Most leaders believe they have a reasonable handle on their workforce capability. They know their team. They’ve done performance reviews. They know who’s strong and who needs development.
The problem is that belief is usually built on job titles, gut feel, and training completion rates — not actual skills data. And the gap between what leaders think they know and what’s actually true is what our second joint webinar with Digital Skills Agency set out to explore.
SkillsTX CEO Paul Collins and Digital Skills Agency Managing Director Daniel Merriott joined host Mary-Anne Merriott for a conversation on what they call the ‘skills fog’ — and why the decisions made inside it tend to be slower, riskier, and more expensive than they need to be.
Here’s a recap of the key themes from the session.
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1. The skills fog
The session opened with a deceptively simple question: what does the skills fog actually look like in practice?
Paul’s answer: sometimes it’s too much data, poorly structured.
“What I see very often is a skill taxonomy or a skill inventory that is literally 40,000 tags. How are you going to work through that fog?”
— Paul Collins, SkillsTX
Daniel identified the other extreme: organizations where workforce capability is essentially leadership impression. Not necessarily wrong, but heavily subjective and skewed. What someone did last month tends to crowd out what they’re actually capable of over time.
And then there’s the middle ground both speakers kept returning to: job titles used as proxies for skills. ‘We’ve got 25 business analysts’ sounds like useful information. It isn’t. Twenty-five people with the same job title can have wildly different capabilities — and different team leaders will define the role differently again.
“I’ll bet those 25 business analysts all do something slightly different, and if you talk to their team leaders, you’re probably going to get 50 different definitions of what a business analyst is supposed to do.”
— Daniel Merriott, Digital Skills Agency
2. Knowledge isn’t the same as capability
One of the sharpest distinctions in the conversation was between knowing something and being able to do it, and how easily organizations conflate the two.
Paul used the analogy of a pilot: you trust a 747 captain because of 10,000 hours in that aircraft, not because they passed an exam. The credential matters, but the demonstrated experience is what actually earns the responsibility.
Daniel put it from a hiring perspective: a 22-year-old with a master’s in project management knows more than most about project management theory. That doesn’t mean they’re ready to set organizational strategy.
“There’s an assumption that if you know something, you can translate that into getting things done. We all know people who are awesome at advising, but they’re not necessarily the people you turn to to get stuff done.”
— Paul Collins, SkillsTX
This distinction matters because most skills assessments — and most training programs — are built around knowledge, not demonstrated capability. Ticking the box on a training course raises someone’s knowledge. It doesn’t automatically raise their skill.
3. Performative skills data quietly enables bad decisions
The session spent real time on something most organizations don’t talk about: what happens when skills data starts reassuring leaders rather than informing them.
Daniel’s diagnosis: overconfidence. Projects take longer than expected, cost more, or quietly get rescued by contractors — not because leaders didn’t care, but because they assumed capability they couldn’t actually verify.
“At what point did you actually ask: have we got the capability to do this? If you had that, you could start addressing it as a project risk at the beginning, instead of getting partway through and scrambling to hire contractors.”
— Daniel Merriott, Digital Skills Agency
Paul flagged the version he sees most often: biannual performance reviews, 20 hours of training logged, box ticked. It looks like a healthy team. It doesn’t tell you whether anyone can actually do the things the organization needs done.
The antidote he suggested is treating skills data the way you treat financial data: with trust, currency, and a degree of external validation. Stale financial data wouldn’t inform a business decision. Neither should stale skills data.
“You get your financial data audited, for goodness’ sake. You make decisions from it that make or break your business. The same is true of skills.”
— Paul Collins, SkillsTX
4. What minimum viable skills visibility looks like
Mary-Anne pushed both speakers on a practical question: what’s the minimum level of skills visibility a leader needs to make better — not perfect, but better — decisions?
Daniel’s answer was two lenses:
- Team leaders need current skills profiles for their people. Not the profiles from when someone was hired — those go stale fast, and faster in larger teams.
- Senior leaders need to see how their skills portfolio aligns with the capacity demands they’ve committed to.
Paul added the piece that often gets missed: the mindset that skills belong to the person, not the job title. Work done on a project — even a three-month project — builds skills that should be recorded and carried forward. Most organizations don’t capture that. Most LMS platforms don’t either.
“The thing I did in that project has now made me better at three other things I might not have had initially. That’s not recorded. And yet if it was, it automatically flows through to current skills data.”
— Paul Collins, SkillsTX
5. What better decisions actually look like
Once skills are visible, what changes first?
Paul brought it back to the individual: visibility gives people the ability to make real choices about their own development and career path. A business analyst who’s been in the same role for years might have the skills to move into project management, or pivot to a different part of the business — but only if they (and their manager) can see that.
Daniel went to the other end: strategic workforce planning. Organizations that have skills data before a transformation — not partway through — can make the build-versus-hire decision with actual evidence. They can identify who’s ready to grow into new roles, where the gaps are, and what capability needs to be built before the work begins.
“It really comes forward into a people-first view of planning, which tends to be more successful.”
— Daniel Merriott, Digital Skills Agency
One client example Paul shared made this concrete: an organization moving to a product-led model defined the future roles first, mapped them against current workforce skills, immediately identified who was ready, and found the gaps that needed either development or external expertise. Importantly, when they brought in experts, they knew exactly what they were trying to transfer — so the investment had a purpose beyond filling an immediate vacancy.
6. How to talk about skills with your executive team
The session closed with a practical challenge: how do you make the case for a skills approach to a leadership team that doesn’t speak SFIA?
Daniel’s framing was straightforward: strip out the jargon and come back to execution.
“Capability is your ability to execute. Your executive team is accountable to the board for executing on the strategy. The question is: can we do this? How do we know we can? And are we effective at doing it?”
— Daniel Merriott, Digital Skills Agency
Paul’s version was the governance angle: show the supply/demand gap. What does our capability look like against what we’ve committed to? When that chart has a lot of red, it tends to get the C-suite’s attention — particularly now, when organizations are pouring investment into AI without first asking what capability they actually have to absorb it.
Key takeaways
- The skills fog isn’t always a data shortage. It’s often too much data, poorly structured — or too little, poorly trusted.
- Job titles and certifications are proxies for skills, not substitutes. Filling positions doesn’t mean you have the capability.
- Knowledge and demonstrated skill are different things. Most training programs build the first and assume the second.
- Performative skills data biannual reviews, training hours logged — gives leaders false confidence. The measure is wrong.
- Skills data should be treated like financial data: current, trusted, and subject to external validation.
- Once skills are visible, individuals can own their development, leaders can plan ahead, and organizations can make build-versus-hire decisions with evidence.
One action you can take right now
We closed by asking both speakers for one concrete action a leader can take in the next 30 days.
Both gave the same answer: adopt a consistent, well-tested skills taxonomy. SFIA is the one they recommend for the tech and digital workforce — not because it’s the only option, but because it’s done the hard work of defining skills at each level of depth and responsibility, which means you can actually compare data across teams, departments, and time.
Paul added one qualifier: don’t just grab the framework. Understand how to use it. Organizations that apply SFIA as a binary yes/no — do you have the skill or don’t you — are missing most of the value.
Daniel’s second action: once you have a taxonomy, build objectivity into the data. That might mean bringing in an external party to run assessments, or asking teams to provide feedback on the teams they work most closely with. Do something to make the data less subjective — because self-reported skills data that hasn’t been stress-tested isn’t data you can make decisions from.
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Can’t watch right now? You can read the full transcript below.
Full transcript
Mary-Anne:
Welcome. Thanks for joining us today.
We are going to be talking about something leaders feel but often can’t name. We call it the skills fog.
This is when you can’t clearly see the skills and capability you have, and that means decisions get slower, riskier, and more reactive. Skills fog is what happens when your skills and capability aren’t truly visible. So today, we’ll talk about how that impacts decisions and what practical skills visibility looks like without drowning in the data.
So, we’ll focus on three things: what breaks when skills aren’t visible, how performative skills data misleads leaders, and how skills visibility creates better workforce decisions.
We’ll keep our discussion practical and leadership focused.
By way of intro, my name is Mary-Anne. I’m the Head of Client Success at the Digital Skills Agency, and I’ll be facilitating today’s discussion between Daniel Merriott, who is the Managing Director at the Digital Skills Agency, and Paul Collins, who is the CEO of SkillsTX.
I’ll be off camera most of the time, so we keep the focus on Paul and Daniel.
Let’s start with an introductory question. Daniel and Paul, can you share one sentence each on what lens, what perspective you’re bringing to the conversation today? Let’s start with you, Daniel.
Daniel:
My lens really is about workforce capability and organisational design. And we use tools like SFIA to help our clients understand both aspects of that.
Paul:
I’m going to play right off that, Daniel, because the lens I’m going to bring, the perspective, is the data that’s behind that. We’re all about system of record here at SkillsTX, and good data helps make good decisions, and we’re going to clear the fog today.
Mary-Anne:
I like the sound of that. So, let’s talk about what it looks like.
How often do you tend to see the skills fog actually out in the wild? What are the signs? Paul, why don’t we jump in with you first. What are the signs of skills fog that you see?
Paul:
Yeah. You know, the way that I summarize this, and fog is an interesting term. Obviously, it’s clouding visibility, and sometimes it’s too much data.
So, what I see very often is a skill taxonomy or a skill inventory or a register that is literally 40,000 tags. And it’s like, how are you going to work through that fog, morass, whatever you want to call it? So that’s certainly what I see, and I use the question a lot when I meet an organization. “Do you have a register?” “Yeah, here it is. The bigger the better.” Mm, not really, so…
Daniel:
Yeah, I’ll play off that and say I’ve also seen the other end of that, where actually what we have is honestly just leadership impressions of team performance.
That’s not necessarily a bad thing if you’re thinking about capability. That is actually the ability to execute.
But it does have a lot of drawbacks, one of which, of course, is it’s very subjective, and the other is it’s often very firmly biased, with a strong recency effect, so biased to what the recent experience has been. It’s not necessarily a great way to predict the future or predict what the team can do.
And of course, in a changing world, that’s actually pretty important.
Paul:
Yeah. Actually, Daniel, there’s something as well that crosses my mind that’s sort of somewhere in between, I guess. And that is we’ve been brought up in an organisational structure type environment with job names and position descriptions and such like.
And quite often, those job titles become a proxy for a skill register. “Hey, we’ve got 25 business analysts.”
Well, I can guarantee those 25 business analysts have all got different skills when you just dig down a layer. So that’s the other side of it. We’ve got all the positions filled, but it doesn’t mean you’ve got the skills.
Daniel:
And I’ll bet you those 25 business analysts all do something slightly different, and if you talk to their team leaders, you’re probably going to get 50 different definitions of what a business analyst is supposed to do.
Paul:
Yes. And that is a rabbit hole we go down often.
Mary-Anne:
So, when leaders say that ‘we understand our workforce capability,’ what do you think they’re usually basing that belief on?
Paul:
I’ll let Daniel go with that. You speak to them probably more than I do.
Daniel:
It is that they have a good impression.
I’ve yet to meet a leader who doesn’t feel like they have a view of their team’s capability. It’s a basic thing a leader is supposed to understand.
But I’ll point back to have we actually got data that we can trust around there, and I’d always ask the question, how do you trust your data?
Paul:
That actually leads exactly to, we’ve got consultant 101, a phrase that we use, which is the skill assumption conundrum. And the first part of that in the Venn diagram is the skills we think we have, and quite often, that’s good enough for many leaders.
It’s like, yeah, okay, we got, I say it might be job titles, or I’ve got a fairly good feeling that I’ve got a good team, but it doesn’t necessarily mean that you’ve got every T crossed and I dotted when it comes to actually truly understanding.
And I’ll actually bring in a really true story here.
We did some conversations with some employees, and one person in particular was really quite upset coming into the conversation because there was a part of her job that she was really… In fact, her exact words were, “Every Sunday night, I do not sleep because I have to present a report on Monday morning.” And it was part of her job. She produced the report. It was beautiful, but the bit she didn’t have was the presenting of it. And as soon as we uncovered that, it was an immediate straight back to the boss, “I need some training in presentation skills.” Done. That was it.
So, I think, again, that extra level of nuance in the data is important rather than the assumption.
Daniel:
I think that’s going to come onto something I’m sure we’ll talk about later, which is definitions.
So, for you and I, skills are about getting something done. What you uncovered there was actually, there was a skill that person needed some support and training in, and it’s not just report writing, a sort of broad task or responsibility. So yeah, the precision is important.
Not to be too uptight about the language, but when you’re actually trying to say, “What data do we have? What is it we actually understand?” If you don’t know what the data’s representing, you obviously don’t have a good understanding of what you’re looking at.
Mary-Anne:
And let’s talk a bit more about the impact of some of those decisions that happen when you don’t understand the data you’re looking at.
So, Daniel, can you share something that you’ve specifically seen go wrong with a leadership decision when they didn’t have visibility of their skills? Maybe pick an example and walk us through it.
Daniel:
Yeah. So, I think skill data’s the same as any other data. So, it’s used to inform decision-making.
I think of a past client where the assumption was that they had depth in their cybersecurity skills because they genuinely have some people who had a lot of knowledge and expertise.
Our assessment, having gone and worked with each of their team, was they were lacking depth, particularly at the operational space. And I think there was a comfort felt because the leaders had their expertise and actually were quite proud of their expertise.
So, we actually got a lot of pushback from that organization around our assessment.
Unfortunately, a few months later, they actually did suffer quite a serious cybersecurity threat. And their lack of ability to respond was actually a big factor in making that issue a lot worse.
So, I wouldn’t wish that on any organization, of course. But I think that that was a big difference between what the leadership impression of their skill was, often skewed by their own skills and capability, and their own knowledge.
But that really led them to feel, I think, probably a little bit safer than they actually were, and a little bit overconfident perhaps.
But yeah, not everything’s as catastrophic as that, but that’s an example where the decision making was, “We really don’t need to do much about this. We’re quite happy.”
Paul:
I think those big brand reputational events sort of catch the eye.
And I have to say, every time I see one, back to what you just said there, Daniel, I read behind it, I bet there were some skills missing.
But on a much more — well, it’s still got an impact — but decisions around upskilling and at the appropriate time.
So, we’ve all got finite budgets when it comes to learning and development. Sending somebody on a training course to rebuild a Ferrari engine when actually what you need is operational cyber skills. But genuinely, and especially now in the world of AI, we are seeing so many people get trained on completely irrelevant aspects of it. Just a blanket approach. We need to train everyone on AI. And those bad decisions ultimately can lead to what you just said, really, Daniel. We just didn’t fill the gaps properly. We didn’t deliver the training when and where it was needed.
I’ve been on the opposite side with a classroom full of 16 people, and 2 of them were there because they needed to be. The rest had just been sent along. And it’s depressing and frustrating for everyone concerned. But with the right data, that wouldn’t have happened. We’d have had a group of people in there that actually needed what the knowledge transfer was all about.
Daniel:
We’re back to definitions again, too.
So, sending someone on a training course is actually about raising their knowledge.
We spend quite a bit of time coaching and training and supporting people leaders on how to have better development conversations. And the first thing we look at is if you’re going to raise someone’s knowledge, how are they going to put that to use? And can we find some opportunities that hopefully are things you need to go and do anyway? So, let’s find some opportunities that are coming up. Give people the knowledge so you can trust them to go and do the work. But also, let’s find peer support or a senior who can act as a mentor, and also act as a quality assurance for things that matter.
But yeah, that’s separating a difference between skill and knowledge. There’s an assumption that if you know something, you can translate that into getting things done.
We all know people in everyday life who they’re awesome at advising, but they’re not necessarily the people you turn to get stuff done. And we know some people who can get stuff done who aren’t great at advising. They’re two different skills.
Paul:
Completely. It’s the old adage, “This is your captain speaking. I read the book and passed the exam. Let’s give it a go.”
It’s not what you want to hear, is it?
And I think that really comes back to that skill fog and the assumption. It’s amazing how many people will use the zero one, the binary. Do you have a skill, or don’t you have a skill?
And as you just pointed out there, Daniel, it’s not how the world works, is it? We get that knowledge that we build upon, and if you’ve done the 10,000 hours as a captain of a 747, you’re trusted to fly the plane.
Daniel:
That’s one of the reasons why they measure the number of hours flying that pilots have, and not just flying, flying in that particular type of aircraft. It’s directly relevant. Experience is crucial.
I can remember interviewing someone who more or less came in and sat down and dropped a whole bunch of certificates in front of me, and one of which is, “I have a master’s in project management. I must be the expert in project management.”
I have a background in project management. I said, “Actually, you probably know more than I do. But you’re 22. You’ve just come out of university. You’ve really had no substantive job in your life. How are you accountable for setting the organizational strategy on project management? You’re not at that level. Actually, you know more than you’re allowed to do right now. Actually, part of your career path is gaining the trust of the people around you, your leaders, so that you can take on more and more responsibility. The pathway you’ve got to go on is you know what you need to know, but actually, you now need to go and develop the opportunity and gain the trust that you can get things done.”
So that was quite confronting for that person, but I think they understood at the end there’s a difference between knowing and getting it done.
Mary-Anne:
Let’s talk about the kind of false confidence that leaders can have about their skills. Paul, what do you think is the first question leaders can’t answer when you try and test how well they actually understand their skills portfolio?
Paul:
I think it does come back to the language that’s used. It can be very ambiguous. So, you’ll get an answer quite often that sounds very credible, but when you just scratch the surface a little bit, it is just a lot of fluff words.
I know, as I said, I’m winding back to what we were discussing earlier, that job titles become a proxy for what they think people can do.
I’ve even come across data where you can load your job in and it’ll say, “I know what skills you’ve got because I know what your job contains.” And it’s like, whoa, that’s a bit scary. So, yeah, I think, again, touched on the same thing. It’s that assumption that just jumping and a little bit as Daniel was talking, certificates becoming proxies. You went and got your cloud engineering whatever, therefore go do cloud engineering. Very dangerous.
Mary-Anne:
Let’s talk about when skills data becomes performative.
I’m wondering, what do you think skills data looks like when it starts reassuring leaders, but it really shouldn’t be reassuring leaders? And what kind of bad decisions does that data quietly enable? Daniel, let’s start with you.
Daniel:
Ultimately, it leads to overconfidence.
The measure that we see for that is projects that take longer, or don’t succeed, or cost a lot more, or ultimately need to be filled by contractors because we just assumed we had the capability at the outset.
One of the things I will step back and say is, at what point did you actually ask, have we got the capability to do this? And every bit of it. And then if you had that, you could start addressing that as a project risk right at the beginning, as opposed to getting partway through and needing to scramble to hire some contractors to help plug some gaps.
So, it’s overconfidence. Often, it’s not catastrophic, but it does result in things taking longer, costing more, and ultimately reduced confidence from people outside of that team.
So, if you’ve got a team leader who is constantly overconfident, their senior leaders are actually gradually going to lose that confidence in them over time.
Paul:
Yeah. One of the things that I wouldn’t say struggle with, but we’re very conscious of, so you talk about performative data there, and that drives a behaviour straight off the bat.
We know what the end game there is and we have biannual reviews and we tick the box and I’ve got a great team because we went and did 20 hours of training.
Completely the wrong measure. Totally the wrong measure.
And when I look at it from a skills data perspective, I’d much rather replace the word performative with development, and see it as an aid to development of skills.
But I agree with what you just said there, Daniel, completely, that those assumptions play out in probably almost every project you see, and then there’s a scramble to bring the contractors in.
And I’ve even, out the words of a CIO when we were saying, “Let’s do a skill assessment and understand your data.” And it’s, “I haven’t got time to do that. We’ve got a big Red Hat project, and we need to get it up and running.”
My response was, “So you’re going to start a project that’s dependent on skills without knowing the skills you’ve got because this is more important than the thing it’s dependent on.”
But everyone had done the performance reviews, so hey, they had a great team.
Daniel:
I see the same thing playing out with long-term planning, too.
So, a lot of our clients, particularly in government, they’re working on a 10-year life cycle and a three-year detailed plan. Lots of initiatives in there, lots of great ideas, lots of things you’d love to support.
What I don’t see in them very often is, we don’t have the capability for this yet, so the thing that comes first is initiative A, we’re going to build that capability so we can do initiative B.
It’s awesome when you see that, but sadly, that’s lacking in a lot of organizations’ planning — actually building that new capability as a normal initiative.
That capability ultimately is the ability to execute. The exec are actually in charge of making sure that they can execute on their strategic plans.
Mary-Anne:
Let’s talk about skills visibility.
Daniel, what would you say is the minimum level of skills visibility that leaders need to have to make better decisions? Not necessarily perfect decisions, but useful decisions.
Daniel:
I think I’d probably take two lenses on that.
One is for team leaders. I’d like them to see the skills profiles of their staff, and I’d like that to be current. They often know lots about the people that they hire, and then three months in, honestly, everyone’s too busy, so that kind of gets lost, and if you’ve got a larger team, it gets lost even more.
But at the senior leadership level, I’d like them to see how their skills portfolio aligns with the capacity demands that they have, the things that they’ve promised that they’re going to do.
So yeah, I think that’s two simple lenses, I think, to look at that.
Paul:
Yeah, I totally agree that that visibility into your team.
And there’s another aspect to this that plays out quite often, and you touched on it previously, Daniel.
We’re all too busy. We’ve got a job to do. Keeping a skill profile up to date so you can make good decisions is just another thing that you’ve got to do on top of all the millions of things you’ve got to do.
And yet what often is missed, and this is a leadership thing as much as the individual, plays from a mindset of we own our skills. The job title can throw it away. The skills are the skills. And not recognizing that the things that you do improve skills that you may already have knowledge of, or you’ve practiced it enough that you’re the go-to person relating to that skill.
And quite often, that’s not recorded. And yet, if it was, it automatically flows through to current skill data. The thing that I did in that project that ran for three months has now made me better at these three other things that I might have not had initially, or I might have just got better at.
So, that really, alongside of the skill profile, is the development activities that keep that up to date. And they are very sadly missing. I see training, development plans because most LMSs, that’s what they do. But that’s just a knowledge bit.
Daniel:
I think I’ll bring it back to the data, too, and I think there’s a lot that’s in people’s heads that’s never captured. And honestly, it’s not difficult to capture that.
And obviously, some data is better than no data, but I’ll come back to questions I asked earlier on around when you’ve got that data, why do you trust it?
And then the other bit, which I think is relevant to what we just said, is it current? Sure, that was great data two years ago. Is it current now? Think about how you would use your financial performance data. If you don’t trust it and it’s not up to date, why are you using that to make decisions?
And now play that back in terms of your people capability. If you don’t trust the data that you have about your capability or it’s not current, why does it make sense to use that to inform how you make decisions?
Paul:
That’s a great analogy. I’m going to steal that one. I’ve got a few analogies of my own, but that one I really like because it’s that stark.
You get your financial data audited, for goodness’ sake. And you make decisions from it that make or break your business. And the same is with the skills.
As you were saying before, Daniel, you make decisions off bad data, you end up with a cyber breach of some description. Worst case.
Mary-Anne:
Let’s have a look at some of the results of those better decisions.
Paul, once people have more visibility of their skills, what kind of decisions do you see changing first?
Paul:
I’m going to bring it down to one thing, and I’m going to do this from a very personal lens.
It gives people opportunities to make decisions about their own development and career progression.
I might meet a business analyst who’s been doing it day in, day out. It’s all getting a bit too ho-hum. Next job, senior data analyst, but in actual fact, they might have brilliant skills to move across into the project team, like as a project manager or even like that concept of transferable skills.
But if you can see it, then you can make choices.
So, I love that concept of pivoting, especially for the young’uns around, like yeah, I’ve actually got some skills that will apply in this other part of the business that really attracts me.
Now, of course, that translates up through team and enterprise levels to workforce planning decisions. But down at an individual level, I think it’s just great to be able to compare yourself to all the roles in the business and see where you would fit.
Mary-Anne:
Daniel, what do you see?
Daniel:
I think the knock-on effects — Paul’s talked at the individual, so I’ll go the other end — will be the strategic workforce planning. And that’s where when you have skills data.
And then you’re thinking about going and doing something new or transforming. What tends to happen is there’s a question of, okay, so what does our data tell us about our ability to do that?
And that’s where that gap that I talked about before, which is we are going to need to hire some new people because it’s too expensive to build this new capability or develop people quickly enough. Or actually, we can grow and develop some people into these new roles. The nature of the work is going to be changing, so we’ll put in place a program for doing that.
That tends to happen ahead of the transformation, as opposed to getting partly through the transformation and realizing we’re actually struggling to deliver the transformation and also to operate in the new way.
So yeah, it really sort of comes forward into a people-first view of planning, which tends to be a bit more successful in terms of what I’ve seen.
Paul:
Yeah. I’m just going to bring in an example of that.
One of our clients was moving to a product mentality, moving away from the sort of structure of the standard project and development teams to this product management type view. And that was the first thing they did. They defined the roles of what the future looks like.
They played that against the current workforce, immediately identified people who were ready to move on that journey, and found the gaps where they needed to put a lot more development, and usually en masse. “Hey, we need relationship skills. Let’s bring that in and do it,” or whatever.
And then, of course, where the other gaps were, it’s like supplement, as Daniel was saying, with we’ll bring in experts. But the even better thing with that is we bring experts in and we know what skills are missing in the workforce.
We know what they’re bringing in. We start working on transferring that so that going forward, we have built that new strategic capability to meet that future demand.
But to me, I always still like to bring it back down to the individual. At the end of the day, you’ve got people that perform tasks, and if you’re anything like me, I like performing the ones that I like doing.
And when I can see that. I can also see the ones I don’t like doing, but I know I’ve got to.
Daniel:
Now, I might just come back to something you said earlier, Paul, which is at the individual level.
Something we see when there’s more clarity around skills data is individual staff members taking more responsibility for their own development, and that takes the load off the people leaders.
So it actually doesn’t make their life harder, it actually makes their life easier because a lot of their staff, honestly, not everyone, but a lot of their staff are then starting to come up with their own plans, their own suggestions, and linking it to, “This is why it’s relevant to my team.” Or “There’s an opportunity come up you’ve given us a heads-up on. That’s actually really useful for that development gap that we talked about last week. Can I volunteer and put myself onto that? And here’s what I’m going to do.”
So yeah, it actually reduces the workload on the people lead once you’re able to enable and support your staff. Never mind staff satisfaction and those kinds of things that we know improve, and the change in culture, and actually, you become a nicer place to work. People want to work with you.
But yeah, just thinking selfishly about people leaders, it actually makes their life easier.
Paul:
That’s 100%. Yeah, that level of visibility and understanding that you are a collection of skills, not just a job title, and you move to the next job title in the list, is a very powerful awakening.
I know you and I use various terminology, but one that we use very much at that starting the journey to actually document what you can do in a more consistent fashion is actually an exercise in self-reflection.
Fantastic. You’re building a skill inventory. But to take a step back, and even to the point of, what do I like? Well, I know I can do that, but now I’m reading what it actually is, I’m not too sure I actually like it.
We had a client that ran an assessment across the whole workforce and came up with the skills of the individuals, comparing it to what they needed.
And they found out that 6% of their leadership didn’t want to be leaders when they actually saw the skills that were needed to be a leader.
Now, that’s pretty scary stuff.
Amazingly, they put a layer of people that like doing those skills into the structure that did the things that those leaders didn’t want to do.
So, they become more operational and task-driven rather than people development driven.
Yeah, so and that’s really back to clearing that fog and, in that case, yeah, don’t like the look of that skill. Didn’t know I had to do that.
Daniel:
There’s a really good topic for probably another day, but around actually how we use clarity in skills to have better position descriptions.
So being clear on what the difference between a functional manager and a people leader are, and they’re not necessarily the same thing, even though they’re often lumped together.
Mary-Anne:
So, there are a lot of people out there who are interested in pursuing more of a skills approach for all of the reasons that we’ve just been talking about, to help themselves out of the skills fog and all the benefits that that can entail. But making that accessible to the wider business, in particular, talking to your executive team about them, is not always easy to do.
So, Daniel, I’m wondering if you can give us an example of how to talk about skills and a skills approach without jargon.
So, what’s something an interested leader could say to speak to an executive team about this to clarify what is the value of using a skills approach?
Daniel:
So, let’s just come back to what is capability again.
Capability is your ability to execute, and your executive team are accountable to their board for executing on the strategy that’s been agreed.
So, I think I would say if you don’t have a clear picture of can we do this? That’s just a simple question. Can we do this and how do we know that we can? And are we effective at doing this? Then you’re missing a trick.
So, I would hope that boards are asking their executive team, and their executive team are replying with good answers around, “We can do this, and this is why we know,” or, “We can’t do this yet, this is what we’re doing to address that gap, and then we’ll be confident that we can do this.”
Paul:
Yeah. Actually flowing on from that, and it’s got a bit of a negative connotation, but if we’re coming at it from a governance risk and compliance perspective — and you look at the harm that can be done to a business overall if you do not have the appropriate skills, can get their attention.
You don’t need to worry about the jargon. We can convert this into a supply/demand graph if you want. So that’s what we look like and that’s what we need. And there’s a lot of red on it.
We actually have an analytic that I call the OMG or, if I’m being cheeky, the WTF.
Because when that chart appears and it shows capability against requirement, exactly what you were just saying there, Daniel, that is the investment picture, whether that’s upskilling or whatever it might be, and that generally gets the C-suite’s attention.
Daniel:
And I think if you’re looking for a step-changing capability, linking it to your strategic plans and actually, “This is why we need to develop this new skill, this is why we need to train and support our people, because you’ve asked us to do these things.”
Now you’re starting to have much better alignment rather than, “We just want to send more of our people on training.”
Paul:
Yes. Go and implement AI. When? Now. Why? We don’t know. Yes, that classic.
And of course, seriously, though, that’s a big deal out there right now. But my goodness, the number that are just jumping into it without asking that first question, what capability do we have?
Definitely, again, getting the board attention because there’s a lot of wasted money going on that right now.
Daniel:
On the AI side, I would actually ask what capability does the AI bring?
Is it actually autonomous enough to actually provide skills independently, or is it actually something that supports and enhances someone’s skill or transforms someone’s knowledge into a skill?
So, what’s the role of the AI and what’s that going to do to your workforce capability?
Paul:
It’s certainly an interesting one.
At the end of the day, an agent is something that’s executing, whether it’s fully autonomous or human in the loop or whatever.
But at the end of the day, if you’re using a proper taxonomy to describe it, you’re describing your agents exactly the same way you’re describing your people.
And that is a powerful piece of data, for sure.
Daniel:
But there’s a challenge in workforce planning that we see quite a lot, which is how do you compare capabilities of staff to the model of going out to a supplier? Do we bring it in as a contractor?
And obviously having a skills taxonomy and assessing the three of those using the same taxonomy really helps with weighing up the options.
God, there’s a fourth now, which is do we leverage an AI to help us do it or to do it for us?
So, I think, yeah, there’s now four areas we need to look at in workforce planning.
Mary-Anne:
So, for people who are interested in moving towards this sort of approach, I’d like to hear from both of you, what is one action you think a leadership team could take in, say, the next 30 days to start reducing their skills fog?
Paul, let’s start with you.
Paul:
Selecting a consistent taxonomy, preferably one that someone else has already put all the hard yards into. Clearly a plug for Skills Framework for the Information Age.
But I’ve seen a lot of frameworks and I have to say, if I was running a big enterprise, I’d be leveraging the intelligence of the industry, and that’s done the heavy lifting. And now my 60 different project departments are all describing a project skill in the same way instead of it, so that would be the takeaway. Agree on a consistent language.
You don’t have to be SFIA, you might be in a different industry but agree on a common language.
Daniel:
Oh, Paul, you stole exactly what I wanted to say, which is use a well-tested, relevant industry skills taxonomy.
Not just because it’s good at the individual, but if you want to aggregate the results across all of your teams and individuals, whether you’re 10, 20, 30, hundreds of people, you need a taxonomy in order to be able to scale up that data in a meaningful way.
Paul:
But selecting or at least exploring industry taxonomies that are out there that are well-tested and reliable, et cetera, is one thing, but understand how to use them.
My goodness me, I know a lot of organizations using SFIA, and it just, like, oh, you didn’t read the book, did you? You just grabbed the framework. And back to what you were saying, Daniel, I’m seeing, here’s a skill. Do you have it or not? I feel good today. Yes, I do. Had a bad night. No, I don’t. It’s just crazy stuff. To some degree, very dangerous, actually, in terms of decision-making.
Daniel:
I’ll add in one more thing for the 30 days, which is when you’ve got a framework, build in some level of objectivity to the data so that you can trust it.
So that might be bringing in an external independent party like ourselves or SkillsTX to help with assessments.
But that might also be something like asking teams to provide feedback on the teams they work with the most and then looking at the spread of results that comes back, rather than asking a team leader how good are your team.
So just do something to build some objectivity into the data you’re using to help with decisions.
Mary-Anne:
Thanks very much, Daniel and Paul. This has been a really good and insightful discussion today, and that brings our discussion to a close.
Thank you again to our viewers for joining us today, and if you’d like us to go deeper on a particular skills or capability challenge, please send us your questions. This webinar series is shaped by what leaders want to know, and we look forward to seeing you all again soon.
About SkillsTX and Digital Skills Agency
This webinar is part of an ongoing series from SkillsTX and Digital Skills Agency on workforce capability.
SkillsTX is a skills intelligence platform built around the SFIA framework, helping organizations understand, measure, and build their digital workforce capability.
Digital Skills Agency works with organizations on workforce planning, capability development, and the people side of technology change.
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