Using Data To Help Your Workforce Adapt To The Post-pandemic World

As we slowly move into the post-pandemic world, it’s becoming quite clear that our suspicions around the future of work were right. Remote work is here to stay, hybrid workspaces will be the norm, job-hopping and “fluidity” will redefine employee-company relationships, and skill-building will be almost mandatory for everyone.

With so many changes solidifying right before our eyes, it’s natural for so many people to have mixed feelings. They might be a little anxious about what the future of work will bring for them and how they can better adjust to the new normal. As a company, you need to help with that adaptation process to keep your team happy and have a smooth transition. But—what can you do?

As it happens with most of the strategic steps your company needs to take right now, data is the answer.

Data as the Foundation for Change

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Using data to better analyze the workforce isn’t precisely a new concept. For years, HR departments across industries have used the information they had to boost their recruitment efforts, assess team performance, and understand the reasons behind turnover figures. Yet, they never enjoyed the data analytics capabilities associated with today’s technology.

I’m sure you’re already anticipating what I’m going to say—artificial intelligence (AI) is already reshaping the way companies engage with their employees and fostering a data-driven strategy to approach workforce-related challenges. AI has been doing so by helping HR experts quickly analyze resumes, identify specific skill gaps, and map out paths to improve performance and recruitment.

Yet, AI has taken huge strides forward lately and can do something more. Working for a bairesdev.com development company, I’ve seen new algorithms that can help companies better understand their employees by providing insights about motivations, habits, moods, and desires. It might seem like something out of a sci-fi movie, but it’s real.

Now you can use AI to deepen your data strategy to inform even more parts of your decision-making, especially decisions related to the workforce. In other words, AI can help you make the most of the employee data you collect on a daily basis and even open doors for more powerful analytics.

The Workforce Challenges Waiting for AI

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Saying that AI can provide insights about moods and desires feels too broad and generic. What are the specific challenges that this technology can help you with?

One of the major workforce-related challenges is knowing how to balance remote work with in-office work. It might sound weird but even when people love working from home, most of them still want to keep going to the office some of the time. Finding the right balance can be tricky, especially because not everyone may feel the same—nor can all roles have the same approach to remote work.

Additionally, you can’t forget that we’re coming out of a deep crisis that had us locked up for long periods of time, when people lost loved ones, saw their communities being redefined, and felt the stress of uncertainty. Some of those scars are still there and you need to account for them.

Finally, there’s also the challenge of job-hopping. While people already switched jobs with a certain frequency in the pre-pandemic world, the rise of remote work and the ability to work for companies from virtually anywhere make it easier for qualified professionals to jump ship to another company when they feel the need for new things. Containing that urge and taking advantage of that phenomenon is a tricky thing to do, but you’ll have to figure out whether you want it or not.

AI to Understand the Workforce

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Fortunately, AI algorithms are becoming more and more mature, to the point where they can provide deeper actionable insights about the challenges I’ve mentioned above. Today’s AI can read brain functions to understand when your employees are more engaged, “read” people’s faces to understand their mood and emotions, analyze people’s performance in real-time, and compare predefined metrics against industry benchmarks regarding employee performance and turnover.

By using such technologies, you can better understand what your employees are going through and define laser-focused strategies to help them move forward. AI can show you that certain teams need to work at a different time of the day, or that specific individual are more productive when they are working remotely. Algorithms can even pinpoint which employees are closer to burnout!

What’s best of all is that you can help your workforce in 2 different moments. On one hand, you can leverage the quick analytic capabilities of AI to take action almost in real-time. You can suggest changes in processes, scheduling, and team confirmation as you go along, reducing stress and anxiety. On the other hand, you can start to build a comprehensive dataset with historical data to understand underlying patterns about employee behavior, which can ultimately inform you to define better employee-centric strategies for the future.

With all those possibilities, it’s becoming quite clear that sticking with past ways of working with your employees is the wrong path to take. That’s because traditional methods of engaging with employees are limited and won’t be able to show you a more multidimensional representation of your team members, especially with all the changes we’ve all been through.

In that scenario, AI is clearly the way to go. It can help you collect data about your employees and assess it with a high granularity level, to a point where you’ll be able to anticipate potential issues and correct them before they even happen. What’s more, AI can also uncover improvement opportunities to tweak your recruitment, onboarding, and overall employee experience, even paving the way for other technologies you can implement (such as augmented reality and blockchain).

It’s true that the post-pandemic world can be anxiety-inducing. But technology has already shown us it has our backs, especially when it comes to helping our employees make the transition to a new working model.