Episode 11

Cia: Welcome to Employee Activation, the HR podcast that takes you into the minds of some of the world's brightest workforce strategists to find out how they make both their employees and their organisations thrive.

Companies know more about the chair their employees sit on. Its cost, its depreciation, its place on the balance sheet than they do about the person sitting in it.

That's something today's guest Richard Pedley says often, and he's right. In a world where people are an organisation's greatest asset, we've got to start treating them that way. That means knowing their skills, understanding their potential, and activating them into roles where they can do their very best work.

Richard has worked in the learning and development space for almost 20 years, most recently with Fidelity as Head of Talent Experience. Over this time, he's seen the evolution of L&D firsthand, but his recent work is especially exciting. Designing and embedding a skills framework that's helping 10,000 people find their next step inside the organisation.

Richard, very excited to have you on the podcast.

Richard: I'm very excited to be here. Thank you.

Cia: Now, Richard, I just wanted to start with the, the chair quote that I mentioned earlier, that companies know more about the chair their employees sit on than their actual employees. I just love this. It's very provocative and in a very simple way captures exactly why so many organisations have a skills problem.

Can you unpack it for me?

Richard: Yeah, so it, it actually came stolen, I suppose, from an event that my colleague attended. And yeah, we both use it a lot because it resonated so much with us. Historically, organisations have spent a lot of time, a lot of effort into knowing the exact cost, for example, that an employee has - their salary their benefits, the energy.

The heating that's required for the, the chair, the role as it were, uh, the technology that they need to supply to them, how much all of that costs, all of that's very known and very detailed and very accounted for. But actually when you start getting into the more human aspects of the, the person, their capabilities, their skills, passions, work, ethics, interests, curiosity.

All of that gets measured usually somewhere on a scale of one to five once a year, which is odd, right? Because there, there is a lot of cost associated with all of that. That's all productivity, that's all things that people can make or build or contribute to, to the organisation, to your customers, they can sell, et cetera.

We don't necessarily know that in the same way. We don't understand cost of, of losing those people, right? Losing those skills or the cost of not developing those skills and those skills that are changing. So I find it odd. Yes. I suppose that the companies spend so much effort in the, I guess the fundamental cost, right?

The, the dollar value of a, of a chair of a role. Don't spend the equivalent in understanding the human that's sat there.

Cia: Yeah. And it's, it's that leading indicator versus lagging indicator thing as well, isn't it? It feels very retrospective the way that people have always, or employers and organisations have looked at their people, you know, how were, or what has been the previous quarter, as you said, the previous 12 months.

And I'm really keen to understand why you think it is. So obviously we know that organisations haven't typically captured the information that they, they need about their people, but why do you think they've historically struggled to really understand their people in the same way that they think about assets and inventory.

Richard: Working in HR, I've got to put my hands up to this along with I think everybody else in the industry should be right. I think actually HR have a lot of accountability for this. Our ability within the broader HR, not just L&D but HR as a whole to, to kind of collect people data, hasn't moved on since we have people processing widgets.

Right. When we moved into this kind of new knowledge workspace, HR has not kept up with the requirements around understanding people and people data, and I don't think it's that the business are unable to do it. I think it's that the business doesn't understand the importance of it and therefore chooses not to do it.

And I think HR has a, has a big role in accepting that part of that is, is down to us, right? We haven't done the job that we need to do, to enable the business to understand the business need for collecting this data. We talk a lot about employee experience and, and we use a lot of research to demonstrate that obviously employees that are engaged make, you know, are more productive, et cetera, et cetera.

But that's very theoretical, it's still very hard to measure. You're relying a lot on external research, but you can't really put a dollar value for that specific business to it. And a lot of that comes down to, to us, right? Because we focused on that and we've not focused on, you know, the fundamentals that sit underneath that for individual businesses.

Cia: Yeah, it's interesting, and I suppose it depends on the organisation that you're coming from, because I hear from a lot of HR leaders that understanding skills and building a skill framework and understanding employee capability is something that they've wanted to do for a while. They've been thinking about doing it for a while.

But until recently, it hasn't been a strategic priority for the organisation, whether that's the executive leadership team or the board, uh, who are now looking across their workforce. They're seeing the impact of AI augmentation and automation. They're realising that this skills problem that the media has been talking about for a while has arrived at the doorstep of their organisation.

And it's almost like HR for the first time are empowered to start to take a bit of action here, I think. Is that, how did it play out at your organisation?

Richard: I think that's fair, and I think there's, there's a mix, right? Maybe I'm, I'm being harsh on HR. I guess economics are part of this as well, right? You know, the world, the world's moved.

We can't just keep hiring the skills that we need into organisations and, you know, on, on an indefinite basis and accepting the cost of people leaving and, and the, the hiring cost that then comes with that and finding rare talent and rare skills is obviously, you know, increases that cost. Organisations can't continue to do that in the current economic environment.

So there is that aspect to it as well. Uh, I think within our own, that's probably a big part of the shift to skills. COVID was a, was for us, a big driver. We found during COVID that actually we were quite successful, which came as a surprise to us. We, you know, within financial services, we thought COVID would be, would be a difficult period for us, but it was actually very much the opposite It was some of our more successful years we've ever had.

But as a consequence of the COVID, what you found is we have people that were incredibly busy. Incredibly busy. And then you had a large portion of your staff that had nothing to do. Um, because a lot of the work, a lot of the projects were getting paused, you know, where you reliant on other parts of the, the supply chain to support us, weren't able to.

Um, so skills really came into the driver there for being able to move people from parts of the business where perhaps we were less busy into those, where the, the demand was very high. And being able to do that in an effective way and skills is a great piece of data that will enable you to do that. By finding those adjacent skills that people have, that means you can upskill them, you can put them into projects or gigs quickly, and they can grow quickly because you know, they have a skill that is closely linked to what you need them to do, even if it's not exactly the same.

So COVID was a big driver, coming out of COVID, uh, the years have not been success, so successful in the current economy. So that, again, has then moved us into, well, how do we take some of that success that we have and embed that more strategically into the organisation on a, on a more scalable and long-term basis.

Cia: Um, so what did that look like in terms of going out and building a skill framework and then starting to map and understand the skills of your employees? Was that a department-by-department exercise? Talk to us about what it actually looked like.

Richard: I, well, I think I would say at the start, yeah, I don't think it's ever finished.

I don't think anyone's ever finished a skills framework. I don't think there's ever an end point, and I think that's a critical piece that the business also needs to understand, right? This isn't a one and done and then you leave it for, you know, 10 years and you come back and look at it again. You have to have someone continually own it.

For us, it was very much, uh, I guess pick your battles. It was very much department by department, area by area. What I would say is we are in a good technology place now. AI is, is your friend in creating skills and understanding skills to roll and, and, and those sorts of things. I think the other thing that that is important is understanding how deep you need to go within the job architecture, when you are defining skills. Do you really need to go all the way to an individual position or is actually a, a kind of job profile that sits slightly above that and groups those positions together, is that deep enough for what the business requires or that particular department requires?

So a lot of work needs to start, I think, in that kind of job architecture data perspective, understanding what you already know, understanding how your job architecture is structured and governed, and then finding areas of the business, departments, locations that will benefit the most and are already, a fairly open door to the conversation.

Cia: While we're on job architecture, that is one of those common blockers we hear about organisations who have very messy job architecture, terrible position descriptions. How did you guys navigate that?

Richard: We still are, I think is, is the, is the simple answer that's not, there's no magic bullet to an ungoverned job architecture. Really start with, where do you need to get to within your job architecture to start bringing benefit? It doesn't need to be perfect, but it needs to make a start. For us, that was job profile level. So we have job families, job family groups, and then job profiles. If we get to the profile level, which thankfully for us is governed and has had a governance kind of around it, so when people weren't randomly creating them, that gives us enough from a business perspective for us to understand the roles that sit within your organisations and the skills those roles require.

What we have found is that obviously, like I guess a lot of organisations, when we built that structure out, our descriptions of those job profiles, were not built for skill inference. So we have to come back and we have to start looking at each of those job profiles with the business and really think about the tasks that those job profiles will be doing very clearly and defining those tasks well, I think there's a desire to start defining the skills.

We tried that it didn't work, uh, asked you this, there's too much variance in people's opinions about what a skill is, for example, and you end up, you know, going round in circles and actually a task is much clearly better articulated, better easily understood by an organisation.

And then you use the AI to do what you are paying for, right? Which is to infer skills from those tasks based on, uh, on market knowledge. That's, I think the key is how deep do you want to go with your job architecture? There's no magic bullet. You're going to have to clean it. Look at it area by area, right?

Pick those areas that really matter and get really good task focused descriptions for those parts of the job architecture you need to get.

Cia: That's great advice. So if we fast forward through the messy middle and we get to the outcomes, so you've got this perpetual framework in place, people are mapped.

You understand the skills in place, what are some of the outcomes that you've been able to achieve as an organisation in terms of how you've used that information?

Richard: So I'm going talk, I, I guess mostly about our kind of pilot work because we haven't finished, um, again, we're, we're still on this journey. We haven't got it all right. We're still learning as we're going, uh, going along. But from a, I guess from an individual impact perspective, what we've already started to see is actual career conversations, and I, I say that in its nicest possible sense, even when you had like pre-skills data, even when you had a really, really good line manager, what you would tend to see is open role discussions.

So when you're talking about careers, it wouldn't be about, you know, all of the opportunities that might exist, whether they're open roles or not within the organisation, it would be based on, well, let's look at what the vacancies are and where we think your next step could be into one of those. Let me help you apply for that job.

That's not a career conversation, right? That's an open role conversation. But it is almost impossible for any line manager in a large organisation to have a really good career conversation without skills data, without being able to visualise all of those different roles, profiles across the organisation, see the skills, see where the skills the individual has versus the skills that are needed, and have conversations about how to grow those.

So we've seen a, a great growth in our pilot areas in those conversations starting to happen, and actually happen with more line managers because it's easier for the manager to do it. We've also seen risk mitigation from line management. So what I mean here is kind of that, what are the gaps in the skills that I have within my team?

How do I, you know, help people to, to, to learn from each other, but also take independent learning where needed to, to kind of close those gaps so that I'm not exposed as a team to some of those areas. And we've also seen a great increase in speed to competency because we can find people that have adjacent skills to those that are needed, meaning it's much quicker for them to develop and grow the skills that we now require.

From a enterprise or business perspective, we're able to start making much better strategic data-driven decisions across all sorts of things. Be that location strategy, be that hiring strategies, be that areas that you want to invest in learning and development, whether that's identifying roles, for example, that may be subject to change because of AI. And actually how do we upskill those people into newer roles.

Skills that are emerging, that actually in the market we don't have internally, and rather than go and buy expense, we can start to grow now so that we become more common, we have a population of people that can do those things. There's a huge amount of benefit, cost saving, strategic direction, et cetera, et cetera, that you can get from skills data.

And we've found that our most open areas to those conversations are our operational areas. Because of the huge amount of cost reduction, they can start to get quickly because they tend to have the highest turnover. And then from our technology teams, again, just because of the growth in emerging skills and the number of emerging skills they're starting to see, being able to get ahead of the curve with them is, is incredibly exciting for, for that population.

Cia: We've referred to that before as the skill lag, and it kind of speaks to that concept of the skill half-life with the fact that particularly in those tech teams skills are becoming redundant at a far more rapid rate. And unless you want to be lagging behind, how can you get ahead of that problem to start to address it, you know, before it is that problem. So I love, I love to hear that.

I would love to also hear, Richard, your advice for someone starting out, because I do feel like we are at a point where HR leaders are often starting off on their skills journey. We've been talking about it for years. It's now a strategic priority. The business is ready, the HR team is ready.

What would you say to people who could learn from your experience?

Richard: Number one, uh, definitely from our experience, start with your job architecture. Start with the data that you have now. Understand it. Find it all because I will, I can almost guarantee someone somewhere in your organisation, if it's big enough, is probably already doing something with skills.

They may not call it skills, but they're probably already doing something. So find all of that data that you've already got. Find all of those pockets. Start with your job architecture. Understand how deep you need to go in your job architecture to get to skills and clean your job architecture, even if it is area by area, but get it clean.

Get those summaries, those descriptions well written, focused on task. What is the thing that this role is going to be doing? Very clearly articulated, because if you do that, A you can let your AI do the hard work for you.

Cia: Mm-hmm.

Richard: And again, you need to position this with the business. It's almost a you go, don't get to decide business what the skills are. You get to decide what the tasks are, and we'll use these millions, billions of points of data that the AI can access from the market to tell us what those skills will be. Right. That's, I think, key. But it also enables you to then get a really good head start on thinking about rewriting your job descriptions to be very skills focused.

Having a good job architecture underpins everything, so I would definitely start there. That was a painful learning for us. The second piece I would say is get the right tech partner for you. Everybody has different needs. Everybody will want different things. The most important thing that we've learned from a tech partner over and above even the, the bolt-ons that they can give to you, is its AI capabilities and its ability to support those people to understand the depth of skills they have as well.

So AI will be critical to help you infer skills to a role. It'll be critical to help your employees get a head start on skills they think they have by looking at LinkedIn or, or job profiles or, or CVs, et cetera, et cetera.

But also get someone that will support you to help them understand the depth of those skills. Because again, a lot of it is very subjective at this point in time, and a lot of employees are not used to talking about skills.

Cia: Now look, the last question I'm going to ask is one that we ask all of our guests, which is, what is your top tip for activating your employees?

So aligning the aspirations of your people with the goals and objectives of the organisation so that both can just thrive.

Richard: Mine. And this, I guess, is a little mini frustration of mine for many years, and I think a new frustration of a lot of HR professionals and a lot of L&D professionals. We see the business doing this so well with our customers, and we need to start treating our people like our customers.

And what do I mean by that? Businesses have an innate and deep understanding of what their customers want, what their needs are, how they can meet them, and then they sell to them. We need to do that with our people. We need to have a really deep knowledge about what our people actually want. We talk a lot about career progression, about the next step in the ladder, whether that's sideways or upwards, squiggly careers.

But actually, a lot of people in the organisation just want to come to work. They want to do their job really well, and they want to go home, and there is nothing wrong with that, but we don't talk to those people. Then we wonder why we have big disengagement. We demand our employees should be driving their own career.

We tell them they own it. We tell them to have those conversations, to drive those conversations with their manager. We have a huge number of employees that are not that self-confident and find that very difficult, but again, we don't necessarily speak to them and sell to them.

So know your employees really well. Know what they want, sell to them like you would to a customer. Link that desire, that purpose, that drives them and engages them to your company and objectives. There's always a way somewhere. Capture your data and use it. And then lastly, I guess, build all of your processes around that data and that understanding of your people.

Often we will build a process and then we'll go off and we'll ask our employees what they think of said process and then we won't do anything about it. But actually if we just take the data at the start, ignore the process, and then build the data about the process of the data, you'll end up in a better space.

So yeah, for me, I guess it's, it's treat your employees like you would treat your customers. There's no difference.

Cia: And it beautifully comes full circle, I think, to the chair quote at the start. At the end of the day, if you know your people, you have the data on your people, you can treat them like your organisation's greatest asset, which is just wonderful.

Look, Richard, thank you so much for the discussion today. It has been so insightful to hear from someone who has walked the path before, who has already done this extraordinary skills exercise that many are embarking on, so thank you for being so transparent with sharing your experience.

For anyone who would like more information on Fidelity or Richard, please head to our website, it's the withyouwithme.com website and head to employee activation where we'll have loads of resources as well as Richard's LinkedIn profile so you can get in touch direct with any questions.

Thank you again for joining us, Richard, and we will see you all next time.