My work at SAP involves directly empowering product teams to build more intelligent and user-centric products through the strategic implementation of 'standard feedback mechanisms.' I take ownership of defining and championing the use of reusable feedback patterns specifically designed for algorithms and various SAP services. This isn't just about collecting data; it's about establishing a consistent and effective way for our products to learn and improve based on real user interactions.

To ensure these feedback mechanisms are truly impactful, I spearheaded extensive research across SAP. This involved a deep dive into current trends and existing practices related to gathering user feedback and, crucially, understanding how that data is being leveraged to refine the output of our underlying algorithms. Alongside this internal analysis, I conducted thorough market research to grasp the current state-of-the-art in feedback collection and identify key gaps that SAP could address.

The tangible outcome of this work is the 'AI Feedback patterns,' which I authored and published within the 'User Feedbacks' section of the General Patterns in the Fiori design guidelines. This isn't just documentation; it's a practical resource that provides product teams with concrete, reusable blueprints for building effective feedback loops into their offerings. By providing these standardized patterns, I aim to significantly reduce the effort required for individual teams to design robust feedback mechanisms, ensuring a more consistent and higher-quality approach across SAP's diverse product landscape. Ultimately, this initiative drives a culture of continuous improvement, leading to AI-powered features and services that are more aligned with user needs and deliver greater value.