Anthony Onesto presents a short, data-focused YouTube segment investigating workplace burnout using a Suzy consumer-insights survey of roughly 500 respondents. He reports higher self‑reported burnout among women (especially low‑income women earning under $25,000), more burnout in lower income brackets overall, a notable 61% of high‑income respondents citing lack of recognition as a stressor, greater reported burnout later in the day, and higher stress in high‑cost urban regions; he argues organizations should adopt targeted, data‑driven interventions (recognition, financial-wellness, tailored programs, and AI-enabled automation).
Questions this video answers
About 500 respondents.
June 20, 2024.
Females earning under $25,000 a year reported the highest level of burnout.
61%.
Later in the day (evenings) respondents reported higher levels of burnout compared with mornings.
Chapters
So May was mental health awareness month. So I wanted to explore a topic that's so pervasive these days, burnout. But I wanted to do it from a data perspective. And burnout is a growing concern in today's workforce and across the United States. Everyone, it's Anthony Honesto. And this is my Burn the box for this week, understanding workplace burnout. And so what I did is I went to Suzy. If you're not familiar, Suzy is a consumer insights platform. And I was able to survey about 500 folks around the concept of burnout. And so let's look at the numbers and then we'll dive into some of the suggestions that that were drawn out, some of those stories. So I use Suzy to analyze workload recognition and work life balance responses. And I considered a whole bunch of different variables like gender, age, and income. Did some Advanced Statistical Method, aka use ChatGPT. And here, what did we find? Well, we found when we looked at gender specifically around burnout, women consistently reported higher levels of burnout than men. We also found that notably women cited lack of recognition or work life balance more frequently than men, pointing to a need for targeted workforce or workpl interventions. So we looked at gender. Obviously saw a higher level of reported burnout by folks that identify as female than the male. Then we looked at income. We have these demographic pieces of information in Suzy, so it allows us to do some really cool advanced analysis. And what we found is the burnout. Lower income brackets face the highest levels of burnout. And you can imagine that's likely because of their financial insecurity, their lower income, they're thinking about finding finances a lot more. In contrast, while financially secure individuals with the highest income bracket reported burnout related to lack of recognition, 61% noted it as a stressor. So the insight suggests that while higher income can alleviate some stressors, it introduces other stressors. But I will tell you, let's take, take the more money. Kanye west says money isn't everything. Not having it is interplay between gender and income. So when we looked at gender and income, we saw some correlations here. Females earning under 25,000 a year reported the highest level of burnout. So females report higher level burnout income at the lower levels. Higher level income. Combine those two things. It does create a demographic that probably requires urgent attention. Interesting enough, despite higher levels of burning high income, females express significant dissatisfaction with workplace recognition. So challenging some of the common perceptions that, you know, income solved everything. But again, we'll take the income and we'll deal with those new stressors when we look at the data, we looked at also timing when people filled out and answered the survey on Susie, we looked at the timing of these things and we found found that respondents often reported higher levels of burnout later in the day, suggesting that some of the work fatigue could exacerbate some of the perceptions of burnout. So people that answered earlier in the morning reported less levels of burnout. So interesting stat there. You know, depending on when you survey folks, you're getting different levels of burnout reported. And then we looked at geography and we found that regional differences actually have an impact. So employees with high cost urban areas reported higher levels of stress than folks that are in low cost suburban areas. So, you know, further research, we could double click on that. But again, thinking about geography as a huge impact. So instead of doing all this sort of, you know, planning from an HR or company perspective in this, in, in the way that we've been doing it, which is like, hey, everyone gets the same thing. You really need to think about the different data points and the different areas of stress and where you're seeing those things. Okay, Anthony, you gave us the data. What does it all mean? Well, I think what I alluded to just before is that this highlights the need for organizations to adopt more nuanced data driven strategies. So I'm guilty in this where I would just have someone come in and talk about burnout, assuming that everyone either felt it in the same way. But that's clearly not the case. Whether it's gender or income level or even geography, work and burnout is very different in these different areas. Policies can aim to reduce workload, although that's not always the answer. I know there's a big push around the four day workweek, but as you can see, it may not apply to everyone in terms of tackling their specific burnout. Recognition and support. Great area. So those high income folks, folks that identify as female, really a great place to provide them more recognition. But also look at the vulnerable groups, the low income female groups. We may need to look at tailored wellness programs for them specifically around financial security. So it's a way of tackling all these things. And of course we have to say the word AI because then we get blessed by the AI. But can AI be an incredible facilitator of reduction of burnout by removing some of the automation of all these different tasks and all these things that allow employees to focus more on value added work? Now I know AI, it's getting better and better each day. So the opportunity to automate some of these things is going to be even greater in the future. So I think what we show here in this research is that companies can in some effective strategies. You just got to do it from a data perspective. Aligning these strategies with the specific needs of the workforce can really foster healthier and more engaged and productive workforce. It doesn't. You know the answer. Don't simply rely on just wellness training, but a real deeper look into the data, into the cultural operating systems that we have have within our companies that allow for either advanced AI tools to help with reduction recognition programs or specified burnout reducing programs in your organization. Hopefully you enjoyed the latest Burn the Box post. We'll see you next time.
