Episode 25

Andrew Wythes on the High Volume of Data Talent Applications & Challenges of Hiring Data Talent

TIM: Andrew, welcome to the Alooba Objective Hiring Podcast. Thank you so much for being here.

ANDREW: Thanks, Tim. Thanks for inviting me on as well much appreciated.

TIM: My absolute pleasure, and where I'd love to start today is to get your views on the current lay of the land when it comes to hiring data talent. For you, if you think about last year, what have been the biggest challenges for you in securing great data talent?

ANDREW: I think one of the biggest challenges at the moment is there's an awful lot of people out there looking for a role at the moment, so in terms of when we do put a job advert out, we are pretty much getting fairly swamped with a number of applicants, so there's an awful lot of people out there at the moment looking for roles. So I think the biggest challenge we've got is how to sift through the amount of applicants we do receive and try and find the right people for ourselves and how that's going to work. Obviously, we're not the biggest team in the world in terms of being a data team as such. The biggest challenge we've got is how to actually whittle down the number of applicants. In some cases, we're getting 800 or 900 applicants for a job for our role, and obviously, there are some amazing people buried in the middle of that, so the biggest challenge we have is how to actually find those amazing people in that and how do we screen them out. So that is quite hard for us to do in terms of doing that, I think, but these days I think most human resources teams are quite stretched as well, and so therefore they can provide you some support but perhaps not all the support you've actually used to see in the past, and likewise the recruiting all fits with us in terms of as part of our business as usual as well. So again, that's probably the biggest challenge of currency in part of the last year, so also then how do you then look at the mix between the soft skills, the academic achievements, what they've done in previous roles, and also the technical skills? Because you, as Tim, look at all those different things simultaneously in terms of trying to find the right person in that sense. You can do some screening on that as well, and also the big change is it's just very, very time-consuming for us, so that's one of the biggest ones, and I think also then the issue you have is that when you do get the shortlist together, and then you have to do some great candidates Typically they're interviewing with other people as well, so you then feel like you're under massive time pressure to try and get through the process and get that person over the line and recruited because you know somebody else could be actually doing the same process as you as well. So I think that's been probably one of the biggest challenges. I think obviously in that sense there are some kind of risks to a point where if you try and speed the process up because you feel under pressure because you know that they're talking to somebody else, and therefore you sometimes have to just keep calm instead of trying to get this person the right person as well and try and persuade them to hang on a little bit while we can, perhaps we can put an offer together as well, and why we've done our kind of due diligence on that candidate. So I think that's been one of the biggest challenges in the last 12 months. I also think graduate recruitment's always been quite hard in some respects because, again, we do use quite a few grads in our team, and again, looking at those grads is how do you differentiate between people. Also, you got a good set of academics that might have one year out in industry, and also one of the things they may want to talk about is some of the dissertations or projects they've done, but beyond that, it's okay what differentiates one grad from the other, so in that case you're probably looking a little bit more at the softer skills and their personality combined with strong academics. So yeah, fit and attitude are equally important as perhaps the academics in those cases, so I think it's probably been some of the bigger things for us, I think, in the last 12 months.

TIM: So the volume issue is something I'm hearing a lot, and what's a lot of people said to me is it's not just the volume of applicants, which is a challenge, but there's a perception out there that maybe the applications haven't been written by the candidate themselves; they might have been optimized at least with chat GPT, which then poses an extra problem of is this really the candidate? And also, is the candidate actually fully engaged in this process, like they've automated the application in some way? Have you noticed or experienced either of those issues?

ANDREW: I think probably I was probably seeing more of the latter at the moment. I'd say I think you feel like this basically done a bulk apply to numerous roles. They're picking out two or three keywords, and that's just a bulk apply across the piece, and it feels a little bit like perhaps a horrible phrase that you're throwing some mud at a wall, and hopefully one of these applicants will—one of these parts of the process will actually stick. Whereas it feels like perhaps less consideration of why they want to work for this particular brand or this particular industry that tends to not come across, I think, with a lot of these applicants, you might be right in terms of the case of how perhaps some people are crafting those responses and their cover letters using AI. That's more than possible these days, but you don't know; it's probably a little bit hard to spot at the moment. It's also then probably quite hard to spot that just given the sheer volume we're receiving at the moment, but I think you're probably right. Tim, it's probably something we need to be conscious of and how more active around trying to spot some of that stuff that's coming through as well. and I think, as you say, it does lead to the question: What happens when you actually come to introduce people? If they are successful in getting through the screening process, where do you go from there?

TIM: Yeah, that's always been a challenge. Isn't it the difference between what a candidate puts on their CV and then what you end up getting in an interview, and sometimes even before Chattopadhyay, there's sometimes a gulf in those two things? I wonder whether that gap is going to be even bigger now because you've almost like outsourced the morality question of how much you exaggerate to an AI system. You're no longer writing it. You haven't lied; you haven't exaggerated. The AI is hallucinated, which I love that euphemism, so one of its problems is going to become even worse.

ANDREW: It could well do, particularly if I think it's also perhaps the more and more applicants and more job roles they apply for, then obviously the model will get used to certain phrases, and I'll pick up certain phrases around their careers, or if you feed in certain buzzwords in terms of, say, in a data space, and people want to say, I can code in SQL. I can use Python. I can use RRF. Got exposure to Google Cloud, AWS, et cetera, et cetera, and then how do you unpick what's been written versus reality?

TIM: Yeah, and one thing someone said to me this week was that not only were they getting a high volume of applications, but also a lot of them looked good, like they had hundreds that seemed to be a good match to the job description, and a lot of them looked very similar to each other. It's almost like a uniformity or conformity. probably meaning they come from the same large language model at some level maybe

ANDREW: I think that's going to be a bit of a worrying trend because as a recruiter, then you can't whittle those people down to a shortlist because, as you say, this might be instead of having 10 on the shortlist, you might have 30, 40, or 50, and then also speaking of the amount of effort you then have to put into that to try and pick those down, it's going to be quite considerable. If you all look very similar on paper, then you think you've got to take them through the next stage because you might be missing out on somebody, but it could be a bit of a worrying trend in the short term for sure.

TIM: And I have a lot of empathy for candidates because they're in this market trying to get a job, and tough market conditions for them, they're probably seeing and hearing Oh, I've just looked at this job on LinkedIn; it's already got 500 applications in a day. Bloody hell, I better apply to way more jobs than I thought I had to. because it's almost a numbers game, though I view it, and you could almost imagine this problem snowballing as much more and more I wonder.

ANDREW: I think you're probably right because I think it's In most cases, it's quite easy to apply on LinkedIn, so you can quite easily put in multiple applications for any role, and some of the roles really require the job title level. Some of our roles are quite broad because we're wanting data analysts or data engineers. but also I guess I'm more specific in some of the skills we want, but the general job title will be data analysts, and that's just quite a broad spectrum for a lot of people, and therefore people pick up on that, or they are actively searching for those terms, and they'll say, OK, I'm going to, as you say, I'm going to put that I've got nothing to lose to put the application in at that time.

TIM: Yeah, especially as if there are these tools now that even automate that step, like that would go through and apply en masse to jobs; you wouldn't even have to fill in the application for me; it would write or optimize your CV for you and complete the application; then the marginal cost is almost zero.

ANDREW: Yeah, absolutely. As you say, I don't think that's going to go away in the short term. For sure, it's going to be a continuing problem, I think, for us.

TIM: And how practically did you deal with getting 800 applicants for a role? Was it actually possible to screen all the CVs? Did you have to share them on the team or

ANDREW: We had to share it out; basically, that was the only way we could do it, so we're looking at some of the keywords. I think we've come to the conclusion we need to be a lot tighter on the keywords we're looking for, really tight on some of those, but as I say, it is difficult because, yeah, It is a data analyst role. Obviously, we've got slightly certain limitations around that in terms of what we're looking for and the skill sets we're looking for or perhaps some of the software we've used in the past, but it is quite a broad title, but again it's quite hard because you're looking at certain answers in LinkedIn, for example, in terms of ticking the box of criteria. I think we typically have five or six criteria against a role, and some people will put down that they meet four or five of those, so you do have to dig into those. Is that actually accurate? So it is a bit of a slog, so I think it could become a kind of AI software arms race that we're then employing technology to filter some of these candidates out as well. Where does it stop, kind of thing?

TIM: Yeah, it's interesting. I feel like the CV has maybe run its race as a screening tool because if you can just create them en masse and optimize them and they just deviate so far from reality, then do we need a new data set? Are there different metrics we could be using or should be using in the next year or two to do that screening to decide who to actually bring to that next stage? I wonder

ANDREW: It's possible in terms of what perhaps experiences are or whether or not you can screen on math for technical competency as a first round, for example. For example, we always, regardless of the Alice role, still most times they do need decent spreadsheet skills, be that Google Sheets or Excel as a bare basic, because you're always pushing stuff out in that. How can you screen for some degree of coding ability in SQL, Python, R, or something like that? Can you screen in advance for if the role requires some sort of BI tool knowledge? Most of the packages are similar-ish, if you like, in the scheme of things, really, so whether you could prescreen some of those things from a technical basis in advance, then on that technical side of things, then you would perhaps cut down a fair chunk of the number of applicants already prior to going into their other side. I suppose again you could perhaps prescreen some of the academics if they could load some of the academics up into a platform as well, and then we can set some guidelines around that as well, so perhaps it might be a different kind of application form as opposed to a traditional CV, where, as you say, do we get candidates to enter certain data points or certain bits of information, which we can then say, Okay, you meet those criteria, yes or no. and then, as you say, with that you can actually automate some of the technical tests as well as the initial prescreening that will then certainly take the number down quite substantially, I would've thought.

TIM: Yeah, and I think at least with that approach it's easily measurable. Yeah, so at least if you use something that's quite objective in the early stages, then maybe covering off the things a bit more subjective, the softer skills, the fit into the organization, that's something that's going to come out in the interview process, but at least once you've gotten them there, you can be sure they've got some of the basic technical skills that might end up working pretty well.

ANDREW: That makes sense, yeah.

TIM: You mentioned also another challenge around, okay, so once the candidate is actually in the process, then realizing, Oh, hang on, this is quite competitive, because we found the one amazing candidate out of one of several amazing candidates out of 800, but everyone else is also onto the same candidate. I watched an interview just two days ago, and I know you're a fan of football. I watched an interview with Graham Potter where he was talking about when he used to be at Brighton and their approach to recruitment and really wanting to take the emotion out of the recruitment decision and use kind of facts more than feelings a little bit, and what you said resonated, which was when you're in this kind of fight for a candidate. It's helpful to maybe just relax and not suddenly change your requirements midway. Can you unpack that a little bit?

ANDREW: Yeah, no, I think you tend to be fine; sometimes you are pressurized by If the candidate hasn't come through our internal HR department, we sometimes also use agencies because they've got access to different talent pools, and obviously the agency knows that the candidate is talking to other employers or other prospective jobs. So sometimes you do feel pressured from the agency, like, Okay, we know this person's interviewing for a second-round interview. They're going to get off this week, etc., etc., so they put pressure on you in that sense, so we know that the clock's ticking, so I think we do try and speed the process up a bit, but we still will go through the same steps. We won't cut a step because ultimately, if they're interested in us and we're interested in them, then you'd hope that they would also then give us a bit more time on their side as well. Stop if you like; stall the other employer to give us a little bit more time to finish our process. because hopefully we've got a strong brand, the company's got a strong ethos as well, and hopefully it's a sector that they're actually interested in and want to work in. Hopefully, there are lots of positives on our side as well, not just all the other bits and bobs. We try and speed things up, but we don't try and cut corners. I think also we're perhaps a little bit sanguine saying, Okay, if we can't get it offline, we can't get it over the line; that's it; it is what it is, because we might be just making a rash decision, and then we were then into seeing you have that probation period, and hopefully they'll see one candidate to succeed, but there's never any guarantees in that sense. So I think we try and stick to our guns as much as we can on that one. We might bring interviews forward or try and compress different parts of the process within the same day to cut that kind of the overall elapsed time down, but I think our preference is not to cut corners, and if it's not meant to be, it's not meant to be.

TIM: What about this: if you think back to all the candidates you've interviewed over the years, differentiating the ones who became successful, who you ultimately hired, versus the ones who fell by the wayside? Maybe they got down to the first interview round, the second interview round, or a test, like how could you classify the types of candidates who you haven't hired? Are there any kind of recurring patterns as to why you haven't ultimately chosen

ANDREW: I think it's probably two or three things. One is it's a very old adage, but I still think first impressions matter. I think at the end of the day, we're all social animals, aren't we? So how we interact with each other is really important, and I think you can tell quite quickly how enthusiastic a candidate is for perhaps the role. Us as a brand I've worked at multiple brands over the years, and also just their personality as well, so one of the big things for me is, are you enthusiastic? Do you really want to join us? Are you interested? Have you got a passion for the brand? Have you got a passion for the role? And that If you can push that across pretty quickly, then us as hirers will have our areas pretty covered because we want to engage in that conversation and explore more with you and understand a bit more about you as a person. I think so. It's a bit of an old chest. It's a bit like when you go around and buy a house. I think when you walk into a house or a property, you know within the first 10 or 15 minutes of this that you want to explore the property a bit more, or you'll go to the real estate agent and go, Thanks, but no thanks. We're going to walk away from this one. It is a bit weird, so you got this. I suppose it is a bit of a gut feel to start with.

TIM: And is there a particular way the candidate would not demonstrate that? Is it just their body language, like how happy or enthusiastic they seem to be, or is it more around the research they have or haven't done? Like, how do they

ANDREW: I think research is an interesting one because I think we have had times in the past where you open them up with fairly soft questions around us as a brand and us as an industry before we go into deeper ones, and if you can't answer the soft questions, it is basically you haven't done your homework. So if you haven't done your homework, how interested are you as a brand or an industry? In some respects, we can perhaps accept that you might not be 100 percent interested in the industry as such, but you'd be interested in the fact that we're going to give you interesting things to do, and we're going to give you challenging things to do, and we're going to stretch you, and we're going to give you all the training and the rest of it. You don't necessarily have to say I'm mad about the news and the media. I really want to be in that small sector. I've always wanted a passion to work in that sector. In some respects, we can balance that off. It's that kind of attitude challenge as well, so I think you expect them to know the basics in terms of what they've done some research and done some prep for us. We had a candidate recently whom we took on board, and they were completely deadpan during the interviews. They're very, I think, we took them on because their academics were great, their technical skills were great, and their experience was great, but you need to use they're incredibly hard to read, so hard. but the reason was I think they're just trying to be ultra professional, so it's all quite poker-faced, but they're a very hard cabinet to read, and we're like, Okay, is this going to work? Are we going to have the fit here or not? and so in some respects we took a little bit of a chance on the basis that everything else stacked up. We've taken them aboard, and they've been absolutely brilliant. They've been here for about six months now. They've been absolutely fantastic, totally smashing it, a great member of the team. So sometimes you don't get those signals; it's really hard, but when we have it okay on paper and logically, this is a sensible decision to hire this person.

TIM: that in the interview process as not particularly enthusiastic

ANDREW: It was just very professional, whereas we're laid back, but we're fairly easygoing, I'd say. Easygoing is a bunch of people as a team. We're not so we have a laugh; we have a joke because we know that we're working in quite a pressurized environment, but we have lots of bits of banter within the team, and we're we'… yeah, we all dress casually here in the office. We're not that kind of environment, and we don't have much hierarchy either. In that sense, we're fairly flexible and fairly laid back, and therefore, yeah, we'll do that as an interview goes on. We'll obviously ask all the standard questions, but we try and be, I'll say, jokey with the candidate and try and be open with the candidate and friendly with the candidate, trying to tease out what they're like as a person. So it's, and obviously we all know each other here, so we can, as part of this kind of interview process, be a bit more open, and not all elements of the interview are quite formal; some elements are less so in terms of trying to understand what they're like as a person. but in this particular case the candidate was so deadpan, very hard to read, but it turned out the right decision, but I think that's one of the big things as well. I think, yeah, and I think also probably some of the ones that don't always work out in kind of the testing process is we don't necessarily give people the toughest tests in the world, but we deliberately time-limit it. because that's a reflection of some of the things you have to do here because being a news organization, things will break, things will happen, news stories will come out, and the editorial team will want to know very quickly what's going on or if it's positive or negative what's happening in the world. So you have to be on your toes sometimes and react to those ad hoc queries, so I think then sometimes people get a little bit how they manage that time to go through that process. Sometimes you can see where they make mistakes because they understand why they've made a mistake. We'll give people a bit of leeway with that, but sometimes they just don't really manage the time through that interview through that kind of testing process whatsoever. And

TIM: That's a test that you do in person in the office, isn't it?

ANDREW: Back in the day, they used to be in person; these days we do them online because typically we don't see candidates until probably the last stage. Sometimes you don't see them in person at all, depending on where they're based and timing all this to it. So what we tend to do is we will email them something. They've accepted that they've received it, and we basically start the clock, and they've got to email it back to us. Obviously, I can probably guess what you're going to say in terms of a testing process these days. Obviously, how do you cope with that with the rise of AI and all the rest of it? Can you answer some of the questions? But there are bits of data manipulation things to do for them to do and present things back to us, so that's where they could stick into a bot if they wanted to, but it's probably just as quick to process the tests as it stands at the moment, but again this might be something to think about. How do we actually deliver those technical tests if we're doing them remotely? So that could be, again, that could become more of a challenge to us as well.

TIM: Okay, theme-wise, where candidates fall over is that some would appear to have a lack of enthusiasm; maybe they haven't researched the company or the industry; on a basic level, maybe they don't seem demonstrably interested; some candidates can't maybe handle turning over the analytics quickly enough in that time pressure environment, which matches your work environment. anything else

ANDREW: I think that probably one of the things is One of the big things is demonstrating what they've done, so concrete examples—if you've said X, Y, and Z in your CV, what are the concrete examples in terms of have you done a piece of analysis that meant churn has gone down by 5 percent or revenue's gone up by 3 percent, or how do you hit these KPIs and ROIs? It's having those kinds of concrete examples in terms of if you said X, Y, and Z in your CV, then what's the example to back it up? And again I think some kind of fail on that basis as well. You've made the statement, so therefore we're going to say, Okay, you've saved; you contribute X or Z, so please give us examples of what you've done to actually do that, and sometimes they struggle with that as well.

TIM: I'm interested in that piece, so then is it that they struggle because they just made it up, or maybe their contribution wasn't really that significant, and there was a part of a team, like if you noticed any particular

ANDREW: think I'd say it's probably more of the latter. How was it? Was it significant? Was it part of a team? How much did they actually contribute to the team when you were there? You're just on the edge of the team or a kind of part of the drive in the team. What tasks have they been given individually to complete? In terms of, therefore, they've achieved more on their own. And how do you unpick some of those things where they've either been part of a team or individually? So I think if you're making certain statements on your CV, then you're pretty much going to say, Please give us examples of how you've actually achieved this. What do you do? What was your role in this? And sometimes the answers can be a little bit waffly in terms of, again, it's unpicking what they're coming back to you and saying, Okay, you've said X, Y, Z. What did you actually do as part of that process? What was your true contribution to that?

TIM: and I would have thought if they haven't really contributed at the level they are presenting in a CV, they must collapse pretty quickly under a bit of excuse me interrogation, a bit of questioning from you as a data expert; it must become immediately apparent when they haven't done what

ANDREW: Yeah, it's absolutely, I think it's, Hey, you've said you've done X, Y, and Z, so demonstrate how you've done X, Y, and Z for us, and therefore you can then feel sometimes that they're then on the back foot because they've not demonstrated what they're claiming to do.

TIM: It's a really interesting problem, isn't it? Because I feel like there's this almost like a motivation for candidates to oversell themselves in a CV to get a foot in the door, because if everyone's exaggerating, if you don't also exaggerate, suddenly your more truthful CV looks less good superficially than people have exaggerated. So I wonder if it's almost like they feel like they have to play the game, but then eventually they're going to come unstuck and interview shortly.

ANDREW: I had a thought, so yeah, because if you get a fairly rigorous interview process, then you are going to go through their CV in terms of, okay, what's your skill set, and how does that match the role, or what's your experience? And also sometimes we recruit within the industry, and sometimes we recruit outside of the industry. so either way it's perfectly fine but it's okay what is your level of achievement in terms of what have you contributed so as you say it's at some point you get found out that you've not done that I think it was also it's you have to look at the level of experience so if you're a grad or you've done your first job then we're probably not expecting you to have done a huge amount of things but you've had a solid one or two years in a role you've developed your skill sets you've got used to working in an office environment you're used to dealing with senior stakeholders whatever it is you picked up the the technical requirements the role and what have you turned on the day to day basis One of the questions we always ask is what does your typical week look like just to get a basic understanding. Monday to Friday What do you actually do in terms of what's your percentage breakdown of your time? How much is it doing analysis? How much is it doing? Reporting: Are you spending a bit of time doing learning and development, or what meetings are you going to? How many ad hoc tasks do you get? And I always get given ad hoc tasks. How many ad hoc tasks do you have every week, and what's the turnaround time for that? Are you on any projects? So I think that tends to give us a decent feel in terms of what they actually look like, and then you can obviously compare that back to what they're saying on the CVs. If they're saying they're spending three days a week doing reporting or something like that, okay, where does that fit with all the other bits of what you're saying? So that's a typical question; it's one of our typical questions as well.

TIM: Yeah, I love that one because I think especially in analytics a title can be so misleading. Like, you could basically be punching out tablet dashboards all day every day, or you could be doing really intense, complicated, deep-dive analysis, and their chalk and cheese rolls really even if they have the same title. so that that question is, I think, subtly really useful in unpacking what they're actually doing.

ANDREW: Yeah, and I think also we've followed up in terms of I think also conscious that what do you actually like doing in your role? Tell us about what you actually like doing; on the flip side, tell us what you find a bit boring, because everybody, I can guarantee, in my working week, some bits of what I have to do is boring because it's just admin and bits and bobs and some meetings you have to go to. it's okay I could probably do something to do with doing something else, but it is what it is, so we try and get them to articulate in terms of what you actually like doing in your role and what is actually where it's not that great you have to do it type of thing where do you find some frustrations in your role or things you'd rather be doing differently or Bit of processes, or you do manual data input, or what is it that kind of makes you go ah, or should I do something else? So we try and tease that out as well because then that gives a better reflection in terms of we know what our role looks like; we'll know what a typical role, a typical week, would look like for an analyst in terms of depending on where they are in the business we've got to refine it out. so we can then understand from them in terms of what they like versus what's friction for them and then understand, yeah, is it good, and we've had some kind of like all they want to do is reporting, or, as you say, they want to build BI dashboards or something, which is typically not the kind of role we have. So it's like we have a mix. It's okay, so you put yourself in this little box, but it's probably not for us; it's probably not for you either, so on the flip side,

TIM: Yeah, I feel like one big theme in hiring is that a lot of it could be improved. Maybe this is just like life in general: a lot of it could be improved by just both parties being as honest as possible as quickly as possible. What exactly does the candidate want to do? What can they deliver? What does the job offer? If it's a data scientist role, it turns out it's mainly tablet dashboards. The candidate is probably going to be pretty unhappy if they get in there on day one thinking they're going to build a regression model and blah blah blah, and then they're just doing dashboarding, and so I feel like, yeah, the more information each party could give as soon as possible, the better off they'd be.

ANDREW: I totally agree. I think you better have been transparent and also say that if part of your role is reporting, then you might be that the whole of your Monday's reporting is potentially the rest of the week, which is project work, our talk analysis insight, and training and development, but you might as well be upfront about that. and so typically it's weekly, monthly, or quarterly on a Monday morning to get them out the door, but after the rest of the week, it's more kind of more interesting stuff, but yeah, that's one of the things that don't go away. You can obviously automate as much as possible if you try and automate as much as possible, but that doesn't always go away.

TIM: Yeah, I can think of my very first experience hiring people. This is 10 years ago, and the environment we were working in was what I describe as XL hell, so this is 10 years ago when if I'd said to someone, Hey, I reckon we should have a data warehouse, they would have said, What's a data warehouse? okay and it was just each month was this kind of epic effort to produce this one Excel report from hundreds of other Excel reports it's kill me now basically and I remember hiring an analyst to come in to join me to hopefully take care of a bit of this workload and they quit in the first week after they realized what garbage environment data they were having to deal with I then hired a second one they quit within two days okay so the first two people I hired quit within the first week I swear it wasn't me I swear it was the data not me okay I was a reasonable boss I think but they were my introductions to hiring and a lesson there was like yeah we over pitched the role because There was so much manual effort It was really if we presented it as, you know, the first three months just automate this because this is hellish, then once we get past this basic stuff, then we can start doing more interesting things, but we probably overpitched and oversold it, and so that was one of my fails as a hiring manager. What about you? Can you remember any particular fails you've had as a hiring manager? Anyone you've hired you thought Oh, I've made a bit of a blunder here.

ANDREW: I think probably massively, I think where we've come unstuck a little bit is around probably perhaps explaining to some people that sometimes the role is quite intense, as I mentioned before. Being a media organization, you have to be very reactive, and therefore it's how do you have that kind of personality to have about 10 plates spinning at the same time? and then to introduce the 11th plate, so I think sometimes we've had candidates where I think they've found that difficult, so whether or not we've expected Blame that enough in terms of it's a fast-paced environment with lots going on; if the site traffic's good, then people might want to know why the traffic's good. They'll definitely want to know why the site traffic's bad, and therefore you need to drop everything, and also you've got things like, as I mentioned, we were recording this seven days after the US election; we were very busy last week, so people want information instantaneously. So it was how, as hiring managers, do we look at people's ability to adapt in that scenario? How do we prepare personality-wise in terms of are they okay with those periods of quite pressurized and periods that it's not always like that, but also how do you actually cope that from a personality point of view, and how do you manage your workload? I think that's probably where a couple of times they've been really good, but the demands and nature of the role have been quite challenging for them, so they've ticked the box in terms of technically you're good, the output you produce is good, but sometimes it's if they just found it hard, and so I think it's quite hard then to probably how would you put that across to a candidate that sometimes it's going to be quite tough. I was speaking to somebody working for the gambling industry last week, and they have the same sort of issues where big gambling events in the UK, like the Cheltenham horse racing festival or things like that, on the analysis I expect this turns around pretty much instantaneously because obviously they know that if they have a good gambling event for a big sporting event, that's going to make their month or lose their month. So they've got to be on it as well, so I've felt a little bit of sympathy for them as well, so I think that's where we've sometimes struggled, perhaps explaining that sometimes things are a little bit pressurized, and it's the ability to manage your workload and the ability to cope with that. We obviously support people as much as they can, but obviously everybody internalizes that slightly differently, and how they approach that, I think, is probably the area we did find quite hard, probably over COVID and lockdown, so we took on quite a few people during COVID and lockdown, and we've perfected our retention rate for those members of staff, which has not been great. I think that's probably been repeated over a lot of businesses as well because I think we've It was very hard to integrate them into the team. Everybody was remote; you barely saw people. You might have a team meeting on a Zoom call once a week to catch up on Zoom, but there were no kind of bonds or people coming together and different ways of working and coming together in that sense. Obviously now we're in a hybrid situation, which is great, but I think that was a massive challenge for us in terms of how you support people, particularly perhaps in their first or second roles during that period. I think that impacts our retention during that time period. It was quite hard to look after people in that sense. and we probably didn't give them the quite hard to perhaps give them support around that because you're stuck in a room on your own, and that's it, so I think that's probably from our kind of hiring challenges; they've probably been the main two over the last couple of years, really on both sides of those coins.

TIM: Yeah, and I would have thought if you were a graduate or recent graduate and your first or second year of work experience was bang, you're working in your bedroom; you now can't see anyone. My God, that must have been tough. It's

ANDREW: I think we're all trying to adapt to it, so I think probably in hindsight, how can you do that better? I don't know, perhaps more check-ins or not; I don't know, or how do you work more collaboratively with other people? But it's all the little things, the silly things, like going around the corner to go and get a coffee or a sandwich or whatever. go and have a drink after work, or we do social events every month in terms of we'll do a public quiz or something, but you kind of miss all those sorts of things, so you just don't have those bonds with people that you

TIM: Yeah, and what about AI? So we've spoken a little bit about that in terms of probably candidates using it to craft a CV, potentially to apply to jobs, maybe to help them with assessments, and those kinds of things. Have you seen AI already impact hiring in any way, and also what do you think is going to happen in the next couple of years?

ANDREW: I think we haven't at the moment; I suspect I don't know if it applies to some of the teams, perhaps with the IT and dev teams; they might see it more than we do, so I think it will impact it. I think, as you mentioned, I think it would. How do you actually unpick somebody's CV? Have they written it themselves? are they Is it factually correct? Again, that's a big thing. I think I can see the benefits from outside, certainly from screening. I certainly see the benefits from technical tests. How to actually go about that, and perhaps we can be more rigorous on some of those tests as well, and I think, as we discussed earlier, how could you perhaps then do it? I think you put through a very interesting question. Do you actually need a CV? In the future, it's something completely different in terms of what information you give us as a candidate so we can actually end screen that through that process, so excuse me, and then so I think that could help us as well in terms of that process actually going through every set and also perhaps even some of the fact-checking stuff. So it might be even some simple stuff like terms of if you've told us XYZ, can we then go out into, say, social media, or can we go out into LinkedIn? Does all this information actually marry up as part of those sorts of processes? I know certain interests certainly do take people's social media profiles as well, and I do know that So it is quite interesting that side, but I think certainly as hiring people, we should probably, I think we will definitely be using it; it might be one, two, or three years down the line. I think we would definitely be using it again to just sound like a bit of an arms race if candidates are using AI to create the information that we're using AI to double-check. and I do know some people who are university lecturers, and they've got the issue at the moment where students obviously perhaps are using AI to generate dissertations or essays, and they're using other tools to double-check the content that's in those kinds of things, and as I said, they're presented back at the university, so it is a bit weird. And also, as you see, I think it was as you mentioned: sometimes AI models get things wrong, and also they hallucinate as well, so I think you've got to be really conscious of that. It's definitely coming; I can see a role for it as well, but yeah, I think it's watch this space.

TIM: Yeah, it'd be amazing to see what happens in the next few years, hey?

ANDREW: but ultimately you still want to have the what's in terms of how does it approach a problem on their own How do you know what tools are being used, and what's their thought process? Not just relying on software at the end of the day as a tool, we also have this interesting concept of it's out of Pandora's box, so you can't uninvent it, and people will use it, and should you be using it? and we're having lots of debates internally about how we approach AI in the newsroom in terms of what the benefits are. What's the potential risk and downside? So today we're a news organization, so what we have to put out there is factually correct, so you can't have any scope for hallucination or inaccuracy in terms of that. So at the moment, all the journalists produce all the content, but also there's scope for kind of operational efficiencies, but you've got to be really careful about that. It's definitely coming for sure.

TIM: Yeah, for sure, and it's just so many paths this could take. It's really going to be fascinating to see where it lands in the next few years. What about on the other side of the table? If you think back to your experience as a candidate getting jobs,

ANDREW: Yeah.

TIM: Any especially memorable experiences you've had, good or bad?

ANDREW: I think it was I was thinking about this. I think it's one thing; I remember back when I just came straight out of uni, and then at that time, I think it's going back a long way, because I'm giving my age; I won't give my age away, but it's a long time ago. But they used to do lots of graduate assessment centers, and looking back on those, there was a huge amount of really challenging but a huge amount of fun. So you'd be like, You should be away for two or three days. You'd be doing all these exercises, team-building stuff you used to have to do on your own, versus that, so obviously they were subtly, quietly assessing you all the time, but looking back on that, it's Yeah, it's a great experience to do that because you're pretty much only 21, straight out of uni; it's before you get into the kind of world of work proper, and you're going to get off being packed away into a hotel for about three days and things like that to do all this kind of stuff. It was all good fun at the time. I think it's, I'm not sure how many people do actually do that these days in terms of graduate recruitment and things like that; it's probably gone by the wayside. Other thoughts, I don't know.

TIM: Yeah, it's funny, so I went through similar things when I was a graduate. I can't say we had them for multiple days; that sounds pretty epic. We had them for maybe a day or maybe a weekend, like Saturday and Sunday or something like that, but yeah, my memory of that was it was always quite weird if you were doing like a lunch session and people were watching you eat and how you communicate. And while you're eating, I don't know, do you wipe your mouth? I don't know what they're looking for; I don't know what the criteria was, but they were definitely inspecting my munching, which I found slightly odd.

ANDREW: This is how you can thresh in team games and things like that, or team tasks, so that's gone as well as that, but now I think also coming to this world as well, so I've been here for seven years now, and again, that was like a really nice my boss there as well. She was amazing, and then that was such a nice process, and so that's very close, probably slightly informal, because obviously I've done a fair bit of work in the industry working for a competitor business, if you like, but also in the same building, so that was a fairly funny process because basically when I changed jobs, I used to work for a different newspaper. I could go to one now. So I literally moved about 300 meters inside the same building, so it was a bit weird because you still saw everybody the same day, but it was like a really nice process with my current boss. She was like very, very welcoming and very laid back, and so that process, but she's on it in terms of the questions and the approach and fit and all the rest of it. She's really on it, but the whole process was quite a little bit informal but very professional. That was like a very nice hiring process as well. She's excellent. Yeah, she's an excellent hiring manager as well in terms of how she approaches recruitment in terms of fit and blend within the team and culture and wanting people to live the brand values and wanting people to be excited about the brand because we got a slightly unique position in the media industry in the UK. And she's very passionate about that, and she asks all very pertinent questions, but she does them in such a nice way, but they're really deep, pertinent questions, but the way she approached it was like how to look at people's kind of personalities and dig into their experiences. So she was very clever in that sense as well.

TIM: My final question was going to be about a hiring hero. Whether there was someone who you thought did hiring in a really impressive way, would it be this lady or

ANDREW: Yeah, it will be with Joe, who's the chief data market officer here, and then, but I think she, as I said, is incredibly passionate about the brand. Why do you want to work here? Very passionate about the brand values and what the business stands for, I think she's very conscious of how everybody works together. Have we got a good fit in terms of the people also being very keen on giving people from less usual backgrounds the opportunity to come into the media and having a diverse team as well? How can we have a diverse team in terms of people's experiences and backgrounds, which we're very fortunate that we do? Obviously, London is a very cosmopolitan city, so that helps in that sense in terms of as a recruiting pool that makes it a bit easy for that as well, so I think she's very conscious as well as that and how we fit it into the business because we're one of the bigger teams in the business, but we're also a central team. So we have to support everybody, so it's that ability then to communicate with other stakeholders as well, so it's always she's always very gentle as an interviewer, but as I say, all the questions underneath are very pertinent, and all the questions are pretty much on the money, and you tease out all those answers around people. A very good person to learn from for sure.

TIM: Amazing, and yeah, I think the diversity angle is maybe even more important, I would think, for a business like yours, because if you had just monothinkers from the same background running a media agency, that is very dangerous, I think, to go down that kind of rabbit hole of thinking the same way again and again.

ANDREW: Yeah, and also we've got different We've got different brands within sub-brands, if you like, different websites that are catered to different audiences, so again, to have that understanding is really important. Some of the audiences are A lot younger than, say, the core brand, or looking at different segments of the market So again, to have that understanding is fantastic. It's also good to have one of our sister brands that is more focused on London, so it's great to have people in their 20s or early 30s who are Londoners, born and bred; they understand what's going on in the city, so that kind of helps as well. I think we've got a really nice mix of people as well from different backgrounds, different academics, and different degrees of studies as well. So it's a good mix, so we're very fortunate for having that as well.

TIM: Sounds like a great environment you guys have got there.

ANDREW: Yeah, we do. It's a really lovely team. They're all very supportive of each other as well, so it's a great bunch of people, so

TIM: Wonderful! Thanks for sharing a little bit about that and for a great conversation today on our Objective Hirem podcast. Thank you so much for your time. Andrew

ANDREW: Cheers. Tim Thank you very much indeed.