analysis of input data and results

easy to use and powerful

Reusability provided by standard model structure

easy to use and powerful

Visualization of data and results in 2D and 3D


  • Use of standard data templates for import and export
  • Integration with SAP or other ERP / warehouse management systems
  • Automatic verification of data consistency and correction of data errors
  • Creation of a unified database for simulation and optimization projects

Product master data, movement data, customer orders, inventory – only a few business areas have the same data information level as the logistics sector. Therefore, structured handling of big data is key to optimize the layout and processes, to recognize long-term trends and to evaluate the alternatives. W2MO offers a variety of configurable interfaces for each use case. Data for planning tasks can be prepared in Excel and can be uploaded as a .csv file. Alternatively, data from WMS, ERP, or TM systems can be transferred automatically each day. The SAP connector provides a standard interface to all SAP systems. W2MO offers algorithmic support to validate used data and allows automatic correction of data errors. Model errors, data gaps and contradictions are avoided and repaired directly. At the same time W2MO has a consistent database for simulation and optimization projects.


  • Generation of product and order data with the help of statistical key figures
  • Creation of future scenarios based on historical data
  • Maintenance or targeted modification of order structure for planning scenarios
  • Easy closing of data gaps
Datengenerierung und Extrapolation

Planning or optimizing of a logistics process is always future-oriented. Exact data on product and order structures are only available from the past. That is why W2MO offers the possibility to create product and order data using statistical distributions. Moreover, a valid simulation model can be created with a very limited amount of data. Sophisticated extrapolation algorithms help to generate goal-oriented foresighted order structures. The result is based on historical data and accurately reflects the expected business development. This methodology is implemented to fill any existing data gaps when required.


  • Diverse analysis and evaluation possibilities
  • Graphical representation in 2D and 3D
  • Heatmaps for data visualization
  • Possibility to export the results for further processing

W2MO provides a variety of analysis and evaluation possibilities for the created database and achieved results. The layout information in 2D and 3D helps to create heat maps for access times, picking amounts and labor costs. Such visualizations often enable identifying optimization potentials and transparently showing inefficiencies in current processes.


  • Scenario-manager for campaign-dependent data management
  • Easy comparison of different scenarios
  • Evaluation of various growth options
  • Comparative analysis of results in detailed reports

Growth scenarios, market entries, segmentations, developments in the product portfolio – with the extrapolation functions of W2MO, you can always create a realistic and structured database for your scenarios. The simulation in W2MO enables evaluation of planning scenarios based on real costs and capacity requirements. Different layout scenarios and different warehouse techniques, picking strategies and warehouse assignment strategies can be quickly and easily modeled and evaluated. The evaluation of scenarios based on simulation allows you to compare the resulting logistics parameters and performance indicators. Not only static parameters are analyzed but also dynamic effects such as bottlenecks and load peaks are evaluated.

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