thyssenkrupp Rasselstein adopts process intelligence to optimize supply chain transparency & efficiency

thyssenkrupp Rasselstein, one of Europe’s largest manufactures of premium packaging steel, is adopting process intelligence to optimize supply chain transparency and efficiency. It is partnering with Celonis to establish a data-driven, connected supply chain to proactively mitigate supply risks, enhance delivery reliability and optimize core processes.

With a legacy spanning over 250 years, thyssenkrupp Rasselstein is a global pioneer in precision-engineered packaging steel. Serving more than 400 customers in over 80 countries, the company operates within a complex international industrial landscape.

Its state-of-the-art production facility in Andernach, Germany – the largest of its kind worldwide – relies on more than 300 interconnected systems, highlighting the high level of operational complexity and potential process fragmentation. 

How process intelligence enhances supply chain transparency and efficiency

To stay ahead of competition and meet the evolving demands of the global steel industry, thyssenkrupp Rasselstein is driving continuous digitalization and process optimization, with an emphasis on enhancing its supply chain efficiency, according to a press release.

The company has three major objectives:

• Reduce manual effort and raise productivity.
• Optimize working capital.
• Improve delivery reliability for the company’s end customers.

With the adoption of process intelligence, thyssenkrupp Rasselstein is driving key business value such as:

• Proactive prevention of material shortages, allowing timely interventions by anticipating potential disruptions.
• Improved delivery accuracy and on-time predictions, resulting in enhanced customer satisfaction.
• Optimized safety stock levels, reducing excess inventory while ensuring production continuity.
• Double-digit million savings potential in working capital, driven by more efficient inventory management and streamlined financial processes.

“Before Celonis, we had limited visibility into our supply chain, which made it difficult to react quickly to supply disruptions,” said Dr Michael Pullen, chief financial officer (CFO) at thyssenkrupp Rasselstein. “Now, we have a real-time overview of our processes, allowing us to manage risks proactively, reduce excess inventory and improve our delivery reliability. This enables us to make better strategic decisions and ensures seamless production planning.”

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Combining process intelligence and AI

Artificial intelligence (AI) has become an integral component of thyssenkrupp Rasselstein’s process optimization journey too. By deploying an AI-powered Celonis copilot, the company empowers employees to interact intuitively with data and make faster, smarter decisions using natural-language queries – without requiring advanced analytical expertise. 

“Process intelligence enables companies to maximize the ROI of their AI solutions – especially in complex industrial settings like thyssenkrupp Rasselstein’s,” said Florian Schewior, managing director DACH at Celonis. “By bringing together process intelligence and AI, we’re helping customers make smarter decisions today and create more intelligent supply chains tomorrow.”

Looking ahead, thyssenkrupp Rasselstein is preparing the rollout of object-centric process mining (OCPM), which will provide an even more connected end-to-end view of its supply chain. This enhanced visibility will drive further improvements in transparency and operational efficiency, reinforcing the company’s commitment to continuous process optimization.

Task mining – unlocking new possibilities in process optimization: Industry report 2025

Task mining is experiencing robust growth, driven by the increasing need for process optimization and automation across diverse sectors. The market, estimated at US$2 billion in 2025, is projected to exhibit a compound annual growth rate (CAGR) of 25 percent over the next eight years, reaching an impressive $10 billion by 2033, according to Market Report Analytics.

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