Supply Chain Analytics

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 therefore naturally also the requirements for the underlying basic data. Supply chains usually accumulate huge amounts of this data. Supply chain analytics helps to define the right up-to-date KPIs, ensure data availability and use this data sensibly via suitable infrastructures by uncovering patterns and providing insights. In summary, this enables companies to make data-driven decisions that strengthen their competitiveness and promote their business success.

We would be happy to support you in optimizing your decision-making processes with meaningful key figures tailored to your company's situation. As a first step, we recommend our Supply Chain Analytics Compass. Find out more about the workshop offer here:

To the workshop

The dashboard shows the most important key figures at a glance.

The scorecard provides insights into operational performance.

Our services for you

Transparency

Based on your individual requirements, we develop suitable key performance indicator models and control systems. With the help of best practice experience, we provide the right input to efficiently integrate new requirements into existing models.

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Risk analysis

Together, we develop the risk assessment of your supply chain based on defined key figures. We identify where the greatest weaknesses exist and what damage could occur, for example, due to delivery failures.

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Data integration

Based on existing data requirements, we identify availability, derive data models and sensible architectures, integrate and harmonize data, and thus ensure a central basis for all relevant data.

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AI Data Analytics

Using AI-supported models, we analyze your data and identify unknown patterns or forecast future developments. Possible is the one-time external analysis or the permanent integration into your system landscape.

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Implementation

We support you in the introduction, expansion or migration of innovative analytics software solutions or technologies such as artificial intelligence, machine learning and IoT.