How to make supply chain projects a success with a clear structure

Structured project management in the supply chain: preparing decisions

Efficient decisions are a key success factor in supply chain projects – especially when complex dependencies, many participants and a high degree of uncertainty come together. This makes it all the more important to structure supply chain design projects clearly.

A structured project approach not only defines goals, but also facilitates data analysis, communication within the team and the selection of suitable methods – be it optimisation, simulation or a combination of both.

Why structure is crucial

A clear project structure…

• defines goals and success metrics,
• reduces complexity through comprehensible phases,
• promotes collaboration between departments,
• improves the quality and traceability of decisions.

This structure provides a clear framework – especially when simulation or optimisation tools such as anyLogistix are used.

The four project phases from the SimPlan perspective

Based on SimPlan’s project experience – particularly in the area of simulation-supported supply chain design projects – four central phases have emerged:

Phase 1: Process analysis

At the beginning, there is a detailed understanding of the processes:

• Which processes are critical?
• Which stakeholders are involved?
• Which data is required?

This analysis lays the foundation for the subsequent model construction and defines the scope of the project.

Phase 2: Data analysis and transformation

In this phase, the database is created:

• Identifying data sources (e.g. locations, customers, suppliers, transport data)
• Validation and cleansing
• Geocoding for location analyses
• Clustering to simplify large amounts of data
• Transformation for model tools such as anyLogistix (e.g. with Python)

Meaningful models can only be created with clean, structured data.

Phase 3: Greenfield analysis and network optimisation

Now it’s getting strategic: with the help of optimisation models, central questions can be answered:

• Where should new hubs be created?
• Which configuration minimises costs while maintaining high service quality?
• Which restrictions (e.g. time frame, distances) need to be taken into account?

Greenfield analyses help to design ideal-typical networks – before realistic restrictions are added.

Phase 4: Simulation

Simulations answer operational questions:

• What happens when demand fluctuates?
• What is the effect of transport delays?
• Are the stocks sufficient for a 99% service level?

With the help of scenarios, risks can be identified and measures derived at an early stage. Simulations bring dynamism and reality into the decision-making process – especially when it comes to implementation issues.

Tools and methods used in the course of the project

• Python: data preparation, clustering, import structures for anyLogistix
• Tableau / Power BI / Excel: result analysis, communication with stakeholders
• anyLogistix: greenfield analysis and network optimisation (e.g. site selection), simulation (e.g. material flows, timing)

The combination of these tools enables data-based, informed decision-making across all project phases.

Optimisation vs. simulation – and why both are important

One of the central questions in supply chain design is: optimise or simulate?

• Optimisation is useful for strategic decisions such as location planning or network configuration.
• Simulation complements these findings by analysing dynamic processes, risks and operational interactions.

The interplay of both methods not only provides the ‘right’ decision – but also ensures that it works in practice.

Practical examples and common requirements

In many projects at SimPlan, we encounter similar issues:

• How many hubs are realistic – and where?
• How can delivery time frames be reliably adhered to?
• Which production planning makes seasonal sense?
• How do you efficiently organise return shipments of special containers?

These questions require individually tailored solutions – standard approaches are usually not sufficient here.

Conclusion: Structure creates decision-making certainty

A clearly structured project process forms the basis for well-founded, realistic decisions in supply chain management. The combination of a methodical approach, suitable tools and practical experience makes it possible to master complexity and develop solutions that are capable of being implemented.

Particularly in dynamic, risky environments such as today’s global supply chain, such an approach is not a luxury – but a necessity.

Here you can view the slides from Till Fechteler’s presentation at the anyLogistix Conference 2024.

You can watch the full presentation by Till Fechteler on the findings from the project phases in the supply chain in the following video.

Do you have any questions or would you like to optimise your supply chain? Contact us for a personal consultation.

Our next webinar on SCM simulation and supply chain optimisation will take place on 8 May. We would be happy to discuss your topics there!

Or contact our supply chain expert, Till Fechteler, directly for a personal consultation about your supply chain.