New Trends in Employee Monitoring Technologies

Investment in workplace technologies, particularly performance management, saw an "eightfold increase in funding" between 2017 and 2022, as per the New York Times . Big companies like J.P. Morgan, UnitedHealth Group, Amazon, and more, have been monitoring metrics like idle time and activity time to make sense of employee productivity and optimise workflows.

It's not just about surveillance; with the increase in remote and hybrid setups, employee monitoring solutions can bring forth deeper insights into workplace behaviour and power a nuanced understanding of productivity to then drive better overall engagement and collaboration.

Of course, the intrusive nature of employee monitoring is a matter of debate, and rightly so. Employees worldwide should have the right to give consent to what's being monitored and companies should adhere to this expectation, while also ensuring that the employee morale isn't compromised in the process — precisely why employee monitoring laws and regulations. are in place.

There's a delicate balance to maintain here — between monitoring for productivity and respecting employee privacy. The right tools, technologies, and approaches are key here. They can usher in ethical and compliant monitoring and increase acceptance towards it.

That said, here's a look at some key trends shaping the employee monitoring technology landscape.

Within the purview of AI, there's a lot to unpack. There's analytics, AI scoring, facial recognition, Gen AI, and more. Before we dive into these, it's important to understand that AI's integration with the monitoring workflow isn't skewed by a certain level or degree. It's, in fact, quite pervasive in how it can influence almost every stage of the process. Right from pinpointing the issues to helping with their objective assessment, it can help tailor workflows to bring the best out of employees.

Imagine having to rely on subjective assessments that vary from one manager to the next. Why subjective? Well, their way of interpreting performance metrics, personal biases, and even day-to-day moods can influence how they perceive an employee’s productivity. A 2022 study by researchers at the University of Florida revealed that managers still can have both implicit and explicit biases, especially towards marginalised groups.

Productivity scoring wards off this by bringing forth a quantifiable approach to employee productivity evaluation. For instance, CleverControl's AI Scoring feature considers the employee's position, industry context, and web and application logs to define a productivity score, provide productivity labels, and the rationale behind that score. The entry barrier to such a feature is as easy as accepting a user agreement and filling in a few details about your business's industry and the profiles you are looking to analyse productivity for.

Talk about machine learning being in full-throttle mode. Facial recognition is proving exceptionally viable for tracking employee attendance, verifying identities, assessing working patterns, reducing time theft, and more.

Our own research based on surveys with our clients found out that:

• Employees buddy-ed for overtime pay. They covered up for one another.
• There's no solution to identifying such time theft earlier to avoid consequences.
• The existing tools that logged in active and idle time didn't actually convey if someone was actually working

Skriva in face recognition. Businesses can use the webcam to recognise and record employees, compare faces to their existing database, and generate easily consumable reports.

Face recognition also gives way to computer vision — a great tool for managing productivity in industrial settings. For instance, the use of computer vision lets businesses to:

• Transform their workplaces and industry settings into safer ecosystems. How? They're able to act proactively in issue identification. They don't have to be subject to post-mortem analysis.
• Track and monitor worker productivity and even optimise workflows — all while ensuring that their costs are low and that they are compliant with industry standards and regulations.

As per the McKinsey Technology Trends Outlook 2024 report, the gen AI use cases can generate somewhere between $2.6 trillion and $4.4 trillion in annual value. More and more organizations are regularly leveraging gen AI applications across their business functions. And with trends like multimodal generative models, expansion of NLP, and advancement in LLMs, the use of gen AI in employee monitoring is gaining momentum.

For example, with gen AI, organizations can:

• Process conversations and gauge sentiment. This can help managers to be proactive in resolving issues and laying out recommendations for better decision-making.
• Uncover patterns in substantial volumes of log data that indicate bottlenecks, team dynamics, employee dissatisfaction, and more.

If you closely look through the recent developments in employee monitoring laws, a significant shift towards consensual, data privacy-first monitoring is quite apparent. And that makes sense because of the growing concerns about data protection and the ethical use of monitoring technologies. Updates to GDPR and other major regulatory frameworks are setting higher standards for how employee data should be handled.

Read more here: Recent changes in employee monitoring laws and regulations

In light of this, employee monitoring software are prioritising transparency and explicit consent taking. New features are being integrated that provide a comprehensive view of what's being monitored and analysed and for what purpose. Plus, there's a constant focus on data security.

We, for one, realized this by talking to clients with different team sizes. Hence, we offer both cloud and on-premise solutions that ensure businesses can choose the level of control they need over their data. They can practice complete data ownership and management.

Employee work tracking is no longer a desktop-specific task. With the proliferation of hybrid setups, it makes sense that managers have the flexibility of monitoring their team's activities from anywhere on their smartphones. This is similar to how project management solutions like Monday.com have mobile versions of their dashboards.

This trend is particularly gaining traction because of the growing need for continuous oversight and greater flexibility in accommodating that. Managers and business owners can't be tethered to the desk all the time. With mobile apps that provide a comprehensive overview of the monitored data, employers can ensure better levels of engagement — especially outside of traditional office setups.

Based on all these trends, there are some clear, actionable steps that you can take to ensure that you have the right employee monitoring software on your hands for simple and better productivity management:

1. Make sure the tool fits well with your privacy policies

   • Does it ensure transparent data collection?
   • Does it complement clear consent processes?
   • Does it allow for the anonymisation of sensitive data?
   • Does it give you the ability to take ownership of data?
   • Will it help in easily complying with regulations like GDPR?

2. Definitely check for mobile accessibility

   Is there an app that replicates the robust desktop system for managers to stay connected across hybrid setups? This is a must for ensuring continuous oversight.

3. Check if the solution is upgrading with time

   The right tool should do more than just monitor productivity; it should continually evolve to meet the changing needs of your business and the broader industry landscape. Point being — latest technologies that can enhance productivity monitoring like AI and proactive responses regulatory laws must reflect in the solution.

4. Do test its user-friendliness and support

   The effectiveness of any employee monitoring software is significantly influenced by how easy it is to use and the quality of support provided by the vendor.

   • First off, make sure that the UI and the overall UX suit your business needs
   • Ensure that the solution fits your enterprise technology ecosystem. For instance, consider whether a cloud or on-premise solution aligns better with your existing infrastructure and security protocols.
   • Evaluate the effectiveness of the vendor in helping migrate or implement the solution. Plus, ensure their service channels are responsive and there's enough guidance for your team.

Balancing productivity, privacy, and adaptability is critical for any productivity monitoring and management endeavour. And the trends in employee monitoring technology are en route to making this easier for businesses to achieve.

Keep an eye on AI integration in particular. It's amazing how it reduces biases from judgment and makes assessments more objective, fair, and data-driven.