Overview

• Theresia Hermes introduces the topic of the 2025 Global Human Capital Trends report by Deloitte, focusing on turning tensions into triumphs.
• Sue Cantrell provides background on the report, mentioning it is the longest running longitudinal research study in human capital.
• The report surveyed over 13,000 respondents, including 2000 executives across 93 countries.
• Sue Cantrell explains the core idea of focusing on both business and human outcomes, which creates a multiplier effect on business outcomes.

Tensions in the workplace

• Sue Cantrell discusses the uncertain environment leaders face, highlighting tensions such as using AI for automation versus augmentation.
• Other tensions include providing personalized experiences versus standardization, agility versus stability, and outcomes versus outputs.
• Leaders struggle to make decisions due to these tensions, and the key is to find a balance and do both simultaneously.
• The report organizes trends into three buckets: work, workforce, and organizational culture.

Change management and human outcomes

• Theresia Hermes emphasizes the importance of considering both business and human outcomes in change management.
• She highlights the need for buy-in from employees to ensure the success of business outcomes.
• The concept of agility is introduced, combining stability and agility, and the need for leaders to provide clarity while asking workers to adapt.
• Sue Cantrell provides examples of how organizations can provide stability and agility, such as through career mapping and skills development.

Work redesign and slack

• Sue Cantrell discusses the trend of work redesign to eliminate busy work and unlock worker capacity.
• The concept of slack is introduced, where organizations allocate a portion of work to be undedicated time for creativity and innovation.
• Theresia Hermes adds that talent strategies should focus on automating tasks to free up time for employees to innovate.
• The importance of not filling slack time with more busy work is emphasized.

Closing the experience gap

• Sue Cantrell introduces the trend of closing the experience gap, where entry-level roles require more experience than entry-level workers have.
• The gap is due to tasks being automated and organizations pushing down responsibilities to lower levels.
• Solutions include redefining experience requirements, bringing back apprenticeship programs, and using AI for coaching.
• Theresia Hermes adds that critical thinking skills are crucial for employees to effectively use AI.

New tech and workforce tech

• Sue Cantrell discusses the trend of new tech and workforce tech, highlighting the challenge of getting value out of tech investments.
• The landscape has changed with hundreds of tech players and diverse use cases, making it difficult to define metrics and ROI.
• Organizations struggle with unrealistic business cases and the inability to define metrics.
• Solutions include expanding metrics, taking a portfolio approach, and involving multiple stakeholders.

AI’s impact on worker experience

• Sue Cantrell discusses how AI is now seen as a colleague by six in ten workers, impacting the worker experience.
• The trend suggests revisiting the employee value proposition to account for AI’s impact.
• AI’s evolution from automation to augmentation to collaboration is highlighted.
• The potential silent impacts of AI, such as decreased autonomy and cognitive decline, are discussed.

Motivation and human performance

• Sue Cantrell introduces the trend of motivation and human performance, emphasizing the importance of understanding what drives behavior.
• Intrinsic motivations, such as achievement and helping others, are discussed.
• Most workers know what motivates them, but few believe their leadership or organization understands their motivations.
• Solutions include manager-driven approaches, modular choices, and sophisticated tech-driven approaches like neuro avatars.

Reinventing performance management

• Sue Cantrell discusses the trend of reinventing performance management, noting that workers still hate it despite efforts to improve it.
• The conclusion is that performance management will never go away but should be part of a broader approach to improving human performance.
• The trend suggests shifting from a single HR process to engineering human performance, which includes workplace design, coaching, and talent management practices.
• Theresia Hermes adds that performance management remains important for internal mobility and retention.

Role of managers in the digital age

• Sue Cantrell discusses the role of managers in the digital age, noting the debate between eliminating middle managers and reinventing them.
• Managers need to continue as coaches, developers, and motivators, and organizations can support them with AI and other tools.
• Managers also need to decide who does the work, whether it’s employees, borrowed talent, or AI, and redesign work accordingly.
• Managers should be catalysts for agility and problem-solving, and organizations need to support them in these roles.

Key actions for talent acquisition leaders

• Sue Cantrell provides three key actions for talent acquisition leaders:
• Communicate the employee value proposition for the age of AI to candidates.
• Rethink years of experience in hiring algorithms.
• Consider a new value case for talent acquisition technology, like the one provided by Eightfold.
• Theresia Hermes adds the importance of clarity in communicating the value of initiatives to employees.

Theresia Hermes 0:24 So I’m very excited for this conversation about the 2025 Global Human Capital Trends report. Deloitte publishes it every year, and this year has been around turning tensions into triumphs. Tell us a little bit about what those trends you’re seeing are, and how we can turn them into triumphs?

Sue Cantrell 0:48 Yeah, thank you. So just a little bit about this research. I don’t know, have any of you read this Deloitte Human Capital Trends report? We are proud to say that they’re the longest-running longitudinal research study in our field in human capital ever. So, thank you. For this year, we did a survey of over 13,000 respondents, including 2,000 executives across 93 countries. So I just wanted to give you a little bit of background about our report. We’re actually now furiously writing next year’s report that will be coming out in March.

So yes, this year was about turning tensions into triumphs, and one of our core ideas that was backed by research is, you can see this equation on the screen. Most organizations focus on business outcomes, right? Cost optimization, efficiency, top-line growth, etc. We found through our research that if you also focus on human outcomes — which is all about creating value for the worker, things like greater employability, skill development and growth, health and well-being — then it actually creates a multiplier effect, and they’re mutually reinforcing, so it has an impact on business outcomes. You’ll see that equation run through most of our trends.

And then one of the other key pieces of this year’s report that you just alluded to—turning tensions into triumphs. It’s no surprise today that we are in an uncertain environment. It’s growing increasingly uncertain by the day, and in our research, we uncovered that leaders are really struggling with these, for lack of a better word, tensions. Some examples up here on the slide are things like, “Do I use AI to automate, or do I use it to augment?” What is the tension between providing a personalized experience—for example, in talent acquisition and in my recruiting experience—versus standardization and the efficiencies that can be gained? Agility versus stability, outcomes versus outputs, empowerment versus control… The list goes on.

What we found was, in this uncertain environment, leaders are struggling to make decisions, especially around these tensions. We found it isn’t so much about picking a side; it’s about finding a balance and doing both at the same time. So that’s how you turn tensions into triumphs. Throughout our chapters, we come back to this notion and point out the tensions. So I’m going to take a whirlwind through some of our trends. We organize them into three buckets: two under work, three under workforce, and three under organizational culture. And I will just briefly give you an introduction to them.

Theresia Hermes 3:49 Today, well, we’re jumping into work, but before we do that, I do want to point something out. In this conference, we spoke a lot about change management, and I think what you just mentioned in the beginning about the human outcome and the business outcome is so important. When we speak about change, we really need to think about what we want to get out of it, not just for the business, but for the human. I know we speak more about the uncertainty. If we’re not getting the buy-in of why we’re doing it and that it will be beneficial for them as well—for example, they are able to upskill, they’re getting themselves future-ready for whatever job they’re doing right now that will help them with the next step—I think you get that hesitation. And if you don’t have the buy-in, there’s no business outcome and there’s no multiplier. So I love that you have brought that perspective in. Because again, I think it’s always about bottom-up and top-down, right? What’s really for the business, but also for the human itself, the employee.

We are jumping in here at work, and I loved that you created a new word, ‘stagility’, and I’ll let you define that in a second. But the tension you just described… We live in a very, very uncertain world, and workers often look for confidence or clarity, and sometimes leaders can’t even give that. At the same time, leaders ask them, “Stay agile. Adapt to the new changes.” So talk to us a little bit about what ‘stagility’ means and how it impacts the leaders and the workers today.

Sue Cantrell 5:25 Yeah, sure. So obviously it’s a combination of stability and agility, right? And you’ll see on the slide the tension point. Leaders in this uncertain environment, they know we’ve got to change. We have to change fast. I mean, you’ve all probably seen the stats that the average employee has more than 10 enterprise changes a year hitting them, up from two in 2016. So leaders need agility. 85% say they want more agile work. They’ve got to respond in a fast-changing environment. Yet, think about workers, think about yourself. When I think about myself, I have a very fundamental human need just to stand on some stable ground for my sense of identity, to have clarity, as you pointed out, of knowing where to go, what comes next. So 75% of workers want stability. So what do we do about this? How do we resolve this? And you can see some data points contrasting workers with leaders also on the slide, that leaders want more frequent changes in where and when work is done compared to workers.

Theresia Hermes 6:38 That just made me realize, I think there is a good translation for it as well, if we think about our own careers, but also for our employees. 10 years ago, the career ladder, the career line, was much more clearly defined, but these days, obviously it’s not one job. You go from junior to senior and all of a sudden you become the CEO. That’s not true anymore. Yesterday, we spoke a lot about how people are moving, maybe in different domains, getting more experience and then going up again. And one of the things we work with many organizations, of course, as well, is the ability to even understand what roles there are.

So with Eightfold, we have the possibility to map out the traditional way, but also, for example, shift and say, “There’s another possibility for you.” Just a real-world example: one of my team members started at Eightfold as a recruiter for the PubSec sector, and through some projects, she was exposed to the product side. How can we get the recruiter perspective into our solutions? She gained those skills within the system, which then six months later, after she also had a mentor, recommended a customer success job. I think that gives the employees more stability of where they can grow, but still allows them to be agile and open to other jobs.

Sue Cantrell 8:02 It’s such a great example, and Eightfold is… I can’t think of a more powerful example of being able to enable this. We talk about old anchors and new anchors, and anchors provide that sense of stability. So the old anchors would be, “Well, I have a linear career path, as you pointed out. I know where I’m going,” or “I have a job with tasks.” The new anchors, to your point, could be, “I have skills that I can deploy in many different places. I have visibility because of technology, like Eightfold’s, of possibilities of where I could go in a networked organization.” So the whole idea in this trend is to focus on communicating what we call new anchors to workers.

Another couple of examples would be, how do we define work? Well, typically, it’s done by jobs. Well, maybe we need to think about defining it in terms of outcomes or the value we produce. Or typically, we thought of work as being done by employees. Today, it’s done by AI, by employees, by contingent workers, all in networked teams. But I think a lot of it is clarity and helping workers understand these new anchors so that they have this sense of solid ground to stand on, but it’s new ground.

Theresia Hermes 9:25 I couldn’t agree more, and I don’t want to jump ahead too much, but you already saw some of the predictions. There’s something of an experience gap we see today, and I think we have some solutions there as well. But there is, of course, opportunity with the systems we have today and the way we are doing the work today, that you can connect workers within your organization for work which might not be traditionally associated with the job description, to develop those skills.

Sue Cantrell 9:51 Well, I might go into the next trend, yes, and then we’ll get to the experience gap. So we jokingly call this trend “When work gets in the way of work.” We all know that… we found an interesting study that when somebody asks, “How are you doing at work?” do you know what the most common response is? Any guesses? Fine? Anything else?

Theresia Hermes 10:22 What’d she say? “Living the dream.”

Sue Cantrell 10:24 “Living the dream.” It’s “busy, busy, busy.” We’re all doing busy work. John Maynard Keynes said decades ago, we were all going to be living 15-hour workweeks by this time and age, and we’re working harder than ever. We have AI; it’s supposed to be making our work easier and simpler. Well, we’re busy, busy, busy, busier than ever. So some of the data from our study: 41% of daily work is spent on non-value-added tasks. And only 22% say their organization is really effective at finding ways to simplify work. I can attest to this myself. I really struggle with this. I think most people do.

So, this trend is all about how do we unlock that worker capacity? AI can help, if used in the right way. We talk about zero-basing work, like zero-based budgeting, if any of you have gone through an exercise like that, where you start with a clean sheet, and then you figure out what the most valuable work is. And then you do that every year. So a lot of it is about work redesign. It’s about involving workers. Who knows the work better than workers themselves? Yet you can see from our slide, workers do not feel empowered to provide feedback on how to simplify work or make it more valuable.

And then, that’s all about identifying places to eliminate busy work. But then once you have some slack, what happens? Usually, you have busyness creep. It comes right back at you. So there’s a mindset shift that needs to be made around valuing what we call slack. And no, slack does not equal slacker. It’s all about having a little bit of time in your day to think deeply, to be creative, to adjust, to change. There was one organization we studied that only allocates 80% of work to their teams, and 20% is protected to be undedicated time. That’s a bit of a shocker, but we, in our research, really found that having a little bit of slack… it’s like a rope. If you have no slack in it, it’s going to fray and it might break.

Theresia Hermes 12:51 Well, we say that children become very creative if they’re bored, right? That’s right, and I don’t think we’re bored at work. We have so much to do. And AI again, should give us some of that time back. I think the hope is that we do have more time for creativity. Because I don’t think anyone sits here and says, “I could finish my work in four days and be out.” You would start projects and innovations which might not have come from different places. And of course, when you cross different employees from different job functions, that’s where innovation can really come and live.

I think when we apply this to talent strategy, this is also what everybody is trying to look at. If you think about recruitment processes, one of our customers, Bimbo Bakeries, really looked at what tasks we can just automate and don’t need to do. And I think you can think of plenty, like moving them through different stages, getting feedback faster, those kinds of things. But then, of course, also what we just spoke about before: Boston Scientific, for example, really wanted to simplify generating leads. Like, how can I find within my workforce who are the right people, but also who might be the right people in my talent pool already? Those, I think, are all examples where we can automate and augment to help them be even better and do their job in a much deeper way than they could previously.

Sue Cantrell 14:19 100%, and the key is not to fill it up with more busy work.

Theresia Hermes 14:23 Yes, we all know that. Which comes back to: what are the business outcomes? What are the human outcomes? As you said in the beginning. Move on to the next prediction.

Sue Cantrell 14:36 Yes, so closing the experience gap, which you mentioned earlier. This one’s interesting. When you think about entry-level jobs or new hires, we have a conundrum. 66% of leaders say their recent hires aren’t fully prepared, and most cite they lack experience. So we’re having a hard time hiring the right people, yet 61% of employers have increased their experience requirements. Most entry-level roles now require two to five years of experience, and how does a 22-year-old graduating from college get that experience? So we’re raising the issue that maybe the big gap is not so much the skills gap, but the experience gap.

Why is this happening? One of the reasons is that entry-level roles—think about them. Their tasks are increasingly getting automated. Organizations are, in the name of cost and efficiency, pushing down responsibilities to lower levels of the organization. So they’re asking more from their entry-level roles. Some people are even talking about, instead of pyramid-shaped organizations, switching to diamond-shaped organizations. So we’re asking far more from our entry-level talent. We have an issue here.

So the question becomes, how do we solve this experience gap? For talent acquisition leaders, I’d be interested to hear how you are working on it. One of the first ways is just redefining what we mean by “years of experience” in talent acquisition when we hire. Is it the number of years of directly related experience? Is that really what we’re looking for? Maybe, instead, what we found from our research is that what we really mean by that is the application of human capabilities—things like the ability to learn, collaborate, professionalism (which is something that we hear from a lot of organizations that entry-level talent is lacking), and technical and functional skills in real-world contexts. So one of the things we can do is eliminate “direct number of years of experience” to help solve this, because there’s a whole lot of talent out there that could be very useful if we expanded our view.

Also, we need to rethink how we learn and grow talent. So yes, we’re automating tasks with AI. Maybe we need to not do that for some of our entry-level roles, so that we provide a training ground. Maybe we need to make conscious decisions about that. Can we bring back apprenticeship programs, mentorship programs, reverse mentoring, team compositions where we have experienced workers working with less-experienced workers? So there’s a whole development piece, and then also AI can help. One of our favorite case studies was Amazon, where they specifically created an AI coach for entry-level talent. It was trained on their own internal data, and that coach sat with entry-level workers throughout the day and provided them coaching based on their own data of what they were working on and the kinds of things Amazon felt like was important.

Theresia Hermes 17:52 I love that example. I do feel for early-career right now, because they are also not going into the office, so they cannot mirror or pick up on their colleagues. And how do you get feedback? One of the other things I keep saying is, if we are increasing AI skills, another skill we really need to focus on is critical thinking. “What I’m putting in there… does it make sense?” and “What the outcome is… does it make sense?” If we’re not training the young workers today to really think critically about it, how can they use AI for the future, for your organization?

So I love that example, because it might be able to bridge that gap where people are not in the office, they’re not getting the exposure, or the practice with those entry-level tasks, which are right now being automated. So I do love that. And I think there’s also, of course, the question about, as you said, mentoring, but also inferred skills, right? That level of experience, not being that narrow, and understanding what similar skills can be applicable. We have one organization, Ericsson, who is really deeply ingrained in those inferred skills, because there are a lot of transferable skills, also from the entry-level talent. And again, our entry-level talent becomes our talent pool in the future. Obviously, especially if you also look at Europe with the demographic changes, those needs will come even faster, and we will see this eventually in the US as well.

Sue Cantrell 19:18 Absolutely. We have more.

Theresia Hermes 19:21 More trends for you. Okay, move us forward.

Sue Cantrell 19:24 Okay, new tech. This is all about tech, mostly what we call workforce and work tech—so things in our HR space, but also work tech, so think of collaboration tools and the like. Here’s the challenge in this trend: How do we get value out of this tech? How do we create the best business cases, and what is our ROI? Organizations, we’re finding, are really struggling with this because the landscape looks different than it did. I mean, you’re a tech company in this space, so your customers probably are struggling with a new reality.

In the past, we might have had four to five tech players, and they were mostly the big packaged ERP systems. Well, now we have hundreds of tech players. We have dozens of use cases. This is probably one of the most important ones: Typically, in the past, our ROI equation looked fairly simple. It was about efficiency. You spend X dollars and you get X better cost savings or efficiency. Well, today, with AI, it doesn’t just automate. It can augment. It can improve those human outcomes. It improves business outcomes beyond efficiency. It can improve innovation. It can improve growth. So there’s a whole wide range of metrics that we need to consider beyond cost. And of course, today, instead of a single functional owner, we have multiple cross-functional owners. So it’s a challenge.

You’ll see some of our stats here. Organizations are really struggling with this. 42% cite unrealistic business cases or a lack of data as the key reasons for tech investment failure. 73% listed the inability to define metrics as their top tech investment challenge. So, a couple of things to do on this one: expand your metrics when it’s needed. Right? That Human Performance Equation—look at human outcomes. In the TA space, we have candidate experience, for example, as a critical human outcome which can provide a multiplier effect, as we all know, on business outcomes. Look at outcomes beyond efficiency. Create a whole portfolio. Take a cue from R&D. R&D takes a portfolio approach. They know some of their investments probably aren’t going to work out all the time, but the ones that do cover the ones that don’t. So take a portfolio approach. Not everything is going to hit it out of the ballpark. And then involve multiple stakeholders. So, a couple of tips on that one to solve this problem.

Theresia Hermes 21:59 I love that, and it brings me almost back to the first trend we looked at: that stability. If we have that clarity, that brings stability with it. But then also, as you said, clearly communicating some of the things we’re doing right now might not work out. So don’t get married to the initiatives you’re working on, but that, I think, empowers the employees as well. So I think there is a lot… again, you can achieve a lot with AI.

Also, one of the things — I think this is fitting with this audience—what I keep saying to my customers: if customers come to me and say, “I want to be a skills-based organization,” that sounds like a great business outcome, but I really challenge those customers and say, “What does it mean for you? Is it because you want to close that experience gap? Does that mean that you want to have a time-to-fill faster because you have very niche talent, and you need to understand what similar skills you can hire?” And so I would always—you have probably heard this — always ask “five whys.” And the ones who have children know, you can also ask 100 whys. It gets you to the bottom of what it means, and really, what does it mean for the business? And if you don’t have that clarity, those initiatives become very blurred, and you cannot measure what success looks like, which is again very demotivating for the employees working on it. So that’s again, the employee performance and outcome for that, because if they’re demotivated, they might be worried, like, “Why am I doing this? Is this just automating myself? Am I managing myself out of the organization?” And that is, of course, again, a sweet spot of being very clear what is for the business and what’s also in it for the employee.

Sue Cantrell 23:31 It’s going to vary based on your… on what you’re seeking.

Theresia Hermes 23:33 Exactly. It varies on your industry, your standard. We spoke with Hershey yesterday—a very traditional organization, but able to innovate. And I think again, every organization is a little bit different. Every industry is a little bit different. But having that clarity of what the pain points are we’re trying to solve and how we improve that moving forward.

Sue Cantrell 23:52 Yep, yep. So this is another tech one. There’s no surprise. AI is finally penetrating the majority of workers. Six in 10 workers think that AI is now their colleague at work, working with it. So the question we raised is, how is it impacting the worker experience, and do we need to think about updating our employee value proposition because it’s impacting the worker experience now? This trend finds that it’s very important to revisit it. You can see the stats: over 70% of managers and workers are more likely to join and stay with an organization if its employee value proposition helps them thrive in an AI-driven world.

So one of the things we found here is that AI is different than it was five years ago. It’s not just automating work, it’s not just replacing human tasks. It’s still doing that, but we’ve moved from a world of… if you think early on in the AI movement, we went from automation (that’s still happening), and then we went to augmentation, which was using AI to improve what humans do. And then we went to this phase of collaboration, human and machine collaboration, where it’s a teammate, but that was more like back and forth, like I hand it to AI and AI hands it back to me.

We suggest in this trend that we may be moving to a fourth level of what we call convergence, where AI and humans are increasingly intertwined. Some people in the space talk about it as a metaphor of a centaur versus a cyborg, where a centaur is half horse, half human, and that’s more like the human and machine collaboration. I give it to AI and then AI gives it back to me. A cyborg is just a meld. It’s increasingly… I know for me, I’m constantly prompting AI, using it in the course of my work. It’s hard to distinguish what’s my work versus AI’s work, and I think many workers are finding that.

So it’s becoming really important to think about the worker experience in using AI. And one of the things we found here is you can see these potential silent impacts. Yes, AI… it’s all about how you use it. AI itself is inherently neutral, but if used in certain ways, it can create unintended impacts. We found this very strongly in our research. Instead of AI making work easier, for many, it actually makes it much harder. It’s taking on the easier work, and it’s making work harder for people. Think about ride-share drivers with the AI system telling them where to go. Well, that decreases autonomy. So if it’s used in that way, it can really decrease people’s autonomy at work.

You alluded to this earlier: there’s a lot of research out there that shows the use of AI can create a cognitive decline or decrease critical thinking. So we need to be aware of that. That’s what we mean by a “silent skills killer.” The list goes on. It can negatively impact well-being, loneliness. So we need to pay attention to this, because it’s creating these silent impacts on the worker experience and on the employee value proposition.

A couple of key points of how to move forward is to think about every talent practice. Like learning: learning should be about “I learn from AI and AI learns from me.” Think about rewards. Can we share in the rewards that AI creates? Can we offer a four-day workweek if AI takes some of our load? Can we offer some kind of rewards back to the workers? And then think about studying these silent impacts. Intel, for example, has an anthropologist, a whole team of sociologists on staff studying how workers work with AI so that they can design the right human and machine interactions. And then I think lastly, on this point, we’re seeing a big trend towards the HR and IT functions working ever more closely together to really design those human and machine interactions in a way that’s really positive for the worker and to achieve those business outcomes.

Theresia Hermes 28:11 It’s so interesting because it’s two sides on it, right? Employees can, for example, as it says here, be scared about a “silent skills killer.” But then on the flip side, we have the hope of a four-day workweek. Exactly. We have some positivity, very positive too. And I do think, as an organization, and especially in our role, we have the responsibility to really define what that looks like and help them overcome fear, but also listen to the fear.

One of the organizations I work with, Softtek, when they rolled out their talent management module, they created their own campaigns where it was really about, “We make you future-ready,” so that employees knew, “I’m working here at Softtek, and I can increase my skills. I can be ready for the next wave.” So they’re not feeling left behind, because I think that’s where a lot of employees fear right now: that they are left behind and the company is just marching forward. So back to the beginning: What is the human outcome? What is the business outcome? And that’s a multiplier we really need to focus on.

Sue Cantrell 29:12 Huge. I mean, when we’re Talent Acquisition professionals, we’re communicating to potential candidates, we should be including things like, “How are we going to be able to give you continuous growth to keep up in this changing world that’s changing in part because of AI? Are we going to empower you with the tools? Are we going to give you the tools to learn how to use AI effectively?” It’s a really important piece.

Theresia Hermes 29:39 Yeah, agreed. So right into org culture.

Sue Cantrell 29:44 Into org culture. Okay, so this is our third bucket area. This one is all about motivation, because when we think about that human performance equation that I opened with—business and human outcomes—people are really the heartbeat of our organizations. It’s their behaviors that drive results. And what causes behaviors? It’s motivations. That’s how we define motivation. It’s what is driving people to behave the way they do. And if we can tap into that, because motivations are going to vary by individual, then we can really think about how much we can drive that human performance, both business and human outcomes.

So what do we mean by what drives people’s behavior? There’s a whole body of academic research on this. I just summarized it quickly in this slide: intrinsic motivations. They’re going to vary. Am I motivated by achievement? I’m personally motivated by achievement. I like to have tangible results. Or are you motivated more by helping or making a positive impact on others? So many of my colleagues, that’s their primary motivation. Is it extrinsic motivation? Job security, competition, recognition? And then, of course, we can’t forget about emotions. Those are going to drive our behaviors too.

So if we can understand what motivates people, we can really do a lot to drive human performance. Most workers know what motivates them. You can see, yet very few believe their leadership or their organization understands their motivations. So what do we do about that? How do we tap into this? Obviously, we need data to help understand what motivates people. It can be sophisticated technology and AI inferences, or it can be as simple as having a conversation with your manager or your coach.

So we have three customization approaches. One is manager-driven: just as simple as making this part of a conversation with your coach, and then have your coach suggest career paths that would be suitable based on your motivations, or learning, or any number of things that are based on what motivates an individual. The second option is what we call modular choices. This is offering the same set of choices, kind of like a McDonald’s Happy Meal, to every worker in the organization, so that they can choose choices based on their own motivations. We do this in compensation and rewards all the time. We give them a set menu of choices, but talent marketplaces, in a way, work like this too. We can give them a set menu of potential projects they can join in other parts of the organization that’s open to everyone, or potential learning opportunities that they can choose based on their own unique motivations.

The last one is a more sophisticated, tech-driven approach. My favorite example of this is there’s a company that developed this technology called “neuro avatars.” And what they are is they have an actor, kind of a combination between an actor and an AI-generated tweaking of the avatar. Has anybody seen that new actress, Lucy or something, who’s like an AI actress? It’s kind of like that. So it’s a physical person, and what they do is they adapt that physical person to communicate to a worker based on their motivations and preferences. The content changes based on their motivations. The frequency of when this avatar reaches out to them changes based on their motivations, and the tone and even the way the avatar is dressed. So there’s some fairly sophisticated things going out there when it comes to motivations.

Theresia Hermes 33:43 I love that. There’s one thing I would add here, especially when we speak about culture. There’s one underlying one. First of all, I highly recommend reading the entire report. We’re just scratching the surface on all the data and the insights we are seeing here. One of the things with culture, which is so important, is trust. And one of the data points in the report which really stood out for me is that I think 70% of workers distrust their performance process. And I think if we bring AI in, this is also where it’s really important.

If we look at how we can bring clarity to it, and especially if we use AI, there’s also distrust about what it means for me, my organization, and my career. And there, what we at Eightfold do quite a bit is, of course, when we go through the selection process, helping everyone to understand that there is no bias in our AI, that we, of course, adhere to the compliance and privacy information, but on the other side, bringing them trust by being very transparent. O-I, for example, really brought their career development in a very transparent way. So it felt and seemed much more credible why people are moving across those organizations. So I think that’s just something to keep in mind, that while AI offers an answer to it, keep in mind, employees must trust that solution and must trust your intention as well.

Sue Cantrell 35:08 It’s huge. We have a whole body of work on the importance of trust. You’re right. There’s going to be no adoption and no value realization unless workers can trust it. And as you said, a key part of that is transparency. This does relate to this new trend that I’m going to talk about, about reinventing performance management. You can see the stat at the bottom that 6% of organizations said they’re doing great things using data, AI, and evidence. Think about it: there’s all this data that we can use now to actually help evaluate people’s performance, but if they don’t trust it, then it’s not useful at all.

So this trend is really about… for those of you like me who’ve been in this field for a long time, do you remember like 10 years ago, there was like a new Harvard Business Review article every week about a new organization throwing out ratings, reinventing performance management? Everybody wanted to rip it out. We’ve gone through so much performance management reinvention, yet our data shows that workers still hate it. We haven’t solved it.

So we really struggled with this one, and here’s the conclusion at least we came to. I’ll see if it resonates with you all. As much as we can do things to improve performance management—and we still can do things: simplify it, make it more trustworthy, use more data and evidence, absolutely—it’s never going to go away. We need to be able to have some kind of a system to assess performance, to make decisions like rewards on. It’s just never going to go away. We have to live with it, was our conclusion, and it’s never going to be perfect. We can continue to refine it.

But I think we realized that one of the big problems with performance management was that we were looking at it as a single HR process to solve so many things: to assess people’s performance and make decisions like rewards, but also coaching and development and improving human performance. Maybe we just need to think beyond a single HR process to achieve human performance. Maybe we’re expecting too much, and maybe that’s part of the problem.

So we have this little chart up here where we talk about shifting from a single process to help improve human performance to what we call “engineering human performance.” We use the word “engineering” because it should be based on data, insights, and AI, but there are other things that we can do to help elevate the performance of workers. So think of things like… a less obvious one is workplace design. There’s a lot of research that says the physical environment in which you work makes a difference on your performance. Managers are obviously huge. We know that they make a big difference in coaching and development and nurturing of our people on an everyday basis. All of our talent management practices, our culture… let’s just think beyond it and not have it try to solve all of our problems.

Theresia Hermes 38:22 And performance management remains important, right? Also for internal mobility. It’s not just rewards. It’s also about who’s our top talent, who drives us forward and who we want to keep—regrettable attrition and, of course, retention of our employees. Trimble, for example, is extremely focused on internal mobility. And again, that’s your talent pool, right? We all know it’s cheaper to hire your internal employees than going outside. Industry knowledge… and then again, the experience gap, right? If you go out, you might not find the right skills anymore. And this is, I think, just something to keep in mind. Performance management will remain, and it’s also important. We just need to find a way of, how can we bring more transparency, more critique, and make sure that the employee understands again, “What’s in it for me?” And, of course, the business also gets “What’s in it for me?” as well, for example, making sure we understand who our top performers are.

Sue Cantrell 39:22 Yep, absolutely. Okay, so we’re on our last one, and then we’ll see if we have time for questions. So this actually is related to performance management: the role of managers. I don’t know if any of you have seen, there’s been a lot of press lately around the “bossless organization,” and organizations either eliminating middle managers or really thinning them out. So there’s this thread thinking that they’re bureaucratic, they get in the way of agility, they cost a lot of money. A lot of it is cost-driven. And then there are other organizations who are saying middle managers are absolutely the most important; they’re the glue of the organization, right? And there’s a lot of research that shows that those with stronger middle managers have 15% better financial performance than those that don’t.

So we think there’s a third path, and this trend represents it. Instead of valuing middle managers as they are today, or instead of just getting rid of them, why don’t we reinvent them and make them more fit-for-purpose for today’s world? Reinventing them starts with what it is they’re doing. Today, this is how, based on our research, they’re spending their time. Basically, you can see 40% of their time is eaten up with fire drills or low-value-added administrative work. So I’m going back to that “when work gets in the way of work.” They’re kind of a catch-all, right? We ask them to do so much, and a lot of it isn’t particularly value-added.

So can we reinvent it? We suggest three ways of doing that, three main areas. One is, somebody needs to continue to be a coach, a developer, a motivator of people. If it’s not the middle manager, then who else is it? That has been shown to produce human and business outcomes, and the organization can better support it. So for example, some organizations are using AI to give managers feedback on their teams, to model having difficult conversations with team members. So there’s a lot more we can do to support our managers.

The second is a new area, which is… I had just talked about AI penetrating the work. Managers have a huge role to play in deciding who does the work. Is it my workers? Is it somebody I borrow from a talent marketplace? Is it AI? How do I resource the work? How do I make sure that workers are working effectively with AI, and how do I redesign work? Nobody knows work better than workers and managers, and the promise of AI is only going to get realized if we actually change the way work is done, and managers are key to that.

And then the third area is helping managers be like a catalyst for agility, problem-solving, a lot of the strategic stuff that they’re doing today. Let’s broaden that out. They have a key role to play in change. I heard on our last Coca-Cola presentation how important it was… it kind of stopped at the middle manager layer. Well, if we can make sure that they are a catalyst for change, then we can be much more agile than ever before, and we need to support our managers in that.

So that is a whirlwind of our trends. I’m going to leave you with three key actions specific for talent acquisition leaders. One is, when you’re recruiting, think about communicating the employee value proposition for the age of AI to candidates. Two is, rethink “years of experience” in your hiring algorithms. And three is, when it comes to TA tech, talent acquisition technology, consider a new value case. Like Eightfold’s, it has so many human and business outcomes that it creates, that we need to rethink the way we value those systems. Anything to add, Theresia?

Theresia Hermes 43:29 No, I think, as I said, the clarity again, to “What are the value cases? Why are you doing it?” is… it comes really down to the same as the EVP. Why is this important for the candidates, the talent pool, for our business? So that clarity, being very clear on the “why,” will help you make that change move forward.

HCI Organizer 43:49 Thank you so much. We have maybe a couple of minutes for one or two questions. Does anyone have questions for Sue or Theresia? Oh, wow. Okay, they shot up at the same time. So I’ll start here, and then we’ll go there.

Audience Member 44:10 So regarding the human performance question, especially with data, what have you seen that makes people more responsive to inputting data to provide more honest answers? The reason I talk about that is because, if it’s in the workplace, if they’re inputting information, then they worry if that information could be held against them at some point. So how do you… obviously, when you’re talking about trust, it is really important. But what have you seen be effective in them inputting or providing more data for growth, for a growth purpose versus a punitive one?

Sue Cantrell 44:51 I’m so glad you asked that question. Outside of this report, I did a year-long research project on exactly that question. So important. Here’s what we found: workers are willing to share their data under certain conditions. One is if they see that it’s a benefit to them. You give to get: “We’ll give you our data if I get value in return.” To your point, and to know that it’s never going to be used for punitive or surveillance purposes. We advise our clients to never go in the punitive or surveillance camp ever. Just don’t cross that line.

I think that a lot of the passive data collection, like AI monitoring the work you’re doing, how you’re working… the baby gets thrown out with the bathwater because we automatically think it’s surveillance. There’s so much benefit in that data if used in the right way, under the right guardrails. Another is transparency, which you brought up. A lot of the principles of trust: be transparent about where it’s going to go, how it’s going to be used, give workers the ability to see it and challenge it. I’ve seen organizations have whole systems where they can challenge their data, like their skills data, for example.

So there’s a whole responsibility framework to be built. And if, our research has shown, if organizations have that, workers almost always want to share their data, and organizations get huge amounts of benefit out of it that have nothing to do with punitive stuff. It’s about achieving those human and business outcomes.

Theresia Hermes 46:41 Plus one to everything you just said. So anything… again, clarity. Why are you doing that? What are you doing that for? Again, also be clear on the business outcome. “Hey, we want this data because XYZ, it would benefit us.” I think employees are buying into that. And then, as you said, this is also what you get out of it.

HCI Organizer 47:00 Awesome. Let’s do one last question.

Audience Member 47:05 So first, I have loved this session. It is really aligned with a lot of things that my organization is facing at the moment. My question was going to be, how can I get more information? But I see that you have offered that. So I guess I would pivot that question to be, do you have different levels of membership or something like that, so that we leaders can stay abreast of all the research and white papers that your organization offers?

Sue Cantrell 47:39 Well, thank you. So we don’t. This is all free. There are no levels of membership. We do this as part of… I feel so blessed in my role, actually. This is my full-time role. I actually used to work in talent acquisition in the HR function, but I have the privilege of interviewing executives across all different kinds of industries and coming up with surveys. And I do human capital trends. It is free. You can see where to get it here. Sometimes we will engage in conversations and do workshops free of charge. It’s just a service that we do. My mission, my personal mission, and part of the trends mission is to just elevate all of us and improve the art of our field. And so we also have a lot of other research, though, as I said, like I did a whole research study on passive data and the ethics of that. So just check out Deloitte Human Capital Insights, and it’s open to the public. And feel free to reach out to me personally.

Theresia Hermes 48:50 Speaking of a great career path: practitioner to strategist. And Eightfold and Deloitte have done a lot of webinars and blogs together, so there’s a lot on the Deloitte side, but also on the Eightfold side.

Sue Cantrell 49:01 We have a Deloitte Eightfold Alliance page that a lot of our joint work is featured on as well. Awesome.