Remote working challenges management, employees and works councils alike. People analytics could offer support, but only if the software is designed with the employees’ well-being and privacy in mind.
An article by Sonja Köhne and Miriam Klöpper.
The past year has left us with many changes in what we called our everyday lives. One of the most significant ones for many was in the way we organize our work: At the end of March 2020, about one quarter of employees in Germany were working from home. With this, remote work lost its reputation as being a lifestyle choice and quickly became a political issue. One major concern in the public debate on a right to work from home are the working conditions people face when they are physically separated from their team. With communication taking place solely by digital means and without traditional supervision, both employers and employees have to re-think their work routines. So-called People Analytics tools offer a data-driven approach to human resource management (HRM), promise to optimize employee-related business decisions and to facilitate leadership – also from a distance. However, these tools in themselves are no cure-all to compensate for the loss of face time. They need to be designed and employed carefully and deliberately. In this way, driven by the pandemic, a new need for action arises and with it the necessity of a thorough examination of the potentials and challenges of remote work.
Challenges of Remote Working
Taskin and Devos (2005) identify three specific tensions in the de-spatialisation of remote work. First, the intensification of work, where tensions arise between professional and private time. Thus, the reduction of work-related stress by opting for remote work appears to increase the level of stress in private life. Second, social isolation, which – despite high levels of autonomy in remote work – has a negative impact on commitment and identification with the company, and can thus negatively influence work performance. Third, what they call the do-it-yourself rule, that describes extensive control and monitoring methods. These stand in stark contrast to the often claimed self-management of employees in remote work. Challenges in supervising employees remotely and the field of tension between autonomy and control strongly dominate the existing state of research on remote work.
Questions of Power and Control
In the 2016/17 Linked Personnel Panel in Germany, two-thirds of employees who never worked from home cited their supervisors’ desire for them to be present as a reason for this. Similarly, one in ten companies who did not offer remote work cited difficulties in management and control as a reason against it. Thus, the spatial separation of supervisors and employees in remote work goes hand in hand with questions of power and control. Supervisors see themselves exposed to a major loss of control when employees suddenly move outside their spatial reach. Information asymmetry in remote work is high, making it difficult to capture whether employees or colleagues are particularly hard-working or committed at any given moment. Due to the physical separation, one of the few possibilities for supervisors to appraise their employees are the work results produced. The increased autonomy of employees vis-à-vis their superiors in remote work diminishes the role of supervisors in regard to the professional concerns of their employees.
Turning to Technology
To compensate for the loss of control, employers can resort to technological tools. Although they are currently not prevalent in Germany, these technologies do become increasingly powerful. Yet, there has been a lack of in-depth theoretical understanding of how they affect leadership dynamics. While the use of communication technologies gives employees in remote work a sense of increased autonomy, it also creates new constraints in an environment where employees could previously escape the control of their employer. These digital technologies are understood by the actors involved not as purely technical but as social, and thus as representative of a “society of control”. In this sense, the newly gained spatial flexibility of remote work comes at a price: employees must henceforth navigate various forms of control. Moreover, these technologies enable supervisors to invade domestic or private spaces. Thereby, remote work changes the management function in terms of roles, expectations, and relationships. Through remote work, however, organisational control by no means disappears, but merely becomes “more implicit, political, social, even cultural”. Aside from the increased use of communication technology, there currently also emerges a growing debate around people analytics tools that promise to make up for the loss of control during remote work.
People Analytics in a Nutshell
Tursunbayeva et al. define people analytics as “an area of HRM practice, research and innovation concerned with the use of information technologies, descriptive and predictive data analytics and visualisation tools for generating actionable insights about workforce dynamics, human capital, and individual and team performance that can be used strategically to optimise organisational effectiveness, efficiency and outcomes, and improve employee experience.” Thus, people analytics tools are designed to measure and analyse employee-generated data. There is a full range of tools available today that capture and analyse data such as the duration of use of individual applications, email traffic, the number of meetings held, as well as personal data such as age, gender, and the distance between home and workplace. These applications aim to support all HR core tasks with a data-driven approach by e.g. predicting and analysing employee potential and behaviour, identifying training needs or predicting fluctuation. People analytics does not always involve algorithmic decision-making and can also be strictly descriptive. The tools are, however, subject to a wide public debate. One of the most widely known people analytics softwares, Microsoft Workplace Analytics, made headlines at the end of 2020 for incorporating a productivity score in their software. Microsoft quickly reacted to public criticism and no longer allows employers to see the scores of individual employees. In Germany, the case of Zalando’s People Analytics tool Zonar raised concerns: employees of the fashion retailer were evaluated and ranked by their colleagues with it – just like products in an online shop. This led to an increased level of stress amongst the workers.
Managing from a Distance with People Analytics
As mentioned above, remote work generates a new demand for technologies that enable supervision and control of employees in dispersed teams. People analytics tools therefore seem to be an obvious choice to track the productivity of employees who are working from home. For example, they enable supervisors to see if a team has worked their scheduled hours. Being able to see the hours a team has worked, however, is not only important for supervisors. The works council, too, can use this data to assess if employees take sufficient amounts of breaks as well as to prevent them from working too many hours. For employees, the introduction of remote work can be associated with higher expectations regarding their availability, and thus lead to increased pressure to perform and consistently working overtime. People analytics may further be adapted to assess the well-being and stress levels of employees, thereby generating early warnings regarding potential risks of burn-out. These features appear to be particularly beneficial during remote work, where in-person communication is missing. When working together on-site, a supervisor is able to gather a majority of this information by talking to the staff or seeing them performing tasks at their desks.
The Dark Side of People Analytics
Besides factors that advocate the deployment of people analytics for teams working remotely, there are various reasons that indicate the contrary. First of all, the software may violate the General Data Protection Regulation (GDPR). People analytics enable employers and supervisors to gain insights into various domains that have previously been private to the employee. Thus, a strong asymmetry regarding the information available to employees and employers occurs; in some cases, employees cannot even verify what kind of data and information is gathered about them. Another valid argument against the use of people Analytics is that some of the gathered data can just as well be accessed directly by employees, without making it available to managers. For example, a software can simply remind people to take breaks instead of alerting the employer, who may not even act on this information. Measuring productivity by the amount of phone calls and emails, as some people analytics tools currently do, in many cases does not provide accurate information about the actual productivity of a person. On the contrary, this approach can cause employees to make unnecessary calls and write pointless emails because of the pressure to appear productive.
People Analytics and Works Councils
Against the backdrop of these developments, management as well as works councils are facing new challenges and important decisions. Whether people analytics tools serve the interests of employees depends on how they are designed, implemented and put into practice – ultimately, involved actors need to define meaningful metrics and be able to draw informed conclusions from the data. If there is a bias in the training data, it will most likely be perpetuated and fortified by the algorithm. An anticipatory process of choosing and implementing a people analytics tool is a vital step for the protection of employees’ privacy. Works councils should thus be involved in the process at all times, including the early stages of choosing a vendor. Nevertheless, even the most dedicated works councils may struggle to comprehensively evaluate people analytics and the variety of implications these tools (may) have for employees. The general need to understand and use digital technologies – with an emphasis on communication technologies – has grown throughout the past year. With it, the range of training opportunities for works councils, organised by i.e. unions, expanded. Taking courses to understand the implications of algorithm-driven technologies such as people analytics is necessary and a useful initial step. However, as people analytics tools can often be described as “black box” systems that are intricate and include mechanisms that are not transparent to the user, more rigorous training and educational resources are needed. To identify which materials and solutions are most helpful to support works councils, we frequently engage in events with their members to investigate their needs and current state of knowledge.
People analytics tools offer a wide range of helpful features. Without guidelines and constant monitoring of the outcome of algorithmic decision-making though, these tools can cause severe problems such as the discrimination. Transparency of the systems and of any sort of data collection must be ensured, so employees can make informed decisions when using them. Works councils need to be trained and supported to fully understand implications of these systems. They play a key role in the deployment of people analytics, as, by German law, these systems cannot be implemented and used without prior agreement of the individual employee or a company agreement. Research about the social and ethical implications of people analytics, especially in the context of remote work, is currently not sufficiently available. The limited knowledge on the topic makes it difficult for works councils and employees to educate themselves about the systems. Further research in this area that provides low-threshold information is therefore urgently needed.
People analytics have the potential to support and empower employees working from home. To prevent discrimation or the invasion of employee privacy though, clear regulation combined with employee participation is needed. Therefore, works councils as well as employees themselves need more thorough information about the consequences of data collection by means of digital tools, and about their own rights in this process.
Miriam Klöpper is currently a researcher at the FZI Forschungszentrum Informatik. She is interested in the social impact of digitalisation, especially in the context of workplace technologies such as (predictive) people analytics. You can learn more about her research project “Anonymous Predictive People Analytics – AnyPPA” here.
Miriam and Sonja both participated in the first Pop-Up Lab ‘Inclusive AI? The challenges of automated tools in HR’ of HIIG’s AI & Society Lab.
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