Transcript for "Pole Position for Progress: How Humans and AI Power F1's Future Organisation": Poll position for progress. I hope you like, what I came up with there, the play on words. How humans and AI power F1's future organization. Okay. Just waiting until it's one minute past ten and then we will get cracking. To those now joining, we're just waiting until one minute past ten and then we will crack on with this webinar. There we are one minute past ten. Let's go. Gentlemen, start your engines. So that's the last one I'll do with that. It's not very funny. Right. So, okay. So we're really today very excited to have Alastair from Formula One with us, who will introduce properly in a moment, to really talk about how humans and AI are working together to power F1's future organization. So before we get into that, just a bit of housekeeping. So if either of us make forward looking statements about functionality we're perhaps working on or roadmap functionality, please keep in mind that future plans can change, so only make purchasing decisions on currently available functionality. So will receive a recording of this webinar in about a day, in twenty four hours. So you can share this with your colleagues if you think they would be interested. At the end of the webinar, we really want to encourage you to ask us questions. We want to have Q and A and we've got Alastair here from Formula One and myself ready to answer questions. And one of my more technical colleagues, Michael sitting in the background. And if you do have any questions, don't wait until the end. As the question pops into your mind, enter them into the Q and A panel on the right hand side there rather than the chat. So please enter those questions in the Q and A. For those of you who aren't asking questions, but have a look at those questions and vote for the questions. Give a thumbs up the questions you would like us to ask. And then what I'll do is those questions with the most thumbs up, we will go to first. And right at the end, we will ask to fill in a survey about the webinar, because we want to hear your feedback that helps us shape the future sessions that we have planned so that we're actually producing content and information that is of interest to you. So we really do appreciate your feedback. So this is the of the agenda. Now we're not actually going to have any slides. This is just to give you an idea of the flow of the session. So we're going to first talk about, obviously introduce Alastair, talk about Formula One, the organization or the business, as it may not be what you think. Then we're going talk about the challenges that F1 was facing and the vision that they had for the future. Then we're going to drill in to really look at a very interesting use case around the AI in HR. Really, Alice is going to share with us the impact in terms of the results that using AI has had in HR and any lessons that they have learned. And then we'll close off the conversation with looking to the future and then we'll open up for Q and A. So we should definitely be at Q and A at the latest by half past the hour. We want to make sure we have plenty of time for Q and A. Okay, so just to introduce myself. So I'm Richard Doherty. I am a senior director here at Workday. Been with Workday for over ten years and my focus is on our HCM solutions and I sit at the intersection of product marketing and sales. And we are joined by Alastair. Sorry, Alastair, I've been banging on, haven't I? You haven't had the chance to say anything. That's quite right. You keep talking, don't mind. No, people don't want hear me. They want to hear you. So let me stop sharing the slides. There we go. So now we're full screen so we can see each other. So first of all, in case I forget, thank you so much for agreeing to be on this webinar and share your experience. It's really greatly appreciated by Workday. You are a fantastic customer and we really appreciate it. So to kick things off, tell us a little bit about yourself and your role at F1. Yeah, thanks Richard. So, I'm Alas Lagos. I'm the HR systems lead at Formula One. We primarily use Workday for much of our systems requirements. So, in short, I look after Workday at F1. I've been here for around eight years and actually began life in the HR team. I was a senior HR business partner, merrily minding my own business when the Workday implementation project came along and was asked to get involved. Initially, I really didn't want to get involved, actually, but begrudgingly said yes. And then, I have not looked back since, as I discovered that systems are easier to manipulate than people. And I enjoyed that much more. I've been in the HR systems world since, I guess, 2022, and very much enjoying the change of career that I've had. I think it's also probably worth introducing the company, right? Because many people will know the sport. I think most people will know the sport. But I think fewer people will know what we as an organization do. Formula One is the commercial rights holder for the sport. We're responsible for three main things: the sports event organization, so where the Grand Prix are held the sports broadcast and whenever you watch a Formula One race, you'll be watching the footage that we have chosen to present to you, and it will be identical across the globe. Ultimately, though, we're responsible for revenue generation both the teams who receive that cash as prize money at the end of the season, but also of course for our shareholders. So back to the question about what I do. Well, want our staff to be focused on those three main things and I think that means having a system that increases efficiency is easy to use and not the other way around. Perfect, brilliant. And know, I mean that's all very good, but you know can you get me some free tickets for the British concrete? No, just joking. Joking. I can, but it might cost me my job. I'm gonna say no on this occasion. Yeah, no, say no, we're being recorded. Formula One, obviously, is a brand synonymous with innovation high performance, right? When you hear future of work, what do you envision? Thinking a lot about this before the session and let's just reflect on the fact that at F1, we don't think the future of motorsport nor motor vehicles more broadly is just electric engines, unsurprisingly. And actually, we believe it's in a combination of hybrid engines and sustainable fuels. I was reflecting on the fact that I think that AI is to the workplace as batteries are to the engine. So, in my mind, I see AI providing the necessary productivity boost that's needed rather than being the answer in and of itself. Yeah, nice. Thank you. Great answer. Shifting to sort of now maybe talk about challenge and the vision that F1 have within HR. So looking at things from an HR perspective, you know, would you say are some of the unique challenges you face operating in this very dynamic, global and high profile FY environment that you've touched on? Yeah, mean, there are many. I mean, we like to think that we as an organization are entirely unique. Of course, that's not the case many organizations operate globally. But there are some very distinct challenges that I think we do have. For me, I think one of the main ones is the mismatch between the size of our organization and the size of our brand. So, we have a current headcount of around 800, yet the sport has over 800,000,000 fans worldwide. So, there's massive mismatch between the size of brand and the size of our actual company. And I think the main challenge that creates and it's a really, really fantastic challenge to have, but we attract people from all over the world for roles that we advertise. But we're primarily based in The UK, face the same employment sponsored challenges that any UK employer faces. And I say, I'm not lamenting that challenge because I say it's a real privilege to be able to attract that many people to roles that we advertise. But I do think it creates a very distinctive challenge that certainly, you know, over the years of working at F1, I have been searching for solutions to try and solve. And if we perhaps look backwards before the current state with Workday and AI related solutions, I guess you relied on legacy systems, manual processes. Can you share with our audience sort of inefficiencies and frustrations this created for your HR team and the hiring managers? Yeah, for sure. When I arrived at F1, in the years that were before Workday, we had many disparate systems. So, our and payroll system was different to our ATS, which was different to our performance management system, which was different again to our time and absence system. And none of those systems talk to one another. Relying on, for example, communicating changes that need to be made in payroll when somebody was on maternity leave was all manual. And it just there was so much that was done manually that needn't be done manually. And so, were really keen to move to a solution that could help us step forwards from that position. And just before we drill into an AI use case, just obviously, know, the organization F1 chose Workday. Can you share with our audience why the decision was to go with Workday? What was it about Workday that you felt would support? Remove those inefficiencies, drive the productivity and so on. Yeah, I mean it's not as many people assume a product of our broader or the broader commercial relationship that we had. I think people do assume that because Workday was a sponsor of F1, it was the foregone conclusion that we would choose that system. But I can categorically confirm, having been involved in the process behind the scenes, that that wasn't the case. Now, Workday was chosen for its own merits and the two relationships, you know, customer and commercial, are entirely separate. And so, really, we chose Workday because it allowed us to take all of our disparate systems processes, not just those four systems that I mentioned, but all of the processes that kind of went in between and around and consolidate them into one holistic solution. And for us, when we were taking a decision, Workday was the obvious answer. Perfect, brilliant. Right, so that's sort of the background, the challenges. So you touched on there, you were receiving a huge volume of applicants per open position, very reflected by the size of your organisation versus the profile of the organization. A nice problem to have nice in quotes, Because it's actually not very nice at all. And you've got to protect your brand, right? You know, you need to be careful of how you manage those incoming applications. So, and I know our audience from all, and also this is generally for the meetings that I get involved in and the events. Everyone's talking about AI, of course, it's transforming work, it's transforming people's roles and it's moving forward at such a fast pace. And I think our audience is really keen on sort of practical AI use cases. How are organizations really using AI? And you're a great example of that. So tell us, you know, how you're using AI to move away from manual processes and specifically let's look at recruiting because that's where you had a massive challenge. So tell us a little bit about that. Yeah, I guess to kind of reiterate what I said about the start around AI, you know, providing the necessary boost. I think it and what I've seen kind of confirms this. I think AI works best when you really point it at a very particular problem. When you give it focus, give it parameters to work within, you say, Here's what I need. You know, it's all about good prompting, right? That's what we're all learning about in our kind of AI journey. And I think for me, I'd say for a long time, both in HR and then as I stepped into the systems world, I had been thinking and wrestling with ways in which we could do something better for our recruitment team. I mean, just to give a kind of bit of a picture of context. So, in the previous twelve months, before we took the decision to purchase HiredScore, We'd had around 78,000 applications for 150 job requisitions. So it's an average of five twenty applicants per role. Our talent acquisition team is only 3.7 FTE. Now, I won't bore you with the maths, that's a lot of CVs to review in a short space of time. Indeed, they don't have the time to do that, right? Screening CVs is not the only thing they're responsible for. We want them to be proactive, to be strategic, to be spending the time with the hiring managers, doing the legwork at the start of the process to make sure we're drafting good job descriptions, all those good things. But actually, because of that high level of applications, I was pretty confident that the team were having to resort to some fairly blunt sifting methods, simply to get the number down to a manageable level to review. And I was also fairly confident, therefore, that we were sifting out stellar candidates at stages too early in the process. And I think that point was really brought home to me when one of the TA team said to me once that they'd had a recruitment agency present back to them a candidate that they had sifted out, who'd, you know, they'd applied directly and they'd sifted them out too early. And they've been sifting out because their salary expectations were too high. But a quick conversation with that person, able to check whether there's any flexibility on that point, and the agency were quickly able to ascertain that actually this person should be in the mix. But the member of the TA team didn't have the time to do that. And so, I heard that I was more convinced than ever that we needed to do something to fix problem. And the choice then is very clear, right? You know, you either hire more people to do that reviewing for you, or you find a smarter way to solve the problem. And as I've kind of hinted, and this won't be a surprise to any of you on the call, AI was the obvious answer. It was there. It could do the heavy lifting for us. I was very keen when I saw HiSCR for the first time at Elevate twenty twenty four. Suddenly, was like, okay, could really be a game changer for us. And I was very then excited to kind of pursue it and try and get it in at Formula One. Perfect. And just to clarify to our audiences, HiredScore AI is a part of Workday's talent acquisition suite. It's a company that we acquired about a year and a half ago. It's now integrated into the Workday solution. It's a fantastic AI based solution. Perhaps Alastair, I mean, before we sort of talk about the introduction of that and how people have responded to it, How is F1 actually using high score AI? What does it actually do for you? Yeah, I mean, you know, we're relatively early in our journey. So, we went live May 19 this year. And I'd always thought that our usage of it would be in stages. You know, solve the initial problem first, I. E. Help the talent acquisition team with their screening, and then step into the other benefits that Hivescore can offer. So, we're using it presently as a tool to help us review CVs at that early stage. We've not yet got into the great functionality, I would say, that offers around fetching candidates. We've got a huge pool of previous applicants. I'm excited to see what HiredScore can do for us in terms of finding great people who've applied previously. But I think that will happen in time once we've really started to see the time saving benefit from those early stages. And again, the other thing that we're kind of working on and we'll be introducing at a later stage is some of the masked screening functionality. But again, that's something we want to do later. Know, as I do it, we're really trying to do this in stages to do it well. You know, as many of you who know the sport will know, F1 has a DNI charter. The teams, the FIA, we have all signed up to this charter and committed to look at our practices to do things differently, to do things better, and to meet some of those DNI challenges that we see within the sport. And again, when looked at Hivescore and the mask screening that it offered, I thought actually that could really help us do that. So in time, again, will be something that we bring in to meet some of our public objectives around D and I. Yeah, and I think as well, I mean, the main point I picked from that is your challenge was the volume of incoming applicants, right, that you were receiving. So that is what you focused on initially. It's not we haven't got enough candidates, so let's dip into our existing candidate database, So it makes perfect sense. So, as introduce AI into our organizations and our employees, and in this case, recruiters, we're given these AI tools to help drive efficiencies and remove a burden from their workload. How did and how have your recruiters responded to the introduction of Hidescore AI? Did they need to sort of build up trust in the solution? What did that look like? Yeah, I think there has absolutely been a period of adjustment for the team. Think, you know, I said the size of the team earlier, so, you know, 3.7 FTE, four people. There was definitely a mix of feeling. Some very, very excited, some less excited, a bit more apprehensive about it. But I think it, you know, for me, I knew it would take some time to get that trust in the tool. As a result, I was really keen to involve them at the earliest stage possible and give them time with HiredScore before we went live with it. And I think the more time they've had with it, the more time they've spent using it, they've got more comfortable with it. And I'd say the more they use it, the more their confidence and trust is increasing. The more they see great candidates being well rated and are doing their comparisons and checking and making sure the more confidence they then have in the that HiredScore is presenting to them as the best ranked candidate. So yeah, it's taking time, but I'm definitely seeing trust increase within the team as we go along. Yeah, good. So obviously, of ways of increasing trust in an AI solution is to have measures of success. And you kind of touched on it there a little bit. So, you know, since the introduction of hiscot.ai there, has the process become more efficient? Have you saved screening time? Have you been able to measure that? Yeah, I mean, it's a really important question. Well, probably the most crucial what impact does this have? Going into the project, I had three main criteria for success. The first, as you know, screening time. Can we bring that down? The second, and again, is that none of these will be a shock to people, but time to fill. Can we reduce the time it takes to fill positions that we've got? And thirdly, agency spend can we decrease the amount of money we're spending with agencies? I think on the latter two, I feel like it's a bit too early to make an assessment on those fronts. Certainly, the first and I always assumed this would be the case anyway. But with screening time, we have seen a pretty dramatic reduction actually. We've had a forty three point seven percent reduction in the time taken to screen candidates. Mean, as I've been anywhere live 1978 and I've already seen that. And I think that's a really big tick. That was the primary aim going into this project. So I'm really pleased to have seen that. Yes, massive, massive benefit. So, I've talked in there about the sort of the recruiters and their experience, but what about your candidates? Do you think this is improving their experience in any way? Yes, I think so. And I was thinking about this before the session. For me, it's in two key ways. I mean, the first is around time spent waiting to hear a decision. So, the faster we're able to screen, the faster we're able to get to interview, etc, the faster we're able to fill, the less time candidates are spent waiting. And I think we're already seeing that time saving on the screening time. We'll hopefully see it on the time to fill as well. I think, therefore, candidates will hear faster whether they've been successful or not. I think that's obviously going to result in an improved experience. The other one is a bit more nuanced, but I think is probably more important. Previously, we had absolutely no way of guaranteeing that your CV would be reviewed. Now, we can. So everybody who applies will have their CV reviewed. And I just think that's absolutely brilliant. A candidate, as I've been for other roles, there's nothing more disheartening than putting your heart and soul into an application and then not hearing anything or not hearing anything for some time or not even being sure that someone's actually going to look at your CV and see whether you know take even a thirty second view on whether you'd be suitable or not. And as I say, we had no way of ensuring that all candidates could be reviewed previously given the numbers, but now we can. And I just think that makes a huge difference to candidates' experience simply to better offer complete parity. We can ensure that everybody gets reviewed and I think that's a really big deal. Perfect. So yeah, optimize the back office, you actually improve the candidate experience. So how did you we kind of touched on this a bit, we can move through it quickly. How did you manage this change within your HR team? And looking back on adopting the AI solution, any advice you give to our attendees today? Yeah, you're right. I touched on this earlier, but I think it's worth reiterating that really it was about bringing them along for the journey and bringing them in at the earliest stages possible. So given the size of the team, I was in a position to better accommodate all of them in the project team, not just take some. Although that meant more time from them was taken at the early stages, I knew that would pay dividends in the long run. So they were involved in all of our design sessions, they were involved in all of our testing sessions, and what that meant is they had time to feel like their input was going to be taken on board with how this thing was set up. But crucially, just to be in it, to use it, to get used to using the functionality so that when we went live, everybody in the TA team had already been in and got used to it. As I say, the dividends were really clear. Training was really easy. We didn't really need to train anybody. They'd already been in testing. They knew how the system worked. And as a result, I think user adoption within the TA team has been very high. And for me, that was really, really important. And I know, you know, for larger organizations with much larger TA functions, that may not be possible. But certainly, I would say bring as many people along for the journey as you can. I think it does pay dividends once you go live. Yeah, and I think as well, you know, Workday we talk a lot about, it's about human and AI collaboration. So the AI is just going to take some tasks from a role. So probably some of those tasks we're just not able to perform because of time and so on, like screening all the candidates to give the actual employee, or in this case, a recruiter more time to really focus on the higher value activities. So looking back, have there been any sort of unexpected benefits and challenges that emerged, either during or after the implementation, that you just didn't initially anticipate from the introduction of AI? Yeah, I mean, I think there was one that was unexpected, but it shouldn't have been unexpected. So it's almost a little bit embarrassing to admit this, but I'll share it anyway and hopefully people can learn from mistakes. Workday make it really clear that the quality of your job descriptions is one of the most crucial parts of this. You don't give the tool good parameters to assess candidates, it's not going be able to do a good job. It's all well and good saying that, but until that fact bites, I don't think we'd really understood what that meant. But it was brought home to us shortly after we went live. We project manager role. So, a role that's unique to F1. Many, many companies have project managers. We had about 600 applicants and they were all ranked A and B. We're looking at it going, Well, on a minute. This hasn't worked then, has it? That doesn't help us at all. But then what we did is we took time, we looked at the job description, we looked at the criteria that we set. We spoke to the hiring manager and we adjusted and we added the necessary specificity in order to allow the tool to do its job properly. So, did that and then delightfully watched HiredScore regrade the existing applicants according to the criteria that we had added in. And then we had a good spread of applicants across the board. We had As, Bs, Cs and Ds and about 60 As. And suddenly, okay, great, breathe a sigh of relief. It is working as we were hoped. And as I say, shouldn't have been unexpected, but it's not I think until you really see how the tool is grading that you can kind of start to adjust and add in potentially the level of necessary detail. The other one, I mean, that was unexpected and I think, I mean, you can judge whether this should have been expected or not. Perhaps it should have been. But again, there's another point around job description. So, a role that we have that is really unique is that of a timekeeper whose job is literally to time the cars going around the second. So, there aren't many organizations in The UK that employ that role. But historically, when we've advertised for it, we have asked for good timekeeping experience. You know, a person knows in the context of the job description that that means experience of timing motorsport events. But that's not what the wording says, right? So, we put the role live and are getting well ranked candidates who are turning up to work on time. You know, because we haven't given the necessary context for that criterion. And it simply needed to be just reworded, right? Good experience of timing motorsport events. That's all it needed. But it's something we haven't really considered going into it. And I think, you know, other organizations may have very unique, very specific roles, terminology that makes sense, they understand it, but I think ensuring that the tool and of course your applicants know what that means is really important. Yeah, so let them learn with AI. Brilliant, so just last question before we skip over to Q and A. So for those sort of HR leaders in the audience, you know, considering their own AI journey, what's the single most important piece of advice you would offer based on Formula One's experience? I mean, I think it's really an extension of the point I made around the talent acquisition team. And that's about bringing your key stakeholders in at the earliest stages possible. So at F1, we have an AI steering committee whose role it is to decide, you know, to review all cases for using AI and make a decision as to whether it's appropriate, whether it's proportionate, is it going to solve the problem that we're encountering, is it safe to do so? And I took the time at the outset of the project to identify the key people on that steering committee, speak with them separately, explain to them the problem that we were encountering and kind of, you know, sell them the solution that I thought high school would be. And then brought them along for the journey, made sure that they had time to do their due diligence, that is putting this at their feet last minute. And what that meant was that when we got to me pitching HiredScore effectively to the AI steering committee, I had already got the buy in from those key people. And it meant that getting the necessary approval to go live was relatively straightforward, not without its challenges. And there was a lot of time spent as I was doing that due diligence, both before the purchasing decision and between then and when we went live. But really bringing those key people in at the earlier stages, not trying to keep them at arm's length, trying to keep them away from what you're doing and kind of only give them the necessary information that you think they might need to give you the approval, but really bringing them along for the journey. And I think that for me, it was a key to our success and I strongly suspect it will be a key to many other organizations' success too. Yeah, no, definitely. Yes, so get all the right people and the right teams involved early. So brilliant. So let's now skip across to the Q and A and to all our attendees. You know, you have to upvote because then we're going to go for the questions with the most votes. And the first one is basically kind of about bias, which is obviously a big concern, right? Don't want to introduce bias by using an AI tool. How did F1 look at this? And obviously I'm assuming it was something that you evaluated and you were very cognizant of. Just What was your approach to the concerns about bias with an AI tool? Yeah, I mean, was long lengthy discussions internally on this topic that I'll not go into the detail of. But I think for me, there are some key things that we looked at, you already touched on one of them earlier, Richard, which is ensuring that people remain and play a key part in your processes. So, AI is not making the decisions in isolation and indeed, that's what the law requires of us, right? So, it was about ensuring that our talent acquisition team still played the right role in determining whether candidates would progress or not. One of the things that we looked at and spent some time with our legal and compliance teams was doing some testing and continuing to do that testing even after we'd gone live, continuing to ensure that we are comfortable with the scores that are being provided. And for us, the really simple way in which we're doing that is a commitment from the team to review a proportion of the lower ranked candidates. And I had some fun discussions with our legal team around what that proportion would be. Ering on the side of caution, they were probably hoping we would review a large amount. But actually, of course, the more we review, the more we're going to eat into that time saving that I was hoping to bring in. So, there was a bit of a trade off there. But ultimately, we reached a point where we agreed a sensible figure, we thought, and agreed a timeframe over which we would expect to see that taper off. So, that proportion reducing, think that was one of the key discussions for us as we considered how we would manage that, how we would defend decisions that we would take. I think the other really interesting point was around whether we allow candidates the opportunity to opt out, to say, I don't want AI to review my application. And we started from the position that we would allow candidates to do that. But then the more we thought about it, the more we realized actually, we can't offer those candidates a comparable grading experience that the AI tool can. So, doing that, we are treating candidates differently and therefore introducing potentially the bias that we are attempting to eliminate. So, we took the decision and time will tell whether it was the right one to say if you want to apply for role F1, you need to agree to your application being reviewed by the tool. And after, I'll say some long reflection and discussion with the relevant teams. I really do think that is the best way to ensure fairness across the board, to put everybody through the same process. I think it's much harder then to accuse us hopefully, at the same time will tell of treating people differently. Know. So yeah, mean, obviously, the AI is not making any decisions, which I think is a key point. And then also, of course, as the vendor who developed this AI functionality, we have a full responsible AI framework and governance process of checks and balances in place to minimize any risk of bias being introduced. So next question, which is from Gabriela. It's a very long question. So Gabriela, forgive me, I'm not going read it all out. But it's linked to the whole thing about how do you get recruiters trust with the AI that it's actually reflecting. It's sifting the candidates in a way that's sort of aligned with how F1 would, you know, the recruiters would look at the candidates. It seems like Gabriela is struggling a little bit. I don't know what technology she's using, but maybe just a little bit about the building up that trust in the tool again. Yeah, I mean, part of it, which I don't know if this helps really, for our team, they were desperate for a solution. So really that helped because they simply couldn't review the number of candidates they were getting. I know that's not applicable to everyone, but for us that really helped. I just want to kind of add that in to reiterate the context. I think we've certainly had higher levels of trust as a result of how difficult things were previously. But I do think, you know, much like any relationship, there is no substitute for time. And I don't really want to talk about relationships with AI. It might get a bit weird, but I do think it takes time to build up trust with the tool. And I don't think there's any way around that really, other than simply giving your TA team time and kind of accepting that they will look at and be reviewing more candidates than they possibly need to, you know, after you've gone live. Checking, making sure. But I don't think that's a bad thing really. I think you want the team to take the time to get comfortable. And we always expected to see that the time the TA team would spend reviewing the lower ranked candidates for all the reasons we've discussed, you know, would reduce over time, but it would take time. And it wouldn't be something that just happened overnight. Yeah, no, good. Thank you. So the next question is from Martin, where he's asking, why did you choose HiredScore as opposed to something? There are other solutions that do something similar ish that could be integrated into Workday. Did you look at other potential solutions to help you with that problem of managing those huge volume of applicants or what was the process there? Yeah, some review of other solutions was done, but actually, to be honest, given the level of integration HiredScore was offering, I think it made the decision relatively straightforward. We wanted to keep that user experience both for TA and for hiring managers as close to Workday as possible in order to increase adoption and make sure that it's always being used properly. And I didn't see anything from anyone else that was being offered that would certainly from my initial explorations would do things better. So, I think for me, that level of integration that was on offer was a kind of particular selling point. Back to my earlier response to Richard's we had come from a world where everything was disparate. And so I'm always keen to try and bring in solutions that don't take us back there and to keep things talking well to one another. Yeah, makes sense. So a question from Leo. Does F1 use Paradox? Paradox is a company that actually what they recently announced we're going to acquire, and they sort of provide the conversational career site, conversational reply and conversational interview scheduling. So Alastair, is that a solution? I know the answer to this, but is a solution that you use? Not yet, no, perhaps we should consider using it. Yeah, let's hope so. For all our attendees, we're very excited about this acquisition. It's a fantastic piece of tech that will really enhance the candidate experience, but also it's going to take away that nightmare of having to schedule interviews, which is one of the worst things you have to do in the recruitment process. And that solution in the last year scheduled, I think, 32,000,000 interviews. So that's one interview being scheduled every second roughly. So, but the answer is no, but maybe that will change. We'll get you back on Alastair. I'll get to see a demo at Rising EMEA like that. Oh, you get to see lots of demos. Yeah, also Asana, which is another AI company that we are in the process of acquiring, which is very exciting, but I'm sure there'll be lots of information flowing around that. So interesting question here from Camilla. Were you involved in shaping how the AI model evaluates CVs, for example, by helping define the screening criteria? We're not involved in how the tool grades, but you can give and should give feedback as to whether, far as I understand it, whether you agree with the ranking that tool has provided. And again, as I understand it, feedback is reviewed and adjustments made where necessary. So, you know, where we were seeing things that we don't agree with, there is, I think, options within know there are options within Higher Score to note that you disagree and change a grade, and it appears differently as a result. And as I say, over time that feedback is collected and reviewed to see whether adjustments should be made to the assessment framework. But that's the same for everybody. You know, all customers have that same functionality and the feedback is reviewed together. It's one solution. We don't have a unique instance for us. Power of the tool is in that huge data set, right? So, I think it makes sense that all feedback is considered and then any adjustments made accordingly. Yeah, and I think as well, you know, you mentioned it earlier on that you needed to refine the job descriptions, right? Because that has a big impact on that scoring. You learn as you go and actually it just shows that actually your job descriptions are very important in terms of getting that screening optimized. So yeah, absolutely. I think just on that point, you know, we've made more adjustments to our job descriptions than we have to candidates grade. So that's what we've seen. There are changes necessary, it's normally been required on our side rather than tools. Exactly, and then the tool uses that information, So you're fine tuning it as you go. Okay, we've reached sort of the forty five minutes and I think that's how long we said the webinar would be. There are a few more questions in there, but I think we covered the ones that were most Let me just see if there's anything that's been really uploaded. No, we've covered all the most popular ones. So apologies to those people, but we didn't manage to get round to your questions. We'll have a look at those and see if we can get back to you. Let me share that and just wrap things up. So please do give us your feedback. There'll be a little survey that pops up and we'd love to hear what you think about the webinar.