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CEO Circle

How HR technology supports new ways of working

Published 24 February 2022 in CEO Circle • 6 min read

Striking innovations, including in artificial intelligence, are redefining the way employers engage with employees, creating a host of issues around privacy and control

 

In  the early stages of the pandemic, many organizations rushed to implement new technologies to ensure effective remote communication and collaboration as people  grappled with the reality of working for home. Now, as companies look to the future and the next stage of recovery, HR leaders must  carefully consider how technology can not only sustain but reimagine the way we work.

That’s because, from virtual reality meetings to algorithmic hiring, new technologies are redefining how employers engage with their staff — and the internal workings of the human resources department. These innovations are also creating a host of new questions around privacy, control and equity.

In addition, successfully navigating the evolution of working practices hinges on how companies approach investing in such new technologies, as well as how they are adopted. 

The best returns from investments in HR technology are likely to come from solutions that unite employees spread around the globe, because many employers plan for a more permanent shift to remote or hybrid working. That has sparked a search for tools that recreate the more natural exchanges or “water cooler” moments that are typically missing from virtual interactions.

Some organizations have created 3D worlds in which workers interact and collaborate through avatars that aim to make exchanges more fluid, while helping to reduce the effects of “Zoom fatigue”. 

Lack of buy-in from the C-suite is one of the main barriers to greater adoption. As excited as HR leaders may be about the latest snazzy innovations, how can they convince traditional corporate hierarchies to invest in new, unproven technologies? 

They will need to demonstrate expected payoff in monetary terms, and develop metrics to measure how the technology ultimately impacts the organization’s wider goals — such as increasing profitability through higher sales and greater customer retention. Ultimately, this will play a part in expanding HR’s growing role as a strategic partner to the chief executive.

Successfully navigating the evolution of working practices hinges on how companies approach investing in such new technologies, as well as how they are adopted

Equally important will be addressing technology’s risks, as well as the associated privacy and security concerns of increasingly dispersed workforces. 

Many organizations use monitoring techniques to measure performance and boost productivity, especially now that more people are working remotely, whether that’s tracking keystrokes, screening emails or browsing history. 

These  are not necessarily a true indicator of productivity, which is a nuanced concept. However, by analyzing vast amounts of personal data, employers can better understand workers’ behavior and use that information to support decisions on hiring and firing, promotion and task allocation.

Yet there’s the possibility of mission creep. With safeguards and regulation often lacking, this level of individual monitoring has raised concerns over employment and privacy rights, as well as employee wellbeing.

This is especially true for organizations that use facial recognition technology to hire and fire people, based on their emotional states, personality traits or levels of engagement in the workplace. For example, algorithms used in AI can work out how excited, uninterested or truthful a job applicant may be, and help employers avoid undesirable traits.

These solutions need a scientific basis; HR leaders should watch out for “snake oil” as the number of AI startups multiplies.

With safeguards and regulation often lacking, this level of individual monitoring has raised concerns over employment and privacy rights, as well as employee wellbeing.

On a practical level , employers must take steps to tackle the opacity of how these algorithms work. Too often, machine learning systems operate like a black box.

Employers therefore will need to be more transparent, both in terms of how  algorithms work (data collection and analysis) and the strategic intent behind their  implementation in the workplace. 

Transparency may also help to mitigate bias. Most employers are using algorithms to sift jobseekers, cutting out the tedium of reading so many CVs and cover letters. Yet these systems can replicate the human bias of the people who create them. Because AI is trained to find patterns in behavior, any human bias that’s already present in the recruitment process, even if it’s unconscious, can be amplified by AI.

That’s why Amazon scrapped an AI recruitment tool that was biased against women. The company’s models were trained on CVs that mostly came from men, reflecting the tech sector’s gender imbalances, so the AI essentially taught itself that males were more desirable.

Such bias can be mitigated by using higher quality datasets that more accurately reflect the diversity in society. That said, AI could actually help to reduce human bias in the recruitment process, and help create more fair promotion and compensation systems.

While humans may have an unconscious sense of the desirable characteristics for a given role, such as academic pedigree, which can lead to homogenous workforces, AI can test a wider range of skills and aptitudes to determine a candidate’s job readiness. This will ultimately help to promote diversity and equity, rather than erode it.  

Giving employees a say in how their personal information is collected, evaluated and used to form judgements and inform decisions will also help, with employers likely repaid with higher levels of workplace trust.

While organizations will want to employ technology to both hire and keep knowledge workers as they spend less time in the office, equally important will be helping staff to switch off.

Technology makes it increasingly difficult to disconnect from work, because it blurs the line between company and personal time. And with burnout becoming a workplace epidemic, many HR leaders are wondering how to stem turnover, especially when labor markets are persistently tight.

Organizations can ensure staff avoid digital overload and burnout through policies such as meeting-free days. Some companies only invite colleagues to meetings if they answer two questions: how will I contribute to the meeting, and how will I benefit? This protocol frees up productive time for employees to work on another project — or take a break. It also makes for a more meaningful dialogue between participants who do join the call.   

Another step to take is encouraging no emails outside working hours; people who work after hours can use software to schedule messages until the next day, reducing the expectation of an immediate response.  

With technology providing “always-on” communication between workers and managers, it’s often seen as a major contributor to employee burnout. Yet this stigma means there’s also a missed opportunity for organizations to use digital tools to disconnect. Ultimately, technology can be both a blessing and a curse for employee wellbeing.  

Authors

Oyku Isik IMD

Öykü Işık

Professor of Digital Strategy and Cybersecurity at IMD

Öykü Işık is Professor of Digital Strategy and Cybersecurity at IMD, where she leads the Cybersecurity Risk and Strategy program and co-directs the Generative AI for Business Sprint. She is an expert on digital resilience and the ways in which disruptive technologies challenge our society and organizations. Named on the Thinkers50 Radar 2022 list of up-and-coming global thought leaders, she helps businesses to tackle cybersecurity, data privacy, and digital ethics challenges, and enables CEOs and other executives to understand these issues.

Amit Joshiv - IMD Professor

Amit M. Joshi

Professor of AI, Analytics and Marketing Strategy at IMD

Amit Joshi is Professor of AI, Analytics, and Marketing Strategy at IMD and Program Director of the AI Strategy and Implementation program, Generative AI for Business Sprint, and the Business Analytics for Leaders course.  He specializes in helping organizations use artificial intelligence and develop their big data, analytics, and AI capabilities. An award-winning professor and researcher, he has extensive experience of AI and analytics-driven transformations in industries such as banking, fintech, retail, automotive, telecoms, and pharma.

Ina Toegel

Professor of Leadership and Organizational Change at IMD

Ina Toegel’s research focuses on team dynamics, organizational change management, top management teams during corporate renewal, and founder influence. She directs the Leading High-Performance Teams program which supports executives in achieving team flow and transforming a group of individuals into a high-performing dream team.

Oscar Stege Unger

Oscar Stege Unger

Founder and CEO of Canucci

Oscar Stege Unger is the Founder and CEO of Canucci, an AI-driven company founded in 2020 with the goal of combining peer experience, technical expertise, and data insights to support organizations and leaders with their transformative work. He is a Senior Advisor to the Wallenberg Foundations AB where he advises them within strategy, communication, and the network for the Wallenberg Foundations and the Wallenberg Family.

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