Smashing the Paradigm: Rethinking Employee Productivity in the Age of AI
We are entering a new era in technology and how it affects the workplace, which hasn’t been seen since the rise of the internet. Advances in computing have finally made AI a viable product that is helping to automate low-level tasks and even some more advanced tasks, such as coding. The World Economic Forum is even calling it the Fourth Industrial Revolution.
With this seismic shift in mind, we have to redefine productivity and how to measure it. Humans are now responsible for being the puppeteers for AI rather than the people who perform all the lower-level tasks, which frees up their time for more complex work. That means things like creativity, ideation, and project management need to fit into the productivity puzzle, too.
Measuring Productivity by More Than Input and Output
With the help of AI for basic tasks, most knowledge workers have more time for complex problem-solving tasks. According to a Deloitte survey, job roles are becoming broader and more integrated across multiple functions. A full 71% are now performing tasks outside their core job description. At the same time, Prodoscore data shows that AI tools are, in fact, boosting productivity overall and helping workers get more done.
While traditional input and output metrics still matter, which we explain in more detail here, we need to also consider business and human outcomes. Business outcomes, such as financial growth, are easy to measure, whereas human outcomes, such as employee satisfaction, are a bit tougher to nail down.
People Metrics are Vital
Measuring finances in the form of business growth, salaries, and business balance sheets is something accounting and the C-suite typically have in place. However, businesses that measure things like employee engagement and satisfaction are also likely to be more successful than those that don’t. In fact, Oxford University found that happier workers were 13% more productive, as well as more likely to stay in their jobs.
Since staff happiness has been positively tied to business growth in numerous studies, these are metrics that can no longer be ignored. Psychological happiness leads to increased teamwork, better decision-making, and reinforcing employee needs so they can thrive as complex problem-solvers.
Collaboration Figures Strongly Into “New” Productivity Metrics
Human resources solutions help to measure employee satisfaction and engagement, but how can you see how these numbers are impacting the business? The answer is in collaboration. The average knowledge worker spends 2.5 hours per day gathering information, a process that can be streamlined through collaboration and the use of AI tools.
Workers can reach out to co-workers to get information they can’t easily find on their own. That interaction also improves morale and trust and tends to boost productivity. Collaboration is measured by how many internal emails, chats and calls take place throughout the workday. Prodoscore data shows that employees who are more engaged internally tend to be better performers and less likely to leave.
In some cases, AI tools such as Gemini, Pilot, and ChatGPT can help employees gather resources faster. AI tool use can be measured by how often your team members are using those tools.
You can measure both collaboration and AI tool use with Prodoscore, our employee productivity monitoring solution.
The key ingredient in Prodoscore is its transparency and non-invasive employee monitoring; workers actively participate in the tool by being able to view their own productivity scores and trends and being given steps for improvement if they need them. This keeps employees happy and offers your business vital data on workplace productivity.
Evolving how we measure productivity will only have a positive impact on businesses. By considering internal collaboration and employee satisfaction we keep employees top of mind. Working smarter and not harder has proven to be a winning growth formula. Putting in hours for the sake of doing so only has the effect of burning out workers and inflating salary budgets. Engaging happy workers in getting meaningful work done yields much better results, and it can all be measured with Prodoscore.
