From early stages to infinite potential : predictive HR analytics use cases in wellbeing services counties
Kilponen, Kaisa (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202502203153
https://urn.fi/URN:NBN:fi:amk-202502203153
Tiivistelmä
The thesis delves into the transformative power of predictive HR analytics, uncovering its potential through compelling case studies within the theoretical framework. The study illuminates customer needs related to predictive HR analytics within the wellbeing services counties through thematic interviews, providing valuable insights for future innovations.
This thesis was conducted for the product development team within a global IT and consulting company. The product development team specializes in providing reporting and analytics services to its clients. The thesis aims to explore expectations and experiences regarding the utilization and potential of predictive HR analytics. The study investigates whether customer needs are common and general or if they, along with models of predictive HR analytics, are always dependent on specific contexts and the organization's characteristics. The former studies in the theoretical part act as examples of different use cases of how to use machine learning in predictive HR analytics.
The research was a qualitative study. The data was collected through thematic interviews. For the research, two wellbeing services counties were interviewed, with a total of eight interviewees. The interviews were conducted as individual interviews via Microsoft Teams. The data was analyzed using thematic analysis.
According to the results, the utilization of predictive HR analytics is still in its early stages in both of the interviewed organizations. The interviewees' opinions on the current situation varied within the same wellbeing services county, but there were also organization-specific differences. The interviews revealed 45 different development suggestions, the need for which has been addressed in each theme. Finally, the development suggestions were prioritized based on how many interviews mentioned each suggestion.
This thesis was conducted for the product development team within a global IT and consulting company. The product development team specializes in providing reporting and analytics services to its clients. The thesis aims to explore expectations and experiences regarding the utilization and potential of predictive HR analytics. The study investigates whether customer needs are common and general or if they, along with models of predictive HR analytics, are always dependent on specific contexts and the organization's characteristics. The former studies in the theoretical part act as examples of different use cases of how to use machine learning in predictive HR analytics.
The research was a qualitative study. The data was collected through thematic interviews. For the research, two wellbeing services counties were interviewed, with a total of eight interviewees. The interviews were conducted as individual interviews via Microsoft Teams. The data was analyzed using thematic analysis.
According to the results, the utilization of predictive HR analytics is still in its early stages in both of the interviewed organizations. The interviewees' opinions on the current situation varied within the same wellbeing services county, but there were also organization-specific differences. The interviews revealed 45 different development suggestions, the need for which has been addressed in each theme. Finally, the development suggestions were prioritized based on how many interviews mentioned each suggestion.