Episode 213: How to Use Skills Data to Solve Business Challenges (Interview with Mikael Wornoo)
What better way to learn about the makes or breaks of skills initiatives than from an organisation whose mission is to deliver reliable skills data across the workforce?
Joined by Mikael Wornoo, co-founder of TechWolf, host, David Green and his guest explore how organisations can move beyond surface-level skills discussions to drive real business impact. Sharing lessons learned from working with global organisations, this episode will cover:
How organisations are innovatively applying skills data to solve business challenges
Contrasts between US and European approaches to skills that could shape your global workforce strategy
The hidden challenges that derail skills projects and what companies often miss when trying to “get started”
The roles required to build a truly effective skills team
Why AI isn’t just the future of skills intelligence but the catalyst for shifting how organisations define and measure talent
This episode sponsored by TechWolf isn’t about skills for the sake of skills—it’s about reframing workforce intelligence as a strategic lever for measurable business outcomes.
TechWolf is an AI-powered solution focused on one mission: delivering reliable skills data for every role and every employee in your organisation.
With TechWolf, companies like HSBC, GSK, IQVIA, Workday, and United Airlines have accelerated time-to-hire by 32%, boosted internal mobility by 42%, and saved around $1,000 per employee annually on talent management.
Visit techwolf.com for more information.
[0:00:00] David Green: Hi, I'm David Green, and welcome to the Digital HR Leaders podcast. How can an organisation understand the skills they have and the skills they need so they can have the right people with the right skills in the right positions at the right time to execute on its business strategy? This is the challenge that AI-powered skills solution, TechWolf, helps companies across the globe solve. TechWolf is able to infer and identify skills from both HR and business applications. Interestingly, in its recent Series B funding round, SAP, Workday and ServiceNow all participated as investors.
My guest today is one of TechWolf's co-founders, Mikaël Wornoo, and is designed to get under the bonnet to examine how organisations can thrive with skills and deliver quantifiable business outcomes. I always enjoy talking to Mikaël and the team at TechWolf as they bring a fresh perspective into the evolving world of skills data and workforce intelligence. In our conversation, Michael and I will discuss what makes the skills project really work, the different approaches in the US and Europe, and where he thinks AI will take HR when it comes to skills intelligence. So without further ado, let's get started.
Mik, welcome back to the show, it's great to have you on. Last time you joined me was all the way back in 2021, and I think I spoke to Andreas, the CEO at TechWolf a year later. So, what have you been up to since, what have TechWolf been up to in those last two or three years?
[0:01:50] Mikaël Wornoo: Yeah, I mean a lot has changed, right? In a way, a lot of things stay the same as well. So we're still an AI company. Now, we get to say that we were really early on the AI train. We still help organisations understand the skills of their workforce at scale. I'd say the number one thing that has changed is just the general level of awareness around AI. People want to use AI in HR. The applications of AI in HR are massive. Second big thing is, we did a massive Series B, one of the biggest rounds in HR tech. For the first time ever, ServiceNow, Workday, and SAP invested together. And I moved to New York, so a lot of things have changed. We got a lot of awesome customers that we added to the Wolfpack. And so, a lot of good things happening on the TechWolf side.
[0:02:33] David Green: So, you mentioned that you're working with SAP and Workday as investors as well, and TechWolf has gained some great investment recently, and you said two of those investors are SAP and Workday. Tell us a bit more about this. What does this mean for TechWolf today and what does it mean for TechWolf tomorrow?
[0:02:52] Mikaël Wornoo: Yeah, I think the thing I'm most proud of is these are massive companies with massive AI teams. They're working on this, and yet they decided to partner with TechWolf to invest in TechWolf. So, I think it's a testament to the fact that we're doing something amazing, that we cracked a really hard problem. And so, we were quite early in using AI to understand massive amounts of data. And so, I think ultimately it will really benefit our joint customers, right? A lot of these platforms now have skills functionality and those platforms need high-quality data, and TechWolf provides that high-quality data. So, I'm super-excited to start building, and essentially really proud of what we have built already. The platforms now have access to high-quality skill data in a seamless way. So, for the end user, HR managers and the employees, it's just a better experience overall.
[0:03:40] David Green: And high-quality skills data is what it's all about, isn't it? We had Sandra Loughlin on the podcast a couple of episodes ago from EPAM Systems, and EPAM have been a skills-based organisation for 30 years. So, they're definitely an outlier there. And she was explaining the foundation of everything is having good skills data. You can't personalise learning, you can't recommend gigs, you can't do all the things that we want to do with skills unless you've got good quality data, and that's the problem that you help organisations solve, isn't it?
[0:04:11] Mikaël Wornoo: 100%. And the way we look at skills data is on the supply side and the demand side. So, on the supply side, you really want to understand what skills your employees have. And that's really hard to do as soon as the organisation has a few thousand employees. On the demand side, you want to understand, "What are the skills related and required to the jobs in my company?" like what skills do people need to be successful? And what we'll see is that organisations will either do it in a very reactive way, let's say when there's a restructuring, then typically a consultant comes in, costs millions of dollars to get a snapshot, a very static snapshot on your skills and the skills you have in the organisation, and then that disappears. But getting that at scale in a continuous way, that's the really hard part, and especially with this massive transformation or this shift towards a skills-first or skills-based way of thinking, a skill-based element; those are two fundamental data points or data sets that an organisation needs to be successful, or to even attempt becoming a skills-based organisation.
[0:05:09] David Green: Yeah, and that leads nicely to the next question, Mik. How are you seeing organisations currently leveraging and applying skills data? What are the most common ways? You talked about transformation there being one of them, obviously hopefully connecting it to a business priority is clearly one of them, but maybe talk about the most common ways, but maybe also any surprising ways that you're seeing companies using skills data.
[0:05:34] Mikaël Wornoo: So, I think that the cool part with skills data is you can use it in a very strategic way, or you could use it to solve very operational, tactical problems, and we're seeing both. There's probably three main buckets, so workforce planning, talent acquisition, and learning and development. So, skills data has a very natural fit there. So, in workforce planning, we had one of our customers reduce the size of their layoff by 6% by essentially redeploying people internally instead of having to fire them and rehire them, actually just analyse what the transferable skills are and then redeploy them in the organisation. On the talent acquisition side, and this is Workday, they managed to reduce their time to hire by 32% in their sales organisation. And then on the learning and development site, we had one customer that essentially used our skill-gap data to essentially create budget for a big learning transformation. So, it's very hard to ask for budget without a clear definition of the problem. Our data was used to actually highlight the size of the skills gap. And so, those are a few cool examples.
We had one customer, one project manager, she had a talent acquisition background. She knew her way around Excel and a few other tools. She redid their entire career framework. She leveraged her talent acquisition background to essentially fill, I think, three VP roles. Because we had data on everyone, she was like, "Okay, I need to be able to find some internal candidates that fit this description", and she actually just went ahead and found them. So, we worked together with her to actually figure out, like, okay, how can we operationalise this? How can we scale this? How can we bring this to other customers? So, on a very strategic level, essentially the Heads of Talent are using this to create buy-in for their decisions or for any type of investment they want to make. And then on an operational and tactical level, it's just being used to solve problems, redoing the career framework, things that just take a lot of manual work that now are a lot easier to do with TechWolf.
[0:07:33] David Green: That's some great examples. I mean you mentioned, I think it was the Workday example in talent acquisition, that it's reduced their time to hire I think you said by 32% in their sales roles. Now, if you've got empty sales roles, then that's having an impact on revenue. So, if you can make sure you're getting the right people obviously for those roles and filling them in time, then then that's going to have a pretty quick impact on your revenue as well, so that's really solving a business challenge there.
[0:08:04] Mikaël Wornoo: 100%. And that's the second thing we're seeing. It's also something that we try to push to our customers, like, leads with a business problem. A skills project cannot be an HR project. So, we try and sit down with the business, and it's typically R&D or IT, sales or operations, essentially functions that inherently have very pressing skills problems. When you approach a business leader saying, "Hey, we want to solve this problem with data", they're actually quite open to have the conversation. They're typically not open to say, "We want to redo the way we're doing talent management for reason XYZ". If we're going in and actually solving a problem with data and they don't have to do anything, that's a completely different conversation. So, it's a combination of knowing where to look, both on the HR side, like what processes are going to be the most impactful for us to address, but also what functions.
An IT function is another good example. Inherently, if you look at the way work is organised in an IT organisation, they do sprint planning. They essentially allocate work based on skills. They have a very natural match with the idea of skill-tracking, skill-mapping, and then using that to match work to people.
[0:09:17] David Green: And actually, you can help companies get to the skills data quite quickly as well, can't you? I mean, literally within a couple of weeks. So, if you've got a business problem and think, "How can we get the data for that?" you can potentially help them quickly.
[0:09:34] Mikaël Wornoo: 100%. I'd say HSBC is probably the best example. More than 200,000 people, they attempted doing this multiple times in pockets of the organisation. We were the only ones that were actually able to do it at scale in a couple of weeks. Although it took a little bit longer than most customers, because it is a very complex organisation, we were able to deliver. And that's typically where a lot of skill projects fail. So, (1) because it's inherently cross-functional, it's almost inherently an AI and a data project, and that's not necessarily realised; (2) there's just so much more complexity once you start thinking about doing this at the global level. It's relatively easy to do it in a pocket in the organisation in a one-off type of way; doing it at scale in a way that is repeatable, that's the hard part.
[0:10:19] David Green: And that's the key thing, isn't it? You're getting that skills data, not just from HR systems, not just from HRSAs or learning systems or talent acquisition systems, you're getting them from business systems as well?
[0:10:31] Mikaël Wornoo: Yeah, 100%. And a good way to think about it, we look at the work you are doing and the work you have done. I mean also, in a way, what you are learning. If you combine those three, you get a really good sense of the skills people have. And in a way, you need those three to solve real business problems. You can get to a roughly accurate picture quite quickly. Let's say if you want to make a workforce planning decision, you quickly want to know if people can be redeployed. But if you want to make your insights and your data relevant for the business, you also need access to business data. And oftentimes, HR leaders underestimate how much data there actually is about the skills of people in various forms. But it's not in HR systems. But the business has lots of process mapping documentation, lots of tools, lots of data sources that are untapped. And so, a big part of what we do and when engaging with the customer is trying to figure out what are the data sources that are easy to access and that will essentially give us a lot of bang for our buck.
[0:11:30] David Green: Mik, you mentioned instruction, you've recently moved to the US from Belgium and I wonder, do you see a difference in the way the US approaches skills versus here in Europe?
[0:13:05] Mikaël Wornoo: I think more broadly, there's just a massive difference in how the US approaches technology versus Europe. I think business is inherently more competitive here. So, people are inherently more motivated to try out new things to get ahead. So, that's something you really feel here. And then you have, I'd say, the translation towards HR. So, obviously you see that in HR technology as well, people are just more open to trying new technology. But the idea of skills-first hiring, the idea of the skill-based organisation, it emerged here. And what I see and feel here in the US, like, everybody agreed yes, this is a better way of managing talent, how do we actually do this? In the US, it's not why skills, it's how skills and why TechWolf, compared to another vendor. In Europe, there's still a lot of education. So, I'd say that the overall approach to working with technology vendors is a bit more mature, a bit more sophisticated.
At the same time, the way a European business thinks about partnering is really in that sense, in partnering. So, it takes a little bit longer to get going, but once you are working together, they really approach it as a long-term partnership. So, every region has upsides and downsides, but I do see a big difference in the way US businesses interact with technology.
[0:14:26] David Green: Yeah, I mean a potential hypothesis there, I mean certainly we see at Insight222, the US is a much more mature market when it comes to people analytics. It's not that the most advanced companies in the US are ahead of the most advanced companies in Europe, that's not the case, but there's just more companies doing people analytics in the US at a kind of mid to advanced level. And I know from speaking to you and Andreas and your team in the past, that one of the key people that you interface with in an organisation is the Head of People Analytics. And it's interesting, actually, our research, 50% of people analytics teams in the research we did last year, which was 270-odd companies, are helping their organisations on the skills-based journey. So, I'm just interested to see what, from your perspective, who are the key people that you work with at TechWolf on this topic around skills?
[0:15:26] Mikaël Wornoo: Yeah, so as you mentioned, people analytics is an incredibly important stakeholder. In the beginning, I was wondering, it's like, look, we were three engineers essentially trying to talk to anyone who would listen. And so, people analytics, they have that link to data. They were the only people that were remotely interested in what we're doing, because we were way too technical in the way we explained it. But as we started working with a lot of organisations, we did realise, okay, there is a very natural fit. If you look at engagement data, survey data, it's very similar to skills data in a way that you have very abstract data and you want to translate that to a set of insights, a set of dashboards that are useful to the business. So, people analytics, especially in the larger organisations, super-important.
I'd say for any customer, just somebody in HR that can crunch data, that can work with data, is super-important, because what we want to do is essentially build a bit of a skills intelligence capability at the customer side, so they don't always have to come back to TechWolf and say, "Hey, we need this dashboard [or] we want this insight". Building that internal capability is super-important. Just like in a people analytics function, you don't want to go to consultants every time, you want to have that internal capability.
I'd say more broadly looking at the project, executive sponsorship in HR in the business is critical, HR and the business. So, having one or the other, it can work. But if you truly want to be successful, you really need both a strong project manager and then somebody that thinks about change. It can be the project manager, it can be somebody that is dedicated to that change. I think it's maybe even a realisation we had. In the beginning, we were just a data provider. We just gave data to our customers, and then we worked with them to help them figure out how to use it. But in a way, you are bringing it to the employee, you are changing a process, you are changing something. Even just using data in HR is a change. So, we've become a lot more vocal about the fact that you need to think about change in communication, you need to think about the marketing of the project, the packaging of the project to get people excited, because otherwise, it will be branded as just this thing HR is doing. So, we try to be very mindful and intentional about how the project is being perceived by anybody else out of HR.
[0:17:38] David Green: I think you've mentioned four elements of running a successful skills project that are really important, (1) what's the business problem you're trying to solve, proper business problem definition around it, and don't be afraid that if that's a specific function or a specific country. It could be the technology function, for example, and the country could be sales, whatever it is; (2) get a business sponsor involved, particularly if you're early on the skills journey, I guess, because ultimately you need that, because providing insight is one thing, but you want to try and get through to action; (3) involve your people, analytics team; and (4) I think a really important element that you talked about there was communication and change management as well, to drive it through to outcomes. Is there any other element that you would say that as an organisation, you would want to include to running a skills project to make it successful?
[0:18:40] Mikaël Wornoo: Probably the mindset. I think it's very easy to essentially try and boil the ocean. It's like, okay, every process needs to be skills-based, or we are going to start skills-based recruitment for everybody. While in many organisations, especially if you look at it from the business's perspective, this still needs to be proven, like, why change if this is not going to have a massive difference? So, in the startup world, something they often say is, "Your product needs to be essentially 10x better than the incumbent for people to even want to consider change". And it's something like that design-thinking mindset, that product-oriented or base mindset, also really important for HR. So, really understanding that you're essentially trying to start a massive change in the way you're doing HR. So, you need to prove value first. And the mindset should be, "How can we prove value first and quickly?" Everything else can wait, everything else can come later.
Too often, it's seen as this thing by the business and by HR. So, the mindset about why you're doing this, how you're doing this, is super-important, probably the most important thing. If everybody is going in there thinking about how can we solve a true problem, and how do we keep going until we have solved the true problem, and how are we intellectually honest with ourselves and say, look, let's say skills-based hiring in a particular function doesn't really make a difference in our finance department, but makes a massive difference in sales, then why should we try and go for a one-size-fits-all approach?
[0:20:14] David Green: What I was going to say, so let's flip it on its head a bit. We've talked about what you need to be successful. Where do you see organisations fail when it comes to skills?
[0:20:23] Mikaël Wornoo: I mean, not doing all the things I spoke about, you mentioned, it's not easy. And I think it's not easy, especially when you try to do everything at once. For TechWolf, the way we approach a skills project is as a data project first. We try to go from data to insight to action. And so, fundamentally, what you're initially trying to do is either highlight a problem, do some diagnosis of some form, using skills data. Because essentially, what are you doing? Essentially, you have some precision on what it is your people do. And either that helps you retain your best performers, that helps you recruit in a better way, that helps you provide training in a way that is more personalised. Not doing that, not having that design-thinking mindset is probably the killer. Getting too excited, trying to essentially solve everything with technology. Technology is one aspect of this, but you need to have your ducks in a row, just as a project management or PM organisation, for this to be truly successful.
I'd say thinking that technology will solve your problem automatically is probably also one of the key reasons. I'd say another one, and this is related to what I've said, but it can very easily turn into a politically-charged project. It is inherently cross-functional. You're going to touch on departments in HR that are inherently siloed in most organisations. So, not being super-mindful about how you're going to interact with the talent team, the learning team, that is just a recipe for people digging in their heels, not cooperating. And so, we've had projects where somebody was exceptionally successful, but the inherently political nature of a transformation like that in HR wasn't necessarily properly taken into account. And that makes it hard to truly scale, even though you have the tangible business impact.
[0:22:22] David Green: Then if we think, Mik, about the capabilities that make an effective skills team, so we've talked a little bit about the business and people analytics as well. But again, in your experience at TechWolf, delivering these projects to companies all over the world, big companies as well, what are the roles and skills that you would say are essential to effectively execute a skills initiative?
[0:22:48] Mikaël Wornoo: I think it depends on the end user. So, as mentioned, you can have a strategic skills project where essentially, you're trying to use data to do decision-making in HR. You could have HR as a team, the recruiters or the instructional designers as an audience, or you could have the employee. So, depending on the end user, the makeup of the project is going to be a little bit different. But fundamentally, as mentioned, you need a strong project manager, somebody who's responsible for change, somebody who has data analytics and data analysis skills, and then you need sponsorship. I think that can really be it, but all the things that we spoke about need to be taken into account. So for me, the change manager, the person responsible for communication, should also think about how are we interacting with our peers in HR? How are we communicating across? How are we communicating up? How are we communicating to the employees?
So, I think the easiest thing to do in a skills project is using data to understand the workforce, to understand the skill gap, to see whether or not you have, let's say, the sufficient adoption of AI skills or another set of critical skills. Then the second easiest thing to do is essentially solving skills management for employees. Here we have a bunch of customers, IQVIA being one, where the main thing we wanted to do is essentially solve skills management for thousands and thousands of employees. Like, how can we actually ensure our employees keep their skills up to date in a way that is easy for them? So, we built an integration with Teams, it's integrated with the learning system, with Workday, so it's seamless. People came to the project team and said, "Hey, this is really awesome that you can infer my skills. I didn't even realise it was going to be that good", and people actually start engaging with their skills profile. I think engagement with people's talent profile went like plus-400%, or something like that. So, that's a massive number.
The hardest thing to do is probably changing an HR process, because it touches on so many things. So, before attempting that, either you need a very strong business case, like you need to have your project team lined up, and then change management is going to be super-critical. You'll probably need a few more people, you need your liaison in the business, you probably need the mirror of your project team you have in HR in the business for that to be truly successful.
[0:25:12] David Green: And again, I know that at TechWolf, we've talked about you're working with people in the tech scene, you're working with talent acquisition teams, you're working with learning teams and other teams within the broader HR sphere. How do those functions use TechWolf differently? Because I think one of the enablers of TechWolf is, it's not a platform, is it, which I think is probably quite helpful, because there's lots of platforms that people have got within their HR tech landscape at the moment. You can really, I don't know, maybe explain a little bit about what TechWolf does, because just for people who are listening that are new to this, perhaps.
[0:26:42] Mikaël Wornoo: 100%, and I'd say we're the only vendor that does this. We're unique in this, in the fact that we didn't want to build yet another HR tech platform. There's plenty of platforms out there. So, we looked at the market and what was very clear was that there is many a data problem. So, to solve a data problem, you don't necessarily need to build another platform. We focused on building really good AI that could just analyse data from various systems, that could grab data out of various systems, and then essentially solve that skills data problem. And so, TechWolf is API first, and what that means is we make connections easy. So, you know how your LMS doesn't talk to your core HR system doesn't talk to your talent marketplace? Every customer struggles with that, and so that's what we solve when we say we're API first. We're connection first, we make it easy to connect. And so, we want to make it easy for customers to, essentially, you don't have to think about a very technological and operational problem.
But then the question is, how do our customers interact with something that essentially lives behind the scenes? And so, there's the direct integrations with the employee-facing platforms, think the Workdays and the SAPs, but also the Visiers and the Crunchrs, so the people analytics platforms. We integrate directly with Power BI, Tableau, the analytics systems, if you will. We have our own admin console. So, essentially there's various ways of interacting with the data, or interacting with TechWolf. What is always front and centre for us, essentially, how do we make sure it's just easy for the customer? They already made a bunch of investments in their HR tech stack. We're not coming in to replace something, we're essentially coming in to improve the ROI.
With one customer, we're looking at essentially driving traffic to the learning management system by essentially improving and iterating on our skills assistant, because we found a way to let people engage with their skills profile. And then the next frontier is, can we find a way to actually get people to the learning system? So, there's plenty of ways of interacting with TechWolf, but the most important thing, if I zoom all the way out, is essentially building the capability in HR to analyse data, to work with data, and to get really comfortable with data. It's something we see across the board. Our customers are actually quite surprised and shocked how much more buy-in they get from their peers in the business once they start leading with data and a good story around that data.
[0:29:10] David Green: Everyone's talking about AI. Well, everyone was talking about AI, but everyone really is talking about AI now, and actually we're seeing it's not just talk, it's actually action, based on the research that we've been doing here at Insight222. So, with this emergence, where do you foresee the HR technology market heading with respect to skills intelligence, but maybe generally as well?
[0:29:32] Mikaël Wornoo: I think we're already seeing this, but the advent of generative AI is completely changing how people interact with technology. So, the idea of going into your platform to do a very limited set of workflows, I think that is gonna disappear completely. You'll have one super-app that is essentially going to be your interface, and that app is going to probably grab data from a bunch of other places. That will be systems of record. I think your engagement layer is going to change completely. So, at TechWolf, we're also thinking about this, and there's probably two layers. You have your AI layer, the one we've been building for six years, that essentially is really focused on grabbing a lot of unstructured data and bringing order in that chaos. And there's a second layer that thinks about how can we interact with that data?
So right now, going from data to insight to action essentially still, it takes some work on the customer side. You need to crunch the data, analyse the data, ask the right questions. I think as Gen AI matures, we'll be able to go up the stack. So, I think in a few months even, we'll be able to go from data to insights to prescribed action, all led by technology. And that's going to be a massive game-changer because, let's face it, not that many people are super-proficient in crunching data. ChatGPT and a few other tools have lowered that barrier. Everybody that is actually brave enough can learn how to code. But I think it's going to go much farther than that. Interpreting data is being codified in such a way that the insight and the action is essentially going to come very naturally out of that gen AI layer.
So, I think HR tech is in for a big change, if you look at agents, because a lot of things in HR are very manual and repetitive work. They're actually prime targets for agentic AI, for agents. So, I think an AI workforce in HR is going to come sooner rather than later. But ultimately, the employee will benefit, right? We're used to all these amazing tools in our life as a consumer. I think the enterprise HR tech stack has some catching up to do.
[0:31:41] David Green: What can we expect from TechWolf next? What should we be keeping our eyes and ears open for in the coming months and years, without revealing all your trade secrets of course?
[0:31:52] Mikaël Wornoo: We have a big announcement coming up at Workday Rising EMEA, so I won't spoil it yet. But in the coming years, I think TechWolf is going to continue to be the market leader in AI and HR. I think the opportunity is there now. There's a general awareness in the public that AI can be a game-changer, and we're seeing the traction in the market. So, I think making HR more effective is a massive market, a massive opportunity. HR is still responsible for the biggest cost in almost any workforce. So, we're laser focused on essentially going after that opportunity and making our customers super-happy. And the process I think, for me, every time I see that we can truly move the needle, I just get genuinely happy to essentially problem-solve and figure out how do we go from data to insights to action.
But for TechWolf more broadly, I'd say there's a few pillars in the short term. So (1) integrations, make it super easy to get started. As we mentioned, there's a wide HR tech stack. So, we want to make working with TechWolf as easy as clicking a button; (2) we want to ensure that we stay the market leader in getting skills data, because that's the hardest problem, truly understanding what people can do; and then (3) as mentioned, going from data to insight to action, making it super-easy to actually action that data, to use that data to drive meaningful business outcomes.
[0:33:11] David Green: Before we get to the question of the series, Mik, we'll probably have many people listening to this episode who are either very early in their skills journey or thinking about getting started. What would be your advice to those individuals, to those companies about getting started?
[0:33:31] Mikaël Wornoo: So, first of all go to techwolf.com!
[0:33:35] David Green: Well, it's not a bad suggestion!
[0:33:38] Mikaël Wornoo: Have a chat with the team. But I'd say, on a more serious note, I can guarantee you that in your sales or IT or R&D organisation, you can solve a problem with skills. So, instead of trying to go big bang right away, try and sit down with somebody in the business, try to understand what people challenges they are facing, and try and figure out if having access to better data on people, if using skills as a framework for talent management would really make a difference. I think that's probably my go-to approach. Don't be afraid to pilot. A pilot needs to be big enough to be meaningful, but small enough to be manageable, and just get started. It's probably the most important thing. Just start, but don't start too big. So, that would probably be my main advice.
[0:34:22] David Green: No, I think that's really good advice for listeners, and I've seen a lot of organisations in this space who are now quite far advanced on their skills journey. They started with a pilot, they carefully selected what that pilot was, as you said. Don't go too big, but do something meaningful that's going to have an impact. And I think the other factor, the other big factor that you talked about as well earlier, was get a business sponsor, someone who's got a problem that they want to solve and is prepared to take action on the insights that you identify through this. So, really good. So, Mik, we're going to get to the question of the series now. So, this is a question we're asking everyone in this series of the podcast, which thank you to you and the TechWolf team for sponsoring. How can organisations leverage skills intelligence to make more informed decisions?
[0:35:16] Mikaël Wornoo: So for me, as mentioned, it's getting started. Something that we've seen with every customer is, you can only truly create internal capability around skills intelligence once you have the data, once you start brainstorming, once you start having the conversation. So, I think getting started, getting your hands on the data and just doing it is the most important thing to make more informed work for a decision, because it's a muscle you need to train. And as you know, the first time you go to the gym, it's horrible, you're really sore, but after a while you get used to it.
[0:35:50] David Green: Yeah, I think that's great advice, just get started, because I think sometimes we're a bit dangerous in HR, we do prevaricate sometimes and we do want to have everything in place before we get started. And sometimes, you just need to get started and learn as you go a little bit, don't you? Mik, it's been a pleasure, looking forward to seeing you next week in Amsterdam. But before we end the conversation today, can you let listeners know how they can keep in touch with you or get in touch with you, and also follow the great work that you're doing at TechWolf?
[0:36:24] Mikaël Wornoo: Yeah, so techwolf.com, you can reach me and the team there, and then you can find me on LinkedIn, Mik Wornoo, and I'll happily have a chat with you to see how TechWolf can help you.
[0:36:36] David Green: Great, it's always a pleasure to speak to you and the team, and take care. I'll see you next week.
[0:36:41] Mikaël Wornoo: Bye-bye, see you next week.