Turning powder allocation into a data driven production decision
A consumer goods manufacturer used machine learning, a digital twin, and real-time data to optimize powder distribution across seven production lines.
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We drive significant and sustainable performance improvements by integrating AI and Advanced Analytics with deep business expertise
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Why do so many AI projects fail to create business value?
AI projects have a stronger chance of creating value when technology, business priorities, organisational capabilities, and adoption are considered together.
Reducing back office workload by up to 30% with AI and intelligent automation
An automotive group analyzed dozens of back office processes across multiple teams to identify where AI, intelligent automation, and platform integration could reduce manual workload and improve operational efficiency. The assessment identified potential to reduce workforce up to 31%, with an estimated impact above 1M€.
The most common mistakes in GenAI adoption
Why organizations that start by asking "how do we automate this?" often end up frustrated and what to ask instead.
From fragmented data and disconnected processes to a scalable master data management foundation
A food manufacturer centralized master data, digitalized and automatized manually-inserted data, and built a reusable foundation for data governance in six weeks.
The hidden 50 percent of AI transformation
Why process design determines whether operational AI succeeds
