Rewiring Roles: How to Build Job Architecture for a Skills-First Future

John Lynch: Alright. Numbers are ticking up, so I think it's a good time to get started. We've got a lot to cover today, so we have a good opportunity to get a jump on it.

Thank you for joining us, everybody. My name is John Lynch, and I'll be facilitating or supporting today's session.

As we get started, I'm going to walk you through a little bit of the webinar experience so we have no hold-up. We're going to talk about the intersection of job architecture and skills.

There's some really deep content today. As you look at your webinar screen, you're going to see something like this. There are slides with a lot of data and pieces you might want to see in more detail. You can click on the icon in the bottom right-hand corner to expand your screen.

The most important thing is that I'd like you to keep chatting and engaging throughout the session. Please drop any questions or comments you have in the chat, and we'll address them as we proceed.

If you have questions, we have a Q&A section at the end. If you put a great question in chat, we'll move it over to Q&A so we can get to it later.

If you'd like to find the presentation for today's session, you can look in the doc section along with some supporting content. The topic we're covering today is aligned with what we offer in a number of different ways at TalentNeuron. If you'd like to request a demo or speak to someone about any of the offerings or case studies we'll walk through, click the Request a Demo button at the top of your screen.

Today we'll be running about forty-five minutes, perhaps a little over depending on how many questions we get. Once we get started, we'll be able to address one or two questions from the chat, but please stick around until the very end for Q&A.

We also have a short survey at the end, and it would be really helpful if you could take a moment to answer it. Anything we don't cover in Q&A, we'll follow up on afterwards.

Alright, we have a great crowd now, so we're going to move on to introducing our speakers. Lynn, thank you for joining us. Lynn Mayes? You might be on mute there.

[0:03:10] Tania Humphrey: Yeah. I'll jump right in.  

Hi, everyone. Tania Humphrey. I'm a solutions consultant here at TalentNeuron. My role is all about helping organizations connect their business challenges to the capabilities of our platform. Lynn?

[0:03:28] John Lynch: You might need to use the button in the bottom right-hand corner to come out on stage. That takes one second.  

The good news is we have a few more minutes to welcome people. Tania, where are you based again?

[0:03:50] Tania Humphrey: I am based in Atlanta, Georgia.

[0:03:53] John Lynch: Beautiful. Have you been to Fox Brothers Barbecue in Atlanta, Georgia?

[0:03:57] Tania Humphrey: I have not, oddly enough.

[0:04:00] John Lynch: That's my one restaurant recommendation. But whenever anybody is going to Atlanta, now I'm worried it's the wrong one.

[0:04:07] Tania Humphrey: I don't know. Now I'm going to check it off, John.  

[0:04:10] John Lynch: It's pretty good. Alright. Lynn? Hello? Can you hear us? Looks like we have some technical issues.

[0:04:27] Tania Humphrey: Let's see.

[0:04:35] John Lynch: Oh, you can hear? Okay. We might be having one or two issues on the audio side because I see a few people in chat saying they can hear me but nobody else.

[0:04:46] Tania Humphrey: Some people can hear me, some people can't.

[0:04:48] John Lynch: Okay. It might just take a moment for the platform to catch up. Bear with us, everybody. Thank you.

Maybe, Lynn, if you drop off and then log back in again, that might help solve some of the issues. Here we go. Just bear with us a moment, folks.  

In a sense, I blame myself because just before we started this session, I was saying we hadn't had any issues in the last few webinars this year. And yet we have one today. Sorry about that.

[0:05:43] Tania Humphrey: John, thank you for that.

[0:05:44] John Lynch: Yeah. I blame myself.

[0:05:54] John Lynch: Alright. Might be just one second here.

[0:05:56] Tania Humphrey: Looks like Lynn is coming back in.

[0:06:01] John Lynch: Okay. Some people have turned on the light mode and now can't hear. Some people can hear me, others can't.  

If you are having audio issues, it's a good idea to log off and log in again. Sometimes it just takes a moment for the platform to catch up.

[0:06:32] Lynne Mayers: I am back. She's back, and we can hear her. Perfect. I am so sorry about that. My headset just decided it was not going to cooperate, so I am on computer audio.

[0:06:46] John Lynch: Well, you sound great.

[0:06:47] Tania Humphrey: Yes.

[0:06:48] John Lynch: I think I was just saying when you were out, I blame myself because I said earlier that we hadn't been jinxed. So I jinxed this. Sorry, guys.

[0:07:00] Lynne Mayers: All good. All good. So, John, let us know where we can pick up and dive right in.

[0:07:05] John Lynch: I was just about to introduce you. So I think this is the perfect time.

[0:07:11] Tania Humphrey: Okay. So, Lynn Mayer, senior consultant with TalentNeuron. She has been with TalentNeuron for the past nine years.  

I'll add that Lynn and I, our teams work pretty closely together. It's nice to have a change of engagement here and work together in this capacity. I'm excited for today.

[0:07:33] John Lynch: Alright. Fantastic.

[0:07:36] Lynne Mayers: Alright. So, John, shall I go ahead and kick us off or is there any housekeeping you wanted to do first?

[0:07:41] John Lynch: I think we're all set with housekeeping. Yes, go ahead and get us started. Thank you.

[0:07:45] Lynne Mayers: Alright. Thank you, everyone, for joining us today.

We're going to be talking about how to build a modern, dynamic job and skills architecture to drive your skills strategy. Tania and I really look forward to sharing some of the trends we're seeing in this space and a couple of examples to show how we're helping our clients move in agile ways and get real results.

It's a timely topic. For the past two to three years, clients have told us they want to double down on their skills strategies. At the same time, we're seeing some organizations stall out or struggle to get going.  

We'll share barriers organizations are running into as they try to build their skills architecture and provide practical guidance for avoiding those barriers and driving momentum. The reality is that the skills mandate could not be more urgent than it is now, not just for talent outcomes but for business outcomes.

And that's where I'd like to start with this slide. A lot of the time, when we talk about the skills mandate, we start with the talent reasons to focus on skills. It helps us address talent shortages, redeploy and upskill talent, expand candidate pools, and yes, all of those things.

But if we really want to drive impact, we need to start where there's urgency and momentum in the business — transformation. Currently, this is primarily in spaces where organizations are adopting AI.  

On the left, you see headlines about organizations rolling out AI software engineers, insurance companies rolling out AI-driven agents, even the first AI-developed drugs coming to market. AI is not a buzzword anymore; it's here.

On the right, 78% of organizations have adopted AI in at least one function, and the average organization has adopted it in at least three. This bus has left the station. But are we on it? The data shows most organizations have not adopted skill strategies at scale.

We think 2025 and 2026 are going to be critical years for HR to show we can deliver practical workforce strategies to support these transformations. Clients are telling us the business is moving full speed ahead in AI and digital initiatives, and technology leaders are saying, "If HR can't come to the table with a plan to deliver the capabilities we need, that's fine. We'll handle it."

That puts HR business partners in the crosshairs. They need to move fast to come up with workforce plans to support these initiatives.  

One of my clients told me that an HR VP came to his strategic workforce planning team with a question from the business: "Help us forecast how many data scientists we're going to need in the future and what their profile should look like." It took them several weeks to answer. He said they know they need to be more agile and provide answers at the touch of a button because HR VPs depend on that data.

This isn't just about broad-based talent initiatives anymore. It's about targeted workforce transformation strategies to support specific business initiatives.

HR needs to know what those top initiatives are. They'll need to answer questions: What skills will we need? How many people? Do we have them inside the organization? Are we going to build, buy, or borrow? Where, how quickly, and at what cost?

Tania, I want to bring you in here because I know you're working with a lot of our clients to implement our job and skills architecture technology. What are you hearing from those clients about the business initiatives driving these implementations?

[0:11:36] Tania Humphrey: Yeah. This sets up a nice little teaser for my second case, which I will dive into. However, what comes to mind is an aeronautics organization we're working with that was facing predictive maintenance challenges, as shown on the right-hand side of the slide.

AI and automation were rapidly changing how critical technical skills were being designed for them. When we get deeper into the case study, we'll talk about how we helped them meet those challenges. But yeah, absolutely.

[0:12:05] Lynne Mayers: Perfect. Thank you so much for that sneak peek. Alright. Let's recap why we need a skill-specific focus for this on our next slide.

AI and digital transformations profoundly impact workforce requirements, but that shows up less at the role or title level and much more at the task and skill level. We've used the example of a software developer here.  

Organizations like Goldman Sachs are rolling out AI that can do coding, but they're still hiring software engineers — just not as many. They're still calling the role "software engineer," but what the job does and the skills it requires are being profoundly disrupted.

It's less about coding now and more about creating prompts for the AI, checking outputs, and framing business problems for the AI to solve. That requires different skills. We need to be able to see those changes and plan for them at the task and skills level.

By the way, you will hear us talking a lot more about tasks in our product in the future. Tania, you're going to share a little today about how we use tasks in our solution.

[0:13:25] Tania Humphrey: The real disruption happens, like you said, at the task and skills level, which is where we start to see what parts of roles can be automated. Later, I'm going to show you how we take it further and use our automation potential to analyze this.

[0:13:40] Lynne Mayers: Great. That's such an important point — most disruption happens at the task and skill level. And sure, there may be some new roles or some that disappear.

But for the most part, the story here is around how existing roles are changing. What does that mean for HR? You need to understand the skills requirements for roles and how they're changing.

In short, you need a skills architecture. We're going to spend the rest of our time today talking about skills architecture on the next slide, John, because it sits at the center of every skills use case you might want to deploy.

It's the bedrock, the foundation. What do we mean by skills architecture? The most basic explanation is that it's about taking your current roles and aligning required skills to them.

Yes, today it typically attaches to roles or at least job families because right now that's the basis for how talent management systems work. But in the future, could that change? Could we be talking about skills aligned to task ontologies or other constructs? Sure.

But today, if you want to build a skills architecture, for better or worse, it attaches to your job architecture. Once you have that skills architecture, you can then deploy all the skills strategies you see around the wheel.  

You can do skills-based workforce planning, build more dynamic career architectures, give skills data to employees and candidates, create internal talent marketplaces that match people to roles and projects based on skills, and identify qualified candidates based on skills versus titles.

There are lots of amazing things you can do once you have that skills architecture. I do want to make sure we double-click into job versus skills architecture, so let's do that next.

Most organizations have some form of job architecture for all or parts of the organization. Job architectures typically define functions, job families, sometimes subfamilies, and roles in organizations, and often describe the levels or grades those jobs fall into. They're typically owned and maintained by total rewards because they're used for job classification and compensation.

Your skills architecture goes deeper. It breaks roles down into skills requirements and, increasingly, tasks as well.

That skills architecture powers all the skills strategies we saw on the prior page. Typically, learning and development or talent management own the skills architecture.

So there's already a need for governance and operating models, and strategic workforce planning is also in the mix.

We'd love to hear what stage our audience is at in creating skills architectures — not job architecture, but skills architecture. John, can you go ahead and bring up our poll?

[0:17:09] John Lynch: There you go, folks. You should be seeing it now on your screen.

Sorry, it just takes a moment to bring up.

So what stage are you at in building a skills architecture? Some people have already mentioned this in the chat. What stage of maturity are you at?

We're seeing answers come in now: about 20% say none today, and the overwhelming leader is "none today but planning to build one in the next year." That's nearly half of the respondents.

Some say there's a partial skills architecture in place. If you have an answer that isn't covered in these four options, please drop it in the chat.  

Alright, I think most responses are in now.

[0:17:57] Lynne Mayers: Okay.

[0:17:58] John Lynch: None today, but planning to build one in the next year. That seems to be the result.

[0:18:02] Lynne Mayers: Okay. That's consistent with other data I've seen.

Lots of folks are just getting started here, which is presumably one of the reasons you're with us today. Thank you for that.

Next, we want to touch on some barriers we've seen to building skills architectures — landmines you can avoid. These are some of the main reasons we think we're not seeing as much advancement as expected on skill strategy.

First, there's a tendency with skills architectures to go big and design for the whole organization. We understand — it can feel like you need a foundation in place company-wide to become a skills-based organization.  

The challenge is that building an enterprise-wide skills architecture is not easy. It takes time to marshal resources and stakeholders. Meanwhile, critical changes are happening fast, and you may miss the opportunity to support them. Getting all stakeholders to agree on a set of skills requirements can also result in a lowest-common-denominator output.

We also see tension between skills owners in L&D or talent management and the strategic workforce planning team. The former want to build for the whole enterprise, the latter focus on solving for specific business-critical needs. Our recommendation: build for action, not perfection.  

Align to critical business initiatives, get your MVP skills architecture in place quickly, then iterate and refine. That's how you build long-term momentum.

And our first client organization, Tania, that you'll talk about, did exactly that.

They did two pilots and are now scaling to the full enterprise, but only after those successful pilots. Amazing. Thank you.

Okay, let's go to the second landmine. Another challenge we see is building skills architecture around existing job architecture. The assumption tends to be, "We've got to take what we have and build skills on top of it." That can be a mistake for some of the reasons you see bottom left.

Often, job architectures themselves aren't in great shape. They might be out of date or have gaps. Sometimes they only go down to the job family level.

On the flip side, sometimes they're so complex, with many levels and grades, that if you tried to build skills on top of every single role, it would be a nightmare to manage. So the first thing we need to do is figure out how to work with job architecture and optimize it for skills.

Depending on the state of your job architecture, that might mean modernizing it, filling gaps, refining, or simplifying it. That doesn't mean the total rewards version of the job architecture goes away or has to change. They may still need their version for classification and compensation, but skills owners need it optimized for their purposes.  

That means job architecture needs to be prepared for skills before building skills architecture. This is something we're helping several clients work through right now.

Let's jump to the final landmine. The third challenge we see is static skills architectures. Organizations define skills requirements for roles—you've got an example there for a DevOps engineer. But skills requirements change rapidly. Some skills grow in importance, others decline, new skills emerge.

Your skills architecture cannot be fixed; it needs to be a living, breathing thing constantly informed and updated by what's happening in the market.

I have a client, head of workforce planning at a large financial services organization. She shared that their skills team had been on a three-year journey to build out an enterprise skills architecture, but the challenge was they had no way to keep it updated. They couldn't determine which skills were growing or declining, and updating it would be a massive effort.

So they're pivoting.

Our recommendation is to start by building dynamic skills architectures connected to market data. That way, you can get constant skill signals about what's growing and declining in importance. You can monitor those signals, decide what's relevant, and stay up to date without massive refresh efforts.

You can also monitor role changes driven by AI and automation. Tania, I know you're working with several clients to implement dynamic job and skills architecture using our technology. How are they working with the alerts they receive in our system — alerts that notify them of new skills or changes in proficiency levels? Tell us who monitors that and makes decisions.

[0:23:48] Tania Humphrey: Yeah. That's a great question. It's obviously about governance. Some customers have dedicated users who are part of a steering committee or pod. On a regular cadence, maybe quarterly or even biannually, they're going in, seeing alerts and notifications, and then taking action. For others, they may have HR VPs who own this and work with business leaders to understand if changes are needed to skill definitions or proficiency. It really depends on the organization, but that's the common theme I'm seeing.

[0:24:33] Lynne Mayers: Governance operating models are not sexy, but so critically important. Thank you. Okay. We wanted to wrap this part of the conversation by summarizing what organizations do to overcome our three landmines, and then we were going to do a quick poll. John, I'll ask you to make a call when we get there if we need to adjust our schedule and skip the poll. But in the meantime, thanks for bringing up our next slide.

Starting with our recommendations for how to address those three challenges:

• First, avoid the pitfall of big enterprise skills architecture projects that take too long by doing a phased rollout or pilots with key areas of the business. That way you can prove out the design, make sure it's actionable, secure business leader buy-in, and then capitalize on early wins to scale further.

• Second, to avoid being stuck with a suboptimal job architecture, refine it for your skills needs. Don't wait for the job architecture owners to update it if it's out of date. I recently had a head of talent management tell us that their company's job architecture redesign was going to take two years. She couldn't wait for the skills architecture. That's okay. Refine it for your needs.  
  

That does mean you need to put in place a strong operating model and governance with total rewards, HRIS, and talent management to clarify ownership. We can help with that. But you must be agile, and you can't wait.

Third, to avoid static, rigid skills architectures that quickly go out of date, build dynamic, market-connected skills architectures that allow you to stay on top of changes. John, should we do our poll or skip it?

[0:26:35] John Lynch: Yeah. We definitely have time for the poll. Let me pull it up. The first one got some great responses. Let me share the second one here. Hang on. Yep. You should be seeing it now.

What is the biggest barrier you have to creating a skills architecture? Please start responding. If you're not seeing it on your screen, go to the polls tab on the right-hand side.

Options are: current state of job architecture, lack of business case or funding, unsure where to get started or how to design it, unclear ownership. That's also coming up in the chat and Q&A. If there's anything else not covered, please drop your answer in the chat.

Early indications: unclear ownership — 25% say that's their top challenge. Unsure where to get started or how to design it—also a big one. Lack of business case or funding — about 16%. Current state of job architecture is also a holdup for those who already have architecture in place but need to revise it.

In our 30-second poll, 37% say their number one challenge is being unsure where to get started or how to design it. I think we're in the right place.

[0:28:08] Lynne Mayers: Did you say 37% for unclear where to get started?

[0:28:12] John Lynch: Where to get started. Yeah. 37%.

[0:28:14] Lynne Mayers: Okay. That's great. Thank you. That's why we're here. We're here to help. We'll turn it over to Tania to take us through two case studies. Tania, I'll go on mute and let you take the floor.

[0:28:34] Tania Humphrey: Thanks, Lynne. The challenges Lynne just shared — long timelines, trying to roll out to the full enterprise, suboptimal architectures, and static skills frameworks — are exactly what we see every day. What I'm going to walk you through are two case studies showing how organizations tackled these challenges and how that comes to life in the TalentNeuron platform.

Our first case study is a large global automotive manufacturer facing urgent pressure from the shift to EV and connected vehicles. Their skills data was siloed, inconsistent, and lacked governance, making it hard to align workforce strategy with business needs. Leadership needed a skills-driven transformation strategy that was fast, scalable, and trusted. They partnered with TalentNeuron to bring structure, market alignment, and governance to their job and skill data.

The first step was ingesting role data. In this pilot, we focused on R&D and IT. We brought that role data into the platform. Whatever role data you have — job families, subfamilies, positions, or job descriptions — we can use it to build the foundation.

The next step was connecting it to market skills architecture to enrich it with market intelligence. On the left, you see a specific role profile enriched with standardized skills and proficiency levels. You also see future orientation signals highlighting emerging, high-demand skills. On the right, you see updates as market intelligence evolves.

This helped them move from broad or overly granular skill data to consistent, core sets of 8–10 skills — a single source of truth. The market connection ensures those skills stay current, addressing the barrier of static frameworks.

Next, we look at future-proofing the role. The client needed to adapt quickly to emerging technologies. This step showed what skills were emerging and how roles needed to evolve.

Finally, with a dynamic job and skills architecture in place, business leaders can utilize outputs such as skills gap analysis. Comparing defined role skills with employee skills data reveals workforce readiness and informs talent investments — whether to upskill internally or hire externally.

Overall, the pilot enabled real-time skill intelligence, consistent definitions, market connections, and a scalable governance model for continuous improvement.

[0:34:05] Lynne Mayers: Amazing. Thank you so much, Tania, for taking us through that and really bringing everything we've been saying about future proofed and dynamic to life there. Question for you. I understand that because this organization is such a large global organization, they wanted to move fast, but they also needed to get the buy-in of their business leaders. Because they were asking those business leaders to move away from some of the skills they had set up in their part of the business and align around this common core. So how?

[0:34:36] Tania Humphrey: Do they accomplish that? Yeah, that's a great question. So this goes back to a little bit of the teaser in the beginning too. They actually created a steering committee. They got folks across the business, HRBP business leaders. They created a steering committee and were able to go in on a quarterly basis, look at those recommendations that were coming through with the alerts and those real-time updates, and decide to take action. Are we adding any new skills in? Are we changing the proficiencies? Are we removing any skills that are now being signaled as outdated? So that was their process that helped them keep on top of a dynamic architecture.

[0:35:18] Lynne Mayers: Great. Thank you so much. Alright. Should we dive into our next case study?

[0:35:23] Tania Humphrey: Yes. Let's jump into case study two. So in this case study, we're looking at an aeronautics organization. They recognized that they had a need for a structured job catalog and taxonomy, and that's their specific verbiage. Not only are they doing this for compliance purposes, but they wanted to manage costs. They wanted to optimize their resources, and then they wanted to streamline their workforce development. At the same time, they faced mounting questions around automation and how that could reshape critical roles.

So how we addressed this with them was we worked to validate how their roles lined up against the external market, what those roles are typically called from a standardized title perspective, the skills, proficiencies they require, and what those skill trends are. And then on top of that, we overlay the automation potential analysis, and we'll dive into that as well.  

So let's walk through some of the steps of how we actually did this. The first one is the same. The process looks a little bit similar to our first case study. We've got to get that role data in. In this particular case study, we were looking at a function of roles that they found were critical and they wanted to address. So we brought in that role data, we brought in those job descriptions, and then we had the lay of the land that we could start to move into the next step, which is tying that to the market data.

I know step one and two look very similar because it is a similar process, but what it means for each of these case studies is a little bit different. For them in the secondary step of marrying it with the market data, it was about validating the roles against the market data, understanding what are those emerging skills or maybe declining skills. They wanted to get an understanding of how the market was trending and take that into consideration for how they want to shape or redesign their roles. That market intelligence component you see to the far right was also important for them.

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What are those role calls? How is this role trending in the market? All of those components were important to them for this particular case study. Let's move into the next slide because this is where we differ a little bit with the different case studies.

Now we get a chance to talk about another component we didn't show in the first case study, which is automation potential. To the far left, we've got the role-level view. Understanding the automation potential of a role allows you to see which technologies are most likely to impact it. You can see here the overall percentage of the role. We take it a step deeper and then move into the middle, which is the task-level view. We break down that role and show at its core the tasks, the duties, and where the automation opportunity is concentrated.

From there, we get to the final view, which is the detail view where you can actually drill into a specific task to uncover exactly how it can be automated and what that might mean for reskilling or redesign. This was really important if you recall when I walked through the context of this particular case study. This is one of their main components they wanted to drill into, and we wanted to showcase what that looks like in the platform and how we can bring that to life and analyze it.

Let's move to the final piece, which is the output. In this particular case study, we created and developed an executive summary that we gave to the business. It provided them a clear line of sight into where that automation could drive the most impact. You can see here across those different components not just efficiency gains, but also where reskilling and role design could be critical for the future workforce, which again was part of their main ask in this case study. So, Lynne, let me hand it back over to you so you can walk through how we partner with clients on journeys similar to these.

[0:39:50] Lynne Mayers: Great. Thank you so much for walking us through that, Tania. Again, really bringing in that case study, bringing not just the skills architecture piece, but the automation potential to life. So let's talk through how you can partner with us, and I see some questions in the Q&A about that. And then we'll close out with hearing some of your questions as well.

So typically, not in every case but quite often, we take the approach of first helping clients to lay the foundations for skills architecture design, and then prove out the value through some targeted pilots and then scale to the enterprise, particularly if you're starting from scratch. In the first stage, that's where our strategic consultant team would partner with you to determine how to optimize your job architecture for skills. We also work a lot with clients at that stage to help them create their skill strategy and road maps, their operating models, and governance with their various internal stakeholders.

We've touched on how critically important that is because there are so many HR teams touching job and skills architecture for various purposes. Once we have our strategy and solution design for skills, that's where we build out that dynamic job and skills architecture in our technology solution. We're going to upload your data, create current and future job profiles, connect them to skills dynamically informed by the market with common definitions as proficiency levels. We're going to show you the automation potential for the roles.

We're going to enable dynamic updating, and then we scale to the enterprise. We turn on all needed integrations and APIs with your systems, and then clients will, at that stage, once they're happy with the skills architecture, start to turn on their skills-based applications like your talent marketplace to do skills gap analysis, internal mobility, or bring skills into strategic workforce planning using our planning module.  

I see Ellen talking in the chat about the talent marketplace module. Those two additional modules, talent marketplace and strategic workforce planning, are how you can take the skills architecture and apply it within those use cases. The key thing here is that every organization is at a different place in terms of job and skills architecture. Whatever stage you're at, we can meet you there and craft the right technology and consulting services solutions to meet your needs.

So let's pull up and see, John, what questions we've got.

[0:42:47] John Lynch: Yeah, absolutely. And honestly, we've had some amazing questions and a lot of activity in the chat. I should preface this by saying we'll try to get to everything within the time we have left, but I think we're going to have to follow up on some of these. There's been a lot of interest specifically in the case studies you were talking through, Tania, and details like timing, who was involved, and the cadence of reporting to the executive level.

I think the first question would be about timing. How long does the process take end to end typically?

[0:43:25] Tania Humphrey: Obviously, that's going to depend on what we're doing in the process. From a general perspective, before looking at building out the job and skill architecture, that's anywhere from two to four weeks depending on some of the pre-work you may need to do with Lynn and her team, or what you already have prepared. Then, of course, bringing everything in, calibrating it to make sure everything looks good, and validating with proficiencies and skills.

So I'd say about two to four weeks to get started. If we're adding on additional components and drilling into certain aspects, it could extend to six to eight weeks depending on the additional capabilities you're looking to build out.

[0:44:11] John Lynch: Okay, thank you. And the other part of the timing, from Vanessa's question, I think this was specific to one of the case studies. What's the cadence for the steering committee? Do they report back quarterly, semiannually? What's the typical cadence?

[0:44:34] Tania Humphrey: For the first case study, the pilot was done last year. They had two different pilots that came together. Over the course of that year, they met quarterly to have their readouts. So for them, that quarterly cadence helped them see success in their pilots.

[0:45:00] John Lynch: Awesome, thank you. And another question, partly related to the space but fairly general: who is involved in these projects? Which functions do you typically work with?

[0:45:19] Tania Humphrey: Obviously, the main stakeholders are SWP teams and talent management. Other stakeholders we see could be HR and talent leaders. I mentioned HR VPs earlier. We also work with workforce analytics and technology teams. Sometimes we see people analytics team members, even HRIS because they have a stake in integrations and related aspects. Change management or transformation teams are also often involved.

[0:45:56] John Lynch: Mhmm. Awesome. Thank you.

[0:45:58] Tania Humphrey: And feel free to add more because I know you may have additional color to share.

[0:46:03] Lynne Mayers: Yes. I'm seeing a question from Tom around who owns the process — meaning the process of creating the skills architecture. Typically, we see that talent management and learning and development take ownership. But as I mentioned earlier, if we want to be agile and align to the business to provide workforce transformation strategies, strategic workforce planning and HR VPs also have a huge vested interest.

That's why having the right operating models is so critical, so that as we're designing, we are working in an agile way. I also saw questions around skills versus competencies. Our definition of skills is broad—it includes both hard and soft skills. Anything else, John, that I've missed?

[0:47:16] John Lynch: I'd say it's worth mentioning Cody's question about finding key skills by role. Ellen answered it in the chat, but maybe an introduction on what we do there would be helpful.

[0:47:29] Lynne Mayers: Well, that's essentially what we've been talking about. When we say skills architecture, the definition is about defining the key skills for the role. The differentiator is that it's not a one-and-done solution, which is what many organizations struggle with. We help you build a modern, dynamic skills architecture connected to market data, so it becomes a living, breathing system that is constantly refreshed and kept up to date.

[0:48:08] John Lynch: Awesome, thank you.

[0:48:10] Lynne Mayers: Great. I want to be mindful of time, John. Should we take more questions or follow up offline?

[0:48:18] John Lynch: There are a lot of really good questions that are either the next level of detail down, so we'd have to follow up after the event, or ones tied to the case study that are better handled one-to-one, where we can talk about our capabilities and how they relate to specific use cases.

So if anybody has questions, we'll follow up. You can also hit the "Request a Demo" button so we can answer those in a more detailed environment. I think that's the best next step. As you say, Lynne, we are a little past time, and I know many folks will have a busy week — especially in the US with a holiday weekend coming up.

So I'll let us wrap up. Thank you so much, Lynn and Tania, for rolling with the punches and our audio challenges at the beginning, and for sharing so much valuable insight today. And thank you to our audience for making time to join us.

[0:49:23] Tania Humphrey: Absolutely. Happy to be here. Thank you.

[0:49:30] John Lynch: Alright. Everyone, we'll follow up with the recordings, and the presentation and all associated documents can be found in the tabs on the right. Thank you, have a great rest of your week, and we look forward to seeing you next time.

[0:49:41] Tania Humphrey: Thank you, everybody. Thanks.  

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