Today’s workplaces are seeing an increase in the use of algorithms and data analytics for monitoring and controlling employees—a practice known as algorithmic management. There are substantial societal costs connected with this strategy, notwithstanding supporters’ claims that it increases production and efficiency.
The rise of algorithmic management
Software algorithms are used in algorithmic management to track, assess, and improve several facets of workers’ performance. These algorithms track productivity data and schedule shifts to maximise output and streamline operations. In order to obtain a competitive advantage in the market, businesses are increasingly relying on algorithmic management systems thanks to developments in artificial intelligence and big data analytics.
In a growing number of sectors and contexts, algorithms are being used to automate management responsibilities. For instance, 7-Eleven, IBM, and Uniqlo use them to monitor the sales success of retail employees or evaluate employee skill sets, and Amazon, Uber, and UPS use them to manage the movements and performance of millions of drivers and warehouse personnel.
It goes without saying that this switch to “algorithmic management” increases productivity and profitability for businesses. However, might it also have unforeseen repercussions and alienating impacts, especially in terms of the dynamics of the workplace?
Unlocking the hidden costs of algorithmic management: Insights from research on prosocial motivation
We have very little evidence to help us answer this question since surprisingly only a few researchers have thoughtfully thought about it. To close that gap, we thoroughly investigate in our research if algorithmic management has an effect that goes beyond worker productivity.
Most recently, researchers looked at how algorithmic management affects prosocial motivation, a crucial factor in the workplace that promotes creativity, productivity, social engagement, and general well-being. By doing this, they were able to identify one especially intriguing and significant gap: workers managed by algorithms are actually less likely than workers managed by individuals to assist or encourage one another.
Businesses that use algorithmic management should be aware of this issue as well as any further detrimental consequences on the social dynamics and psychology of their workforce. Fortunately, their study indicates that businesses can lessen these consequences by actively promoting social contacts at work, as we’ll cover in this piece.
The problem
Research was done using a field survey of employees in the logistics, distribution, and transportation industries—sector areas where algorithmic management is prevalent. It was in this initial location that the researchers discovered that employees handled algorithmically have a lower propensity to assist or back peers. After controlling for variables unique to their employment (such as management satisfaction or overall job satisfaction), their organisations (like size or average employee tenure), and their traits (like gender and income), the pattern remained.
Next, to verify the behavioural effects of algorithmic management firsthand, they carried out a field experiment in association with a German van rental company. For this experiment, the researchers hired over 1,000 gig workers through an online labour platform to come up with catchphrases for the social media marketing campaigns of the van rental company.
Two groups of workers were randomly assigned; one group was led and assessed by an algorithm, and the other group was overseen by a human. The researchers assessed the workers’ readiness to help others by asking them to provide advice on how to write catchy marketing slogans after they had finished the task.
Remarkably, the researchers discovered that the workers supervised by the algorithm gave their counterparts had 20% less guidance overall, and the advice they did give was of worse quality. Interestingly, the two groups’ actual slogans did not significantly differ in terms of quality, suggesting that algorithmic management may not have an impact on workers’ task-based performance.
The solution
Research on a field survey of employees in the logistics, distribution, and transportation industries revealed that routine social interactions between employees serve as a buffer against the detrimental effects of algorithmic management. This implies that businesses can actively reduce negative effects by encouraging a setting where employees can interact and have deep conversations. This could entail taking steps like setting up shared break areas, putting team rotations into place, and planning get-togethers or cooperative recreational activities.
When algorithms are used to track and assess employee performance, the detrimental effects become more noticeable. Businesses must be aware of this impact. They should endeavour to integrate human managers if they determine that they would like to rely only on algorithmic management for HR-related duties like performance evaluation.
However, research indicates that using algorithms for performance evaluation still runs the danger of having a detrimental impact on prosocial conduct, even in the presence of human supervisors. Both the previously mentioned study and another one that examined the impact of human intervention found that prosocial conduct was negatively impacted when human managers used algorithms to assess staff performance.
Companies and managers should prepare for this by informing staff members in advance and involving them in choices about the application of algorithmic management. Incorporating and acknowledging employees as partners in the development and execution of algorithmic management fosters prosocial behaviour and reduces the likelihood of objectification.
What other companies are doing
Employees at companies like Haier, one of the biggest appliance manufacturers in the world, are empowered to set their performance standards above and above the minimum targets set by algorithms, which helps them adopt automated performance evaluation systems successfully.
Companies also need to make sure that there is open and thoughtful communication about the use of algorithms and who makes the ultimate decisions. For example, IBM uses algorithms to determine remuneration, but it makes it very apparent to staff that these are only suggestions that managers have the authority to disregard.
Algorithmic management undoubtedly provides businesses with a plethora of new chances to enhance their workflow. However, firms should take extreme caution when implementing this practice because we still don’t fully understand the consequences it can have on team dynamics, collaborative behaviours, and personal well-being.
Specifically, they must take proactive measures to lessen the adverse impacts that algorithmic management may have on prosocial conduct, considering the general importance of this behaviour for both individual and group performance in the workplace. Companies must put in a lot of effort to find the balance that needs to be struck in this situation.
(Tashia Bernardus)