Innovating Leadership:
Co-Creating Our Future

Resources:

Learn more about Brian’s company (and the neuroscience behind it) at https://richardsonconsultinggroup.com. Information about his roundtable session is online at https://richardsonconsultinggroup.com/skills-roundtables.

Our host, Maureen Metcalf, posts a newsletter every week on LinkedIn. You can subscribe here.

Maureen’s latest book is Innovative Leadership & Followership in the Age of AI. You’ll find details about it at https://bit.ly/LeaderInAI. Her other 10 books are available on Amazon here.

Books we’re reading for fun or personal development right now include:

• Everyday Ubuntu: Living Better Together, the African Way by Mungi Ngomane. Hardback (https://amzn.to/48Doh6j) and audiobook (https://amzn.to/48YCRF4).
• Nerve: Lessons on Leadership from Two Women Who Went First by Martha Piper & Indira Samarasekera. Paperback (https://amzn.to/3tOtzg4) and audiobook (https://amzn.to/41OYdT5).
• Jilly Truit murder mysteries by Beverley McLachlin:
  • Full Disclosure – https://amzn.to/46TxW6Q (paperback) https://amzn.to/46VDL3Q (audiobook)
  • Denial – https://amzn.to/46YCbhs (paperback) https://amzn.to/3GJc0AA (audiobook)
• Women and Leadership: Journey Toward Equity by Sherylle J. Tan & Lisa DeFrank-Cole

NOTE: As an Amazon partner, we may make a small commission from books you buy through these links.

Guest(s):

Guest(s) Bio:

Brian Richardson is Founder and CEO of Richardson Consulting Group (RCG).  RCG helps organizations unlock their hidden human potential by creating transformative learning experiences, putting performance support in the flow of work, and driving behavior change at scale. Brian has been a featured speaker at global and local events for the Association for Talent Development, the International Society for Performance Improvement, the Finance Development and Training Institute, the Project Management Institute, and others. Brian also hosts monthly executive roundtable skills-based organization (SBO) strategy and implementation sessions, where leaders come together to share challenges and best practices on how to use skills-based approaches to improve business performance, organization agility, and employee experience.

Transcript
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Maureen: [00:00:00] This is Innovating Leadership Co-Creating Our Future. I’m your host, Maureen Metcalf, founder and CEO of the Innovative Leadership Institute, where we help leaders be future ready. Helping us in that mission today is Brian Richardson, founder and CEO of Richardson Consulting Group. We’ll be talking about leading the skills based organization.

Brian, thank you for joining us.

Brian: Thanks for helping me, Ryan. So, skills based organization is a recent conversation. It’s both old and new. Skills is not new, but skills-based organization has taken on kind of a new life. And really the core idea is moving from jobs orientation to a skills orientation. So you’ll hear terms like pixelization of work or atomization of work.

It’s really breaking work down from this idea of we move work to jobs and functions. Two, [00:01:00] we really take a skills-based approach, which is much more of a micro approach. So this cuts across a number of different dimensions, including business strategy, talent strategy, talent lifecycle, and it really affects job and workflow design, the design of work, because we’re moving work to skills and not to jobs.

So. Fundamentally, it’s about having a better understanding of our people’s skills. So what can they do? What can they actually accomplish as well as their potential? What are they able to accomplish given the right opportunity, given the right support, and we’re able to manage the workforce in a much more adaptable.

And flexible way that kind of the future of work. So it’s really has wide ranging implications. It’s an organization transformation. This is not like a one and done project. This is really a multi-layered, multi-year transformation type of effort. And it’s gonna land differently in different parts of the organization at different places and different times.[00:02:00]

Maureen: As I think of applicability, there are a couple things that come to mind. I’m working with a client right now, traditional manufacturing company.

Brian: Mm-hmm.

Maureen: They are, quote, modernizing. So as many organizations post COVID ID, how do we operate now so that we can meet the challenges that are coming at us. It sounds like using a skill-based approach is crucial in taking a slice of how do we get the work done rather than, I’m trying to make sure John stays busy all day.

Brian: Exactly. And manufacturing is a great example. Manufacturing you need is becoming more digitized. There’s more technology, there are more screens and so forth in manufacturing facilities, and we’re starting to see skills-based. Approaches enter into the workflow. In manufacturing, just as one example, there’s systems called Connected Worker and that are being deployed in manufacturing environments.

If I come into my shift, I come out [00:03:00] to a machine and let’s say I have to do a machine setup. So in these connected worker platforms, when I log in and knows who I am, and it knows what my experience and skill level is with that equipment. So if this is my first time setting up the equipment, I’m gonna get a really detailed step by step, by step by step procedure for how to set up that piece of equipment.

If it’s something where I’ve done this a hundred times, I’m gonna get more of a checklist type of assistant on the screen. At the same time, that system is collecting information on, did I complete that sub? Did I do it correctly? And it’s feeding that into my skill profile and then adapting the experience the next time that I come into that machine.

So, for example, if I miss a step or something like that, it might gimme some additional information or support on that step the next time I come in and do that task.

Maureen: This is brilliant. As we think through this connected platform, could say, if I’ve run this batch, a connected worker [00:04:00] framework and technology could pop up a similar batch

Brian: ahead.

I mean, a lot of my background is in the learning development and performance support. We’ve been talking for years about in the flow of work.

Maureen: Mm-hmm.

Brian: Getting support in the flow of work and that’s increasingly possible with ai, with these skills-based approaches where it’s kind of this always on system where it’s gathering data about what I’m doing and how I’m doing and then adapting my experience, personalizing it to me, the level of support that I’m getting, the learning that I have access to, the opportunities that are presented to me.

Based on my skills and capabilities, that is something that is accelerating in terms of trend of getting it into more and more spaces where people are doing actual work. We had the manufacturing example, but this is also starting to get into systems of work for knowledge workers teams, slack chat, even Microsoft Office.

Google applications. They’re increasingly [00:05:00] AI enabled, adaptive, and really data rich in terms of how they’re collecting data about my skills and capabilities, and then adapting my experience and the support of that experience to what I can do and what I could do in the future if given the right support and opportunity.

Maureen: Let me pull another example from back office. ’cause we’ve used manufacturing and production. If I add someone new to my team who’s gonna use my finance system to start paying invoices

Brian: and it

Maureen: would it similarly then pop in a job aid for welcome to X financial program. Here’s how you do X task.

Brian: Exactly.

There’s adapting it to like what the system will have. It will know something about me. How often have I done this task? How experienced am I with it? Have I done it in the past? At what level? Proficiency, and then it’s gonna adapt the support of that experience to whatever my current capability is. We’ve had systems of performance support in one form or another for a very [00:06:00] long time, but it’s kind of a one size fits all.

You know, I have access to online help or job aids or procedures, but what we’re seeing more and more now is this adaptive. Personalization driven by AI and other tech where it’s really conforming the level of support to my current task and level of proficiency and ability.

Maureen: Say I have a high turnover role.

Brian: Is it

Maureen: I run a restaurant? I would certainly build the job aid so that if I have a 25% turnover a year, I can accommodate that. What if I’m running a smaller business and I don’t have the capacity to build all of this tool set? Are those built in to the larger platforms? The job aids and instructions?

Brian: They can be.

It’s a trend and it’s gonna increase some, not. I’m not gonna tell you that every single system has this adaptive technology built into it. But what I am saying is that as we look to the future, that’s gonna be more [00:07:00] and more commonplace in these type of systems. The tech is there and it’s just the adoption and the implementation of it and how quickly that’s gonna occur, but it does exist in many systems.

I gave a connected worker example. I mean, those are out there. Are they being used in every single manufacturing facility to date? No. Will they be in the future? Most likely, because I think the value stream with being able to do this level, skill-based personalization of experience at scale is a competitive advantage.

And so at a certain point, if you’re not doing it, you’re gonna be left behind by those that are.

Maureen: One of the points you made early on is it promotes adaptability. Mm-hmm. And as we think about the speed at which organizations will need to change, the example I read in, I think in the Wall Street Journal was how long we used an Axe before we went to a chainsaw.

And we still use chainsaws, right? We right. I mean, there were technologies that are used for thousands of years and any [00:08:00] person using that tool has time to master it before they go to the next one. The time we have as workers, including senior executives to master a thing before we go onto the next thing is short, right?

But we’ll continue to elevate assistance and that will allow us to adapt and remain competitive.

Brian: That’s right, and I think more and more of these systems are gonna become increasingly personalized. Increasingly adaptive skills is really at the heart of that because of skill is really what is my ability to create a result is one definition that we use of a skill.

And if I’m surrounded by systems that know what my ability to create a result is. And then are able to support and assist me in creating the results that are requiring that in the current situation. But that’s just gonna continue to, to expand into more and more systems of work.

Maureen: I assume most of the leaders listening to this are listening through the lens of how do I create competitive [00:09:00] advantage?

And many of the workers and supervisors and managers are thinking both, how do I stay competitive and how do I also help my company stay competitive? Let’s talk about a case. Study now that you’ve used that helps us make this more concrete rather than just conceptual.

Brian: What organizations that we talk to, and I talk to literally hundreds of organizations that are engaged in this type of work, is it’s really not about skills per se.

It is about solving problems with skills-based approaches. So identifying a business problem, something very concrete, and then taking through utilization of a skills based approach, solving that problem in a way that’s gonna make a difference for the business and for the people in the business. There has to be really a double or a triple win.

It’s gotta be a win for the organization. It’s gotta be a win for the employee. And really what we’re finding also is it’s gotta be a win for the managers, for people leading teams. [00:10:00] They have to be winning too through these skills-based approaches. So it’s not like this bolt-on extra thing that we need to think about or action against.

It’s something that needs to be integrated into the business. And like I said, it’s really solving a preferably urgent business problem. So just a couple examples. One is a very large industrial equipment manufacturer that is taking a skills-based approach to their jobs, to their career pathing. To their learning strategy.

It’s really comprehensive, but at the same time, they’re taking a very deliberately simplistic approach. How this shows up in practice is. They said, for each job we’re gonna identify eight skills. Eight. The reason we’re doing eight is not because eight is all the skills that are needed for each of those jobs, but because it’s gonna enforce a discipline of what are the most important eight, what are the most critical to success for that job or that role.

And then also by limiting it, it [00:11:00] makes it more scalable. See, jobs has a quote. Simplicity scales, complexity, fails. That is definitely true in this skills conversation. We see organizations that are not as successful that really get themselves wrapped around the axle of defining this four layer taxonomy of skills on 37 per job or role that in an effort to be comprehensive and complete.

They box themselves into something that that doesn’t really work outside of that one narrow use case. So when we look at this industrial equipment manufacturer, they stubbed their toe a number of times in trying to do this, and then they finally became fairly relentless about keeping things as simple as possible so that it would scale.

And they had like 150,000 employees globally, but they’re identifying that eight skills, it’s only eight. You can have any eight you want, but you can only have eight. And the engineering department fought against that because they have 40 or 50 that they think [00:12:00] are required for each shop. And that’s fine, but for the purposes of what we’re trying to do across the organization, you, you just have to prioritize the ones that are most critical to success for each of those roles.

Maureen: Well, you and I both came out of Accenture together.

Brian: Mm-hmm.

Maureen: While we may not have narrowed it to eight, we certainly had that sense of scale that the thing we sold was people doing work. So we had an inventory of humans, and next to those humans were a set of skills. You win a job in Kansas City building something.

So implement a system, build out the training program, build out the change management project, define the processes. You go through the inventory, who’s available and who can go on that job. And we all have to be able to show up and work kind of interchangeably.

Brian: Mm-hmm.

Maureen: Kind of mental construct allowed us the flexibility that as clients begin and end, as people get promoted and build new skills, you shift around in the inventory.

[00:13:00] We were able to adapt to market changes pretty quickly.

Brian: What is also important about that example is that there’s a baseline of not just skills, but also behaviors that were hired for, promoted within the consulting firm. So you hired for people that were detail oriented. People that were self-starters.

For example, people that were continuous learners because the pace of change, I was hired in and my first role was COBOL programming. Well, that is still a thing. There is, I, I think something like 70% of the financial transactions in the world still run on cobol, but the demand for COBOL programming is significantly less than what it was 25 years ago when I started.

Now we’re onto Python and r and. Other programming languages, other technologies in the mainframe systems that were kind prevalent when I started. But by having people that were adaptable, I learned cobol, but I was able to adapt to client. Server [00:14:00] was kind of the next big thing. Eventually object oriented programming and those kind of things.

But by having some of those baseline traits of being detail oriented. Having good problem solving skills, curiosity, alluring mindset. Those are the types of things that you needed to succeed over time in a consulting firm. Consulting firms and technology firms are some of the very early adopters and some of the more advanced use cases for this skills-based because it comes very naturally to them because that’s the business of consulting.

It’s always been a knowledge based, a steels based business, and so as you get. Better tools, better tech, better approaches to really leverage the skill sets, build the skill sets of your workhorse on a continuous basis that’s so core to those types of businesses, that they’ve really been at the forefront of some of the adoption of these skill face approaches.

Maureen: The other thing that was prevalent that I think you’re alluding to is we had some kind of knowledge management, in fact, an incredibly robust knowledge management [00:15:00] system, and it sounds like the worker assistant tools now would be a more sophisticated version of, instead of, I have to go figure out and sift through the range of deliverables, this would kind of serve up to me, here’s an example or a use case for this situation.

Brian: Yeah, A really simplistic example is. Google search, like I’m typing a question or something that I’m interested in, into a search. I’m getting back the top 10 results and then I’m going through those to try to find the answer to my question to. We’re down in Chad, GPT world where I just type my question and then I just get the answer to that question.

I’m not scanning a bunch of different sources to try to find the exact information. I’m getting the exact information presented to me. And what we’re talking about with these systems of work, it’s just gonna increasingly be hyper-personalized, hyper adaptive, hyper aware of my context, my goal, what I’m trying to accomplish, and it’s going to [00:16:00] be continuously supporting me in accomplishing whatever it is that I’m trying to do.

I mean, there’s obviously a lot of complexity. You just think about the roles of somebody in finance versus somebody on line in manufacturing. I mean, the use cases are many, many, many of them. But particularly with artificial intelligence and its ability to really deal with a lot of data, be able to reliably, if not invalidly, but reliably predict certain like kind of next things that I’m going to be thinking about or doing.

To be able to anticipate and then to create an experience around that really is adaptive and supportive is really I think where we’re headed in the future.

Maureen: I see that evolving, and back to your point of where we are using it consistently, we will have a competitive advantage over people who are not.

We’ve heard this phrase before, but I, as a leader, I’m not competing with AI for my job. I’m competing with people who use [00:17:00] AI versus people who don’t. Similarly, my organization, if it leverages AI effectively and leverages tools like skill-based tools, effectively I will compete better than people who are still using legacy mindsets and tools.

Brian: Just the example that I gave earlier about a search. And go poke around a bunch of resources to find an answer. Versus ask a question and get an answer. I mean, the efficiency gains are incredible and they’re enormous, and that goes straight to productivity for the organization. So being able to adopt these type of approaches at scale is gonna be very important part, uh, the future for really every organization.

Maureen: Given that is the business case, that if I wanna succeed and thrive in what the next two years, I should probably already be making some of these adjustments.

Brian: Skills and skills based organization. I mean, it shows up as a top three issue across C-level [00:18:00] executives, certainly for HR learning and development talent practices.

It’s top of mind, top of the agenda for a lot of organizations from the C-Suite as well as the people suite. Are working on this and really trying to figure out how to adopt these approaches in their organization. Where does it make the most sense? It’s not unlike digital transformation, which almost every organization is engaged in at some level.

What does that really mean? What it really means is it’s solving problems for the business, for customers, for employees. In a different way, in a digital way. This is in a skills-based way and like digital transformation. It is not the end all be all, like you have to be a hundred percent skills all day, all the time in everything that you do.

That’s not what this is about. It’s about using these approaches, being able to gather this data about skills at scale, being able to adapt experiences, personalize those experiences at scale. That is [00:19:00] going to really give organizations another really robust set of tools to advance the productivity of their organizations, the career opportunities for the people in those organizations.

Roles are changing quickly. The demands of the marketplace are changing quickly and using these skills, skills-based approaches gives organizations a way to be more adaptable, to be more resilient. To be more able to flex and be agile in the face of demands that are changing very, very quickly.

Maureen: If I am an executive interested in making this shift and I call you and say, I’m running a billion dollar organization, I heard your podcast and I wanna explore this.

Brian: Mm-hmm.

Maureen: How do I start?

Brian: What we’ve developed through the conversations we’ve had with organizations and seeing what’s successful and where people get tripped up is what we call a. The four s model, start somewhere simple. Sue, if you’re a leader, engage your HR talent organization. [00:20:00] If they’re not already working on this or thinking about it, they should be, and their task is not to go away for six months and figure out your skills architecture or your data model, or perfecting something that nobody outside of HR cares about.

Pair them up with a partner. Another function within the business that has an urgent problem. It’s an attrition problem. It’s a career development problem. It’s a learning problem, something that relates to skills and have them work together. To solve that problem with the simplest possible skills-based approach.

Don’t go into it thinking that you need new tech. You don’t need new data streams. You don’t need a robust taxonomy that’s gonna stand the test of top for the next five years. You need a problem to solve. You need a list of skills. And you need a strategy and approach to solve that problem through skills based learning, skills based support, skills based coaching opportunities, whatever that [00:21:00] might be, but just putting that lens on that problem to solve it in a novel way, and then with an eye toward what’s gonna scale.

You’re gonna implement some things for, let’s say you’re doing it with it as your business partner, and they’re gonna work on that, and they’re gonna do some things that work in it that are gonna have to change when you go to manufacturing or engineering, or finance, or your customer service. But that’s okay.

They can put some stakes in the ground in terms of what’s gonna work, what’s gonna solve this problem today. With an eye toward what? What’s gonna scale for other problems, other parts of the organization. That future,

Maureen: unlike some transformations where I have to have a strategy, everyone has to follow the same approach.

We have to be able to plug it in. So if I’m looking at data cleansing and a data dictionary, everyone has to use the same terms, or we end up with a pile of mush. In this case, it sounds like different groups can go off and experiment concurrently. [00:22:00] We don’t need that level of standardization here that we would in something like having consistent data across the enterprise.

Brian: Yes and no. I do think that what we have found Microsoft is actually a good example of this. One thing that Microsoft will tell you that they did early on that was very important was getting the language consistent. So what do we care about? What’s a skill? What’s a competency? What’s a capability? How do those things relate to each other?

Just some of those, and it all fits on one page. It’s about 10 things that they had to define, but they got that definition so that everybody’s working off of that same understanding of what we’re talking about when we talk about deals, when we talk about building capability, what does that mean? I do think having that level of consistency and language is important because organizations that don’t do that have run into trouble because it is gonna show up differently.

For example, in this frontline manufacturing, they’re [00:23:00] gonna define the skills themselves at a much more granular level than like your finance or your HR department is gonna have a much higher level of naming per skills. They’re gonna talk about things like problem solving. Whereas in manufacturing, they’re gonna talk about solving a problem with this piece of equipment that malfunctions in a very specific way.

But the definition of what a skill is can be consistent across those two groups, even though the level of granularity where they drive the detail of what they care about is gonna be quite different, if that makes sense.

Maureen: It does. And this then leads me to, so now that I have all the skills map, I still need to then map those two 10 people show up to work this morning.

How do I make sure that people with the right skills show up in the right spot in the right chair? To get the work done.

Brian: That’s one of the core use cases or really sources of value, is that that staffing, being able to put people in the right spots at the right time. From a very [00:24:00] practical standpoint, again, I’ll use a manufacturing example.

If somebody doesn’t show up, I need to know who else can do the job of that person that didn’t show up. And I don’t have a lot of time to figure that out. I mean, I need that information. I need that data at my fingertips. Either somebody that can do that job or somebody that can learn it really, really quickly.

In the skill space, we have this concept of skill adjacency, like what skills that I have are similar to other skills that makes it an easier lid for me to learn this new thing because I already have this baseline and this other discipline. Having that kind of visibility into what my workforce is capable of doing as well as what their potential is, like what could they do if I give them the right level of support, if I give them learning opportunities, if I give them assignments or job opportunities that enable them to.

Develop in a way that’s gonna serve their interests and goals for their personal development, their career, et cetera, but is also gonna be, it’s matched to what the [00:25:00] organization needs to do to be successful.

Maureen: This sounds like a very different culture than some of our traditional organizations where I have a job description and I do what’s in my job description and when things change.

My job description gets updated and I start doing the new thing. Mm-hmm. This sounds more like a larger percentage of organizations will have a culture like we did in consulting, where you started as a COBOL programmer and you ended up doing human change management. That’s a bit of a jump, and you may not have had a lot of input into that shift.

Brian: I do think that’s a good analogy. The career path at that time was you start as an analyst first two years or so. That was your title. Analyst could mean cobalt programmer, it could mean training developer. It could be a bunch of different things, but your, your job title was analyst and then you move to consultant and then manager, senior manager, et cetera.

That is something that is a consequence of this skill-based [00:26:00] approach in that the job descriptions. Are gonna be much broader, they’re gonna be much more flexible in terms of career levels. Salary is gonna be much wider ranges because you’re gonna have, based on people’s skills, you’re gonna have people in certain roles.

Let’s take this consultant role as an example. Instead of staying in that role for two years, they might stay in it for 20 years, but their skills are gonna continue to develop. Their capabilities are gonna continue to develop. And their compensation is gonna have to reflect that. So it’s gonna be much broader definitions of those roles.

And it’s gonna be more emphasis on the skills. What can you do? What is your potential, what are your goals and interests? And then from a career development standpoint, it’s less about can these ladders where you just kind of keep going up, up, up in the organization, increasing levels of responsibility for other people.

It’s gonna be more, and we’re seeing this already. More of a, a lattice type of metaphor where people are [00:27:00] moving across, not everybody’s gonna move into a, into a supervisory role, but they’re gonna be able to continue to progress. Advance both their career as well as their compensation based on the skills that they’re developing and the value that they’re adding to the business, whether or not that involves managing other people.

Maureen: So I become the world thought leader in X. I may never supervise anyone, but that world thought leader role entitles me to a larger compensation because I’m more valuable to the organization. The other path would be I have a lot of adjacencies, so I’m a. Chemical engineer. I may know how to work on a broad range of products.

I may also work in new product development. If somebody doesn’t show up to work in the morning, I may be in the lab. One day. I may be on the plant floor. One day I may be working with clients. That level of fluidity across my skillset also makes me worth more than the [00:28:00] person who can just work in a plant.

Brian: Right, exactly. Skill-based compensation is not a new thing either. You have in a plant environment, if you’re able to do more different roles, you tend to get paid better. Again, you don’t necessarily need to be in a supervisory role, but if you can troubleshoot and fix different pieces of equipment, if you can operate that equipment, you grow your value because you’re growing your versatility.

And you can fill a bunch of different roles and there’s, there’s a lot of value in that and the compensation for that. Polls,

Maureen: some of these concepts are not new. We’ve been talking about them for decades. It sounds like though, where it may have been optional, it is now required for most, if not all organizations to maintain strategic advantage.

Brian: Yeah, I think so. What’s different in a sense, this skills story is really a data story. Our ability to collect, analyze, and action data on a scale like never before. [00:29:00] I don’t wanna make it about tech because that is also a mistake that organizations make, which is investing in new tech way too soon before they figure out the problems that they’re actually trying to solve and how this is gonna show up in their organization and in their culture.

But it is really behind why this conversation is top of mind, because it is knowing what our people can do at a really granular level and be able to action that data at scale. That is something where the capabilities are evolving very quickly and being able to deploy that in our organization in a, a smart, focused way, it can create a lot of value.

I mean, just think about. If you have work that needs to be done and every day is gonna be different in terms of what’s most important and what’s most critical to the business. And if you’re able at scale to take that most important work and give it to the person with the [00:30:00] minimum level of skill required to do that work that’s available right now, if you’re able to do that at scale.

I mean, that is a massive productivity play, and that’s really what organizations I think are moving toward. But this is not a buy a new platform and plug it in and hope for the best. Hope is not a method, this is an enterprise transformation in terms of mindset, culture, you know, the way we think about work, the way that we design work, the way that we design jobs, the way that we design roles with the way that we design organizations.

It affects all of it. And we have to get all of it tuned in such a way to, to really take advantage of what the data management, ai, other technologies are offering us in terms of capability.

Maureen: We talk about skills leaders need in the age of ai, and as I listen to you, one of the things I’ve been bouncing in my head is.

What does the [00:31:00] organization of the future look like? What does the performance management process look like? How do we compensate people? How do we make the job exciting and help people stay engaged in a time where if you value stability, this is gonna look like one of Dante’s rings of hell. You don’t get to have stability anymore.

In most organizations, your job’s gonna change before you ever get comfortable with it. So how do we help actual humans navigate those changes? And how as organizational leaders, do we even think about organization of the future?

Brian: You know, there is a sense of skills-based organization. Again, I’ll use the analogy of agile organization or digital transformation.

It’s not a destination. It’s not like, oh, okay, well we’ve arrived. So now we’re a skills based organization. It is something that is a transformation. It’s gonna happen at a different level, gonna land differently and [00:32:00] different parts, even within an organization, based on the nature of the work, based on the roles, based on the skills, the problems that need to be solved, the value that needs to be delivered in those different contexts.

Again, where organizations kind of stub their toe is they try to solve everything for the organization all at once. You know, sort of the boil, the ocean approach. Like we’re gonna have this universal skills taxonomy or job architecture that’s gonna work for everyone in the organization at all times, you know, and now and into the future.

And that’s just not the right way to approach it. It is starting somewhere simple soon, doing proof of concepts and pilots and these kind of things and starting to build. Really the skills muscle within the organization, within the culture. I mean, this is a big culture shift for a lot of organizations and then be able to build those pieces and parts that are gonna scale.

And then at a certain point you do start to bump up against some constraints in terms of technology platforms that you have or the data [00:33:00] environment that you have. And you, you do need to solve those problems. But where we see organizations being successful is they’re very strategic and purposeful about.

The problems I’m solving today versus the things that I’m gonna worry about later. I’ll give you another example. Big insurance company. And what they were really solving for was internal mobility and opportunity, and they very purposely did not gather a lot of skills data. They didn’t really address their job architecture, but their skills architecture.

They strictly wanted to create a culture of mobility, and so they, they were implementing a internal talent marketplace as part of this, but what they did for the culture, very important strategic decision they made at the very beginning was that managers did not need to review or approve employees applying for other opportunities.

And these opportunities could be just like projects that they worked on in their current role. There was some internal roles that you [00:34:00] could apply for, but they decided that really was most important for them was to build this culture of skills-based mobility, like people having agency and autonomy to be able to develop themselves and develop their careers in a way that that made sense for them.

I mean, of course, they message us with managers and talk to them about like, if you’re a net exporter of talent. That’s a good thing and here’s why. It’s not just that you’re gonna lose all your best people to other projects within the organization. You’re also gonna have the ability to recruit people from other parts of the organization to work that you have that needs to be done.

And so they really focus on the culture and the mindset around skills and development. And that’s what they tackled first. Now they’re coming back and they do know that they need to define like the skills architecture for the organization, and they’re engaged in that work now. But that’s not where they started.

They didn’t start with infrastructure and data, data collection [00:35:00] assessment. Now there are other organizations that do start there, but it’s because the problem that they’re solving demands that they need to assess the current level of skills and capabilities in order to determine what the next steps are.

Falling in love with problems and set up skills as a solution that needs to be. Fully baked and developed for the entire organization, start shopping around for problems to solve is exactly backwards. It’s, it’s gotta be a problem first approach.

Maureen: I love the idea of falling in love with a problem, especially from my change management background.

If I’m solving something that’s really important to me, I am more likely to put the energy into that than creating an architecture or a taxonomy or something. That’s never gonna be my priority. One, I’ve got real problems to solve

Brian: for the HR and learning people out there. Your taxonomy, nobody cares.

Nobody cares about your taxonomy. They care that it exists because you know you do need it at a [00:36:00] certain point to be able to scale your efforts, but it’s like, do you really care about the generation facilities for the electric company? Not really. I mean, you just want the

Maureen: lights to go on,

Brian: you know that it’s seated and somebody needs to care about that.

But it’s not gonna capture hearts and minds to talk about solving your job architecture or your, your skills architecture. Does that work need to be done? Yes, but that’s need to be out there with partners in other parts of the business. HR is a part of the business, l and d is part of the business, but you need partners in other parts of the business that have real problems to solve, where you can take these skills-based approaches.

And really create some value that you couldn’t do as well without this view of the skills-based view and mindset, et cetera.

Maureen: So I’d say a p and L based problem.

Brian: Yeah. Engagement problems. I mean, we see people going after things. I mean, nothing that shows up in the research [00:37:00] is always a top three issue is.

Opportunities for skill and career development is a reason that people leave organizations. It’s always one of the top three. So that unmanaged attrition, that is a problem we’re solving. Employee engagement, employee experience. Most larger organizations do these types of surveys, allow to do pulses on different issues.

Those are problems worth solving. And still development. And development in general. It is a very foundational human activity. We are literally learning machines. We are built to learn, to acquire new skills, to be curious about what does it take for me to do that thing that this other person just did? How can I learn to do that?

It’s just very natural and foundational and the extent to which. As organizations, we can feed that natural curiosity, that natural desire to develop, make that accessible, make it available to people, make it strategic [00:38:00] in terms of aligning people’s skills, interests, capabilities, their aspirations, line up with what those things are for the organization.

Again, it makes it a, a win-win. The organization wins, uh, people in the organization also.

Maureen: Ryan, thank you. You’ve shared so much. Everything from the wins need to be the company, the manager, the employee ultimately leading to supporting our clients. Whatever our product or service is, that this helps solve a range of problems, and it really enables us to be more AI enabled.

I don’t know that that’s the right term, but we can leverage the latest thinking and technology through not only skills-based approaches, but all of the things that go with that. The change in culture, change in mindset, change in how HR operates, how l and d operates, how we think of jobs and recruiting and engagement, that this is a wholesale look at people [00:39:00] differently.

Being skills-based is one part of a much bigger initiative that you’re also helping facilitate.

Brian: It is. Both old and new skills is not a new conversation, but it is very much tied to the ability for AI to personalize. To adapt experience at scale, to gather data, to create action insight based on that data.

To be able to do that rapidly with very big data sets is a really important part of why this conversation has come forward in the last few years. The two, I think, are definitely connected. I don’t wanna say that the tech should really be leading this transformation, but it does play an important role in supporting being able to do some of these things that we’ve been talking about for decades, really, in terms of learning the flow of work, adapting experience, personalizing experience, so that each employee, each person in the organization can be their best selves, can grow themselves personally and their [00:40:00] careers over time.

Technology plays a very important supporting role, and it’s getting better and better. Every organization is as good as the talent and the people in that organization. And you know the capability that’s enabled by not just the technology, but the culture, the ways of working, the ways of thinking, and this is one of those trends that’s gonna stick.

It’s gonna last. Every organization is really undertaking this at some level, and I think the organizations that really embrace this and are able to do it in a thoughtful, strategic way that again, solves real problems. It doesn’t solve for skills for their own sake. But solves for skills-based approaches to advance the business and advance the people in the business are gonna be very successful.

Maureen: Thank you very much, Brian. How would our listeners follow up and learn more about you and skills-based approaches?

Brian: We can plan you on LinkedIn, uh, Brian Richardson, Richardson Consulting Group, and you can also visit our website, richardson consulting group.com. We have a lot [00:41:00] of articles. We have a newsletter about skills.

I do host regular at least monthly round tables on this. Those are four HR talent, LD, and business leaders that are engaged in this work. We come together on a monthly basis, different aspects of the skills conversation. We talk about culture, we talk about data, we talk about analytics. Really bring the top of mind challenges from the group and work through those together.

Bring best practices from a variety of industries. So anybody listening to this is welcome to attend those as well. And more information on our website, richardson consulting group.com.

Maureen: Thank you Brian. And thank you to our listeners for engaging and continually elevating your organizations to meet the challenges that we’re all facing [00:42:00] today.