Prerequisite: None
This session will include a moderated Q&A featuring questions from the live audience.
Korbinian Lindemann will share his company’s experience in strategically implementing an advanced analytics practice within an industrial setting, emphasizing capabilities and culture over tools. This innovative approach fostered knowledge sharing, collaboration, adoption of best practices, and enhanced impact of analytics projects.
Key elements of the approach include:
- Centralization of Analytics: Data science projects were consolidated under a centralized analytics and data practice, supported by the CFO, enhancing focus and collaboration.
- Pragmatic Project Approach: Focusing on small-scale projects with minimal project governance allowed for rapid iterations and immediate feedback, leading to a better understanding of business issues and quick wins by the analytics team.
- Internal Marketing: Promoting the analytics team's capabilities across business units helped to boost visibility and encouraged data-driven inquiry across the enterprise. The hype of AI led to additional advanced analytics opportunities.
The organization’s experience in making this transition demonstrates the importance of a structured approach to analytics, prioritizing a deep understanding of business challenges before applying advanced analytical techniques. This method not only strengthened the company's analytical capabilities but also fostered a culture of data-driven decision-making, driving sustained competitive advantage.