The great redesign: Redesigning work and how talent connects to it

Transcript

Stuart Crainer:

Hello. I’m Stuart Crainer, co-founder of Thinkers50. Welcome to the series of four webinars celebrating the skills-powered organization. This is the third in our series.

In the opening webinar, we looked at the data you need to make the skills the currency of work. We had a brilliant discussion featuring Ravin Jesuthasan and Peter Stevenson from Mercer, alongside Britt Alcala from Delta Airlines. Then on September 18th, we had another great session on how organizations can reshape how they manage talent and skills to be prepared for an uncertain future. Lauren Mason and Jessica Kennedy from Mercer were joined by Jennifer Acosta from Kenvue talking about how to make job architectures future fit. Both of the first two sessions are now available on YouTube. They’re worth checking out if you couldn’t join us live.

Today, for the third in the series, we’ll be looking at the great redesign of work. Outdated and traditional work frameworks, and systems based on static jobs, and employees in jobs still dominate the working world. But those systems and frameworks need to be remade for an increasingly volatile, and machine-augmented world, to enable talent flow, to perpetually reinvented work based on the seamless matching of skills and tasks. The shift to a skills-powered organization will transform every aspect of planning, acquiring, deploying, developing, and managing workforces.

To chart the great redesign of work, and how talent connects to it, we are joined today by Tim Flank and Tanu Gupta Jain. Tim is the HR and workforce transformation leader at Mercer. And Tanu is the workforce and organizational transformation principal at Mercer. They’ll be exploring why organizations are increasingly making work design core capability. We’ll share some great practical examples.

As always, please send in your comments, queries, thoughts, and questions at any time during the session. I’ll make sure I share those with Tim and Tanu. Please also let us know where you are joining us from today.

Welcome Tim and Tanu. Let’s start with some basics. Perhaps we could start with you, Tim. What is work design, and why is it increasingly important for organizations?

Tim Flank:

Sure. We have a few slides that I think we wanted to bring up to help illustrate the concept, and set the stage for our conversation today. This slide in particular really highlights the tool itself, and what it aims to accomplish. But let me take a step back, and before we even dive into this, this concept was really spearheaded by a leader at our firm who was actually on the first conversation of this series, Ravin Jesuthasan in his book, Work Without Jobs.

The idea that was discussed in that book, and also is buzzing across the industry right now, as we all know, with the increase of automation, artificial intelligence, and the fundamental change of how work is getting completed in the modern era, it’s really changing the underlying definition of how jobs and work are being considered, and defined. What I mean by that is that in legacy, and even still today in many organizations, we’ve always thought of jobs as a linear set of responsibilities.

You have a job description. In that job description it lists what that role aims to do, perform, execute, and lead as part of the organization, and what it aims to deliver within that job. What we’re seeing now is that it’s really democratizing how work is being done. Instead of thinking about jobs in such a linear way, we’re thinking about the partnership of work alongside the technology and artificial intelligence that’s being developed. We always used to think about technology as an enabling tool, and something that I use to deliver my work. You’ll notice the word I just used before that is now it’s being transitioned to partnership.

Now, we’re thinking about how human capital can work alongside technology, and really partner with it to deliver the work. What that’s really done is it’s really broken apart this concept of work. Instead of it being now linear jobs that are performing different types of functions within the organization, now, we think about, what is the work that really needs to be completed? And, then what are the combination of skills that I need in order to deliver on that work?

Humans, instead of increasingly being aligned to these linear jobs, are now just a part of the equation, and are assigned to different types of work based on the skill sets that they bring to the table. We’ll talk more about that later in some of the case studies. But that’s really one of the underlying principles of this product, and how it drives into the future. Because work design in and of itself is meant to really rethink, and challenge that status quo that I just discussed.

Thinking about how work is going to be completed in the future, and what this tool is, is A, it’s an online AI enabled tool. It’s won awards from HR Tech as one of the best practical applications of AI, and it’s connected to the Mercer skills library, and our global job catalog. Over 26,000 positions, and thousands of skills are already uploaded into the tool.

At its core, it really does three things. You’re deconstructing the jobs and processes into tasks. You’re starting with a job. You’re saying, “What are all of the different components of the job, all of the different tasks that are comprised of that job?” We think critically about them. Then we analyze them across things like, “Are they independent or interactive? Is it mental or physical?” We ask ourselves some important questions there.

That then enables us to do the second thing, which is deploying those tasks to the optimal combination of talent and automation. We take the test. We deconstruct it. We think about it through the lens of … We also assign time allocation to it. Then we say, “Okay, here’s all the individual tasks. What’s the best way to deliver on this? Is it through talent or is it automation? Is it through augmentation?” There’s a lot of different options there.

Then finally, we reconstruct the jobs to meet the business growth. We actually move to the next slide to illustrate on this a little bit further.

This is what I was just talking through in a little bit more detail. But the other point I want to make is that this is a really bottoms up approach. It’s taking jobs at their core, and really to the point I was making earlier, enables us to take away the lens of linear jobs that we’ve thought in the past, and more so think about what is the actual work that’s being done, what are those tasks, and skills that we’re able to identify through the deconstruction process?

Then through those improvement actions, and redeployment, we’re able to have a few different types of actions. It could be work substitution, and augmentation. Based on AI and automation, it can be alternate talent models like shared services, job talent pools, internal talent marketplace, which we have some really great use cases for that as well.

Or it can be work redeployment to lower levels. We’re thinking critically around, where is the best way for this work to be delivered? Sometimes it can be centralized, and you can get efficiencies that way. Sometimes for engineering roles, we strip away the jobs altogether, and instead we think about what are the products that we’re developing, and the software we’re developing.

Then we go into our pool of engineers. What are the skillsets that are most qualified to perform that role? Is it something that just a higher level person is doing, that could be done more efficiently at a lower level? Is it something where we can use social robotics? Or, to help in a warehouse setting, which we’ll talk more about later. Then that last step is then that reconstruction. More impactful jobs that are really future-proof, and ready to deliver in this age of AI and automation.

Actually, Tanu, I don’t know if you want to just take this last slide here on slide three to talk a little bit more about, how we think about different types of jobs across the spectrum of a substitution, automation, and robotics? I know that text is small, but do you want to talk about how this can come to play out in practicality?

Tanu Jain:

Sure, of course. Thank you, Tim. Before I get into the details of this slide, just adding on to what Tim shared, skills, of course, is an important foundation, and the baseline of some of this work that we do. The other important piece to consider when we talk about our work design methodology is the nature of the work. I think that the core essential, as Tim talked about, the deconstruction and the redeployment stage is to really go granular, and understand at the time allocation task level, what’s the nature of the work, what are the key characteristics of the work that people are doing in those different jobs, and what are the primary skills associated with that?

As we talk about the future of the work, and we look at reshaping the work, whether it’s due to the impact of AI that all of us are observing, impacting the organizations, and the work and workforce today, or if it’s, let’s say, there are talent shortages in some industries like healthcare, et cetera, or if it’s with regards to any other transformational initiatives that organizations might be taking, in those kinds of scenarios, as we talk about how the work will change, and get reshaped in the future, we talk about how therefore the skills that we associate, that we hired people for, or we are upskilling or reskilling people for, how will that also change in the process?

The work design methodology talks end-to-end, and captures that lens versus the fixed traditional legacy model of having employees in a fixed setup that we’ve seen over the years. How do we move away from that, and really go deep into understanding the work, the skills, and moving to different alternate kind of models, and reshaping the work for the future?

With that, let me talk a little bit, and share more perspective on this slide. This particular slide gives a view, and overview of select industries, and types of jobs and roles across a spectrum of how the work is going to get impacted. Based on some of our client experience, and some of our recent work and research, we came across select categories of work. As you see on this slide, in those small bubbles, I’m sure it’s hard to read, but I’ll share some examples as I talk through, on the spectrum of the impact of AI, and automation.

On the left-hand side of the x-axis, you see machine learning, and deep learning, some of the traditional AI impact, and then moving from there into more generative AI, and the other end of the spectrum around social, and collaborative robotics, impacting more of let’s say the warehouse related jobs or manufacturing jobs, any frontline related work today.

How are different categories of work, and different jobs are going to get impacted across this whole spectrum of AI, and automation? We looked at some of the data from some of the labor statistics data from the Bureau of Labor Statistics. For the recent years, what are the typical average volume of jobs across these different industries or work categories and segments? Therefore, just a broad view in terms of the significance of the impact that we are talking about here across some of these industries.

The bubbles denote the volume of the jobs or the size of jobs in those particular categories or industries across the US. The color coding illustrates how different types of work or jobs are affected within a group. On the Y-axis, as you see, how the different kinds of automation or different types of automation are going to impact the work. What is the role of the automation, as Tim also covered a little bit of that in the redeployment part of the work design methodology. The role of the automation, is it going to substitute the work, replace the work leading to more efficiency, and cost reduction? Or, is it going to augment the work, helping us increase, and improve productivity in those jobs, make the work more effective, and better for the incumbents in the job?

We are basically trying to understand, what are the optimal combinations of talent, and technology going forward? What are those industries or jobs that we can already see getting highly impacted or are more susceptible to that change in the near future, and the longer term across the different segments? Anything you’d like to add, Tim, to what I just talked about?

Tim Flank:

No, I think we … Hopefully, that Stuart’s question of giving a background, some of the conceptual theory behind the tool, and where our point of view comes from, our philosophy behind it. I hope that we were able to get that across, and now open, hearing some other ways that we want to take the conversation.

Stuart Crainer:

Yeah. There’s quite a lot to unpack there, I think. What about the history of work design? I was just thinking, as you were talking, that work is something that’s universal. People have been working for centuries, centuries, and millennia. When did we start designing work? Does that go back to scientific management, Frederick Taylor, beginning of the 20th century or earlier? Where do you see this in the tradition of work design?

Tim Flank:

Yeah. I could start, and you could chime in on that piece as well. I think personally, work, the construction of tasks, and how individuals can contribute to a greater good was something that was fundamental to the beginning of probably humanity, honestly. Even thinking back to some of the agricultural, the different roles that are on the farm, and things along those lines.

But I think over time, as you think about some of the different revolutions that we’ve encountered, you think about the industrial revolution, and then in the early 2000’s we had the .com boom. Then now we have this new onset of artificial intelligence, and its impact. I think with each one of those over time, it’s changed the nature of the worker. It’s changed the nature of how work is completed, what are those tasks that you’re doing, and how are you contributing to the mission of the organization.

What started with jobs that were just all very manual, even if you think about professional services setting, and some of the work that we do from a consulting standpoint, just basic rewards consultant, just as an example, started with writing everything down, going and looking at what people are paid, calculating it, and writing that into a book. Then eventually there was some basic spreadsheets, and processing tools that you work alongside. Now everything can be extracted from a proxy or from a statement in real time. Then you can just spend more time analyzing it.

I think what it’s done, Stuart, is each one of those steps along the way is it’s really elevated, and unlocked some capacity for the human worker to focus more on the things that humans deliver best, our intuition, our critical thought, our strategic thinking. AI, automation, and those forces that will, are hopefully if they’re being deployed in the right way, are helping organizations gain efficiency, but they’re also elevating the impact of the human worker.

I think that that legacy is very consistent with what this tool is trying to accomplish in a lot of ways, which is like, “How do we isolate the tasks that humans can contribute to, and add the most value in a way that’s going to ultimately help organizations succeed?” That’s my perspective of how this has all evolved over time. But Tanu, anything to add from a historical point of view?

Tanu Jain:

Yeah, a couple of other things that come to mind. As to your questions, Stuart, historically, and I think in recent times, we’ve seen some changes emerging in the talent, and the workforce landscape. One, of course, the generations, the workforce that we are getting into the organizations, that’s walking into the organizations today, is changing, and the workforce expectation, the attributes that they associate value with, what motivates them, et cetera, that’s changing from what we’ve seen probably 20 years ago or so.

Hence, I think it’s important to also consider how we might want to rethink how we design work, how do we associate what’s important for that workforce. How do we keep them engaged, and motivated? How do we marry the work with the skills rather than the traditional aspects of those fixed jobs, fixed job profiles, and people coming in with certain set of fixed experience or qualifications? And so on. The workforce is eager to learn, these days. They’re constantly developing newer skills, and the organizational expectations are also moving fast. I think keeping all of that in mind, the augmented methodology emerged to move away from that traditional way of working, to rethinking how we should think about the skills, and how we should associate the skills with the workforce coming in, and reshape the work.

Then the other piece is, as we saw, some of the organizations, of course, moved faster in their journeys while others are catching up in terms of concepts related to internal talent marketplaces, the agile talent pools, et cetera. We have also seen some organizations that made headway in some of the recent years around different exploring, and experimenting with these kinds of different talent models that led to … These models, like internal talent marketplaces, these, of course, not only helped the workforce be more engaged or develop newer kinds of skills on various projects, but also made us think about how skills are becoming the foundation for a lot of what we do.

Then, of course, on top of it, we are all facing, and I’m going through this impact of AI, and automation and how the technology is also impacting the work more than ever. I think keeping all of these things in the view, our methodology emerged, and it’s constantly getting more and more upgraded and progressive in keeping all of these changing workforce dynamics into consideration.

Stuart Crainer:

You talked also about the democratization of work. I think we’re assuming that democratization is a good thing. In what way does your work democratize work then? How does it make it free or give people more power? Can you just explain a little bit about that? I think that’s kind of a fundamental driver behind what you are talking about. Tanu, Tim?

Tanu Jain:

Yeah, I mean …

Tim Flank:

Can I answer that?

Tanu Jain:

Go ahead. Go ahead.

Tim Flank:

Yeah. The question about is it a good thing, that’s one that I think it depends on who you’re talking to, then context and nature of the work that you’re doing. There are organizations depending on their financial health or the industry that they’re in, that certainly look to tools, like work design, or technologies like AI and gen AI to gain efficiency, to try, and deploy less labor, achieve economies of scale in their labor costs.

However, there are organizations that are more forward-thinking, and more so focused on unlocking work in such a way that enables people and human capital to really grow, and skill themselves with the types of capabilities that they need, to deliver on work that’s most critical to the organization. The way I always like to talk about this is, think about historically, organizations would recruit, and hire individuals based on a job requisition that was open.

We have a new financial analyst. The person just left. We’re back filling the role for this job. The way that this is evolving, and what we’re seeing in the industry is more and more organizations are hiring individuals less so into a linear job, but more so they’re acquiring them as an asset to the organization. They’re acquiring those skills that they bring, that they think that they can leverage to generate value for the organization.

It’s almost a liberating concept, because it’s enabling folks to evaluate the types of skills that are going to be needed for the work that’s available within a given entity. Whether it’s product design, whether it’s actual manufacturing, whether it’s more in the healthcare setting, whatever it might be, I can then have conversations with leadership to understand, how is this work emerging? How is it developing? What are the types of things that we need to do today, and what are the skills that I need to make sure that I’m being deployed, utilized, and contributing to the organization?

It’s almost creating this empowerment of the workforce, to work alongside employers, and this renewed focus on learning and development, around what skills do I need that I don’t have today. Or, the skills that I have, how do I best deploy those? It’s enabling more focus, and it’s enabling more people to really lean in, and deliver on different types and varieties of work, and really leverage their skill sets to the way that’s most mutually beneficial for them as well as the organization.

Is it a good thing? I think it depends on the context and nature of the work. But I think for the most part, I think it’s enabling the workforce to think more critically about what skills they’re bringing to the organization, how do I leverage those, and how do I evolve and develop based on the needs, which I think almost has a liberating feel to it. Tanu, anything you’d add to that?

Tanu Jain:

Tim, very well put. I think the only thing I’ll add is it’s a good thing, and also probably given some of what I talked about, given the changing workforce landscape, democratization is helping not just the employees or the people walking into the workforce, but also the organizations to, one, for them to be able to leverage the skills in a lot more optimal way. It’s also opened up so many more different kinds of talent pools that can be accessed by the organizations, rather than just having fixed jobs, and people in fixed positions.

You can have freelancers or a gig workforce for several different kinds of jobs. You have some of these agile talent pools. The concept of fungible skills that can be mapped within an organization, and people can be pulled across projects, it not only makes most cost-efficient sense for the organization, for the business, but also it keeps the workforce engaged. It can open different kinds of different opportunities to learn and grow for the employees within the organization, and several other kinds of talent pools can be accessed.

I was listening to this interesting discussion on the web yesterday where Ravin makes a very interesting quotation by William Shakespeare, which goes as, “Jack of all trades is a master of none.” Ravin emphasizes how we often forget the second part of this quote where he says, “Oftentimes, it’s better than a master of one.”

I think it’s the same mindset where we want to understand the importance of different kinds of skills. If people are able to multitask or develop parallel skills, and the organizations are able to leverage it across different areas within the business, I think that makes democratization in that sense a very good value add, and a win-win for both the workforce, and the business.

Stuart Crainer:

Yeah, thank you, Tanu. I think Tim’s phrased it, deployed in the right way. It is quite important, which has always been the case. Steph Kantorski makes a point. “Where do human emotions about work come in? What about how humans feel about losing the work they love, and self-worth, pride, mental health in general? Why is this all about serving the organization writ large?”

I refer Steph back to Tim, and Tanu’s previous answers that it is about organizations, but it’s also about individuals. It seems to me, it’s getting that balance right.

Tanu Jain:

Exactly.

Tim Flank:

Yeah. I think … Go ahead. Go ahead, Tanu.

Tanu Jain:

Yeah. Like I said, and again, of course, we cannot emphasize enough that that needs to be deployed carefully like Tim said. But I think it’s a win-win if we get the recipe right. What I think we forget in the process is that it also gives the humans in the job an opportunity to be more effective in their work or to develop different kinds of skills, and explore different avenues.

The workforce today has this hunger for constant learning. They have this need to develop some new skill or learn something new, and explore new avenues every few years unlike what probably we have seen in the past. This just not favors the organization, but if conceptualized correctly, appropriately, it also helps the workforce be more engaged, and motivated.

Tim Flank:

Yeah. I would just quickly add to that is, I think when you look at organizations that are starting to deploy things like talent marketplaces, and are really embracing this concept of thinking about work through this new light, what it does for the human is it creates more stimulating opportunities at work.

There are different types of people. That some people, they want to go in, and deliver the same work day in and day out. They’re comfortable in doing that. That’s where they find they generate worth in that way. Honestly, jobs in that fashion are not going away anytime soon. I think there’s still going to be a place for certain types of work where it’s very repetitive in nature. There’s still going to be a place for that.

However, what I think is interesting is this new environment of being able to deploy your skills in a variety of ways, creates this agile workforce, and it ends up being more stimulating for people. I can contribute to a finance project. If I have an analytical skillset, I can do more consultative, and advisory work. Another question about, what are the skills that are most in need? A lot of that is around decision-making, and advisory around data. There’s so much data and analytics that are available in this current world. How do I make sense of that? How do I generate insights from that?

There’s all these different types of ways you can lean on your skillset to deliver work. If the organization is marrying that correctly, you can really have a really interesting time to work, where you’re getting exposed to different things, and then you’re really developing at a rapid pace, which is something that a lot of people are looking for.

The last thing I want to say, too, is that there’s this concept in HR where HR was kind of historically the steward of personnel. Now, they’re the steward of work. I think eventually, it’s going to be the steward of the human. What I mean by that is, I think as automation, and AI continue to take more and more of a grip on how work is completed, I think what’s going to be left to differentiate organizations from one versus another in a competitive landscape, is going to be the human. How the human is treated, is there a well-being program. I think that’s what’s going to ultimately draw, and differentiate. That’s something I also think that is not going to go away anytime soon.

Stuart Crainer:

Yeah. The question you mentioned, Tim, was from Robert Stabbert. It would, “be good to hear about the new skills needed to partner with the new age of technology. What are the emerging soft, and hard skills? What human elements are in high demand? And, where, what industries, and roles are in need of human abilities?”

From what you’re saying, Tim, there’s still a premium on judgment, and decision-making.

Tim Flank:

Definitely, judgment, decision-making is one. The other one that we see a lot of is advisory, and consultative skills. Like I said, being able to make sense of all the information that’s out there, right now. AI platforms are getting better at this, but I still think humans have a premium on synthesizing information, looking at data in really large quantities, and being able to interpret it, and distill it into actual decision-making insights.

What am I bringing to leaders to say, “Here is the actual conclusion of all this available data. How are we then going to act on that in terms of making decisions?”

Stuart, you’re spot on. Judgment, decision-making, data, and analytics are still very much at a premium. Then, Tanu, I know there’s others particularly in the manufacturing setting at large as well.

Stuart Crainer:

Yeah. Please send in, if you’ve got any questions. Megan Waterworth says, “Does this tool help design jobs for flexible working? For example, to enable a full-time job to be designed in a way that enables a part-time pattern.” Tanu, any thoughts on that one?

Tanu Jain:

Yeah, thanks for the question, Megan. Yeah. This tool, absolutely. The way the tool is designed, it helps us understand how the time is being spent in a job on an average by incumbents on a typical day at work. On a daily basis, I might be spending, let’s say 5% of my time doing a lot of, let’s say team management work, and I might be spending X amount of time across report generation-related work, so on and so forth. It sort of gives us, and helps us break down and deconstruct the work in terms of how the time is being distributed today.

Is there spillover of work across certain levels? Are people too stretched to be able to focus on the actual meaningful work that the job was originally designed to do? Are there a lot of non-value-adding activities or redundant work that’s creeped into the job, and seeped into it over years? And so on.

First of all, the tool helps us really diagnose, and assess what’s happening today in terms of how the time is being spent, and so on. That’s where we start finding, and identifying the opportunities to optimize and move away from some of that. Let’s say non-value-adding work, move the work down to lower levels, which senior levels were managing because of some spill over, skill gaps, or proficiency issues, and so on and so forth. Is there any impact of AI and automation that would, on certain process touch points or workflows for that particular job, that would either substitute some of the work that the human in the job is doing today or help augment, and free up some capacity?

We get really granular with this tool in terms of assessing the current state, the potential opportunities for future state, and the redeployment. If I take example of some of the clients that we have done work, and use this tool recently, we’ve seen significant capacity gains, and time savings as a result of some of this redeployment and opportunity identification across jobs in the range of 25, to as high as 50%, as a result of these various redeployment opportunities. That helps us understand whether we need a full-time employee for this, or could this be managed better through a part-time employee. Could there be any other alternate talent pools that we can consider for this?

Yeah. The tool offers us, and helps us design jobs in a much more flexible working model. It helps us identify opportunities for part-time models, agile talent pools, for shared services, for outsourcing the work completely, and so on and so forth. I hope that answers … Megan, happy to take any follow up.

But yes, the tool helps us identify how to move away from that fixed employee setup, and explore those alternate talent models, including part-time as one of the options based on some of the capacities, the detailed elements, and characteristics of the jobs that we assess.

Stuart Crainer:

You just clarified, Tanu, 50% more efficient?

Tanu Jain:

Yes.

Stuart Crainer:

That’s what you said. Yeah. Which is quite a lot, isn’t it?

Tanu Jain:

Yeah, yeah. We have seen in some of the processing kind of work in, let’s say, financial services clients, and some of other similar industries, where there is a high potential impact of especially automation or moving the work across levels so that those levels are able to perform at the top of their license.

We have seen capacity gains in that range. We’ve been able to reshape the work across the levels to not only make the early career levels, their jobs more meaningful and richer for the young workforce walking into the organization, but also giving back time to the senior levels, for them to be able to focus more on let’s say client management work, more strategic kind of work, and so on.

Then a part of this capacity gain, we also always encourage clients to think about the mental well-being aspect that we talk about a lot, but oftentimes gets lost in our day-to-day, business as usual. If we see capacity gains in that range, is there an opportunity to give the time back to employees for their mental well-being or their skill development, and for them to be able to spend time to grow, and develop new skills, and so on?

Stuart Crainer:

I think there was a sense that the usual interpretation was that AI would get rid of repetitive, menial, low level jobs. But what we’re talking about now is AI getting rid of repetitious elements of management, and professional work as well. It’s freeing up managers to do what they’re hopefully good at.

Tanu Jain:

Absolutely. I think the considerations, and that’s where the role of automation as part of our methodology comes into play, is the automation. That’s where some of the repetitive work that you talked about, Stuart, the nature of that kind of transactional work gets impacted, and gets substituted in those cases. The automation and AI replaces some of that work. We might not need as many incumbents to be performing that work, because of AI and automation coming in.

But then for the more professional work or where there is more nuanced work or there is higher complexity, et cetera, their AI and automation, in our experience, we have mostly seen AI augmenting the work, and helping improve the productivity. We would still need the same employees in the job, it’s just maybe they might need slightly different skillsets now that the AI is there. Something that they might be doing partially or fully manually earlier is now becoming more effective, and productive with the help of automation or technology.

There is a very careful, I think, consideration when it comes to AI. It would be wrong to say that AI will just replace everything, because when we work with our clients, we have seen a significant proportion where AI is helping augment the work, still freeing up some capacity because now, it’s just becoming a lot more efficient for the person in the job.

Stuart Crainer:

Which organizations, and which sectors really understand this, and are using this technology successfully now? Can you say in particular sectors, it’s being embraced enthusiastically or particular organizations, it means you’ve worked with lots of companies?

Tanu Jain:

Yeah, absolutely. We’ve been working a lot with companies in the financial services space, financial services for different kinds of verticals, and sectors. But I think some of the examples would be loan processing, general processing jobs, accounting jobs, customer service, or contact center-related jobs. We’ve worked with some telecom organizations, seen an impact in those cases also in engineering, and network engineering jobs given the nature of the work.

Then I let maybe Tim chime in on some of the frontline work where this technology and product has had significant impact. Tim?

Tim Flank:

Sure. Yeah. We did some work. I actually partnered on this work with a North American Beverage company. They were actually looking at their merchandising role. These are the folks that are actually employed by the organization. If you think about it like a supermarket, in a supermarket setting, you see people that are stocking the shelves, and those people generally work for the supermarket, but this particular company, and some of the other larger companies have their own merchandisers that are in the stores employed by that organization. They’re essentially in charge of doing inventory management, and then arranging the product, putting it into the proper displays. Unpacking the pallets that come directly from the distribution centers, and then organizing it on the shelves, and building out different arrangements that you want for that given setting to maximize the buying power from the individual.

It was a really interesting piece of work, because what they were interested in doing was actually mediating some of the physical burden that the role inherently has. If you think about it, the demographic that was doing this job was largely young males, because it’s like lifting heavy products off of pallets, bringing it around the stores, and putting it on shelves, a lot of lifting.

There were some different types of social robotics that we were considering to help alleviate that work, and different types of actual wearables that you can put on your person to help reduce some of the physical burden. Ultimately, they wanted to increase the pool of talent that can fill these jobs. They had very significant turnover issues. They wanted to see, “Can we make this more of an inclusive job? Can we have it open to more different types of demographics, different types of people in the workforce?” That was one element of it.

Another element was, these folks were not getting the support that they needed in the stores to A, feel onboarded properly. And, B, grow their careers in a way that they felt was fulfilling. One of the other concepts that we introduced as part of this work was basically an effectiveness onboarding, and training rule that would go into the different regions that across the US that they operated in, and would essentially be a resource for these different roles to help them real time in onboarding, and helping them make sure that they’re acclimated to the store properly. Also, their training in real time to make sure that they’re getting the skills that they need, that they’re growing the way that they want, and that they understand how they can expand their career.

The last point I want to make, too, that was one of the more interesting pieces that we uncovered is we actually were starting to experiment with some technology that would actually optimize the process between ordering the actual new product. The up, up based on what’s left from an inventory perspective, what’s coming in from the warehouses, which there’s some really interesting image recognition technology. Basically, you can take pictures of what’s left on the shelf, and it would automatically generate how much you need, and at what rates you need that.

Then going a step further, it would actually then optimize in the facilities, how the pallets are arranged in a way that makes it more conducive to delivering the product from the merchandisers in the stores. Again, in what’s called a more optimal format. There’s a little bit less lifting, and a little bit less juggling around the product because it’s actually ordered in a way that’s logical for that given merchandiser. The words they use, basically they use Tetris-type pallet building. It was a really interesting way of leveraging that technology. Again, to really alleviate the end user, and have them have a better experience in their roles.

Stuart Crainer:

Tanu, what kind of pushback do you get with these ideas? What are the obstacles that are getting in the way of achieving the 50% efficiency Tanu talked about? What do people object to, or struggle to understand?

I think there’s probably quite a large degree of explanation of how it’s going to make their working lives better, is probably required.

Tanu Jain:

Yes.

Tim Flank:

Yeah. Yeah, go, Tanu.

Tanu Jain:

Of course, when we talk about any kind of workforce or organization transformation work, there’s always that initial resistance or the need for alignment, and the understanding of, what’s really the vision here or what’s the case for change? How will this help, and how will this not be really disruptive for the organization? The idea is to make things more efficient, effective, and not disrupt how the organization or the business is working.

I think it’s important when we get into those conversations, one, to manage that initial hesitation or resistance. You talked about, Stuart, we work very closely with the business stakeholders to first align on what is the shared goal here, and how is this methodology going to help them think through the future?

Because we cannot deny that in most of these cases where we work with clients, the organization is transforming, the business landscape is changing. That’s something that’s evident. We cannot close our eyes to it. I think it’s important that the stakeholders, and the clients, they are willing to think through, they appreciate. I think once we understand the context, and the reality of the organization, we try and contextualize it for them, and make it real for them. That’s when they understand the importance.

Also, I think the other piece is to really understand, and help them see how this will be beneficial to the employees. It’s not just a business decision. It’s not a financial decision to use or deploy something like this. This is also going to make the work mode meaningful, and effective for the people in the job. We’re not talking just in terms of FTE here. We are really getting deep into the work.

When we’ve worked with clients, we’ve had business stakeholders tell us that we knew what our teams are doing, but it’s been a while. We really thought through about the work so granularly, and so carefully. That makes them also rethink and revisit what is going on in the teams, how are people spending time, how can we really make things better for the people in the jobs for the organization itself?

The only last thing I’ll add here is this methodology is not a prescriptive kind of an approach. The Mercer team doesn’t sit in like a back office, and come back with some recommendations. This is a collaborative tool.

The clients get access, and can license the tool. The methodology involves live working sessions with the client stakeholders, the business stakeholders in the same room with us. We problem solve, brainstorm, and we jointly co-create the future jobs with them, which is where the real engagement is. That’s where they start seeing the value, and appreciate the methodology.

Stuart Crainer:

Now, Barbara Robinson says, “Skills are not the only ingredient for success in completing a project. Personality characteristics are key as well.”

I’m not sure what the answer is to that. Tim’s nodding. You obviously understand there. I’ve got some response.

Tim Flank:

Yeah, it’s a great point. I think what you’re basically alluding to is the sense that you can’t just take random people within an organization that have the right skill sets, and say, “Boom. You’re on this team that’s going to complete this type of work, because you have the skill sets to qualify for that,” and expect them to always work in a way that’s collaborative, productive, and know they need to lean on.

Honestly, I think what it speaks to is the need for one of the questions earlier about, what are the hard and soft skills that humans need to bring to the table in this new era? It really speaks to the need to have people inserted into these teams that A, understand basic org effectiveness principles, and B, just basic project management, and team leading dynamics. It’s not going to be sufficient to your point when, let’s call it a new product that’s being developed or a new software that needs to be designed and engineered, to just bring in folks that have those technical capabilities.

What we need to layer on top of that, whether it’s a part of the mix of the people that are doing it, or just an additional individual that’s quote, unquote, “assigned to that work,” is someone that’s going to be able to think about team dynamics, is going to think about enabling functions around how do I get the team to work best together? How do I get them to understand what each other’s strong suits are? What are the means of communication for partnership? How do I best encourage collaboration? How do I make sure that we’re unified under a singular mission and vision, and ultimate target objective? So that quality of basic leadership, and then of course managing tasks from a project perspective, and then also just understanding how this fits into the broader model from an org effect in this point of view.

These are important skills on top of the technical skills. To your point, those are types of roles, and those types of skill sets, they may not be specific to the technical nature of the project, but it’s what actually helps blend it together, and really ensures that there’s a good output. It’s a skill that you can’t ignore when you’re building teams in such a way.

Stuart Crainer:

We’re nearing the end of the session. Looking forward, where does this all go next? In 5 years, 10 years, the relationship between technology, work, jobs and skills, where does it go?

Tanu, perhaps you could have a first go at looking at a crystal ball for the future.

Tanu Jain:

Of course, there’s a lot that’s happening in the workforce landscape today. AI, we are hearing about innovative technologies, new and innovative ways of working, and use cases of AI every day. Skills, a lot of organizations are already on their journey to embed skills as the foundation for a lot of the way they hire or their overall talent landscape in the organization.

I think it’s hard to predict, but it’s going to be very interesting to see how organizations evolve. Like I said earlier, some are way ahead in that journey. Some are catching up. I think there is a lot to be discovered where I think when we talk about AI and skills, organizations are at different stages today. Some have made a lot of progress, and they understand where their business is getting impacted, they’ve already embedded and deployed some AI, they have moved forward.

Some are still in that education phase. A lot of organizations are at a stage where they understand that they need that, and that they’re going to get impacted. No denying about it. But they’re still discovering, and trying to identify what do they really need when it comes to AI.

I think organizations are at different stages. That links to how they then need to start thinking proactively about how to reshape the work, how to start rethinking about the work and skills we’ve had. We talk with some clients where they know that, “Okay, four months or five months from now, we are going to have major process impact as a result of this AI we are going to deploy. How should we already start thinking about the work, and our people?” That’s where this methodology, and tool has been helpful.

We have initiated those discussions. To keep it short, I think what I would say is a few years from now, five years from now, definitely a lot of organizations would be at a different stage altogether. I think skills would be the foundation of a lot of what they’re doing, and how they’re thinking. A lot of progress is there to see, is what I think. Anything, Tim, that you’d like to add?

Tim Flank:

Yeah, I was reflecting a few, just not to force a mnemonic on it, but there’s three P’s that come to mind for me. I think precision, being predictive, and then power are the things that I think organizations are going to continue to embrace over the next 5 to 10 years.

What I mean by that is I think as these technologies learn more and more around the optimal combination of talent and automation, and what works best, it’s going to enable organizations to be more targeted around the profiles that they want to hire. It’s going to enable organizations to be more precise around the skills that they need to develop in order to be successful. Then from a power standpoint, it’s going to just really enable organizations to leverage the data and information that they have available to them, and really, really much more, I’d say unique, and interesting ways in terms of how they’re going to shake the norms of certain industries. I think that’s going to be one of the biggest unlocks in all of this, is the sheer decision-making power, and sheer power of these technologies in basically helping them really think through, and work through all of this available information to create insights, and direction for their particular products or services.

Stuart Crainer:

Thank you, Tim. Thank you, Tanu. We’re out of time. That was a really interesting discussion about work design, and how the future of work is unfolding.

Thank you everyone for joining us from around the world. Please join us for our next session on the 16th of October. That’ll be the final webinar in this four-part series. In that session, we will have Ravin Jesuthasan, and Tanuj Kapilashrami crystallizing the key messages from their book, The Skills-Powered Organization: The Journey to the Next Generation Enterprise, which is published by MIT Press. Thank you once again to Tim. Thank you to Tanu. Thank you to everyone who’s joined us today. Thank you.