We demonstrate how Natural Language Processing can be used to discover actionable insights from untapped sources, such as unstructured text from performance evaluations. Our use case leverages N = 80k managers’ free text performance feedbacks that unravel key topics related to corporate culture. Our approach allows creating data-based evidence for how culture is being lived in the organisation.
This session will explore:
- From unstructured text data to key topics
- How to find evidence for corporate culture in performance evaluations.
- Awareness and inspiration to use free text from performance management
- Concrete example of how to use NLP to get insights for corporate culture.
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Gianna Pfiffner leads the People Analytics Data Science Lab at Credit Suisse. Her team delivers global Advanced Analytics and Data Science projects for the area of Human Resources and strongly supports data-based decision making by providing insights from data analyses. Applying state-of-the-art methods and delivering high-quality work as well as considering ethical aspects are important corner stones of the mandate of her Data Science Lab. Gianna is an I/O Psychologist and has previously worked in Assessment & Selection as well as in the broader People Analytics team delivering strategic projects. Before joining Credit Suisse, Gianna was selecting military pilots for the Swiss Air Force.
Marius Leckelt is part of the People Analytics Data Science Lab at Credit Suisse, where he works as a Data Science Expert. Previously, he was a data scientist for customer analytics at a leading pharmaceutical company. Before working in industry, he completed a PhD in personality psychology at the University of Muenster, was an assistant professor for personality psychology and psychological assessment at the University of Mainz, and completed a data science fellowship at Faculty AI in London.