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Big Data or Big Brother? - Big Data HR Control Practices and Employee Trust

English title Big Data or Big Brother? - Big Data HR Control Practices and Employee Trust
Applicant Weibel Antoinette
Number 167208
Funding scheme NRP 75 Big Data
Research institution Institut für Führung- und Personalmanagement Universität St. Gallen
Institution of higher education University of St.Gallen - SG
Main discipline Science of management
Start/End 01.03.2017 - 28.02.2021
Approved amount 636'129.00
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All Disciplines (2)

Discipline
Science of management
Legal sciences

Keywords (3)

HR Analytics; Control Practices/Mechanisms; Trust

Lay Summary (German)

Lead
Big Data kann Unternehmen produktiver machen. Auch in der Schweiz setzen Firmen zunehmend neue Techniken ein, um die Leistung ihrer Mitarbeitenden zu kontrollieren. Doch überrissene Kontrolle kann das Vertrauen in den Arbeitgeber zerstören. Wir wollen zeigen, wie Unternehmen dies vermeiden können.Daten-basierte Entscheide sollen Unternehmungen produktiver, transparenter und flexibler machen und Willkür vermeiden. In der Personalführung sind Big-Data-Analysen zunehmend gefragt, weil sie Unternehmen erlauben, die Leistung ihrer Mitarbeitenden besser zu kontrollieren. Doch neben vielen Chancen birgt Big Data am Arbeitsplatz auch Risiken. So kann die übermässige Kontrolle der Mitarbeitenden zu einem Vertrauensverlust führen, welcher die wirtschaftlichen Vorteile von Big Data zunichte macht.
Lay summary

Unsere Arbeit gliedert sich in vier Phasen:

  1. Zunächst bauen wir ein Schweizer Netzwerk von Praxis-Partnern auf, in dem alle relevanten Stakeholder vertreten sind.
  2. In einer gross angelegten Umfrage unter Schweizer Unternehmen ermitteln wir, wie Big Data heute am Arbeitsplatz eingesetzt wird.
  3. Detaillierte Fallstudien ermitteln dann "best practices".
  4. Aus den Daten erstellen wir ein Modell, welches verschiedenste Arbeitsplatz- und Privatsphären-Szenarien umfasst und welches wir schlussendlich testen und im Dialog mit der Praxis weiterentwickeln.

Die gewonnenen Daten und Erkenntnisse teilen wir sowohl mit der nationalen und internationalen wissenschaftlichen Community als auch mit den beteiligten Unternehmen in der Schweiz.

Wir wollen folgende Fragen beantworten:

  1. Welche Big-Data-Methoden setzen Schweizer Unternehmen heute im Personalmanagement ein?
  2. Inwiefern fördern oder beschädigen diese das Vertrauen in den Arbeitgeber?
  3. Welches Verbesserungspotenzial gibt es aus personalwirtschaftlicher, ethischer und juristischer Perspektive?

Wir suchen den Dialog mit der Praxis und führen empirische Untersuchungen mit verschiedenen Methoden durch, etwa Fallstudien und eine grosse Umfrage unter Schweizer Unternehmen.

Viele Aspekte unseres Projektes sind Pionierleistungen. Bisher gibt es keine belastbaren Daten darüber, wie Schweizer Unternehmungen Big-Data-Methoden im Personalmanagement einsetzen und wie sich diese Methoden auf das Vertrauen in den Arbeitgeber auswirken. Ausserdem wurden ethische und juristische Aspekte in diesem Kontext bisher ignoriert. Unsere Forschung stärkt mit ihrer interdisziplinären Perspektive den Wissenschafts-Standort Schweiz und ist gleichzeitig praxisrelevant.

Direct link to Lay Summary Last update: 26.07.2017

Lay Summary (French)

Lead
Le Big Data est à même de rendre les entreprises plus productives. En Suisse également, elles sont de plus en plus nombreuses à introduire de nouvelles techniques afin de contrôler les performances de leurs collaborateurs. Des contrôles disproportionnés peuvent toutefois détruire le rapport de confiance avec l’employeur. Nous voulons montrer comment les entreprises peuvent éviter cela.Des décisions basées sur des données sont censées rendre les entreprises plus productives, transparentes et flexibles, et éviter l’arbitraire. Les analyses Big Data sont de plus en plus demandées dans la gestion du personnel car elles permettent aux entreprises de mieux contrôler les performances de leurs collaborateurs. À côté de nombreux avantages, le Big Data sur le lieu de travail présente aussi des risques. Le contrôle sans mesure des collaborateurs peut induire une perte de confiance qui réduit à néant les bénéfices du Big Data
Lay summary

Notre travail se divise en quatre étapes :

  1. Nous mettons tout d’abord sur pied un réseau suisse de partenaires de terrain, dans lequel tous les acteurs importants sont représentés.
  2. Grâce à un sondage de grande envergure auprès des entreprises suisses, nous cherchons à savoir comment elles utilisent actuellement le Big Data sur le lieu de travail.
  3. Des études de cas détaillées permettent de définir les meilleures pratiques.
  4. À partir des données, nous élaborons un modèle qui comprend différents scénarios concernant le lieu de travail et la sphère privée, modèle que nous testerons et développerons en dialogue avec les acteurs sur le terrain.

Nous partageons les données et connaissances ainsi acquises aussi bien avec la communauté scientifique à l’échelle nationale et internationale qu’avec les entreprises concernées en Suisse.

Nous souhaitons répondre aux questions suivantes :

  1. Quelles méthodes Big Data les entreprises suisses utilisent-elles aujourd’hui dans la gestion du personnel ?
  2. Dans quelle mesure ces méthodes favorisent-elles ou nuisent-elles au rapport de confiance avec l’employeur ?
  3. Quel est le potentiel d’amélioration du point de vue des ressources humaines, de l’éthique et du droit ?

Nous cherchons le dialogue sur le terrain et menons des études empiriques au moyen de diverses méthodes, comme par exemple des études de cas et une vaste enquête auprès des entreprises suisses.

Notre projet fait œuvre de pionnier à divers égards. Il n’y avait jusqu’ici pas de données fiables sur la façon dont les entreprises suisses utilisent les méthodes du Big Data dans la gestion de leur personnel ni sur la manière dont ces méthodes influencent le rapport de confiance avec l’employeur. Les aspects éthiques et juridiques avaient également été ignorés. De par sa perspective interdisciplinaire, notre recherche renforce la place scientifique suisse et se révèle aussi pertinente pour la pratique.


Direct link to Lay Summary Last update: 26.07.2017

Lay Summary (English)

Lead
Big Data can make companies more productive. In Switzerland, as in other countries, firms are increasingly introducing new technologies to monitor their employees’ performance. However, unreasonable monitoring can destroy trust in the employer. We want to show how companies can avoid this.Data-based decisions should make businesses more productive, transparent and flexible, and promote fairness. Big Data analyses are in increasing demand in human resources (HR) management because they enable companies to monitor the performance of their employees more effectively. However, Big Data in the workplace presents risks as well as many opportunities. Excessive monitoring of employees can lead to a loss of trust, which wipes out the economic advantages of Big Data.
Lay summary

Our work is divided into four phases:

  1. First of all, we will build up a Swiss network of partners from the real-world setting, in which all relevant stakeholders are represented.
  2. We will carry out a large-scale survey of Swiss companies to find out how Big Data is currently being used in the workplace.
  3. Detailed case studies will then identify best practices.
  4. We will use the data to construct a model that covers a wide range of workplace/private life scenarios, which we will then test and develop further in dialogue with industry.

We will share the resulting data and findings with the national and international scientific community as well as with the participating companies in Switzerland

We want to answer the following questions

  1. Which Big Data methods are Swiss companies currently using in HR management?
  2. To what extent do these foster or damage trust in the employer?
  3. What scope for improvement is there from the HR, ethical and legal perspectives?

We aim to enter into a dialogue with industry, and we will carry out empirical investigations using a number of methods, such as case studies and a large-scale survey of Swiss companies.

Many aspects of our project are groundbreaking. At present no hard data is available on how Swiss companies use Big Data methods in HR management and what the impact of these methods is on trust in the employer. Furthermore, ethical and legal considerations have been ignored in this context. Our research, with its interdisciplinary perspective, strengthens Switzerland as a centre of scientific achievement and also has practical applications.


Direct link to Lay Summary Last update: 26.07.2017

Responsible applicant and co-applicants

Employees

Publications

Publication
Goldgräberstimmung im Personalmanagement? Wie Datafizierungs-Technologien die Personalsteuerung verändern
Weibel Antoinette, Schafheitle Simon, Ebert Isabel, Goldgräberstimmung im Personalmanagement? Wie Datafizierungs-Technologien die Personalsteuerung verändern, in Zeitschrift für Organisationsentwicklung , 3, tbd.

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Exploratory Dialogue “Remedying wrongs on a decentralized internet” Talk given at a conference Safeguards for new technologies to protect employees’ privacy at the workplace 15.03.2019 Oxford , Great Britain and Northern Ireland Ebert Isabel; Schank Christoph; Wildhaber Isabelle Sarah; Weibel Antoinette; Kasper Gabriel; Schafheitle Simon;
FINT2019 Talk given at a conference Trust and Technology - A Multilevel Perspective 11.01.2019 St. Gallen , Switzerland Weibel Antoinette; Schafheitle Simon; Wildhaber Isabelle Sarah; Kasper Gabriel; Schank Christoph; Ebert Isabel;
AKempor, Arbeitskreis Empirische Personal- und Organisationsforschung Talk given at a conference New Technology Control Configurations and Employee Trust - Towards an Integrated Framework. 21.11.2018 Salzburg, Austria Ebert Isabel; Schafheitle Simon; Weibel Antoinette; Kasper Gabriel; Wildhaber Isabelle Sarah; Schank Christoph;
Amsterdam Privacy Conference Talk given at a conference Privacy under Limited Rule of Law 05.10.2018 Amsterdam , Netherlands Wildhaber Isabelle Sarah; Schank Christoph; Schafheitle Simon; Ebert Isabel; Weibel Antoinette; Kasper Gabriel;
OMTF2018 - Organization, Theories and Management of the Firm Talk given at a conference New Technology Control Configurations 27.09.2018 Zürich , Switzerland Schank Christoph; Ebert Isabel; Kasper Gabriel; Schafheitle Simon; Weibel Antoinette; Wildhaber Isabelle Sarah;
Academy of Management Discoveries Paper Development Workshop Talk given at a conference No Stone Left Unturned? No stone left un-turned? Towards a framework on the impact of datafication technologies on organizational control 21.09.2018 Paris, France Wildhaber Isabelle Sarah; Ebert Isabel; Kasper Gabriel; Weibel Antoinette; Schafheitle Simon; Schank Christoph;
Datenschutztagung 2018, IRP-HSG, University of St. Gallen, Talk given at a conference "Big Brother» in Schweizer Unternehmen? Daten, Privatsphäre und Vertrauen am Arbeitsplatz" 12.09.2018 St. Gallen, Switzerland Schafheitle Simon; Ebert Isabel; Weibel Antoinette; Schank Christoph; Wildhaber Isabelle Sarah; Kasper Gabriel;
Society for Business Ethics Annual Conference Talk given at a conference Workplace Surveillance & Big Data: Contextualizing Digital Threats to Employees’ Moral Agency and Integrity 10.08.2018 Chicago, United States of America Wildhaber Isabelle Sarah; Kasper Gabriel; Busch Thorsten; Schank Christoph; Weibel Antoinette; Schafheitle Simon;
Academy of Management Annual Meeting 2018 Talk given at a conference New Technology Control and Trust - A Multilevel Perspective 10.08.2018 Chicago , United States of America Schank Christoph; Kasper Gabriel; Wildhaber Isabelle Sarah; Weibel Antoinette; Ebert Isabel; Schafheitle Simon;
Departmental conference of SHSS (HSG) Talk given at a conference "Die Rolle von Vertrauen in einer datafizierten Welt" 17.05.2018 St. Gallen , Switzerland Kasper Gabriel; Wildhaber Isabelle Sarah; Schafheitle Simon; Weibel Antoinette; Ebert Isabel; Schank Christoph;
Law and Robotics Workshop Talk given at a conference Diskriminierung durch Big Data in der Arbeitswelt? – Rechtliche Überlegungen 16.05.2018 Basel , Switzerland Weibel Antoinette; Ebert Isabel; Schafheitle Simon; Kasper Gabriel; Wildhaber Isabelle Sarah; Schank Christoph;
Academy of Management Specialized Conference: Big Data and Managing in a Digital Economy Talk given at a conference Workplace Surveillance and Big Data: Contextualizing Digital Threats to Employees Moral Agency and Integrity 18.04.2018 Surrey , Great Britain and Northern Ireland Schafheitle Simon; Ebert Isabel; Schank Christoph; Weibel Antoinette; Wildhaber Isabelle Sarah; Kasper Gabriel;
Forschungsseminar Individual talk Vertrauen und Kontrolle 22.11.2017 Luzern, Switzerland Weibel Antoinette; Schafheitle Simon; Kasper Gabriel;
CSR in the Digital Economy Talk given at a conference Surveillance Capitalism 10.11.2017 London, Great Britain and Northern Ireland Busch Thorsten;
OMT Theories Lausanne Talk given at a conference New Technology Control Configuration 28.09.2017 Lausanne, Switzerland Weibel Antoinette; Schafheitle Simon;
Data Power Talk given at a conference Big Data or Big Brother 22.06.2017 Ottawa, Canada Busch Thorsten;


Self-organised

Title Date Place
FINT2019 - First International Network on Trust 10.01.2019 St. Gallen , Switzerland

Knowledge transfer events

Active participation

Title Type of contribution Date Place Persons involved
CM-HSG; CAS (HSG) in Compliance Management. “ New Technology Control und Vertrauen – Wie können datafizierte Compliance und Vertrauen Hand in Hand gehen?“ Workshop 21.03.2019 St. Gallen , Switzerland Kasper Gabriel; Ebert Isabel; Schafheitle Simon; Schank Christoph; Wildhaber Isabelle Sarah; Weibel Antoinette;
Axa Tagung „Future Workforce Engineering” “HR-Tech: Becoming a Digital Champion“ Talk 05.02.2019 Winterthur, Switzerland Kasper Gabriel; Schank Christoph; Ebert Isabel; Wildhaber Isabelle Sarah; Schafheitle Simon; Weibel Antoinette;
ZHAW Workshop - Automatisierung der Führung. Rechtliche, ethische und personalpolitische Fragen Talk 07.11.2018 Winterthur, Switzerland Weibel Antoinette; Kasper Gabriel; Schafheitle Simon; Schank Christoph; Ebert Isabel; Wildhaber Isabelle Sarah;
PWC Workshop - Results from our Swiss PMA Benchmarking Survey Talk 10.10.2018 Zürich , Switzerland Wildhaber Isabelle Sarah; Schafheitle Simon; Kasper Gabriel; Weibel Antoinette; Schank Christoph; Ebert Isabel;
ConnexHR (HSG Alumni) "Business Excellence and Big Data in Human” Talk 09.10.2018 St. Gallen , Switzerland Wildhaber Isabelle Sarah; Weibel Antoinette; Kasper Gabriel; Schafheitle Simon; Ebert Isabel; Schank Christoph;
Data Protection in Labour Law "Automatisierung der Führung" Talk 22.05.2018 Zürich , Switzerland Ebert Isabel; Kasper Gabriel; Schafheitle Simon; Wildhaber Isabelle Sarah; Weibel Antoinette; Schank Christoph;
CHRO Roundtable Talk 27.10.2017 Regensdorf (SAP), Switzerland Schafheitle Simon; Kasper Gabriel; Weibel Antoinette;
Sounding Board Meeting Workshop 23.06.2017 Zürich, Switzerland Weibel Antoinette; Kasper Gabriel;


Self-organised

Title Date Place
Big Data on the workplace 16.10.2018 Zürich , Switzerland
NFP75 Sounding Board Meeting - Business Excellence and Big Data in Human Resource Management – Results from our Swiss People Management Analytics Benchmarking Survey 26.09.2018 St. Gallen , Switzerland
CAS in HR Value Creation 23.05.2018 St. Galen , Switzerland

Communication with the public

Communication Title Media Place Year
Media relations: print media, online media Chancen und Risiken der Datafizierung am Arbeitsplatz PANORAMA Fachinformationen für Berufsbildung, Berufsberatung und Arbeitsmarkt German-speaking Switzerland 2019
Media relations: print media, online media So sammeln Unternehmen Daten über ihre Mitarbeiter – und nutzen sie für das Personalmanagement NZZ Italian-speaking Switzerland German-speaking Switzerland Rhaeto-Romanic Switzerland Western Switzerland International 2019
Media relations: print media, online media Vom Computer bei der Bewerbung diskriminiert Tagesanzeiger German-speaking Switzerland 2019
New media (web, blogs, podcasts, news feeds etc.) Big Brother in Schweizer Unternehmen? – Rechtliche Schranken für die Big-Data-Überwachung SNF Blog International 2018
Media relations: print media, online media Big Data or Big Brother at the Workplace? Nachhaltigkeitsbericht Uni St. Gallen 2018 International 2018
Media relations: radio, television Big Brother in Schweizer Firmen? HSG Fokus German-speaking Switzerland 2017
New media (web, blogs, podcasts, news feeds etc.) Homepage (und diverse Posts) German-speaking Switzerland 2017

Associated projects

Number Title Start Funding scheme
187473 Socially acceptable AI and fairness trade-offs in predictive analytics 01.06.2020 NRP 77 Digital Transformation
180717 Managing Team and Organizational Boundaries 01.12.2018 Postdoc.Mobility
172752 Stakeholder Distrust 01.09.2017 Project funding (Div. I-III)

Abstract

The advent of big data holds the promise that organizational decision-making may change from more intuitive types of reasoning toward more deliberate kinds of choices (George, Haas, & Pentland, 2014). Particularly, in the field of Human Resource (HR) Management, big data techniques offer the potential to improve many HR functions, such as retention and performance management (Young & Phillips, 2015). Despite this potential, HR practitioners have been reluctant to implement more refined analytical approaches. One major obstacle for the more widespread use of big data in HR is the expected skeptical reaction of the workforce. At the moment, we have little systematic knowledge of how employees will perceive their employers’ big data-enhanced monitoring and measurement activities, but drawing from research in management fields with a more mature big data literature (such as marketing), it seems likely that employee trust in their employer will play a key role in whether organizations can effectively apply big data techniques in their HR management.Thus, the aim of this project is to understand the impact of big data-based HR control, i.e. HR’s big data-based goal setting, monitoring, feedback and punishment/reward practices, on employees’ trust in their employer. Drawing from literature on HR control practices (Weibel et al., 2015), we expect three main contingencies to shape the association between employees’ perception of big data-based HR control and their trust in the employer: (1) the specific type of implementation of metrics and predictive analytics actually used by HR for controlling purposes, (2) ethical guidelines and processes on what is being measured for what reason and how individuals’ data is dealt with, and (3) the implementation of legal requirements by the employer (employment law and data and privacy protection laws). We will study these influences using a mixed-methods approach of four modules including the following research steps: (1) interviews and discussion techniques with professional experts on big data who will serve as our sounding board for the entire duration of the project, (2) a survey of 1,200 Swiss companies on their big data-based control practices, (3) in-depth case studies of companies applying forms of big data-based HR control, and (4) a factorial survey that will allow us to test causal hypotheses on interaction effects of big data-based control and specific contingencies on employee trust derived from Modules 1-3.Our research project will generate systematic and relevant knowledge in three areas: First, we contribute to trust and human resources management theory by testing how and under which conditions big data-based HR control activities influence employees’ trust in their employer. Second, we contribute to HR management practice by describing the role HR departments could be playing in the effective use of big data-based control, and how HR departments could contribute to an ethical stakeholder dialogue and the implementation of legal regulations. Third, we analyze how ethical guidelines and legal regulations should be adapted to meet both legitimacy and effectiveness criteria.
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