Supply Chain Analytics
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Transparency - more important than ever!
Decisions such as the adoption of the Supply Chain Duty of Care Act place new demands on the transparency of supply chains, particularly with regard to compliance with human and environmental rights. However, the increasing importance of supply chain risk assessment also requires new approaches to analysis. How can the risk or resilience of the supply chain to unexpected events be assessed? Innovative key figures such as TTR (Time-to-Recover), TTS (Time-to-Survive) or PI (Performance Impact) help to identify hidden risks and increase the resilience of the supply chain.
Overall, this increases the complexity of the required KPI models and thus, of course, also the requirement for the underlying basic data. In supply chains, this data usually accumulates in huge quantities.
Supply chain analytics helps define the right timely metrics, ensure data availability, and make sense of that data via appropriate infrastructures by uncovering patterns and providing insights.
In summary, supply chain analytics enables companies to make data-driven decisions that strengthen their competitiveness and drive business success.
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Transparency
Risk analysis
Data integration
AI Data Analytics
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