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  • Guy Brahms, Manto AI CEO

People Analytics, Employee burnout and the age of remote work

When I talk about employee burnout I like to think of this problem as having three dimensions. The first and most obvious one is that of the actual employee sentiment: working remotely increases the risk for being burned out. In fact, 58% of the American workforce feel burned out in light of the current remote work situation caused by Covid-19, According to a survey conducted in August 2020.


The second dimension is that of the management practices: we have little to no idea what’s the right way to manage employees remotely on a daily basis in a way that minimizes their chance of burnout. Many managers have yet to acquire (or worse, fundamentally lack) the skillset needed to do so.


The third dimension has to do with awareness and intelligence: put simply, limiting face to face interaction makes it harder to sense the general wellbeing of the workforce and ability of individuals to cope.


I believe people analytics has a lot to offer to help each of these dimensions, particularly the second and third (which obviously effect the first). However, I believe that in order to do so, people analytics practitioners – myself included – need somewhat of a paradigm shift.


Since remote and hybrid work are bound to aggravate the existing trend of organizations becoming less hierarchical – this should also be the emphasis for people analytics (and perhaps HR tech as a whole). Using periodic employee surveys and creating dashboards and reports for senior management and HR leadership might have been fine when managers and HRBPs “walked the halls” and had a good sense of the individual employee, but it definitely isn’t during “the new normal”.


For me, this means a few things:


Focus on lower to mid-level managers, not HR leadership:

No doubt, the link that has suffered the biggest hit when it comes to workforce management are the managers themselves. To be as relevant as possible, we need to focus on them. Helping managers gain insights that are relevant for the daily management of their employees It is by far the most crucial thing we could be doing to serve the organization right now.


Pay attention to delivery methods:

If we want to produce value to team leaders and middle managers we need to think about how they deliver their insights, not just on the content of those insights. Will managers - who are most likely overwhelmed themselves by the changes to their working habits – read hefty reports on employee engagement? Will they enter an HR-driven dashboard on a daily basis? Not likely. The more precise we are, even at the expense of being thorough, the more value we will produce.


To get a pulse check on the state of the workforce, Invest in new, passive data points:

With the risk of being cliché, I’ll refer to the famous quote by Henry Ford: “If I had asked people what they wanted, they would have said faster horses”. When talking to people analytics professionals during the past


few months, I often (not always) hear them say their solution to the loss of touch with “the ground floor” is – increase survey frequency. I think it’s rather self-evident, so I won’t go into why I find this fundamentally wrong. Instead, I’ll recommend to anyone reading these lines to think of how much data the organization generates on a daily basis that could be indicative of problems we used to be able to spot by taking a walk to the espresso machine. Possibilities are endless: from the amount of communication over time, the responsivity and initiative of those interactions, the amount of meetings per day, or the amount of code lines written each week.



Lastly, I’d like to reassure any reader that I’m putting my money where my mouth is. Manto AI, The people analytics startup I co-founded a couple of years ago, is going through this very process: shifting from a high-scale periodic analysis of employee turnover, to a continuous manager-centric burnout and wellbeing tool. It’s not an easy process, but I truly believe this is the future of people analytics.

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