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Welcome to Mercer's podcast series on the new shape of work. I'm Kate Bravery, Mercer's talent advisory and insight leader. And today, I'm joined by Will Self. He's Mercer's workforce strategy and analytics leader, and he's co-authored with me on a new point of view, Talking About Productivity.
Will, I'm so glad you could join us today. I don't know if you're feeling the same, but everywhere I turn, whether it's talking about AI, new ways of working, the expectations on productivity are high. So I'm glad we're going to spend a bit of time today chatting about it.
I totally agree. Thank you for having me, Kate. It just feels like every conversation right now is going back to productivity in one way or another, and when it's top of mind for our clients, it means it's top of mind for us.
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Or at least we're having lots of conversations on it, but yes. And I do think we've got some ways in which we are solving the productivity equation. And as you know, this is also a topic very close to my heart. Delivery all sort of human centric productivity is a big theme in this year's global talent trends. So looking forward to having the conversation today.
All right. Well, why don't we cut straight to the chase? I think the biggest issue is these AI and automation productivity gains that executives believe are going to come through. I think our research has 2 in 4 predicting more than 30% gains.
So executives are really bullish that, wow, this is going to change the game for everyone. But on the same time, employers are just worried that what this is going to mean is they're going to have to work harder, longer, maybe not smarter, I don't know. And then, of course, HR is often caught in the middle.
They're inheriting some of those pretty big expectations, either about the productivity outlook or we've invested in this technology, and the reality of actually delivering against those goals. And that's not always the best place to be. So I think there's a lot of things that feed into that productivity equation, and on the positive side, I think we've started to understand that we're not cogs in a wheel, you know, as humans have, you know, up days and down days.
And I think we've also recognized that technology isn't the panacea that maybe it was presented to be or our vendors told us it would be. So it's clear that if we want that productivity uplift in a sustainable way, we're going to need to think a little bit differently about it. Maybe you can share your views about what's feeding that productivity equation today, and how broad are opportunities to be if we really want to have an impact.
I think that's great, and I think the first thing where we have to start is with human, right, and the sustainability part. Yes, we want productivity gains, but we also don't want to lose our workforce trying to get those productivity gains, right? I don't see a lot of context where employers can simply replace human workers with AI or other forms of technology at scale without there being real repercussions that often aren't intended.
And some of this is caused by the fact that generative AI has arrived at a specific moment in time when other dynamics are already in play. Remember that the pandemic isn't that far behind us at this point, and the nature of work itself has undergone a significant evolution over the past few years. We lived through it. How we work itself is different now.
Physical spaces, like the office, just don't have the same gravity that they had prepandemic, which has unlocked unprecedented opportunities to inject flexibility into the workplace. People work in different locations. They also increasingly work at different times, with an explosion of hiring across time zones, and even countries, along with growing adoption and acceptance of asynchronous work. On top of that, the macroeconomic environment has been a roller coaster, continual uncertainty, stress, and both workers and employers are feeling that.
It feels like we hear about new layoffs every day and more companies are trying to do more with less. We hear that all the time from our clients, and that creates an atmosphere where fear of change and fear of the future rule, and where companies are increasingly looking to well-being programs as drivers of productivity. I know it's not a surprise to you, Kate, that our research shows that almost 83% of employees are at risk of burnout.
That's a real problem as we think about driving productivity gains in the future. And so all of this is the context that we're walking into when we start talking about AI or other productivity drivers. And it shows why we need a delicate hand when we're thinking about navigating these changes. We need to bring our workforce along with us on these productivity journeys so that we can create sustainable change and don't accidentally undermine larger goals.
Yeah, I agree with you. I think sustainability-- sustainable change begs us to think differently about the productivity equation and update it for a new era. You called out lots of things there, and I love the fact that your thoughts around the pandemic is not that far behind us. We have really short memories.
We do.
And it changes shape how we work. It also changed people's expectations of what they wanted out of their life. You know, we all use that period to do a lot of introspection, and I think that's also playing into the equation here.
But I am also hearing that as we've accelerated out of that pandemic pawns, the load on people from new technology, new ways of working, new expectations, has become exhausting. And so I am interested on what is really giving a productivity lift, and what maybe is actually contributing to those burnout stats that you mentioned.
I love how you just brace that, and it's so true. We've all experienced when more technology just shifts work around or takes work off of one person's plate but adds it to somebody else's. I think about in the context, when we start putting in HRS systems, we always talk about self service as this wonderful panacea to overwork.
But what it just means is that we're moving work from an HR business partner onto a business manager, and there's someone out there actually doing the self servicing with the new system, right. But, well executed AI can be different from this story, and that's where I get really excited about the intersection between AI and larger productivity conversations.
It really can remove work entirely and allow processes to move faster, allow people to be more productive themselves. Let me give you an example that hits close to home. At Mercer, we recently introduced a new offering called PAYAI. It's a tool powered by AI that helps recruiters and hiring managers set the right pay for new hires in a way that ensures consistency, equity, fairness across the organization.
What we found when we talk to clients was that they had been investing a lot over the last couple of years into improving candidate experiences, really thinking deliberately about their talent acquisition funnel, taking out unnecessary points of friction, making things easier and faster for everyone. But we kept hearing that these processes fell apart at a specific moment when it was time to actually give an offer to the candidate.
Everything would go really well and then all of a sudden, the brakes would come on. And people needed to pull in additional stakeholders. They needed, not only the recruiter and the hiring manager, but their bosses, sometimes their boss's bosses. They were pulling in the compensation team. They were pulling in HR business partners.
They were having a lot of meetings to get alignment. And what that meant was, you know, number one, and probably most importantly, the candidate experience suddenly went off the rails. But also, all of this cost a lot, right. It costs a lot in time, it costs a lot in mindshare. And so the process just didn't work great for anyone.
With PAYAI, with this kind of AI first process change, clients were suddenly allowed to make-- allowed the AI to make the pay decision within human oversight and move straight to an offer, bypassing all of these extra stakeholder conversations, bypassing extra meetings, actually resulting in faster and easier work.
I mean, that's the goal here when we're talking about higher productivity with AI, right? I know you talk to clients all the time, too. Do you have any favorite examples of where we've seen actual meaningful productivity gains from AI and not just hype?
I do. I think one that we're probably most familiar with is the way AI has being used for talent intelligence, so understanding what skills you have in the organization. Or AI is being used within assessment to speed up how reports are written or information is integrated, or to nudge people to take development and careers that's tailored for them, based on what you know about them.
So I see a lot in that space. But your comments there also made me think about a word of caution, because you talk about these productivity opportunities we have when we bypass stakeholders. And I think that's really tempting and I think that's one of the risks we have to be careful of because AI can bring as an efficiency gain, but at what cost?
And so I certainly, you know, as an organization psychologist with an assessment background, I worry about that a lot because as we start to lean on some of these tools for decisions about our health, our wealth, our career, these things that really do change our life trajectories. We've got to make sure that the human stays in front. I know a lot that's been said on that.
So that was sort of just triggered in mind. But well, you know, you've talked about our own organization. I also think we've got our own large language model in house. We've seen productivity gains from that, you know, using it for article creation, searching our thought leadership to find trending insights on something, responding to government requests for information and more increasingly, information about our own cybersecurity and AI ethical practices.
Those requests are being automated. Create FAQs when we launch a new HR product. Even summarizing meetings or even summarizing this. I mean, we've got RJ AI tool, you know, summarizing that as we go. I think all of that, in aggregate, must be giving us a bit of a productivity lift.
But I do know that it's taken us about a year to get adoption up, even though we had made that early decision to bring a large language model insert, it wasn't until we had our senior leaders talking about it, making it an expectation, sharing what percentage, in what businesses we're using it, did we really start seeing people flock to it.
So I do believe that getting that productivity lift is a lot about people's readiness to actually experiment. I also was chatting to a client just last week who I think he's getting a bigger productivity lift. It's in a very technical area. It's in the chemical space, which I think we know is a bit of pioneer in this space. And they've brought on board like 8 to 12 very specific small language models because of that technical specialism.
They said it really well to me. They said, I don't want the MBA answer, the US MBA answer that I get from ChatGPT. I want the P in physics as my partner. And they have really seen a lift as they've also moved internally from chat bots to agents. And they've also opened up their models so that everyone can think of what ways they want productivity assistant.
I think there are about 1,000 projects that have happened and but that I think is really at the bleeding edge. And I still believe that we've got a lot of way to go, not just in using AI, to improve productivity. So what parts of our work today could be better done by machines versus humans and then redesigning that work?
But we've also got an opportunity to say, if it can tell us early warning signs when people do have fatigue, or better customize a report for them, or say, Kate to your personality style when you're working with Will, and you should adapt it that way.
Some of these ways, which I think will make us work better together, more creatively, more personalized, I think that's where we might even get a bigger lift, more from innovation and from better working together, rather than just the productivity gains we're talking about now. But I'm getting ahead of myself.
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You know, as you also know, you quoted global talent trends research earlier. We did ask, you know, what holds you back in driving up productivity to gains? And very, very few said, it's not having access to a large language model.
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And the number one reason for people saying that their productivity is depleted was what you mentioned before. Too much busy work. Number two, I think, if I remember right, it was not enough thinking time, then I think it was ineffective structures and unsustainable workloads.
So, if those are the things depleting productivity, even though there's this shiny opportunity over here, we're not even going to have the capacity to think about it, let alone adopt it. You know, fix some of this stuff over here. I don't know. What are your thoughts on that?
I love the way you just spread that out, because you're right. I mean, when we look back at history, technology has never been the panacea by itself. There's always this bigger question about how it's being used and how we look deeper into ourselves and how we work, how we come together, our processes, in order to make real change sustainable.
And in this situation, I think it's important to look really beyond the technology, even beyond the job itself, to look at the individual worker and think about what the work itself looks like. For example, I'm increasingly being asked by organizations to combine traditional strategic workforce planning that they're often very familiar with and comfortable with, with a bigger attempt to redesign the work itself, and to go deeper into that organization.
And this is relevant right now, whether you're talking about AI or not. I mean, there are plenty of situations where we're talking about increasing productivity, but AI is not necessarily top of mind or the top of the conversation. Let me give you an example. This combination bringing together, not just strategic workforce planning, but also rethinking work. Redesigning work.
It's been really, really popular with our healthcare clients lately. When you look at the healthcare labor market, you see the demand for healthcare workers, I mean, it just keeps growing. It never goes down. And while the number of healthcare workers has been increasing in the labor market, especially after the pandemic, it's just not growing nearly fast enough to keep up with demand, which means that no matter how you run the numbers, the math just doesn't work. It doesn't work today.
It won't work in three years. It won't work in five years. There's this intractable collision here between supply and demand. And that's especially true for in-demand healthcare roles. You know, nurses, medical assistants, home health aides. This matters means that no matter how many workers you want to hire, you're ready to hire in health care, you simply may not be able to find enough qualified candidates in the market.
We've worked with a number of healthcare clients to close that gap by fundamentally rethinking jobs. That often means allowing health professionals to work at, the way we phrase it is, the top of their license. For example, when we redesign a nurse's job, we look at each task being done by the nurse and ask, does this work have to be done by a nurse?
The result is that we're able to allow nurses to focus on what they uniquely contribute at the top of their license and look to other less constrained labor markets to find employees to take on other parts of the nurse's job. Not only does this approach allow us to circumvent some labor market constraints, but through automation, AI, offshoring, outsourcing, we're able to unlock substantial productivity lifts.
And the end result is not just that employers are happier because productivity goes up, but it actually makes the job better for the people who are in it. We're able to take seriously how they spend their days, the things they like about their job, the things they don't like about their job, and we're able to think about alternatives for doing the mundane, repetitive, day to day tasks that we know eat up so much of our actual productive time.
What I really like about that is not just, let's-- got this opportunity to actually rethink how value is created today and who creates the value, but we can actually think about making the jobs more enjoyable and more relative. If we're trying to solve that or trying to compete in the talent wars where, as you say, the math doesn't work, that's got to be part of the solution as well.
All right. So we've established that, if we're going to move forward, we actually need-- if we want to redesign the work, we've got to redesign the work. And that's not just looking at what tasks humans and machines do best, but it might also demand us to rethink the value of human contribution.
And I think that's really exciting because I think if we get it right, our jobs aren't just to get more interesting, but we'll also have a pathway to doing more higher value work. But it does really challenge how we think about measuring productivity today as we combine that.
And to me, it makes me think we need to quicken the pace around skills development at the same time as tech development. But, yeah, maybe you can share a little bit about how companies are thinking about measuring productivity today, and what might need to change.
You know, it's funny you say that because we are really good at talking about productivity at the organizational level. It's a pretty straightforward conversation. You can look at metrics like revenue per employee, and you can start to understand that aggregate picture of productivity.
But at the same time, we are quite bad at thinking about productivity at the individual level. I mean, think about the debates that emerged around companies wanting to return to the office. We looked at surveys. They consistently showed that most employees wanted more flexibility in where they worked.
And they justified that by saying that they felt they had actually become more productive working from home. But then when you talk to managers, they argued the opposite. They said that productivity was dropping. They said that out of sight, out of mind. When people left the workplace, the work stopped happening.
And the reality is, neither side brought great data to the conversation. It's almost like they were just yelling past each other. And what that showed to me is, number one, a lot of us don't have a great point of view on what it means for an individual to be productive and how to measure and chart that productivity over time.
And it also showed that we're not necessarily training our managers to think about productivity or performance management through a lens of productivity, because a lot of our managers have shown their cards. They don't know how to even talk about productivity unless they can watch their employees doing the work and can judge what they're seeing as they watch them at their desk. And that just came to a head recently, right?
Yeah, I mean, you really hit the nail on the head there because it isn't just an experiment. It's also given as real insight into whether there's maybe some gaps in leadership and management today. Because despite what we might say, the reality is as uncovered level, one of the things we did do in global talent trends this year, we asked companies, how many of you are moving towards more flexible working and how many of you are moving towards more on the side?
The ones that are moving more flexible working, the number one reason was productivity gains. The ones that were moving on site was because managers struggle to manage across time bound borders, cultural borders, remote, hybrid. And then the second one was just some challenges around cyber. But, to your point, maybe we need to focus our attention there as opposed to the great swings that we've seen there.
But that is fascinating and I think you're right. I mean, I don't know about you, but I'm constantly saying to myself, am I doing busy work or is this unproductive productivity? So what approaches are you seeing on the metrics landscape? I'm certainly seeing a lot more dashboards.
I mean, on the one hand, I get excited that they include some healthcare indicators like never before. So that for me feels like we're heading in the right direction of a more human view, but what are you seeing?
Yeah, I like that and I don't want to undervalue how hard this shift in conversation is. Talking about productivity used to be a lot easier. When we think about the way work has evolved, when we think about knowledge work, it's not straightforward to answer a question about what does productivity even mean.
How do you talk about how a staff accountant contributes to the bottom line for their company, an HR manager? These aren't clear cut connections. They require some harder work than they did in the past. When we were talking about things that could be easily counted, number of sales made, number of widgets produced, then it was just a clean line between tracking the work, tracking productivity at the individual level and then aggregating it up to a company.
But knowledge work, the types of things that so many of us spend our time doing, are just a lot harder to put your finger on. I think part of the response to that is thinking broader about what productivity means. And you're right, we're seeing executive dashboards or dashboards popping up all over the place, and they're including metrics that no one would have even thought about five years ago.
The questions like well-being, trying to get leading indicators like, how many people have gone on short term disability lately? How many people are working overtime? These well-being metrics that, again, rarely were part of the same conversation as productivity. They now are because we know that how people feel, and how they're showing up to work, and what's happening to them outside of work matters in terms of their ability to show up and do their job well.
And so I think the conversation has expanded. The other side of this equation, I think though, is the complexity of the work to figure out metrics in the first place, and a lot of the work that I'm doing with clients right now. When a client comes in and says, we want to measure productivity better, or we want to think about how we can better support our employees, or we want to draw more clean lines between workforce decisions we're making and financial implications for our company's performance.
The way we're going about it is by really thinking about complex statistical modeling. How can we connect specific workforce factors to real business outcomes, and how can we do it in a quantitative way that brings the data to the conversation? Tells us how our levers actually stack up and lets us pretty reliably what's going to happen if we pull those workforce levers.
In the past, I think there was a lot of trial and error. We would change something about the workforce and then we would see what happened. But the reality is, we can be much more intentional and much more forward looking at how we think about the workforce system. And when I'm looking at best in class employers, that's what they're doing right now.
And the other part that makes me excited about this, part of it is the agency. It makes it feel so much more doable. If you have a question like, how do we increase short term revenue, or how do we cut costs in the short run? If you understand the productivity equation, if you understand your levers and the effects they have, the answer to that feels very reachable.
But the bigger conversation on that, I think, is where HR fits within the organization? And I think historically, we often looked at HR, HR practitioners, we often looked at ourselves as cost centers. We just cost money. We were responsible for the personnel line item in the budget and that line item is huge.
But what I'm seeing increasingly as HR practitioners are becoming more sophisticated in how they think about productivity and the workforce role in driving productivity, is that they're actually casting themselves as profit drivers or at least profit maximizers, which is a completely different way to show up to the table and really empowers HR to think about their role in achieving a larger long term corporate strategy. And I don't know about you, but to me, that's the conversation shift I've been waiting for for a long time.
Yeah, I couldn't agree with you more. But it fits so well with really identifying, not just how value is created in the business today, but how value is created in the business tomorrow. And then, coming to those conversations with executive, with different scenario plans, and how maybe with a different size shape skill set of the workforce, you can still deliver those outputs.
And we've talked about that for a long time, but we haven't had the tools, I think, to do that at an enterprise level before. I mean, I think we've harped on a lot about, your data hygiene has got to be there because if you don't have the data, it's pretty tough. But actually, some of that was a big kind of computational lift.
And I think that's another way that I'm seeing AI help with those conversations, allowing HR to have the more strategic conversation, which is a lot more exciting and interesting. Plus, HR wants to be on the side of saving money for the executives, delivering on the promise of their tech and making employees work more joyous.
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Absolutely. I mean, we have to keep going back to people.
Yeah, and of course they're all related. But getting it all right together, I think is a shift and I think you already really called that out. And I do love the fact that many of the clients that we're working with are asking individuals to think about how they can disrupt their job, how it can be made more effective.
But I also love the fact is, when you do some of that deep analytics about what actually shifted the needle and feed that back to them, that's really interesting because we're not always the best judges of our own productivity. Will, I just noticed there that you've got one of these Aurora rings as well. And I think, again, it's another piece of feedback on how we spend our time, what adds value, what affects our own health and well being.
All right. Penultimate question because we are absolutely at time. A big theme, I think, cutting through the paper that we've just got out there is around human-centric productivity. I find the human-centric word, and I contribute to this, is an overused word. But what is that for you mean actually in practice? So if you're an HR practitioner listening to this call, what do they need to do differently, or how can they unlock that for their workforce?
I mean, I think it's important to just say, full stop. AI is about people as much as it is about technology, and productivity gains from AI depend on people being able to navigate change management, process evolution, tool adoption, like you mentioned before, and really the mitigation of people risk because people bring risk to these systems that go beyond the technology risk, the cyber risk.
It's important that businesses govern AI responsibly. That just is a given, I think, at this point. But they also have to foster a culture of productivity and well being, and proves that those things go well together, that you can drive productivity and well being and that it's not an either/or conversation. And you have to consider how AI can empower diverse teams and drive sustainable business practices over time. And this is all a good thing.
A lot of research actually suggests that human in the loop AI, so combining the best of the human brain with the best of AI, actually can outperform pure human or pure AI approaches in many situations.
So again, I feel like we've gone back to the same theme over and over again, which is about myth-busting, that some of these kind of dualities that we assume are false, that we actually can break that down. And it's about bringing together two kind of opposing or different perspectives and being better for it.
Yeah, and I think we've known that for a while, even from back in the deep blue chess days, that actually if you combine the two together, you actually end up with amplified intelligence and a new way forward. I said that was the last question, but I am curious since I've got you. If we were to zoom, let's say, to 2030, how do you think measuring productivity will look different to the way it looks today?
You know, I think you nailed it when you mentioned our sleep rings, right? I think we're going to see just much more organic fusion between the human and the AI in these discussions. I think productivity conversations of the future will talk about the productivity of humans enhanced by AI instead of it being either or conversation.
Imagine a world where AI helps us throughout the day. It nudges us to be more productive. It gives us a second set of eyes on our work throughout the day. It helps us navigate org charts that can be really complicated when you think about wanting collaborate, right?
Yeah.
It ultimately helps us show up as our best selves. We often use the phrase, unlocking the productivity of one here at Mercer, but that's what this is about. How do we use AI? How do we use other productivity gains in the workplace to really allow us to show up with more power, more multiplicative impact as a single individual? And I think that's a really optimistic view of the future, and really how all of these conversations come together.
And I love that. The power of one and its knock-on effect. Well, you've certainly, I think, had an impact on conversation with me today and hopefully with on our listeners. I love that phrase you just mentioned there about organic fusion of humans and AI. I hadn't heard that before. I love that. I'm just a couple of my takeaways.
I think you said first, let's take a broad view of what depletes and drives productivity today. It's not linear equation. Let's have a look at where value is actually being created or maybe where it's going to be created today, and that might allow us to think differently about who does that work.
I think that allows unification and some of these other trending topics. And I love your comment about resetting strategic workforce planning by maybe combining it by work design at the outset, and think a little differently around that. I think that's great. And then at the end here, you've talked about, let's take this once in a lifetime opportunity to redesign work, to actually redesign it around what people like and enjoy, and where they want to go.
And I think that's one of the most exciting things that you showed. Will, thank you so much for joining today. It's been great. We are over time, and I think your productivity point of view is actually up on the mercer.com website. So if people are thirsty for more, they can take a look there.
And everyone, thank you so much for tuning in today. I've certainly enjoyed this conversation. I hope you enjoyed it as much as me. If you're interested in this topic or others associated with the new shaper work series, you'll find them all on mercer.com, as along with the productivity point of view and the global talent trends study that we referenced throughout.
And obviously, link with Will and I. If you want to continue the conversation, as you can hear, we're pretty passionate about the topic. Thanks, everyone for joining. Thank you, Will, for today. Wish you all the great rest of day.
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