How “talent intelligence” data combats reactive workforce decisions | with Toby Culshaw

Hello, everybody. And you're very welcome to this week's edition of the Shortlist. My name is Holly Fawcett. I'm the director of content here at Social Talent. And you're so very, very welcome to this week's episode here in early December, Wednesday the 7th of December. And today we are going to be talking about how talent Intelligence data comes combats reactive workforce decisions. And I'm sure many of you have noticed over the past couple of weeks, some of you may personally yourself have been very personally impacted by some of these decisions. But in very difficult economic times, most business decisions are really boiling down to numbers. And those numbers relate to dollars and cents rather than personal decisions. And what if that data that we were relying on, those numbers that we were relying on was humanized instead of a cycle of overly reactive firefighting to particular investment decisions? Whether that's we save money over here, we invest money over here. How can workforce planning look to the much longer term to create a more sustainable, steady approach? That's what we're going to be talking about in today's episode, using talent intelligence data because we hope that this might offer a very different perspective. So joining us on the Shortlist today to chat about this is none other than Toby Kulshaw, who quite literally wrote the book around talent intelligence. Toby is the talent Intelligence leader for worldwide operations and consumers at Amazon. He's also the author of Talent Use Business and People Data to Drive Organizational Performance. And yeah, hopefully we'll dig into what on earth talent intelligence really is, how this might offer a more balanced perspective to workforce planning and strategy. And then more importantly as well, how, how this data can offer a much more alternative route to worst case scenario planning and mass layoffs as we've been seeing lately. So, Toby, hello. You're very welcome. Tell us all about yourself, how you got here and this book that you've written.

Thank you. Well, firstly, thank you very much for having me. That's a heck of an intro. So I appreciate that greatly. So Toby, I run Talent Intelligence for we've changed our names. We're actually worldwide Amazon stores now. Oh, big name change. Okay, same difference. So essentially that's a part of our business. It's anything from that you're buying from us as Amazon, samson.com, our Whole Foods businesses, anywhere you're buying anything from us through to how it gets to you. So it's the warehousing, logistics, pilots, how we want to get to us apart from the associate workers. So I don't cover the army, literal army of workforce associates that we have, which are some amazing people but my team don't cover that section but pretty much everything else in between. It's fairly big organization so a few hundred thousand people within within the org and we cover the full gamut, full remit, all job types, levels you could think of within there. So pretty big and broad spectrum and we cover talent intelligence. So you know, as we can dive into what that means for, for us as an industry. Can't necessarily dive into Amazon specifics, but we can dive into what Amazon talent intelligence is, how it all fits together. Me as an individual, I come from research, sourcing, headhunting, search, that sort of stuff. I guess from, from day one I was used to kind of getting information, getting data and trying to influence through sourcing intelligence. And it was, it was really a few years back where that started to scale and I started to realize that actually if I got earlier in that decision making chain and that decision making process, I could make my sourcing team's lives way easier downstream. If we effected that decision upstream rather than waited for that decision to be made and then trying to kind of influence the impact of that downstream. With the sourcing intel life was just easier. So started on this kind of talent intelligence journey then and that's two, 10 years ago, something like that. And then for the last probably seven, eight years been very much pure play in that TI space. So I was over at Philips previously, the Dutch technology company where I ran talent intelligence there for a number of years and we built an internal consulting function doing ti and then I've been at Amazon for the last couple of years building over here.

Fantastic. Can I dive a little bit more into that? So you were at Philips before that you were at SAP kind of working on similar kind of talent intelligence kind of things. What was the journey from sourcing so to speak and how to make as you're saying, make your sources lives much better downstream and kind of really bringing those decisions to the fore much earlier in the process. Can you tell me an example of a story about maybe how some of those decisions have played out or some of the impacts of those decisions and what they meant for those organizations?

Yeah, sure. So some of the earliest in hindsight pure play TI work we were doing was back in my Talis days, so many, many moons ago. There are a number of things. So for example we were sourcing for some warehouse workings, we had a manufacturing site and we just couldn't get candidates, we couldn't find any candidates for this location. We couldn't understand why? It was a site that we'd been in for 10, 15 years. It was always been very stable. We couldn't see what was going wrong. So we started diving into it a bit deeper and we realized the particular industrial estate we were on 15 years ago when the site was launched, it was a really bustling industrial estate, loads of talent, really good location, good infrastructure, really worked well, lots of people for us to approach and to have local talent. Fifteen years later, we were literally the only people left on the estate. There was no one else there. Recruitment was all remote from that location. So no one had realized that that was the case and there was genuinely no one to poach from, There was no one in the location. So we looked at that, looked at the feasibility of that site essentially going forward, tied in HR and all the other project teams and eventually that site got moved and we moved to another location, a similar sort of timeframe. We were looking at some cyber security work and we realized, and this is the thing about ti, it's always worth remembering, it doesn't always pay off. Your best of intentions doesn't always work. So. And we can dive into that as well. But you know, we were looking at the particular type of cyber accreditation. It was a cybersecurity accreditation that the government, to do any kind of government contracts in the uk, you had to be accredited in this particular accreditation. And there were genuinely only a dozen people in the whole of the UK with this accreditation. And to be accredited, I'm getting really granular, sorry, I'm getting really geeky. But to get accredited you had to have one of these people on your team to get accredited. You couldn't just send your team wherever to get rubber stamp. You had to already employ one of these people, then all your team get accredited, then it spirals out and keeps going so on and so forth. And we were looking and we were struggling from a sourcing perspective. You know, we'd approach these people, they weren't making huge mega bucks, they were making 30, 40, 50K. We'd offer them 60, 70, they'd get counted 90. It was, the counter was just aggressive because everyone knew if you didn't have this person, you can't bid for government work, you couldn't be accredited. So my team at the time made a, a business proposal to take them all, get all of them out the market, even if they were on 30, 50k now give them 120k, give 150k, doesn't make a difference. Get them out of the market for an entire year and you'd have no competition because no one else would be able to bid for government work. So we get ourselves accredited, no one else would be able to get anything going and it would just be an open field. Obviously going to the business, love the idea. But going to finance and saying we're going to have a dozen people that are sitting on a beach somewhere and doing their work for a year or 18 months, they weren't so thrilled on the concept. So that one didn't really work. But we carried on on that thread of how can we use the data we're seeing from a sourcing perspective to influence decisions. And we ended up changing pay leveling for cyber security, we ended up moving our cyber hq, they ended up moving, changing the whole role descriptions and lots of different things within that space. That was all coming from initially sourcing data. And I think that's the key for me is when you start looking at the data. We see as ta, we see a lot of really rich information but we're really bad at bubbling that up, really bad at bubbling that up in a consistent way to decision makers. We can bubble up to the hiring manager. Hiring manager doesn't generally care. They think we're making excuses to why we're failing. But we struggle really to bubble that up and consolidate that through to a decision maker that can actually affect a decision upstream. And that's really at its crux, what TI is all about. It's all around bubbling up to get upstream.

Very good.

We've got a guest.

Oh, we have a little guest. Hello, Good afternoon. When it comes to that talent intelligence piece though, what are the key stakeholders then that you're influencing? Who are they at? What sort of level in the business are you talking to on a, on a regular basis then that folks might need to inside other organizations if they want to start implementing TI where they come from?

Yeah, it's, it's really at its core around who is the decision maker, that that's the number one. So it could be directors, it could be VPs, it could be the C suite. Generally speaking you find that the C suite is, is more around thought leadership and they're looking further out. It's usually that VPSVP type level that are actually making the decisions that impact the business on a day to day. So generally I'd say it's that direct to vp.

Everyone speaking your microphone, they can hear.

You on the microphone. That's Holly we're talking to now.

Hello. Hiya.

So it's really that VP level generally it's that decision maker generally and you're really looking to impact upstream wherever the decisions are being made. So if it's a centralized organization, hit those central functions. If it's decentralized and the decisions being made in the business move out to where the customer is. It's all around identifying who the customer is, who's making those decisions and then moving accordingly.

I will, I'll take the instructions from your, from your little boy there on your lap certainly. And make sure that they go back upstream.

Happy.

Take your time.

Toby.

Oh, I love it when we have unexpected guests on the short list. He is so very welcome to come back anytime.

Future. The future. I tell you about future Intel.

Absolutely. Future intel is right. We keep growing them. So can you describe for me maybe what some of the so obviously we have those decision makers in terms of you look really looking at senior vice presidents and very senior directors within organizations to really make those decisions. What are the types of data that they're looking for? Are they looking for your rough work? Are they looking for conclusions? Do you find a difference with the types of organizations that you're dealing with? You know, whether it's a Dutch organization who probably come from a much more principles first type culture versus an American type organizations where they might be just like give me your conclusions Toby. Like what kind of intelligence or data or conclusions are they looking for from talent leaders to start making decisions about where we host manufacturing facilities or sites or whether we take all 12 cybersecurity professionals in the whole country.

Yeah, great question. So I'd say the culture of decision making is generally dependent on the the country that that organization was formed in. So if you're a a German it's going to be quite hierarchical, quite structured as a default state. If you're in a Dutch company it's lots of decisions by consensus. So lots of very general opinion. Everyone's got the opinion to and a power to veto. Very much consensus decision making. American organizations are generally going to be fast decision making organizations. Not always fast to transform but faster to make decisions and look to move quickly. So I'd say that the decision making process can change dramatically. The mechanism for delivery can change dramatically. If you're in a B2C type company or a lot of organizations nowadays will be very PowerPoint driven very much around Take me on the journey. I don't want to get into the Excel. I don't want to get in the data points. Take me on the journey. Talk me through this, walk me through this. Show me where we're going from and to, and what this, this whole journey is going to be. So understanding how to create that journey and take people along with you is really important. But then other organizations are going to be very, very data first. And it's going to be, you know, high engineering organizations. They could be long form text. Amazon were famous for our long form text. We don't do any PowerPoint here at all. It's all long form documents. So, so that the mechanism for delivery can change. It could be a dashboard versus a white paper versus a PowerPoint. So the mechanism can change and the delivery mechanism can change. But essentially all leaders are really looking for the same thing. They're all wanting data. Data is your absolute friend. It can be really hard because psychologically anecdotes and gut feel, if you try and combat that with data, the natural reaction subconsciously, people don't even do it consciously, purely subconsciously, is to double down on the. Your initial gut feel. So you're, if you're saying, if the leader is saying, I really like this location, I went on a site tour there, there's some really great people. And you say, but the data says that there aren't enough people. Naturally they're going to double down and say, well no, I've met, I've met the really good people. I know they're already good people. I've been there, I've seen it, I feel it. I know that. So you've got to be really careful about how you're positioning the data. Understanding how different functions within your organization position data. So is it an Excel? First thing, do you want reams and reams of data that people can analyze themselves? Is it a. Do you know what? Just give me the three key talking points you want me to take away this meeting from. And then everything else, I'm going to dive into my own leisure. So understanding kind of that mechanism, I hark back to mechanisms a lot because it's a big thing with Amazon culture. But understanding those mechanisms of how decisions are being made, what data people need to make the decision. And being open with that, being open, like, you know, this is what I can get, this is what's out there. But what are you going to need to make a decision here? What are your key parameters you care about? Is it supply? Is it demand, is it cost? Is it competitiveness? Is it the overall infrastructure? Like what do you really care about? Because quite often depending on who is the actual core decision maker in your organization and who's got the power, they're going to care about different things. Line and business leadership. They care about access to talent because they want the best people they can possibly have in their teams. They want all those high performers. They really want to drive it really, really in as high performing team as possible. If you're talking to finance, they might not want that. They might want really cost effective solutions. They might want low attrition, they might want high duration within the organization and big stickiness within an organization and low competitiveness. So depending on who the decision maker is within that chain, you're going to have a slightly different answer and a slightly different proposition essentially. And it's not always obvious who the decision makers are. In companies, quite often there are functions that will drive core decision making. It's either going to be finance, it's going to be sales, it's going to be ops. There's strategy, there's usually a function that really rules the roost depending on your organization and the organizational culture.

That's really interesting actually. I wonder who or how somebody who is working in recruiting today who really wishes to bubble the information, all the insights that they're gathering as they go about their ordinary recruiting work and they're noticing this trend. They're noticing for example we just can't get the caliber of talent that we seek at this particular location. Can we do something else? How do they go about rooting out who the key who the actual decision maker is to in order to then influence at the right level? Do we go to a committee? Do we just, we just go go to our skip level manager? Like how do we go about that?

Does that actually happen? Don't be afraid of asking the question like ask questions. And quite often I think in TA and I think this is my gut feel is this is inherited from, from agency side. We like to look like we have all the answers. We like to look perfect and we're giving this perfect down selection of candidates and everything is great and hunky dory and we're like the duck floating across the water and we don't show the legs feverishly going away underneath. Because of that we're sometimes scared to ask questions and look naive and be open with these things. Ask your hiring manager. So go to them, say, look, we're really struggling to recruit in this location. I don't think this is the site for us for our next five year expansion plan here. Who makes a decision around where this next five years develops? Is it you? Is it your boss? Is it your boss's boss? Is it the country leader like who's actually making these Strategic plans and then just go and ask, go and talk to them. If it's strategic workforce planning, time to strategic workforce planning. Most companies don't have SWP in all honesty. Most companies you'll look at, even if it's called swp when you start diving into it, it's actually operational planning. They're only really looking the next 12, 18 months out. They're not necessarily diving in as far ahead as you'd like, but somebody will have an eye on, on the future. Somebody will be looking at it, going, what's this five year horizon? If this all goes well, if this goes according to plan, where are we trying to get to? And it's, it's just around slowly picking at these threads until you get the right person. It's a bit like the old fairy tales. You know, you kiss enough frogs, you're gonna get prince and just keep kissing those frogs. Have those conversations and just be open. You know, it could be finance, it could be strategy, it could be your market leaders, it could be the business leaders, it could be a whole range of different people. But just keep asking those questions around. I'm seeing this problem. Who needs to make this decision if we need to go further with this?

Yeah, absolutely. And I, I myself was, you know, I was at a lecture around innovation for, for a whole weekend, which was riveting stuff, interesting way to spend a weekend certainly about business innovation. But the, the difference between a sort of an 18 month versus 5 year versus 20 year roadmap and strategic plan for an organization is incredibly different. And it's not really until you recognize the, the components of such a long term view that you realize all the things that I've been working on in the past have generally been incredibly near term. And, and we think we're being strategic by looking a year down the line. But wait till you see five years down the line. You know, it looks way, way, way different from here. What kinds of things have you seen when you've been moving from a much more, you know, much more tactical workforce plan now to a very actually strategic workforce plan? What, how, how different does.

Yeah, good question. I'd love to say it's massively different in a lot of ways. I think it's very similar. I think it's repositioning. So I think a lot of the data inputs, data outputs are very similar. People are struggling with the same sorts of questions, it's just leveled differently. Instead of struggling on a rack and hiring whatever the role is in a given location, it's more around the Question of is that location even feasible? Have we got that are we going to be in the same shape as an organization in 5 years, 10 years time? Do we want to be in the same shape in 5 years, 10 years time? I think there's probably a bit of a cultural clash going on between people that are looking truly long term out so five, 10 years and making predictions and trying to steer organizations in a really long term thinking way versus people that are looking at it going well. Actually the markets and the whole industry and the environment is moving so dynamically at the moment. I don't think anyone can forecast five years out. You could maybe go a year out and give a best estimate. You could maybe go two, three years out and say this is where directionally we want to be going. But I don't think anyone could really go that far out with any kind of degree of certainty. I think it's having that transparency, transparency to say, okay, well look, directionally this is where we want to be going. Whether it's actually these functions we want to move from high cost country to low cost country, or these areas we want to invest into from an M and a perspective and expand upon or these functions we think are going to be the future of our organization. We need to develop this out. These, the skills we need to go to. All of them are great. They're all directionally the right thing. But I think we've got to be smart about these things and saying if this is the direction we're going in three, five, 10 years time and this is what we're seeing from a 12 month perspective, from a TA slant, for example, how do we tie those together, how do we get those demand signals? So we go, well actually we know we're pushing in this direction. We probably don't want to keep hiring in this location. We want to start trying to manage those hiring managers expectations early to say, well actually look, if the average tenure here is two years on a roll and we know we're going to be shifting over there in three, maybe we don't want to be hiring as heavy in there. Maybe we want to get ahead of the curve and get some leaders in this other side. So a lot of it's just around trying to get ahead of the curve so that we make our own lives easier.

Yeah, I think that's it in a nutshell. Right. It's understanding that as a direction what we're going in rather than just constantly seeing the next hurdle that's in front of you going okay, Grant, I have and almost Accepting that requisition at face value by explaining, perfect, no problem. Yeah, I'll find you that, that person in this location. Great. Off I go. Right. Rather than understanding what the, what the long term impact of that particular hire is going to be on this function or this entire business.

It'S hard, honestly, it's, it's really hard. Particularly if you start kind of getting into organizations and looking at kind of the headcount planning versus the strategy planning versus the finance planning. They're all going to have different versions of the truth and they're all going to have slightly different answers. And you know, depending on the organization, your finance planning might be really granular and really clean. You can get a really good demand plan. As ta to say, actually we know for the next 12 months exactly what we're going to hire in a given role, given location, given level, everything really clean and crisp. Other organizations it might be, we know we're going to be hiring X number of headcount plus or minus 50%. We have no idea. It's just we're going directionally in this way. So you understanding, okay, where, where do we think we're going to have flex? Where do we think we're going to have some areas we have to challenge on? And equally, where are we just comfortable, where are we comfortable saying, you know what, these roles, they're not business critical, they're not time critical. If it takes another month, that's fine. Let's not put our resources into worrying about those ones. We know we've got a stable of candidates, that will be fine, it's going to be okay. But these ones, these are really business critical. We can't drop the ball on these. And it's not quite often the criticality piece that people fall into the trap of saying it's the senior stuff. And it's in my experience it's very rarely the senior stuff is actually business critical. It's, you know, if you're in a widget factory, it's the widget maker that's been doing it for 20 years and he's retiring next month and no one's actually flagged up that he hasn't got a replacement. And if he's not on the widget line, the widget isn't made. That's the business critical stuff. That's the stuff you really need to go, do we need that widget maker in the next 10 years? And we see that truck driving is a great example of this whole situation where people have been recruiting short term, medium term, they've been looking 612 months out. The truck driving industry has been saying for a decade, we're on our knees, we're collapsing, the infrastructure's not in place. We've got an aging workforce. We don't have the youngsters coming through. We're on our knees, we're in trouble. And then through the whole Covid period, obviously it collapsed and we had some real issues on truck drivers. Now, in a really interesting situation from a kind of strategic workforce planning perspective, because you say, well, do we build up this, the whole infrastructure? Do we build out the facilities? Do we build out the skill set and develop this whole next generation of truck drivers? Or do we say, well, actually we've got automated driving coming in and you've got all these autonomous trucks coming in in the next 10 years. Let's say, what do we do to plug the gap in between? So do we, do we go for human element, we go for the automation. And if we do either, what do we do about that, that gap and that variance in between? And there's good, there's going to be whole rafts of industries that are falling in a similar way. We've got knowledge cliffs coming where you've got the baby boomers all retiring. Granted, there's an element of unretiring going on at the moment as well where people retired through Covid thought, I'm putting my feet up, got cost of living crisis and the economy collapse. I should probably go out there for a little, trying to earn a bit more money because it's a bit tight. But we've got this whole knowledge cliff coming through where a lot of organizations I don't think are necessarily looking longer term to think, well, actually we've got a huge percentage of our workforce and our leadership are going to be leaving in the next three, five, ten years. What are we doing to backfill that? And it's hard because organizations generally now aren't looking at individuals to stay for a long, long period. It's not jobs for life. It's average tenure in organizations is dropping year on year. You know, it's now sub two years. That's very hard then for an organization to say, well actually we're really going to invest in our people. We're going to do leadership development programs. We're going to do huge amounts of training because it's really hard to keep them. So it's this paradigm of the old saying of, you know, what if we put loads of investment and training into people when they leave? Well, what if we don't and they stay. We're in this hard situation at the moment where we know these big ticket items are coming down the road. But how do we address that? How do we fix that stuff? That's really hard.

Yeah, absolutely. And I'd love to get your insights as well as to how talent intelligence can be used for internal mobility because I think once you get to the three year mark within an organization, the ten year does tend to stick even further. It's just once you can get them to that magic number of three years, it's wonderful. But how can talent intelligence intelligence be used for those particular purposes like for instance, understanding and forecasting when retirements are planned or probably going to happen when you are going to have board seats opening up, all that kind of stuff to really help to retain the workforce that you do have?

Yeah, I think this is a great example of where TI can't be an island. There is a danger with talent intelligence and we see it with talent acquisition data as well. We end up being an island of data. And quite often acquisition analytics sits by itself. It's not part of HR analytics. It's not tying into the broader spectrum. It sits by itself in ta. TI is very easy to do that too. It's very easy to say, I look at the external data, you've got HR people analytics over here looking at the internal we own dux. Now that's really dangerous because you need to tie it together. You need to tie it together and understand what are the big ticket items coming down. HR analytics people analytics teams can be your best friends. They give you those demand signals. They know the internal data, but they might not necessarily know the internal skill set because a lot of internal HCM platforms don't have talent cards granular enough. So they might say, well actually can you use those external platforms to cut back into our own workforce to know what skills we've got at the moment? If we do both those things and say, well actually we can see this is the skill set that the knowledge drop we're going to see from workers that are retiring the next five years, is that even available in the market? Have we built an entire skill set that is so niche and so specialized we can't go and headhunt this from other companies and other competitors. So how do we then tie into LMD and training development or etc to say we need to build the skill set internally because it's not going to be available externally? Or equally that we, we've built this skill set, the rest of the market's moved over to this now actually we need to pivot. We need to do our entire tech stack or our entire offering from product sales to solution sales. We need to pivot because everyone else is moving in this direction and this is why. So you can absolutely use that external lens reflecting back in to see what skills you could be losing, but also that external lens looking at competitors and the landscape to say, well actually this is how everything's changing. We need to be aware of that for moving forward.

That's really interesting actually. And I think it would be like that kind of data again, it's which stakeholder you're trying to influence here. If I knew as a sales leader that the way that we've been doing sales, while it works fine for us right now, you know, considering the product offerings that we're going to be bringing to bear in the next, I don't know, 12 months or whatever else, actually uses a fundamentally different process. Whatever else. And my team are amazing at this old way and not great at the new way. My gosh is to go great. I'm just going to bring in all, all the newness and they'll just teach everyone else. But actually they may not have that benefit either of bringing in newness as well. There's a lot of organizations who are on hiring freezes right now who have absolutely zero remit whatsoever to backfill any churn and they're relying on natural churn as well as a way to downsize their organizations and they desperately don't want to lose folks as well. So yeah, again, other ways in which we can bring in talent, intelligence to highlight other opportunities within the business for like L and D or a culture change and stuff like that to really retain and, and boost the performance of our people. Does that make sense?

Yeah, absolutely does. Absolutely does. And we'll, you know, both my previous team and my team now, we do a lot of work with our HR teams, PXT we call it here, people experience. But we do a lot of work with our HR teams to both benchmark to look at how we can build the stuff moving forward. But the point around the sales leaders just may triggered a thought in my head where don't forget this stuff can be really commercially impactful as well. So tougher economic situation. We obviously often think about how do we stabilize, how do we keep our people, how do we use that resource better internally. But equally there are commercial opportunities with that. Equally we're at a bit of a bear market. It's going to flip to a bull at some point. There is Going to be a break. So working with that sales leader, say well actually if I do competitive listening and I'm targeting our competitors and I'm looking at what jobs they're hiring for, what are the new VPs they're hiring, I'll be able to see when they start breaking that. When do they start breaking into a new market and hire a VP in APAC that they've never broken into that market before. Where do they hire a VP of a product line they've never had before? Looking at the job descriptions you can say well actually they've never hired, they've never had this product before ever. But we can see they're pivoting and they're trying to build something back end time with your intellectual property legal, legal team to say well actually can you see what this competitor is doing from an IP perspective? Because we think they're trying to build something out here and they haven't had this before. Are they putting any, anything through IP that we should be aware of? And suddenly you're getting this whole commercial intelligence sense where you're saying well actually we can see what they're doing as a competitor, but it's triggering from the labor market data is triggering from the VPs they're hiring, from the jobs that they're pushing out there. You can start seeing them pivoting as competitors much earlier than when they're going to go to market. They're not going to go and announce to the street that they're pivoting in whatever direction, but you can see from what they're hiring, where they're hiring much earlier.

So this is why your executive search background matters so much. That sort of COVID intelligence gathering that one can build when they're, when they're interviewing execs or you know, like I, I, that is obviously something that, that happens, but it shouldn't happen. You know, that sort of COVID intelligence in that way. But yeah, it can be used.

It gets super dangerous. So, so a lot of the, a lot of the competitor intelligence I'd say you can do with OSINT or open source intelligence. So looking at job descriptions, looking at press releases, looking at new hires, that's often tracked on their corporate websites or tracked on their, on LinkedIn or whatever platform you're in and whatever jurisdiction you're in, looking at their press releases, looking at their company accounts, etc. A lot of that stuff, it's all open source, it's all out there, it's all being discussed and open. When you get into that human side of intelligence. So human intelligence. And you are looking at primarily talking to people. You're primarily going to be looking at the interview process. You do get into a whole realm of data ethics. And I think it's something that TI has got to be very careful of. And we've seen sourcing and sourcing intelligence skirt around this a lot. We've got to be really clear that just because we can do something doesn't mean we should do something. Just because we can inject our intel questions into a recruitment process or we can approach a VP to say, you know, we want to hire you for this job, even though, you know there's no job there. You just want to dig into their experience and dig into a competitor. Can you do it? It's possible to, yeah, for sure. But should you do it? Is it the appropriate thing to do? It gets into some really gray or black areas. And I think we've got to be really careful that we, we set a precedent and say we're going to be very clean on the data we use. We. It's very sensitive information. It's very sensitive data we're using. Generally, we've got to be making sure that we don't fall into those traps because it's far too easy to. Because you sit there and think, I've got access to all this information, this rich, rich data. But we've got to remember these are individuals that are going through a recruitment process. They're vulnerable, they're open, they're being transparent. We can't take advantage of that. We can't use this information unfairly. So we've got to be very clear about from a data ethics perspective where we draw that line in the sand.

I'm so, so, so glad you came to that actually, because I know as a, as a founder of the talent Intelligence collective and you know, as if somebody wants to become a member of that, I'm sure they can also. You know, is that something that you're trying to set, you know, as one of your kind of founding principles? Like here is where our ethical line is. We now want to spread across of the TI or just even sourcing functions within organizations that as you're gathering talent intelligence, look, this is where we can go. This is where we can't.

Yeah, yeah, that's one of the things we set up. Yeah, for sure. No, there's nothing formal in process. Like the TIC was founded as a networking group primarily, and it's kind of evolved from that and developed around that. But for sure, we've had Many conversations within the group and we have monthly calls and we have chats on WhatsApp and Facebook and every other platform you think of. Data ethics has comes up quite a lot. And I think we've got, as we start broadening the field of TI and we're seeing more people coming in from people analytics, from IO psych, from all these different over. From economist backgrounds, like from all these different backgrounds. IO psych, industrial organizational psychology. Oh my God.

Jesus.

Right? Some cool stuff that goes on out there, I tell you. You wanted to see the cat. He's just coming to annoy me as well.

Oh, hello. Thank you.

So as we bring in all these different individuals with different backgrounds, I think they're holding us to account from a data standards perspective. And the reality is, Tati, it's quite new to us the way we handle data and what we can do with data. We're used to seeing things from GDPR perspective and personally identifiable information. We're used to seeing things in a CRM and safe harbor, etc. But we're not used to seeing, okay, well, how else can we use this from an intel perspective and an intelligence gathering perspective? We may be used to seeing that from a exact research stance or from a sourcing stance, but when it starts scaling out beyond hr, beyond ta, beyond hr, into the business and commercial intelligence, it's all very, very new and it's very scary. And yeah, we've got to be very, very careful how we play in those fields.

Yeah, 100%. I think it's right to draw a fairly clean line in the sand where nothing feels terrifying or like icky to those who are doing the data research or then utilizing it. Right. You want to be able to wash your hands and go, yep, this is fine, this is great. No one's going to come at me 100%.

And you know, we always got to think, what's the worst possible case scenario? What's the worst headline that could be written about this data? Or if this gets out, what's the worst? Then we could think. And you know, even if you do things with the best of intentions, sometimes it can go horribly wrong. And you just got to think, okay, well, just because I didn't mean for it to do that, that doesn't mean that that's not what's going to happen. And I think we've got to be very clear from the start. Whatever you're building, build it with the best of intentions, but with the worst case scenario in mind. Because if you think something could go wrong, chances Are it's probably going to go wrong at some point and you just don't want that hanging over you.

That was a good, definitely a good line then for interviewers as well. Again, you're interviewing with people for the best of intentions, but what is that you write down as you're, as your evidence gathering? Imagine it's going to be published somewhere. So like please be kind and you know, factful etc, all of those things. I, oh my God, we are way, way, way, way into our time and I probably have another 12 questions I wanted to ask you. Is there anything that you can be said, I think around the transactional sort of relationship that recruiters or and, and sourcing teams are having at the moment to, you know, what they want to push into ti have any advice about how to make some of those initial inroads? And I always spoke at the very, very beginning around like who to go to and kind of to bubble up some of those decisions. But how do they make some of those initial inroads to becoming a little bit more strategic with the data that they do have today? That might just build up to a much more talent intelligence function.

Yeah, I think there's two different ways. I think there's the more structured approach where you just start taking data more to your conversations. So easiest way, when you're going into a brief and you're about to go into a hiring brief, make sure you've done some research beforehand. Take the data in at the brief stage. So you're setting expectations, you're challenging the manager on the skill set, your challenge on the location, you're challenging them on comp, you're understanding the capeta landscape, et cetera, et cetera. Bring that to the conversation at the front. Biggest mistake I see across TA generally and you know, we've all been guilty of it, myself included, you're really stuck for time. You just go into that brief, you take the brief and then it's only like six weeks down the line. You're like, you know what, we're really struggling here. I should probably do some research on this. You run some research and you're like, no wonder we're struggling. This is a terrible location with no competitors, with a terrible salary, etc. And then you take all that data to the hiring manager and they're like, I think it's too late now. It looks like you're scrambling for an excuse. So I'd say start just putting it into a standard workflow now. Get it in there quick. Get it in as early in your process as you can. And that will just start seeding the data culture, I think, in terms of the bigger ticket items. Ask questions, find out what people care about, find out what people are looking at next year, obviously this time of year, looking at goal planning for next year, find out what those goals are. What's going to stop you? Generally, any CEO, what's your biggest assets, your people, what's your biggest risk for not delivering, not access to the right people. It's the same all the way down. So just work out what the big ticket items are for your business lane or business area or customer group, whatever it is, and to say what's going to stop you from achieving that? And then you suddenly, then you've got the points circuit. Well, then I can drill into that from an intel perspective. And then finally I'd say don't be afraid to do what I'd call a loss leader. So sometimes there are big ticket items you look at and you think, I know this is a problem. I talk to candidates all day, I know this is a problem. No one seems to care about it. But I'm just going to write a paper on this. I'm going to paper, do a little mini video, get whatever PowerPoint, whatever mechanism you want to choose. But I'm just going to write something and create this and just send it out there, send it out to some leaders and say, look, I think this is a big issue. I don't know if it's on your radar. Just wanted to make you aware of this. It's amazing how often whether it's working from home and return to work, whether it's hollowing out of cities in America and the fact that all the workers shifted out to the suburbs. How do you draw them back in? Whether it's the amount of jobs candidates are applying for, remote jobs versus the number of jobs comparison on LinkedIn. So 50% of all applicants go to 15% of jobs that are saying remote. Whatever it is you think is a really hot topic, just write something on it and just send it out. Some senior leaders and honestly, I think the worst case scenario, you send it out. A leader gets annoyed that you've given them extra information. They tell your boss, I'm annoyed you've given me extra information. Like, no, no decent boss is going to worry about that. It's going to be okay. Glad my team are looking after you. So I'd say just be curious. Be curious. There's always going to be people that want information. There's always going to be new things out there. So just be curious and start pulling at threads.

Yeah, you're so right. There's a lot of people who are hungry for information and the hungry will feed, but certainly the ones who are, who are upset that you gave them more bedtime reading look, we can do with them in our organizations generally, I.

Think the worst case scenario, you get more work into your function and your capacity gets slammed. That's the worst case scenario, you know, and suddenly it's, well, how do I balance the reactive ta? If it suddenly switches on and you're looking for a load of jobs again, reactive TA versus the more strategic intel, how do we balance that out? And suddenly that's how you start driving into those conversations around. Actually, I need to carve out some capacity for ti. Actually, we've got enough work. We need to stand up a whole TI function and that's, that's how you start building this stuff out. It's from those initial conversations where it's just, this could be curious, this could be interesting.

That sounds really great. And the last thing we ask all of our guests is to leave us with, with a final piece of advice. It can be something around this topic itself or it can be something that you've heard from somebody that you've just always lived by. Would you like to, to share what that last piece of advice might be? Please.

I, I'd say just continue to be curious. Like the two things that I always hire against is productivity and passion. As long as people are proactive and that they're curious and they're being passionate about what there is, there's going to be interesting routes forward. There's always going to be work needed to be done. There's always interesting problems to solve. I think we get far too hung up within, specifically TA within our silo and we get these false blinkers that this is our world and this is all we can engage with. No one's put those walls up apart from us. No other function in the business cares about those walls and those barriers. Go out and talk to people. Go out and find out what, what their problems are. Because there's a lot of problems in organizations that can be solved with labor market data that we have access to. People just don't know it exists. So yeah, I'd say be curious, go out there, just talk to people.

Sounds good. Yeah. Productivity and curiosity will, will get you lots of places, including to a talented old as well. Toby, thank you so much for, for sharing such amazing insights and stories. I really want to find out what happened to those 12 cybersecurity people in Dallas that your finance operations didn't go for. But that's, that's certainly for another day. And just one last plug for, for your book about talent intelligence. The use business and people data to drive organizational performance. Where can one get this lovely book?

Either on the Coogan Page website, which is the publishers. So that's cooganpage.com I presume. I should know that. I have no idea. Or on Amazon. Amazon is on there. There is a hardback version which is like £85.

You don't have £85 now. It's gone up.

It's a bargain. It's a bargain of a book.

Demand pricing is not happy.

But, yeah, you don't have to buy that one. There are other, other versions available. But, yeah, it's. It's quite a long name. If you put Talent intelligence, Toby Koshaw, it's the only thing that comes up. So, yeah, feel free to find it there too.

Happy out. Happy Out. That sounds great. Brilliant. Thank you so much, Toby, again. And join us then again for next week. Next week we will have Johnny back with this time with Demetra Julius on how leaders can nurture and support resilience in the workplace. Really be looking forward to that conversation at long last with Demetri, who is the head of Special Progress. Sorry, excuse me, the head of Special Projects at Icon. All right, that is it for this week. Thank you so much, everybody, for listening. Those of you who listened live and those of you who are on the podcast afterwards, thank you so much and we'll see you next week. Thanks, everyone. Bye.