Big data in human resources
Author
Prof. Antoinette Weibel
University of St. Gallen
Interview with the principal investigators of this NRP75 project.
What was the aim of your project?
People analytics tools should make businesses more productive, transparent, and flexible, and promote fairness. However, their benefits can come with various, often incisive pitfalls, such as trust losses. With our project we answered four questions: (1) What does a sound conceptualisation of Big Data in HR look like? (2) Which Big Data-based practices are Swiss companies currently using in HR? (3) To what extent do these foster or damage trust in the employer? (4) What scope for improvement is there from the HR, ethical and legal perspectives?
Results?
Trust/HR Management: Our modular framework offers an initial possibility to systematically disentangle the complexity that comes with the implementation and use of big data. Besides, the framework can be used by managers to assess the impact of technology inside workplaces, or even as a tool to train digital literacy in a leadership context. Additionally, our results are forward-looking in that they outline trust challenges that emerge from ongoing leadership automation and point to critical management strategies to mitigate such trust-harming effects.
Business Ethics: Development and implementation of big data-based HR tools are accompanied by significant normative challenges, which we have systematically elaborated from the perspective of personal integrity. In our publications, we have opened up new perspectives on the responsible use of technology and have explored concepts that have received little attention to date, such as monolatry or moral imagination. We argue for the organisational development of critical data literacy, moral awareness, participatory design and (beyond the implementing organisation) new private regulatory regimes.
Law: Employers face data protection, employment law, and discrimination law challenges. Our publications have analysed these legal challenges and proposed solutions to issues that have not been addressed in Swiss law before. We have argued for professionalisation and democratisation of data protection law to achieve better law enforcement in practice. We have also shown that discrimination law does not adequately prevent or compensate algorithmic discrimination nor will it be capable to do so even with a revision of the law. We have analysed the employment law issues arising under Swiss law.
Does your project have any societal implications and recommendations?
Practitioners such as managers, developers, or organizational members can experience algorithm-based HR decision-making as a culturally and ethically complex, socially embedded phenomenon through our interdisciplinary studies. Our studies are intended to contribute to the development of corporate digital responsibility. Against this background, we emphasize the particular importance of critical data literacy, which is not limited to technical expertise. Only careful normative consideration of digitization processes generates sufficient moral awareness to enable organizational members to participate in critical discourses. Practitioners trained in this way and sensitized to the issues can successfully take part in participatory design methodologies that enable a new generation of algorithm-based HR programs. Such participatory design approaches and organizational spaces for reflection on normative concerns could avoid many of the pitfalls identified and pointed out in our studies.
Keyword “technology transfer”: What are the activities of your project?
The evidence-based results of the interdisciplinary studies have found their way into various academic courses and formats. From an HR/trust perspective, we have performed a 2020 edition of our 2018 “Swiss People Analytics Survey”. Based on these insights, we have set up a bi-annual forum, labelled “HSG Tech Breakfast”, where we exchange with Swiss tech practitioners, also presenting findings from our research.
At the Institute of Business Ethics, the findings around personal integrity have taken a permanent place in management education and training. Especially the established further education in the field of corporate social responsibility benefits immensely from a broadening of the perspective and the integration of questions around the dynamically advancing digitalization.
From a legal perspective, we have presented our research at Swiss conferences and have taken up discussions with SECO’s Eidgenössische Arbeitskommission and with SECO’s Direction du travail in several seminars in order to present our regulatory proposals for people analytics under Swiss law.
Big Data is a very vague term. Can you explain to us what Big Data means to you?
Our project has contributed to a nuanced understanding of the term “Big data” in the context of leadership and management. We have conceptualized how new technologies and big data alter and transform the way how organizational control (as a pivotal leadership and management task) is executed. From this, we have also contributed to what it means for organisations if big data develops its momentum in workplaces, such as how automation of leadership will manifest and also, what tasks will remain for humans in this very likely triangle-relationship.