Supply chain analytics - data-based control

Introduction

Supply chain analytics - data-based management is a key topic for companies that want to make their supply chains more robust, transparent and sustainable. Digitalization, automation and smart data analysis form the basis for a modern supply chain.

What is supply chain analytics - data-based management?

Supply Chain Analytics - Data-based management describes strategies, technologies and operational measures that can be used to plan, manage and optimize supply chains. The aim is to minimize risks, increase efficiency and enhance flexibility - even in times of crisis.

Relevance in the corporate context

Global markets, ESG requirements and volatile framework conditions require a new understanding of supply chain management. Companies that implement data-based supply chain analytics create a decisive competitive advantage.

Typical challenges

• Non-transparent supply networks
• Poor data availability and fragmentation
• Lack of automation & integration
• Reactive instead of predictive control

Practical example

A mechanical engineering company used supply chain analytics - data-based management to introduce a digital supply chain dashboard with real-time data. The result: faster responses to delivery bottlenecks, better forecasts and increased customer satisfaction.

Our approach

1. Supply chain analysis & data availability
2. Define target image & roadmap
3. Tool implementation (e.g. SCM platforms, dashboards)
4. Process design & training
5. Continuous monitoring & optimization

Conclusion

Supply chain analytics - data-based management is the key to a resilient, efficient and sustainable supply chain. Thinking ahead digitally ensures stability and innovative strength.