Crunchr created The Consortium to bring together people analytics professionals with the aim to explore innovation together, initiate (research) projects and discuss how to get people analytics to the heart of HR professionals.
Companies are keen to explore the art of the possible in people analytics. They are inspired by examples of how people and business data can become a competitive advantage to companies. Workforce analytics summits are organized everywhere and people searching on Google for “People Analytics” have increased with 335% over the last 3 years.
However, according to the 2016 Bersin report by Deloitte Research, 92% of companies struggle to start or advance in people analytics and are stuck in basic HR reporting. Apart from practical constraints of data consolidation and validation, we observe two underlying reasons: companies do not understand what is possible with the data nor how it can be made possible.
Crunchr believes that techniques from non-HR domains can be applied to the HR domain. For example: workforce planning is an application of logistic optimization, while the strength of succession planning networks relates to graph theory, and talent identification can be solved with pattern recognition.
To really help the HR domain in advancing and facilitating next steps, thorough research needs to be done on how these existing techniques can be applied. Whilst every company has different challenges, we believe that techniques are relatively similar. Therefore, we see a joint research consortium as a platform to do fundamental research and to share (non)success stories so that everybody can learn from them.
We've collaborated with companies and universities on the following topics:
Succession Planning. How likely is a succession proposal given the current succession network?
Thesis research done by Bastiaan Kars, under supervision of dr Evert Haasdijk, S. Bhulai and Dirk Jonker
Analyzing real career pathing and predicting talent traffic jams at Wolters Kluwer
Research done by Marielle Sonnenberg, Rianne Kaptein and Dirk Jonker
Predicting voluntary employee turnover using core employee data
Research done by Sjoerd van Bekhoven, under supervision of M. Reinders, M. Loog, B. Bhulai, W Kouw and Dirk Jonker
Distance based source domain selection for automated
sentiment classification
Thesis research done by Lex Schultz, under supervision of Marco Loog, Rianne Kaptein and Dirk Jonker
Identifying pockets of cost savings opportunities with
organisational inefficiencies
Research done by PwC North America and Dirk Jonker
Marco Loog, Assisstant professor at the Pattern Recognition Laboratory, TU Delft University
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