Ep 836: Continuous Improvement In TA

0:00Just before we start this episode, a quick word about a live webinar that I'm hosting next Monday, the 9th of November. Candidate fraud is a growing problem and talent acquisition is at the front line of it. Organised bad actors are using stolen identities, deepfakes and proxy interviewees to get inside companies. And TA teams don't often have the tools, the budget or the support to deal with it. So I'm bringing together a panel of experts for a discussion on where verification belongs in the hiring process. We'll look at the impact candidate fraud is having, the solutions that are actually working, what TA teams should be doing across the whole hiring process and how to get buy-in from the wider organisation.

0:44So that's Monday the 9th of November. If you can't make it live, please register anyway and we'll send you the recording. You can sign up at matalda.me slash proof. That's matalda.me slash proof. You probably already know the three or four things your TA function most needs to improve. The difficulty is rarely knowing what's wrong. It's deciding what to tackle first. And a market offering an AI tool for every item on your to-do list only makes that choice harder. So how do the best teams move forward? Keep listening to find out.

1:49recruit while giving you consistency and control across your organization. And because more of your hiring happens in one place, Pinpoint captures the context that makes AI more useful. Your team can automate repetitive work, make more informed decisions, and spend more time on people. To find out more, go to pinpointhq.com slash recruitingfuture. That's pinpointhq.com slash recruitingfuture.

2:24There's been more of scientific discovery, more of technical advancement and material progress in your lifetime and mine, than in all the ages of history.

2:39Hi there, welcome to episode 836 of Recruiting Future with me, Matt Alder. TA leaders usually know what's needed to improve their function. The hard part is deciding what to do first. AI is just adding to the confusion, with an ever-expanding vendor landscape and technology that's getting stronger for many use cases by the day. So what are teams that keep improving do differently? My guest this week is Tony DeGraff, co-founder of the Recruiting Excellence Foundation, whose global benchmark measures the maturity of TA functions around the world against a single framework. In our conversation, Tony shares what the benchmark says TA does really well and where it falls short, how to make sense of the AI vendor landscape, and the one question high-performing teams use to decide what to improve next.

3:35Hi, Tony, and welcome back to the podcast. Thank you. Thanks for having me again. A pleiser. According to my records, this is the fifth time you've been on the podcast. The fifth time already? Yeah, yeah, yeah, over the years. So it seems a bit strange to ask you to introduce yourself, but do that anyway in case someone's listening to you for the first time. Tell us who you are and what you do. Yeah, so I'm Tony, Tony de Graaf, that really Dutch last name. So I am Dutch, living all over Europe, to say it like that. And I am the owner of the Recruiting Excellence foundation and we work with TA teams around the world to help them improve their TA capabilities so to become a high-performing TA function and that stretches from simple workshops hiring manager trainings hiring process design all the way to full-blown transformations and reassessing the the operating model that some TA teams actually use and any type of work in between so you do some really cool stuff but I think amongst the coolest thing that you do is the benchmarking exercise that sort of sort of runs continually through the year and it's something that we've collaborated on a few times, and I've sort of sent listeners in that direction to look at various aspects of their TA function.

4:40Tell us a little bit about the report and how it works and what it measures. Yeah, it's actually started from maybe a personal frustration. Is that the right English word for it? Is that it is really hard to compare TA teams across the world. And we do get questions if we work with customers in Australia, like how are we actually comparing to Europe or when you are in America they want to know how Europe is doing or the other way around so interestingly enough a lot of regions always feel that they are behind other regions for some reasons and there is not a fantastic global data set there are some data sets and people that do benchmark but they're very regional heavy so very Europe heavy very United States heavy or somewhere else and between them because they measure in a different way it's actually not difficult, I would almost say impossible to compare them or paint a global picture.

5:35So what we set out to do is we standardized the way that we actually measure the maturity of a recruiting function. And we are running this benchmark globally. So we got results in from Southeast Asia, all the way to China and Japan and the Middle East, Africa, North South America, and all over Europe, of course. And all those TA teams, big and small, sometimes it's a company of 600 people. Sometimes it's a company of more than half a million people. They are measuring the way that they're doing recruiting following the exact same framework, the recruiting excellence framework. So this gives us a not only a picture for them individually, so they know where they stand, but we can actually offer them a proper global benchmark.

6:17So you know exactly where you stand versus the globe, to say it like that. When we spoke a few weeks ago, we were focusing on the areas that you sort of have found TA teams or reported that they struggle the most with. And it was the intake meeting and the hiring decision, which we're kind of discussing is almost kind of strange because that's the, you know, they're the kind of biggest two aspects of it. Just to change the focus slightly, what is it that you found from the research that TA teams actually do really well? What is it that, you know, where are they the strongest? What do the sort of highest scoring TA functions have in common?

6:54Yeah, I like the question. It's not the typical doom and gloom, what are we doing wrong type of question, right? So I like to flip it on its head because TA is doing very well, I think, in general. It's more, of course, there are always areas to improve and we always like to focus on that, like the entire AI discussion that we'll touch upon later as well, right? There is always something happening that we need to do. But looking at what we do very well, we do a lot of things very well. And that really centers are in the, if you look at the benchmark results. So just for the listeners, we break down the TA function into 21 individual components.

7:30And the components that score strongest, nice English sentence, are the ones in the core of the process. So everything from sourcing, the first reviewing, the interviewing and assessment type of things. that at the core of the function is where you see that recruiters are just really good at their job in general right that's where you see the highest maturity and that also makes sense because it's the core of a job so i think that is where they are really well and good and it is more around so i think it's that ever going question from being an operational recruiter to becoming more a talent advisor or that strategic thing whatever that elusive strategic thing is that is where the areas of improvement usually show up so really becoming more advisory role in terms of who to actually hire and who you're actually looking for the workforce planning bit being able to report on how you're actually performing with the right metric so i think the core of the recruiting function is very well and it speaks also to that that the areas where we can improve are the ones that i just named like the coming more strategic things it's not so much about the core of the actual recruiter profession that we struggle with.

8:40I think that's a positive thing for sure. Yeah, I think that makes a lot of sense as well. It's kind of like where the sort of the core skills of the industry have been for a really, a really long time. And, you know, as things change, things have to adjust. I want to go back to what you were saying right at the beginning about people asking you how they benchmark against different countries and things like that, because I get asked that all the time as well. It's like, oh, this place is ahead of this place and this industry is ahead of this place. And the picture is always much more nuanced than people think.

9:10What do you find? How do different countries benchmark against each other? Are there any learnings or interesting insights there? Or is it as random and as nuanced as perhaps I think it might be? Exactly. The funny thing is we ran all the comparisons that we could, but we could not identify. There are differences, but not significant enough to call them out in the benchmark. so funny enough it's not that europe is behind america on a b and c or the other way around or australia or the middle east it's more that you see the differences more a little bit in in the culture so for example in the middle east it's more a classic and formal culture so you will see this also in how they organize recruitment it's way more a formal relationship with the business and recruiting and how you're also treated as a candidate where europe of course is an extreme example of everybody is equal doesn't matter if you're an intern or a ceo it's a little bit exaggerated but you do see that in how they organize their ta functions and how collaboration comes to fruition i think in europe it's sometimes easier to call out hey we should improve this area where in the more classic and formal type of organizations and cultures it's not always expected from you or accepted from you that as a ta function you call something out that should be that should be changed, but that doesn't mean that it doesn't happen.

10:34It just requires a different cultural lens and a different approach to achieve the same goal. So that is more what we see. So the issues are not fundamentally different, but how do we call out the business or point to the mistake or find a way to collaborate with the important stakeholders? Sometimes it's leadership. You fundamentally need to find another way to get leadership involved and find this important if you're working with a company that is mainly Indian in culture versus an American company. So that's more what we see in the differences. So how do we actually solve these things and get it moving?

11:10But the funny thing is that the more technology grows faster and faster like it goes in the last decade, the differences really start to shrink between the regions. Like every region basically has access to basically the same type of technology. Yeah, the same type of tools. So those differences start to disappear more and more. Yeah, I think that's the thing. You know, what I see is any differences are cultural or down to individual legislational regulations in specific countries or sectors. And yeah, the technology thing's changed massively. I think if you go back 20 years, it was a real differentiating factor.

11:48But these days we've all got the same tools pretty much at the same time. So yeah, less of a differentiator these days. Yeah, I think that's a good thing. Yeah, no, it is definitely. I think it, and also I think that there is the way that we communicate these days has meant sharing across borders is a lot easier than it used to be. Sticking with technology, let's just talk about AI. I almost need like some sort of jingle or music to come up when we have the AI section. Yeah, exactly. It kind of has to happen. So the way that AI is spoken about by the people who develop it at the moment is they talk about this sort of, it's got a jagged edge, a jagged frontier, which kind of means it's good at some things and not good at other things.

12:27And I'm kind of seeing that jaggedness happening in the way it's being implemented in our sector. So some companies are doing lots of stuff. Some companies are still experimenting and some companies are not touching it. So what are you seeing? What's kind of going on out there? How is it developed maybe over the course of this year? Yeah, that's also funny. Over the course of last week. Yeah, exactly. We last spoke in June. But let's go with this view. A lot happened between we spoke in June and now, because now everything is about bots. I will circle back to that in a moment. But I love the jackedness that you explained.

13:04Thank you also for explaining it. Elsa, I would have asked you the question what it actually means, because the real English people who speak native English always have very beautiful words to explain a lot of things in nuance that us non-native speakers just don't have. So thank you for explaining that. Yeah, exactly. Yeah, the jackedness. I still think this is a big issue, right? So a lot of the AI tools are very, very narrow. So they can do one thing good or okay, depending on your personal opinion, unless you say good for the argument of the discussion. So they can do one thing very well. So for example, you see some of those sourcing tools, right?

13:43So that you then can find candidates. So you give it some information and it gives you back like 20 people or 25 people. And where it pulls that from the internet, we don't exactly know they basically have a big ass library that they actually go to they try to engage these people okay fantastic but that is just what it does and i think the issue is is that how much time does that actually save us because we do need to set it up we do need to feed it all the time you spend feeding and instructing it before it goes out that was time you didn't spend before because you just opened linkedin recruiter and off you go so there is a percentage of time that you actually spend more instructing the AI, then the AI is saving you some time.

14:26But then it gives you that list of 20, 25 people or random example that you then also have to process and pick up again. So I think we need to become better and that's just learning by doing, I guess. Figuring out if we apply AI to something, what is the actual benefit? Because sometimes it's speed, but we don't really gain a lot of time personally because I don't have extra free time because I now instruct all those AIs on all those searches and I'm processing all those lists. So my day doesn't particularly change but I can move those roles faster to say it like that. So the game of applying AI is still I think the most difficult because all of them also cost money.

15:11So if you work with such a sourcing tool and it costs you a couple hundred a month depending on, or you have that individually or as a company, does it actually save that money? Do you earn that back? Because if it doesn't, you shouldn't apply it. And that is a little bit where I guess the difficulty now is. A lot of AI tools are out there, but if we would assume that all of them are very good and at very nice what they do. So we probably need to go out today and buy 10 or 15 of those AI tools. But that means that we have 10 to 15 new subscription models of a thousand to a few thousand a year does it actually save us that money do you actually get that back if you can't explain that then it's not time to actually implement that then i would say yeah keep keep experimenting and keep trying and it's fantastic just call some of those ai companies and say we're very curious we don't know where we're ready to buy but can you show us the product convince us why we should care about this and why we should potentially make a buying decision in this field.

16:16They're more than happy to show you. They also understand that not everybody is ready to adopt it. So I like this type of mindset around the AI. If you see something cool, you work in-house, call them. Just send them a message. Be informed and learn. And because it helps you internally, I think, with building the business case on, okay, this is the issue that we're trying to solve. This is what we actually gain versus the cost. So I think it's a fantastic reason to try this and pilot this to see if it actually gives us this back. But I would not wait, but I just go and do some demos and take a look at it because everybody is figuring this out.

16:52It's not a set field. It's not very easy and straightforward to have. This is the exact business case and this is how AI replaces humans or will be cheaper or will be faster. We're figuring this out as we're going. So also approaching it with that mindset, I think, helps. Support for this podcast comes from Pebble. I know that many of you listening are hiring internationally and you'll be all too familiar with the wall of paperwork, rules and approvals. And you know just how much this red tape can slow things down. That's what Pebble is designed to fix. Pebble makes global hiring simple through embedded compliance and AI-driven workflows.

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18:17Terms and conditions apply. Yeah, I think it's an interesting time because I think if we sort of fast forward a couple of years, and this is another conversation if we can't get into this now because we don't have time, but I think if we fast forward a few years, we'll be in this kind of, you know, one agent to rule everything and things will look very different. In the meantime, I think we're at a difficult place because all the vendors out there want to offer everything now across the recruiting lifecycle. So you can technically go to one person, they've got all these areas mapped, they've got AI, everything, agentic this, agentic that.

18:51But, you know, Some of them are better than others at certain parts of this. Some of it is just an add-on that they put on because they're losing a bit of traction to some competition. And then there are people that are really, really good at doing one thing. And I think it's just a confusing landscape to kind of get your head around. And I like the approach that you sort of talk about there because I think being curious, asking questions, and just understanding the breadth of what's going on is just probably the most important thing to do at the moment, definitely. Yeah, exactly. Yeah, and the problem also is I don't think all the AI companies know what the value of their proposition exactly is.

19:28Because I have an example. I am experimenting now with grogbots. I would advise everybody to do that. It's the big next thing. If it's OpenAI Dots or Meta Muse or grogbots, it doesn't particularly matter. Go play with bots. Personal agents. Yeah, personal agents, army of bots that can do different things for you. Go experiment that. That would definitely advise. but an example i was trying to figure out if i could build a bot i was like wouldn't it be amazing if one of my bots could call my candidates and schedule interviews reschedule interviews in the completely fluent and normal way you can talk to a grog bot because that is really human-like and it's super fast so i tried to set that up and there is a vendor that does that but they are asking a whooping I won't call them out of course but they're asking a whooping$200 a month just for the phone number and the technology and that is not including the unlimited use of the phone so you still need to pay for the phone usage and this is the exact problem because you are on a bot plan for 60 100 or 200 a month and then for one plugin you pay another 200 oh yeah you need another one for 100 or 50 or 10 or even if it's a 10 or you build everything up and then you're already at a thousand or 1500 euros a month for one person just for those for those plugins you can almost hire a personal assistant fractional for that to actually well yeah that's the thing it's just like i'll get a human to a human to do it and in fact they can bring their own ai and pay for the ai themselves and do it and something yeah exactly yeah yeah it's going to be a really interesting conversation as this sort of stuff kind of comes over into recruiting so i definitely want to pick up with and talk about in depth as it sort of happens.

21:10Coming back to sort of TA function improvement, doing the benchmarking, you've got all this data, you know, really granular stuff that tier leaders can really dig into to see where they stand. What do the best TA teams and leaders do with this kind of information? How do people actually turn data and benchmarks into a real change that creates value? Yes, exactly. It's a good question because this is where a lot of the potential stalls, the right word to say it like that. Because for me, it is not so much about knowing what to improve because in my experience, 99 % of every TA leader I ever speak to, they know what the big topics are.

21:56They can give you the top three or top five issues that they think they should improve or where the biggest delays exist or where they lose the most candidates whatever it is in general ta leaders know it this next step is usually what is most difficult what should you improve first and ta teams that seem to be on that track to really be high performing ta teams they don't see it as okay the topics that i need to improve what annoys me most, but they change the mindset, what has the highest business impact. So they don't say, like one of the examples, if you talk to TA teams that are not in a full continuous improvement mode, there are always things in the process they want to fix on the career side, in the email templates and the candidate experience stuff.

22:45Great, important, but not urgent. It never is. Because even if we improve all those things, there is usually very measurable impact on your ability to consistently deliver the right person exactly on time. And that's exactly what should be in your mind. You are delivering for your customer, which is the business. So the mindset should be, whatever I prioritize to improve, what has the biggest impact on my ability to consistently deliver the right person exactly on time? And that's it. That's the literal only sentence that high-performing TA teams are focused on. So sometimes an improvement can be beneficial for us because we are clicking around, the system is annoying, but we'll just leave that for now because it doesn't have the highest impact on our ability to consistently deliver the right person exactly on time.

23:37So if you constantly focus on that, then it takes away that discussion of the five or top 10 topics that you have, because you can have in general without any training or any strategy consultant that you need from your top 10 list, you can say, okay, these two or three probably have the highest impact if we would fix it on our ability to deliver the right person exactly on time in a cost effective manner. So that is the mindset that you see with high-performing TA teams. They really focus what they improve on their ability to deliver. I guess that is the key. And the second biggest thing is that there is not an improvement mindset that is a project.

24:20An improvement mindset is continuous. Nothing is set in stone and high-performing TA teams will probably not have a process. like 80 % of the entire function isn't the same two years ago or three years ago. Everything is up for discussion. It's not the goal to map a process, train everybody on it, standardize it, and we never touch it again. No, we can touch everything if it actually helps us improve our ability to deliver. So those two are, I guess, the biggest mindsets we see with the high-performing TA teams where you see that they are always running faster and getting further ahead versus other teams.

24:57Yeah, that's really interesting. When you were talking there about focusing on that, you know, that kind of one purpose there, there's a brilliant book I read a few years ago. I know it's one that does the rounds that people talk about it a lot called, Will It Make the Boat Go Faster? by a guy called, I just looked it up, by a guy called Ben Hunt Davis, which is, it's a story of the kind of the British Olympic rowing eight from, I can't remember which Olympics or which world championships. And it's just kind of a diary of how they became the best in the world. And they just focused on any changes, anything they did, they just asked that question, Does it make the boat go faster?

25:27And if it did, they did it. If it didn't, they didn't do it. It's just a really great philosophy. And you just reminded me of it there. So you are now actively collecting data for the next kind of annual report so people can benchmark themselves. I would urge all the TA leaders listening to this to go and take the survey. It doesn't take very long to do. The data that you get is fascinating. And obviously you're contributing to the overall picture. If you head over to matwalder.me slash 2027, and that's in numbers 2027, that'll take you to a page where you can start filling this in. Tony, tell us a little bit more about what people can expect from sort of taking part in this.

26:09Yeah, exactly. I think the biggest difference between a lot of surveys and benchmarks that are out there versus ours is that the moment you complete it, you get a personalized report instantly. So you don't have to wait until we have completed the benchmark so that you do the survey and say, well, we contributed it. You have to wait for five months to hear something back and get some insights. No, we already have global benchmarking data. So that's already in there. Plus the report is automatically generated and you get the full version the moment you click and answer the last question. So if you actually do it, you get something in return instantly.

26:46and the second thing is that because i said it goes across the 21 individual components of the ta function that we've broken our function down into say it like that it takes you around 15 to 20 minutes you can continue with any moment because we're always busy we always get this phone call we always get distracted you can just start you directly receive a link you can continue whenever you want and there is even a mini assessment version that only takes less than two minutes if you want to get a feel with the format if you're like i'm not sure i actually want to invest already like 15 minutes you can do like a two minute assessment you get a mini report to get a little bit of feel of the of the format and if you decide that you like it you can continue fantastic so we'll put the link in the show notes but if you want to take note of it now matt alder.me slash 2027 so final question for you what are you expecting to see in this new set of data.

27:40Where do you think things have shifted over the last sort of year or so? What would not surprise you if you saw it in the results? It's a good question. I think, I hope to see that the general maturity, so the average has moved a little bit because we measure the maturity over four levels and where you get to level three and level four, AI is more part of your TA function and how you do your work. So I hope to see a shift that we see a total of companies that are more functioning at that level three. That will be fantastic because that means that we move forward. The weakest point last year was indeed the job kickoff meeting or the job intake.

28:23I hope to actually see that we improve there as well. But I also think that it could very well be the weakest again this year because that one particularly is not solved by any form of technology. it's a token to see where you actually are on that journey from being an operational recruiter to becoming a strategic talent advisor so that really requires a transformation from your team and how you actually engage with the business to achieve higher maturity there so it could still be maybe lowest I don't know because it takes maybe a little bit more time and effort to actually make that change so that could be a multi-year transition but those are my two predictions I will be definitely looking at first when the data actually comes in.

29:06Maybe we catch something else. Yeah, I'll see. Well, looking forward to talking to you about the results when they're done. In the meantime, everyone, make sure you take the survey. Tony, thank you very much for talking to me. Thank you for having me. The fifth time was fantastic. Thank you. My thanks to Tony. You can follow this podcast on Apple Podcasts, on Spotify, or wherever you listen to your podcasts. You can search all the past episodes at recruitingfuture.com. On that site, you can also subscribe to our weekly newsletter, Recruiting Future Feast, and get the inside track on everything that's coming up on the show.

29:40Thanks very much for listening. I'll be back next time, and I hope you'll join me.

30:02Bye.