Episode 218: How to Turn Strategic Workforce Planning Into Impactful Action (Interview with David Wilkins)
Are you still struggling to get it right? Are you struggling to make that transition from Excel sheets, align your data effectively, or executing your plans in a way that drives real impact.
In this episode of the Digital HR Leaders podcast, David Green sits down with David Wilkins, Chief Product and Strategy Officer at TalentNeuron, to uncover what it really takes to master SWP.
Drawing on years of experience and TalentNeuron’s extensive research, David shares actionable insights and forward-thinking strategies to help organisations transform their workforce planning efforts. So, hit play to learn more about:
Why the question of ownership is central to the success of SWP—and who should take the lead
How to align internal and external data for smarter, more impactful decision-making.
Why getting the right data architecture in place is just the first step—and what comes next.
The tools, strategies, and skills organisations need to move beyond traditional methods and drive real workforce transformation.
Whether you’re leading SWP efforts, navigating workforce transformation, or just trying to keep up with the rapid pace of change, this episode, sponsored by Talent Neuron, is an absolute must-listen.
TalentNeuron is shaping the future of workforce transformation. From Strategic Workforce Planning to skill gap analysis, TalentNeuron seamlessly combines external talent intelligence with internal data into one powerful platform. Join leading global enterprises already using actionable insights to boost organisational readiness and performance.
Visit talentneuron.com today.
[0:00:00] David Green: Strategic workforce planning, it's a topic that's been on the radar of HR and people analytics professionals for years, but it's arguably never been more important. BCG describes strategic workforce planning as a perennial challenge for organisations, and that while the core principles are not new, the urgency to act has increased, with the availability of data-driven insights changing the competitive landscape. So, why is strategic workforce planning becoming a top-three priority for most people leaders? And how can organisations establish an effective strategic workforce planning muscle that delivers business success?
I'm your host, David Green, and today on the Digital HR Leaders Podcast, I'm joined by David Wilkins, Chief Product and Strategy Officer at TalentNeuron. At TalentNeuron, David and his team work closely with organisations tackling some of the biggest strategic workforce planning challenges, and he's got some incredible insights to share about where the market is headed. We'll talk about who should really own strategic workforce planning, how organisations can better align their internal and external data to make informed decisions, why getting the data architecture right is only the first step in the process, and what it really takes to move beyond the traditional tools and methods to make workforce transformation a reality. So, whether you're trying to get a better handle on strategic workforce planning, immersed in workforce transformation initiatives, or looking for new ways to execute your plans effectively, this conversation is packed with practical advice and future focused ideas. With that, let's get the conversation with David started.
David, welcome to the show. As a Chief Product and Strategy Officer at TalentNeuron, I'd love to learn more about your role, but also what enticed you into the world of strategic workforce planning and workplace transformation?
[0:02:07] David Wilkins: Yeah, so it's interesting. I started actually at TalentNeuron in the role of Head of Marketing and was asked to take on the product role in February of this past year, which is pretty exciting. My current remit is to oversee the overall strategic direction of the organisation as well as the overall product, roadmap, and vision and the direction of the business overall when it comes to software and technology efforts. The journey here is sort of an interesting one, David. I've been in the HCM space now for over 30 years. I'd say I probably spent the past 20 of it talking about strategic workforce planning, in some flavour or another, right, whether it was during my time at Taleo or Oracle. This has been a subject that's crossed L&D subjects, ATS subject lines, obviously HRIS. So, it's been something I've been keenly interested in pretty much my whole career.
Here at TalentNeuron though, what's interesting is when I started in February, I did this thing that I think a lot of us would do in a new role, I interviewed as many clients as I could get my hands on. And what I learned was that a lot of our client base, they were using our external labour market intelligence, that we provided as TalentNeuron, really as a driver or as fuel for their strategic workforce planning efforts. And they were frankly doing a lot of that stuff manually, like connecting the dots between internal understanding of skills and taxonomies and job architectures, with our understanding of the labour market conditions and the similar view of those same things. And pretty early on, I had said to Julie, who was our CEO, "I really feel like we've got to pivot this talent intelligence thing that we're doing as TalentNeuron, really more firmly into the direction of strategic workforce planning, since that's what the majority of our clients are doing with our data".
It was right around maybe just a few months later that we ran into HRForecast. They were looking for us, we were looking for them. We made an acquisition of them in October, and of course that's all they do is strategic workforce planning. So, that's kind of how the journey happened for us, was really listening to our clients and understanding what our clients were doing, which really almost gave us a roadmap to pivot the organisation and really build this relationship with HRForecast, which is pretty exciting.
[0:04:33] David Green: You and HRForecast coming together, it must make your role, particularly being responsible for product and strategy, particularly exciting coming into 2025.
[0:04:44] David Wilkins: Probably the most exciting time in my career, actually, David, to be honest. You know, I think about my time at Taleo and earlier parts of my career, and some of the things I dreamed we'd be able to do someday, this combined organisation now actually does, AI powered taxonomy creation, the ability to ingest and distil really big data, like global data sets, and then discern from that signal and intelligence and insight, drive company decision making. Yeah, it's pretty crazy. And I think when you think about the merger of these two organisations, it's an unusual situation. And often when you bring companies together, there's a lot of overlapping stuff that you have to really think through, "Well, how are we going to deprecate that, or merge these things together?" And in some ways, this is a very, very complimentary merger, in that we've always come at it from the standpoint of external labour market data as our primary win, supply, demand, cost, understanding of competitors, what competitors are up to, right? They have this ability to ingest all of, your internal data and then distil that through job architecture analysis and skills analysis and things like that; but then also, to help with demand planning and figuring out where you need to think about talent investment in the future to match to your company objectives.
Then, they have other interesting tech, like a talent marketplace, that sits on top of your LMS and distils the courseware into the skills so that you can do personalised learning journeys that then help you with the build. And we have stuff that help you with the buy, with our hiring analysis module with talent calibration. So, it's really interesting, because now we have the sort of end-to-end capability, David, where we can say, "What's going on in the market? Where do you think you need to go? What talent do you already have? What are you going to need down the road against your future needs? Then, through our location planning and hiring analysis tools, we can help you with the buy. Through their talent marketplace tools, they can help you with the build. And then, there's some automation prediction kind of technologies as well that can also identify where things are going to automate.
So, it's moving companies beyond just the understanding and the planning, into like, "How do I actually go do it?" And that, to me, is a fascinating place to live, to sort of have this end-to-end sort of story. So, yeah, I mean if you can't tell, I'm pretty excited!
[0:07:12] David Green: Well, and actually it's an exciting juncture I think for strategic workforce planning. I mean, you said you've been working in this field for a long time and strategic workforce planning is obviously a topic you know well, both prior to and since being at TalentNeuron. And it's definitely one of the top topics of discussion among HR and people analytics professionals, has been for a number of time. But we see things like the Gartner 2025 HR Priorities, we see the BCG Report last year, you know, strategic workforce planning is a top-three priority for CHROs; and it's not just CHROs, it's beyond that, it's business leaders and CEOs as well. Why do you think this topic, strategic workforce planning, is so critical for organisations now, today, in 2025?
[0:08:04] David Wilkins: Yeah, it's a question I put a lot of thought on actually. And it's funny, because I just recently came across something that PWC did last year. They did a whole study on resilience, and they found that something -- they surveyed something like 1,800 business leaders. 96% of them had experienced some sort of crisis related business disruption in the last couple of years. And 76% said that it had a medium to high impact on their business. And it struck me that I haven't seen much of that quantified before, but I feel it, I think you probably feel it. I think we all, as business leaders, have felt like there's a faster pace of disruption. And I also think there's an interesting intersection of longer-term things that we kind of knew were coming all this time. How many years have we been talking about boomer retirements, right, and the impact that that would have on skilled labour, right?
But we also have known, I mean, if you're looking for a CDL driver in the US or any other kind of heavy machinery or truck driver type of role anywhere in the world, really, they're hard to find, right? Oil and gas, difficult. Anything in the health care space, difficult. Anything in AI, obviously, incredibly difficult. So, there's these large pockets where we have systemic challenge. But I think in a world that feels like the pace of disruption is happening faster, organisations are feeling this need to be more nimble, proactive, to plan more effectively. And I think that starts with having a new mindset about SWP, which is that it's always on and that it's a constant thing that the business just needs to build this muscle and just get good at it, because I don't think it's going to change, I don't think we're going to see a return to normal. I think this volatility maybe, in the way that we experience sort of the absence of a steady state, I think is the new normal. And I think organisations are starting to see that as a reality and therefore investing more in this area. That's my sense of it.
[0:10:11] David Green: I'm sure at TalentNeuron you've conducted research, or obviously you've got the experience of working with the companies that you're working with, on the current trends and challenges that businesses are facing with their strategic workforce planning efforts. What are the main things that you're seeing in the market?
[0:11:21] David Wilkins: Yes, so interestingly, we did our own study last summer seeking to better understand, with quantitative data, how pressing an issue is SWP for our clients and non-clients. So, we surveyed the client base and also sort of the whole prospect base, which of course is, at our size company, it's many thousands of people. And what was interesting is 67% of the respondents overall said that strategic workforce planning was either very important or extremely important. 83% of our clients had that same very important or extremely important sort of answer, which is interesting because I think as you probably know, David, we skew to the Fortune 2000, which sort of suggested to me that it's probably an even more pressing priority for large orgs, which would make sense because if you think about some of the things that impact large orgs, more things potentially could impact them on a global scale because you're global, right? So, that wasn't terribly surprising.
In that same survey, we also started to enquire about what specific subsets within the universe of strategic workforce planning were either key priorities or areas of key challenge for them. And what was interesting is the top five things in order, in terms of priorities, were number one, understanding the current and future talent landscape, which not surprising, I think we probably could have guessed at that one; demand planning was number two; skill analysis was number three; labour market intelligence was number four; and then internal talent intelligence was number five. Interestingly, where they felt their lowest maturity overall -- and by the way, there were another ten or so items, right? But the areas where they felt lowest maturity were also in the top five. So, skills analysis was an area where they felt low maturity, demand planning, and then their internal talent intelligence. And so, there's this interesting disconnect between things that are rated highly in terms of their importance of priority and the lack of maturity or capability that the business is currently possessed to chase those.
I think as I started to dig into that further and started to really talk to clients about it, the overarching rationale for some of that, I think, for me comes to a lot of lack of tooling. What's come through loud and clear this year is that the vast majority of strategic workforce planning, as we think about it today, from what I can tell, is happening in Excel or Power BI, right? And there's a lot of manual manipulation and manual marrying of external frameworks, internal frameworks, external taxonomies, internal taxonomies, external job architecture, internal, to try to get to a sense of what's going on between my internal state, what's available to me externally, and then how do I adjudicate the delta and begin to put a formative plan together that makes sense? But in the absence of tooling that can marry some of those things together, via AI or via other sorts of techniques, the end result is people are ending up in spreadsheets.
So, you think about skills analysis, like how do you do that effectively if you don't have an ability to ingest big data, look at labour market intelligence, look at or to understand your current skillset internally? But what if your skill taxonomies are different? How are you going to manage that gap? A lot of the stuff ultimately I think is going to come back to, do we have the right tooling in place to support some of these gap areas? Because I think the areas where things are most gapped are areas where there's the least amount of tooling. And so, there seems to me to be some level of correlation there. Unlike other areas of HCM where we have all the tools in the world, this is an area where it doesn't feel like we've reached a point of even basic level of tool sets. So, that's my read, but it's an interesting problem, where I think a lot of what companies seem to be putting importance on are things they can't quite do yet all the way, from what I can see.
[0:15:48] David Green: So, obviously, and you'll see this more than me, organisations are increasingly investing in new technologies to help them with various tasks and processes associated with strategic workforce planning. And obviously, those tools, like TalentNeuron, like HRForecast, they provide data, but they also give you the ability to put that data together, deliver insights and help you hopefully make some decisions around that. But it's not as simple as that, is it? What else do organisations need to be doing, or maybe stop doing, to actually move the needle when it comes to strategic workforce planning? Because again, I think we make this mistake a lot of times in HR that we think it's just a technology solution. It's not, it's technology-plus-plus, isn't it?
[0:16:37] David Wilkins: Yeah. I mean, I think the way I think about this particular part of HR or the HCM spaces, I think of it as sort of railroad tracks. I think you absolutely need one rail that is your technology, and then I think you need another rail, which is everything else. And absent either of them, I think you're gonna be challenged. But you're absolutely right, David. I mean, I think the first thing, I mean, let's think about it as a start/stop/continue kind of thing, right? On the stop side, stop thinking about this as a demand planning exercise in the case of small 'd' small 'p', like, "I'm just going to figure out what headcount I need for the next year", which is mostly how people think about demand planning. Stop thinking about this as a financial exercise to fit the headcount I need and for my available budget, which the corollaries to all of those is start thinking about this as a continuous ongoing process where you need to build serious muscle memory.
I was talking to Telenor earlier today and I was talking to Christian Inglingstad over there, and interestingly, he doesn't call this strategic workforce planning, he calls it 'workforce shaping', which I thought was really interesting. It gets you away from that notion that you do the plan and you're done, right? Shaping is something you do all the time. We've been using the language of 'workforce transformation' for the same reason, that transformation is continuous, you should always be doing it, it just should be part of who you are as a business. So, that's an important thing. I think the other is to just embrace a state of agility, and we therefore need to continuously monitor where we're at and evolve and change and inflect and constantly iterate where we're going and what we're up to.
I think the other big thing that I've seen is I think organisations need to get to a place where this is a cultural and systemic norm. And I know you've seen this too, but sometimes you get a really strong champion who's in a department, the one that really thinks about strategic workforce planning, and then they leave the organisation, or they get transferred to a new group, and all the stuff that was in flight just goes away, because it's centred on that individual as a hero, rather than being inculcated into the business as systems and processes, and established norms of how the work gets planned for. So, I think some of those things are really critical.
I think the other thing, which I've been railing against my entire career, is we've got to get really serious about breaking down the silos between L&D and talent acquisition and performance and comp and all of those different groups. I sometimes jokingly say that HR is a little bit like light. You can measure light as a waveform or as particles, and all we're ultimately trying to do is make sure the business has a talent that needs to achieve its business objectives. I mean, fundamental, right. And yet, we break it down. Once we observe it, we break it down into particles, and now there's a this thing, and there's a this thing, and there's a this thing, and they no longer live in that super position where they can inform each other and exist simultaneously in multiple ways.
[0:20:04] David Green: Maybe looking at it from a data perspective, so maybe two elements to this question, David. Again, for those listeners who are thinking of maybe investing more time and effort into their strategic workforce planning or workforce transformation, there we are for this year, what are the internal market and external market data that they should really be focusing on? And maybe then, the second part of that, is what sort of data architecture should they be looking at as well?
[0:21:28] David Wilkins: As you might imagine, we've been thinking a lot about this subject in the last few months! What's fascinating to me, David, is when you break all this stuff down and you look at it sort of, "All right, let's forget about there's SWP tools and there's tools like what TalentNeuron used to be on its own, which are sort of external labour, market talent intelligence kind of tech", and then you've got LMS stuff which does its own thing and you've got all these different… so, if you just stop and say, "Okay, what are the essential data sets that we need?" What's really fascinating is it's almost the same data set, but like opposite sides of the same coin. So, take for example supply. You want to understand what the labour market supply is, what the skillsets are, what the capabilities are, where in the world it is, what it costs, right? Well, don't you need to know that about your own team as well?
I need to know where my team is, what talent they have, what skills they have, what capabilities and what they're costing. Okay, so I need supply data on both sides, right? I need to understand demand data. I need to understand where in the world there is high demand, so that I'm not going to chase in the markets where I'm going to get slaughtered by a Microsoft or an Amazon, who are hiring the same kind of talent as me. So, I need to understand the demand signal, what kind of jobs, what kind of skills, what's the pace of change, where it's changing, how it's changing, and am I going to move into a buzzsaw, like I said, right? But I also need to know my own demand against where I'm trying to go as a business and what capabilities I'm going to require. What am I going to need? What skills will I need? Where will I need it; where in the world; in what roles; in what functions? You need to understand cost. But again, I need to know that internally, I need to know it externally. If I'm going to chase wage arbitrage strategies or reduction in labour cost strategies, I need to know what the cost is externally, but I also need to know where I'm currently spending.
Wouldn't it be cool if I could also tell you, what are you spending for your IT function based on your geographic distribution versus what your competitors are spending based on their geographic distribution? That's interesting. That sure would be helpful from a strategic workforce planning perspective. We have all that data, right?
[0:23:40] David Green: And also, what talent are your competitors hiring? Are they going into new areas? And then suddenly, you can -- the best and probably the earliest indication you're going to get about that is who they're hiring, I guess.
[0:23:53] David Wilkins: Yeah, are they hiring different kinds of people? Are they hiring different kinds of skills? Are they hiring in different parts of the world? Is the pace of hiring changing for a given role in a given place for a given set of skills? I mean, all of that is super-rich, competitive intel, that if mined properly can give you all sorts of sort of interesting insights, right? Skills is the other big area. Again, I need to know how are skills evolving in the market? What skills are no longer being asked for that are assumed to be present or no longer in demand? What skills are now highly in demand or are growing? But then, what do I have and how do my current skillsets match against what that is, but also against what my demand signal suggests, right?
So, it's a long-winded answer, but I think what's really fascinating is when you start really peeling it all back, what you realise is you actually need almost the exact same data from an internal perspective and an external perspective. Which then leads to the job architecture and methods and models question. If I'm going to evaluate a candidate for external hire based on the job profile and the required skills and acquired experience and everything else, and I'm going to do a match score or something like that to say, "Yeah, these people are a good match for this", shouldn't I use that exact same algorithm on my internal team? That way there's no bias and I'm effectively looking at people the same way across the whole thing, right? If I'm looking at, like, the availability of talent or my requirements, shouldn't I be using the same kind of algorithm when I look at the role and I look at what typical expectations are for what's in it? Shouldn't I be applying that internally and externally.
So, we're coming rapidly to a place where in our data architecture, and the way we're thinking about this stuff, David, we're really trying to come at it and say, for as many of these things as possible, it should probably be the same algorithms, and the same methods, and the same models that are applied internally as we're applying to the external market, to ensure consistency in the way we're doing the eval. So, when that problem that comes up today, when I'm doing my internal taxonomy and my external one, did I get it right? Did I map it right? Did I marry this? Did I take this plug and put it in the right spot, and this one, put it in the right spot? And let's take that all off the table and just say, we're gonna have a shared taxonomy for skills, a shared taxonomy for job architecture, a shared way to evaluate degree of fit of people against that, and then build out a shared data architecture and a shared set of methods and models, so that we're looking at all of that stuff the same way and taking away all of that pain of having to go from this system to this system and their version to this version. Just take it off the table and just do it all behind the scenes.
So, that's where our heads are at in terms of reducing the complexity of all of this, is just to kind of bring it back to foundational pieces and forget about whether it's internal or external and just look at it the same way. And in the process, I think we can dramatically simplify a lot how we do this and unlock the power of AI and machine learning techniques, and things like that, because we don't have to then do this Rosetta Stone thing of marrying the different taxonomies together, we would just come at it with a shared framework.
[0:27:19] David Green: Yeah, and that probably leads nicely to the next question, David, please add anything around maybe AI and machine learning as well that you're starting to see maybe in this area to this. Let's say you have the right tools and the right data architecture in place. What are some of the other challenges you find that companies will face in ultimately executing their strategies? You talked about some of these, I think, what you should stop and what you should start.
[0:27:49] David Wilkins: Yeah, the only one we haven't talked about, that I see everybody stumbling on, is they always start too big. There's this daunting sense, David, which I'm sure you've seen a million times, of like, "We're gonna do SWP for the whole company". And you're like, "No, no, you're a 150,000-person global company. Don't do that, that's crazy. Pick a very small business unit with a very strong champion and build your muscle memory, build your capabilities. You're going to fail a little bit here and there, it's not going to go well, but find the right champion, find the right project where you can have an impact.
The other thing we recommend, you don't have to start with a whole SWP project. Start by doing, like, a job architecture analysis or automation prediction assessment, and just understand what that means and how would that inform your SWP strategy. That's the only other thing I add on to the other things we've said, is just be really thoughtful about what your starting point is and give yourself some grace and some breathing room to learn and grow. Because if you're successful, word of mouth will go, and then you'll be doing another project, and another. Then, the next thing you know, you're doing all of North America. The next thing you know, you're working on an entire division of a company. But that's the only other advice I'd give, is start with manageable-sized projects and don't be daunted by the notion you've got to start at the company level.
[0:29:13] David Green: So, David, before we head to the question of the series, what are the skills and characteristics that you believe organisations need to invest in to drive success in workforce transformation and strategic workforce planning?
[0:29:26] David Wilkins: I think there are two critical things, right? I think organisations that are not inherently agile and just are able and willing to embrace continuous change is a necessary component of this. Because depending on what your workforce transformation requires, I mean that could be rethinking your buy strategy, rethinking a build strategy, could be org redesign, could be job redesign. I mean, there's pretty hairy things in there that organisations have to have a willingness to really sit down and be willing to make change. I think the other big thing is organisations that are not comfortable with uncertainty in making decisions based on probabilities, I think that can be challenging. I mean, I think you probably have seen some of the same works I have over your career where they have to know every nth level of detail in order to make a decision. And that's not this, right? It's more probabilistic and directional and sort of getting comfortable with the notion that we're really sure we need to head north. I can't tell you yet whether we're going to Toronto or Quebec, right? But I'm heading north from Florida. At some point, I'm going to hit Canada! And along the way, somewhere between here and there, I'll figure out if I'm going to Quebec or Toronto. I know it's north though.
So, that notion of continuously iterating on the plan and sort of having enough information to move, that's not a skill a lot of orgs have. And it requires almost a belief in your ability to do long-term planning and to sort of stick with a plan. I think it's one of the reasons, frankly, European companies are ahead on this issue versus many North American companies. I think European companies tend to be longer planning horizons and North American companies tend to be more driven directly by stock price and the immediacy of returns. And so, from what I've observed, I think Europe is ahead of the US as far as this particular side of HCM, I think because of that. And I think that mindset of being more long-range and being more planful is an absolute necessity to make all this work successfully.
[0:31:47] David Green: Well, as a European, it's good to hear that we're ahead in at least one area of HCM!
[0:31:54] David Wilkins: I'm sure there's many! I was highlighting just the one, but there are many others. ATS, as in hiring, I think is another area where Europe does it much better. But anyway!
[0:32:06] David Green: Yes, we could definitely have a Europe versus North America conversation!
[0:32:09] David Wilkins: Yeah, yeah, that's a whole different conversation!
[0:32:12] David Green: So, this is the question of the series, David. So, this is a question we're asking all the guests on this series of the podcast, which you're kindly sponsoring at TalentNeuron. How do you leverage people analytics to inform strategic workforce planning initiatives?
[0:32:28] David Wilkins: Ooh, that is a meaty question. Well, first, I don't know that you can do strategic workforce planning successfully in the absence of strong people analytics. One of the top items that people felt was important was an understanding of their internal talent landscape. It's also one of the areas where they felt most gapped. People analytics is certainly a pathway to that kind of understanding and knowledge. It's also going to be necessary for other components. You've got your SWP, understanding your DEI characteristics, understanding your age demographics, who's aging out, what does attrition look like, is attrition different in different market segments, is it different in different kinds of job families? I mean, all of those kind of essential data points are, I mean in my view, in the remit of people analytics. So, in the absence of that kind of understanding and knowledge, I don't know how you can drive an effective strategic workforce planning initiative.
I do think an interesting sort of analogy here, though, is worthwhile. I was sharing with David Perring a couple of weeks ago, I have this weird notion and how I describe the HCM space, David, and I will sometimes say, "We've all gotten really good at understanding the characteristics of the car". Like, I know what my internal temperature of the car is, I know when my tyres need more air, I can see the air pressure of every individual tyre now, I can heat two different sides of the car to two different temps, I know what I need to change my oil, my transmission fluid, I know my gas mileage on average. We've gotten really good at sort of tooling the vehicle. But it wasn't really until fairly recently that we got really good at helping the vehicle do what it's meant to do, which is to go from A to B. The purpose of the vehicle is to move you from where you are to where you're going to go. And nothing other than the operation of the vehicle at a fundamental level is informed by all of those previous metrics.
What does inform my A to B is a GPS and especially a modern GPS that can also give me different routes, tell me when there's an accident, tell me when there's a slowdown, tell me whether I want to pay more or travel faster, whether I'm going to go through tolls or not, right? And I think we need to marry together all the things that people analytics has historically done, which is get really good about how my car is doing, with how do I get my car from A to B, right? And I think expanding the remit of people analytics to include not just how my car is functioning, but what are the road conditions, is there an accident up ahead, are there alternate routes I can chase, what's it going to cost me to take the route that I'm about to be on, right? That kind of intelligence folded into people analytics, as we think about it today, I think suddenly is that lighter fuel or that gas on the fire for that SWP stuff. So, that to me is how we bring that together in a meaningful way.
[0:35:34] David Green: Well, that seems a good point to close the conversation, David, and obviously I look forward to chatting, hopefully face-to-face, at events this year. I presume I'll see you at People Analytics World again in London and if not before. Thank you so much for being a guest on the show, I really enjoyed the conversation. Before we part, can you let listeners know how they can keep in touch with you and follow all the great work that you're doing at TalentNeuron? And I don't know if you've fully integrated the HRForecast branding yet, but if there's two places that people should look, then please let us know.
[0:36:10] David Wilkins: Yeah, so fortunately, we're on the path to integration. We're not all the way done but I'll give you the one URL to go to. That would be talentneuron.com. So, that's nice and easy. And you can get to all of us that way, all the former HRF stuff and us. For me personally, it's simple. I'm just dwilkinsnh at LinkedIn. So, just look me up on LinkedIn and I'm happy to connect with people and would love to continue the dialogue with you and others at any point. I love this stuff. So, thanks for having me on, really appreciate it.
[0:36:39] David Green: Thank you, David. And as I said, look forward to seeing you in person in a not-too-distant future.
[0:36:44] David Wilkins: Sounds good. Thank you.