Designing Data-Driven Supply Chain Networks

This page presents our approach to Network Modeling and Analytics and explains how we help companies design, analyze and optimize complex supply chain networks using advanced digital tools and data-driven methods.

Network Modeling and Analytics

We deliver holistic network studies that provide full transparency across your supply chain. By integrating all material and goods flows into a single analytical environment, we create a reliable foundation for strategic and operational decision-making.

Our projects combine structured data modeling, advanced analytics, and clear visualizations to turn complex networks into actionable insights.

Ent-to-End Network Modeling

We consolidate all relevant goods flows, locations and constraints into a unified network model. This includes suppliers, production sites, warehouses, distribution centers and customers.

For this purpose, we use W2MO by Logivations, a proven software solution for large-scale supply chain network optimization. The tool enables robust modeling of real-world complexity while remaining flexible enough to adapt to changing business requirements.

As-Is Analysis and Visualization

Based on your current data, we create detailed As-Is analyses of the existing network.

Key capabilities include:

- Transparent representation of current material flows and cost structures
- Identification of bottlenecks, inefficiencies, and risk concentrations
- Graphical visualization of the entire network for clear communication and alignment

The results are presented in an intuitive and visual format, making complex interdependencies easy to understand for both technical and non-technical stakeholders.

Scenario Simulation and Optimization

Beyond analyzing the current state, we simulate multiple future scenarios to evaluate strategic options.

Typical scenarios include:

- Warehouse relocation or consolidation
- Changes in demand, volumes, or service levels
- Alternative sourcing or distribution strategies
- Cost, lead-time, and resilience trade-offs

Each scenario is calculated consistently within the same network model, allowing direct and objective comparison of results.

Digital Twin of the Supply Chain

Our network models can be extended into a digital twin of your supply chain. This digital twin reflects the real network structure and behavior, enabling continuous analysis and scenario testing.

Benefits of the digital twin approach include:

- Ongoing decision support based on real data
- Faster evaluation of strategic and tactical changes
- Improved resilience through proactive risk assessment

Your Benefits at a Glance

By applying Network Modeling and Analytics, you gain:

- End-to-end transparency across your supply chain
- Data-driven support for strategic network decisions
- Quantified impact of changes before implementation
- A scalable digital foundation for future optimization initiatives
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Our approach ensures that network design decisions are not based on assumptions, but on validated data, advanced analytics, and a clear understanding of system-wide effects.