Episode 102

Hoa Truong on Adapting and Thriving in the AI-Driven Hiring Landscape

TIM: We are live on the Objective Hiring Show today. I welcome Hoa. Hoa, welcome to the show.

HOA: Hey, nice to meet you. And thanks for having me on.

TIM: It's absolutely a pleasure. And I think what would be a great place to start is just for our audience to learn a little bit about you. Who are we speaking to today?

HOA: Yeah, sure. As Tim mentioned, my name's Hoa Truong, and I'm currently the head of data at Equals. I've been at the company for about four years now, but prior to that, I had about 20 years in financial services across a number of data science and predictive analytics roles.

TIM: And so you've seen a bit of everything in your career, I imagine.

HOA: It's one of those where I guess the longer you've been in the industry, you feel a bit like a bit of a dinosaur. So there's this constant drive to keep learning, keep developing yourself.

TIM: Yeah. And I don't know about you, but in the last couple of years, I felt that feeling almost slightly overwhelming at times with the rate of change. It's God. Like, you blink, and you've almost missed some development in large language models in particular. Have you felt something similar?

HOA: Yeah, definitely. With like you say, Gen AI, LLMs, and the fact that this sort of technology is more accessible than ever to everyday, everyday life. And it's trying to differentiate. The real opportunity, the real benefit versus the hype.

TIM: Yes. And do you feel like at the moment companies are missing more opportunities where they could be using Gen AI, or are they wasting money on opportunities where they shouldn't? Do you have a sense of that balance at the moment from what you've seen?

HOA: So I guess from my perspective, I think the main thing is around knowing the most appropriate use cases for Gen AI, as whilst it's an absolutely amazing, advancing ML, deep learning capability, maybe there are cases where more traditional machine learning methods are more appropriate, whether it's from a cost perspective or a speed perspective or an interpretability perspective. I think using is that whole square peg round hole situation. I think we need to just remember that we've got other things in the tool set.

TIM: Yeah. And maybe it's not helpful if we just start brandishing the AI. Descriptor on everything and everything from an Excel spreadsheet with a macro to Gen AI to everything in between, so maybe it'd be helpful if we were a little bit more precise in our language potentially.

HOA: I think it's one of those because it is that, it's that longstanding joke where an executive might say we're going to use the AI to do something. And it might be something that sounds really outlandish, but we've gotten to that point where the AI can do some pretty amazing things. So it's just. Trying to keep ourselves honest in a way,

TIM: The last company I worked at, which was six years ago now, we used to have the joke when we were, you know, planning on some kind of analytics. We were doing that, which was going to be a very elaborate task to write, I don't know, a lot of sequels and build a lot of data pipelines and blah blah blah. We'd always talk about it, and then we'd have to jerk the, okay, now we want to do the do analytics button or the do SQL button, this kind of magic button that would just do it all for us, which six years ago was a joke, but now it feels almost closer to reality with the way we can prompt Claude or ChatGPT to spit up all this code for us. Is that generally a good use case of AI? It's just coding, content generation, and good use of Gen AI, I should say.

HOA: I'd say it depends on the user and depends on the use case as well. So I think, say for the non-technical user, or someone who just wants to have a benchmark that they can iterate and improve on, I think it's a really valuable tool to see what, The size of the opportunity could be; I also feel like, in many ways, that I think for me, AI is really good from an internal efficiency perspective. So it's a bit like an extension to the IDE that you typically use at the moment, things that really boost your productivity. Undifferentiated lifting, I think they call it. Yeah, the things that you just have to do, and it lets you focus on the value aspect of your role.

TIM: Yeah. And. I would be interested to see where this goes, because I did see a quote. Was it maybe from Sam Altman yesterday, who, to be fair, could not be more biased in this regard, but he said something like, As the cost of anything that AI can produce could be produced almost costlessly, therefore the value of that thing will be driven to zero through time because AI can just make it infinitely. Which then might, you might start to think about software and the knowledge work and coding and whatnot fitting into that category. Do you feel that sense that, like, some of your skills, the value, the true value, might be getting eroded with AI? Or do you feel like there are some elements that are just not going to be touched by Gen AI anytime soon? What's your thoughts on that?

HOA: To be To be honest, I think there's, yeah, as AI continues to develop and become more sophisticated, I think pretty much all of the traditional skills that we have come to value are probably going to come into question. And it's about us. understanding where we can continue to add value and where we should try to develop so that we can maintain our ability to actually do our jobs.

TIM: And. When I speak to people about this, they'd normally say that it is the people skills, stakeholder management, influencing skills, sales skills, keeping people honest, and keeping people happy. Is that the thing that AI can't really take away from us anytime soon? Or are there other things, maybe more just pure creativity or unstructured problem solving? Where do you think AI is not going to touch anytime soon?

HOA: So it's one of those where I've been surprised before, but I'd say at the moment, yeah, those are the areas where I'd say A qualified and talented individual does definitely have the edge over AI, but it wouldn't surprise me if that started becoming a thing that was harder to distinguish. Anecdotally, I've met people who see more AI than AI itself and vice versa, so you never know.

TIM: And what does that mean? People who are particularly robotic or talk in cliches, or

HOA: some very robotic people and some very expressive AI.

TIM: I'd like to meet this character as well. At some point, maybe it'll become impossible to differentiate if we have our own AI avatars. You won't know whether you're talking to Tim or TimBot, maybe in the future.

HOA: Amazing. I

TIM: That's, yeah, maybe a little way off at the moment. I should think and hope about what, in terms of how you think about bringing it back down to the reality of delivering business value for your projects and making sure that whatever work you're doing is connected with those businesses? Those business goals. How do you think about the problem? Yeah. Do you have any kind of strategies in that space?

HOA: So I think from my perspective, it's about having allies. So you're being in the conversation, being relevant, and understanding what your key stakeholders need. Maybe we've all been in that situation where we have a solution and we're looking for a problem, and that's the exact situation where we shouldn't be.

TIM: Yes, I would always have agreed with that. But then I've heard of a few companies recently that want to go on and on about Gen AI where they've told their organization, they've basically said, Hey, let's stop working for the next month. Don't do any tasks. Don't do anything. We just want you to sit there and think about how you can adopt Claude or ChatGPT or whatever it is in your day to day job, which is like a solution looking for a problem. But I feel like they probably justify it because the technology is potentially incredible and powerful if you don't carve out time to sit down and think about how to apply this in your role, you'll always keep doing things in this way. That's now automatable. Potentially, maybe there's some argument to say, Yeah, let's just throw the AI solution. It is a bunch of things because, yeah, half of it might be irrelevant, but for half of it, it will stick. Is there some merit to that? Do you think the technology is just improving so quickly?

HOA: Yeah, definitely. I'm definitely a fan of having a commitment to R&D and just the time to actually breathe. And I guess another pitfall is just being stuck in your day job. and doing the same thing over and over. It's about how to move the business forward in a meaningful way. I think being able to do that is really valuable. I think on the flip side, there probably comes a point where people are asking, where's the value add? And I think that's the point where you'd have to ensure that you have something to deliver.

TIM: And I know one thing we've tried in the past in this space, sorry, was hackathons where we did maybe two, three, or four-day hackathons where each engineer could just work on whatever they thought was best as a way for them to really put their stamp on things and get things into the products. And so it was a little bit less biased than, let's say, me deciding what we needed to do. Have you tried that approach, or have you seen any other approaches work well?

HOA: Yes, so I'm also a really big fan of having team hackathons as well. So one thing I found is maybe it was a bit unexpected is how not only do you get the time to focus on an innovative problem or an innovative solution to a problem, but you also learn more about your own team than you would do in the day job, because you start seeing the creativity and the team dynamic can really benefit from having these events.

TIM: And so it's almost by removing their constraints, you start to see them flourish in a way that you wouldn't otherwise have seen.

HOA: Yeah, for that reason, I think it's really valuable to exercise that type of dynamic in a team.

TIM: Yeah. And a few other things I've noticed about hackathons that were really helpful for us were, one, just the time pressure. So what's that? I think there's a law, Parkinson's law. That's right. That work expands to fill the time available. for it. And so having this deadline, like you have to ship by this time, we're going to invite judges in to do the judging. There's like prize money on the table. So it just is; it's like a forcing function to make people just solve the problems faster. It's really incredible. I've often thought about how that could be incorporated into day-to-day work and life because this is nothing like a deadline to make you ship stuff quickly.

HOA: Yeah, it's the absolute distillation of the whole MVP concept.

TIM: Yes, absolutely. And when you guys have run your hackathons, what was the end goal? Were you trying to create a prototype? We were trying to ship real products. Yeah, what was the kind of goal of those?

HOA: I guess we have a number of depending on the particular hackathon; will we set a specific objective? So that we have cases where we'll set a learning objective, as a team, we'll try to do something new that none of us know much about. We have ones that are project-based but not necessarily work-related. So we'll take something that we've seen or something that someone's thought of and say, Let's try. Let's put a twist on that, and then we have ones that are You know more work is focused with a clear application in mind.

TIM: And do you do them in teams, or do people do their own projects? Have you done it in the past?

HOA: So we tend to work in a team; sometimes we'd get guests from other teams, so maybe it's someone from a product team or someone from a sister engineering function who just brings a different skill set in from the immediate data team's skill set.

TIM: Yeah, that's cross-functional teams can be interesting and hackathons. Sometimes it might make it a little bit harder to coordinate. But yeah, there's definitely like a value add of having those different perspectives involved.

HOA: Yeah, definitely.

TIM: One thing we'd done was we had, yeah, either had a theme for the hackathon. So I think some themes in the past we've had were, like, around our values. So it might be that one of our values is around fairness. So making it a fairer platform for candidates to use. And so everyone had to somehow have a project that was aligned to that overall theme. Other times, though, we'd left it completely open-ended and said, You can work on literally anything you want. Doesn't matter; you have full reign; you can do whatever you think is best. It's interesting how in the first scenario, even though there's a bit of a constraint, that constraint almost helps people to narrow their thinking of what they were going to do. When we left it completely open, people were like, This is just too many opportunities. It's like walking into, I don't know, a massive supermarket. You can have anything; you just need to refine it a little bit. Otherwise, it was overwhelming. Did you find something similar?

HOA: Yeah, it's that whole, yeah, that whole saying where they say that limitations breed creativity or something along those lines. Agree?

TIM: Yeah, for sure. One thing we'd also done, which was cool, was we invited external judges. So we'd have some of our customers or industry people come in. To just the demo session. So our engineers would work for, I don't know, three or four days sometimes with very little sleep, and then they'd come for this, our demo session. So they get maybe a few minutes each to demo their product they'd built, which is really nice, and then the external guests—I like that because they provided this almost unbiased view because they didn't know the engineers that didn't know the details of what we've done in the past and blah, blah, blah, blah. They just came at it with this fresh perspective. And it was very interesting to see. That I could never predict who the guests were going to choose as the winner, like every single person in my head, as I was watching the presentations, like I would pick that winner or I think the guests will pick this one. I was wrong every single time. So it was fascinating to just get other people's views, like, Oh, wow. I didn't see that perspective at all. When you've done hackathons, do you have some kind of demo? presentation to finish it up. Do you have some kind of celebration or prize money or prizes or anything like that?

HOA: So it's funny you should mention that because recently I'd say, not really, no, but that does ring a bell. Back in my previous role at Lloyd's Banking Group, they were very competition-based, the hackathons. And I think it brings a really fun element because I think that it may put, it gives you that incentive to put your best foot forward when you present it and present it in a compelling way.

TIM: Yeah, exactly. It's a nice upside. One interesting thing we have with our hackathons also was we had a rule, which is I think pretty unusual for hackathons is to be eligible to win. Your feature has to be live on the production website, which in three days is a pretty amazing turnaround from idea to shipped. Without breaking the entire product, we did that as a forcing function again to go, You're going to have to somehow make this such that it actually works with real users. It's not just like a vague idea or whatever for your hackathons; did you do it that way, or was it more like a prototype was the end output?

HOA: It was always like a prototype-type thing. Although, hearing what you just said, yeah, that sounds like a high-stakes situation.

TIM: It is high stakes, and it makes It, yeah, makes it more difficult. I feel like the proto, if we had gone down the prototype route, I think we might've gotten more wild ideas. We might've gotten more, more like an outlier that could have been something amazing, even if it was just a tiny speck of it. And by having the rule, you have to ship it. Maybe we've got slightly narrow ideas that were a bit more realistic, a little bit less crazy, but we got. Shipped product, which is always valuable.

HOA: I'm going to make a note of that. It could be good on,

TIM: Yeah. Yeah, it works. I think overall you have to, of course, then have other people available to actually do the QA testing, do the testing on staging, be able to run your QA tests or the automated test, and then ship it without breaking the entire infrastructure. So it does require a little bit of that. And also, yeah, a little bit of a little bit more risk tolerance in shipping product really quickly, but yeah, I think it worked overall for us really well. We've got loads of features in our product now that were used in that hackathon. Projects initially, including, actually, because this is a nice segue, including our AI CV screening tool, which was a hackathon project probably two years ago. Now it's from one of the early versions of ChatGPT. Do you currently use any AI in your hiring process? On the hiring side of things?

HOA: It's funny, me personally, no, not really. It's probably a bad thing to say given my role, but I can't really speak in terms of the initial screening process that happens with our in-house recruitment team, but personally I don't see the requirement; I don't see the need just yet. I think it's for three reasons from my end, one being scale. I guess in the grand scheme of things, we do recruit for fairly specialized roles. And for that reason, we don't receive nearly enough applications for me to start thinking that I need something to help me cope with the scale. And the second is around team fit. So I think it's that thing where it's not really one size fits all. I'd like to be able to review. Applications for myself and make that judgment. And I guess the third is around just courtesy, because I feel like if someone takes the time and the effort to apply for a role, I'd like to repay that in kind and give it the proper consideration. But having said that, I'm keen to keep an open mind, though, and I guess as long as we're mindful about what transparency looks like in terms of using AI in the recruitment screen process, and I'm keen to avoid the situation where. A bigger number is better when you're looking at applications. Someone's got 10 years of Python experience. Does that make them more eligible than a five-year experience candidate? Maybe not.

TIM: What about if you had? Would you ever consider just using your own? prompts to Chachapiti and says, Here you go. Here's this page. Chachapiti. Here are these 100 CVs I've got. This is exactly what I'm looking for. Here are the red flags. Here are the green flags. Here's the type of typical person who might look good, but I don't want; here's the kind of person who might not look good on paper that I do want. Like I mentioned, some kind of really elaborate prompt that is just distilling exactly what you're looking for into an AI. Have you ever considered trying that? Or is it still just that the volume is so low, it's not even worth it?

HOA: Yeah, I think it's just that. It's around if I was ever dealing with that type of volume; I think having that ability to summarize would be amazing. But at the moment I think we're okay just reviewing them case by case.

TIM: And what about on the candidate side? Have you started to notice candidates using an ether in terms of creating their CV or taking tests or in an interview?

HOA: Definitely. Embarrassingly embarrassing on their part, but my part as well. We once interviewed a candidate who we asked to prepare a presentation. And I think the presentation was largely AI-generated, even to the point where it had a different company's name on the presentation. I think that there's that kind of pitfall where people aren't really—they're not giving the application due consideration. Bringing it back though, I find with all these tools that are out there, it's becoming quite difficult to actually differentiate candidates in a meaningful way. I think maybe part of that is a learned behavior because maybe these people think that's what hiring managers want to see from them. They want to hit the key words, the key qualifications; they want things to read the same, professionally. And I think it's up to recruiters and companies who are hiring to actually set that tone, set that expectation. That is not, maybe that's not always what we want to see.

TIM: Yeah, it is such a tricky scenario. I think for candidates in this market, especially in some geographies, the United States, especially. If you're a candidate for a data analyst or data scientist role, you're looking at the ad, and you're saying, Wow, a thousand applicants in a day. My God, that is a lot of competition. I thought I had to apply for, I don't know, 50 jobs to get two interviews. Now I think I have to apply to 500 to get two interviews because there's just such a huge volume. So then I assume that then using these tools to either, here you go. Here are these 50 job ads. Rewrite my CV for these 50 job ads or just apply automatically to jobs. But in doing that, they're almost undermining themselves because, as you say, they're all starting to look the same if they've all been customized or tailored based on the same job ad with the same AI; it's inevitable. It all starts to sound like muchness.

HOA: Yeah, and it's that thing because I don't really have an answer to it, but it doesn't help people; it doesn't help me find the people who have the skills that really matter to me. Things like problem-solving: how do they respond to challenge and adversity? What's their resilience to setbacks? Yeah, that sort of thing. I think the rest of the application process needs to uncover that.

TIM: Yeah. And that's the kind of thing you just can't tell from a CV at the end of the day. I wonder if. What if part of the challenge or part of the solution maybe is going to be to unlock a new, better-quality data set than a CV, because even before AI, anyone could put anything on a CV. I could claim to be a rocket scientist. Can't really tell me I'm not until you've gotten me to that. Maybe that interview stage started to give me. Questions about physics and realized I knew nothing, but at the same stage, you just have to take people's word for it at a certain level; maybe we need some new data set to do the screening with.

HOA: Yeah, I agree. I think for me it's not the answer. I think we're quite conventional at Equals in terms of our interview process, so we'll have a technical element followed by a competency-based interview, maybe a couple of other stages after that, but I think there's no substitute for a real conversation. Cause I think it really gives you that ability to gauge a person's experience. They might have the 10 years of Python or SQL experience that I mentioned. What happens when the numbers don't look right? How can they deconstruct or unpick a problem? I think for me, aside from talking about successes, I also had to put a due emphasis on the things that didn't go so well. And the learnings that they took from it, that sort of thing.

TIM: And when you're going down that path in the interview, what would be considered, from your perspective, good answers or bad answers to that kind of, when did you fail and how did you learn from it? If you think about the candidates who did well and not so well with that question.

HOA: It's a good question, really. I think for me, it's just seeing that a candidate is willing to have that conversation. It's a bit like that question around what your strengths and weaknesses are, and you'll always get the tried and true answer. Like I said, I'm a perfectionist. That's my weakness.

TIM: So that would be a red flag if someone said that.

HOA: Yeah. It's a bit too, it's a bit too prepared. It's. Not really telling me anything.

TIM: The other one I like is, yeah, maybe it's an extension of this thing, but it's wrapping a strength and a weakness. So it's a very thinly veiled strength. Yeah, that ends up being, yeah, working too hard or. Caring too much or something like that, but it's presented in this negative way initially, but then you think, hang on what are you talking about? That's a strength. Yeah. your actual weakness,

HOA: Yeah, it's that thing; if I was working with the person, I want them to be honest with me rather than wrapping it up and yeah.

TIM: Yeah, that one's really tricky, isn't it? And I personally feel like hiring in general could be improved a lot if both parties were as honest and transparent. Down to almost being brutally honest as early as possible because then you could filter each other out as soon as possible. Do you take that approach, or do you feel like there needs to be a bit more of a kind of dance involved in hiring?

HOA: I'm all for an honest and candid conversation, and you're right about that two-way dialogue because I think as much as we're looking for the right candidate, we also want to make sure that the candidate is going to be happy in the role and make sure the company's right for them.

TIM: Yeah, and there's no point stringing a candidate along. This is why I sometimes get slightly worried when I hear about, like, talent attraction, candidate marketing, these kinds of things, which is fine. Of course, we have to attract the best quality candidates to our job. That's fine. But when I hear about marketing and sales or recruitment as a sales process, to me, that gets me a little bit thinking about are we really being honest or are we trying to, massage this job and make it seem as though it's something that's not, which I think is a very short run game because us. The candidate will get in on day one and realize, hang on, you told me this was 80 percent data science and 20 percent reporting, and it's 80 percent reporting and 20 percent data science. And they're going to be pretty annoyed pretty quickly. So I feel like, yeah, the more honest both parties can be, the better off we'll be able to save everyone a lot of time.

HOA: Yeah, I think the only kind of sales that you should be doing to advertise a role is just getting that exposure out there to say, Look, there's a role here, and it's X, Y, Z. Yeah,

TIM: They like it. If they don't. I agree with that. And I can tell you from my own Speaking of learning from mistakes the two people I hired first, which was now. 11 years ago, I was a senior analyst with a company and looking to hire an analyst, commercial analyst, and I was operating in what I'd call Excel hell. So this is, the idea of a data warehouse was anathema to them. It was just a lot of spreadsheets being sent around all the time to do all this kind of basic reporting. It was hellish. Part of the reason I wanted to hire an analyst to start taking care of some of this manual reporting was so I could do something slightly more interesting. And I remember we sold the role as maybe more than what it was. And we said, Oh, yeah, we've got a lot of data. We've got a lot of interesting data sets about this, which was true, but realistically the person coming in still had to deal with lots of crap. And hats had probably spent several months automating some of this crap so that we could do something actually interesting. And I didn't really sell it that way. And the first candidate lasted. One way you can, the second last two days, that was about as bad an introduction to hiring as you could possibly imagine. And from that point forward, I feel like I was much more brutally honest.

HOA: It's one of those where I think there's no hiding. The fact that most roles do come with the good and the bad. The only success I've had in hiring for those types of roles is if, budget willing, saying this is the role that you're coming into, but I'm also looking for a way out or a way forward and help them, ask them to help you define what that good looks like going forwards.

TIM: Right. So you're really trying to get into the specifics of the career growth rather than just a general answer. You're like, okay, this is the exact role you could maybe move into in this period of time. What do you think about that? Is that the conversation you have with them?

HOA: Yeah, it's that whole ownership and accountability piece, where it's you're coming into this, but, with my help, we're going to build something better; we're going to move it forwards in a certain way. Now hopefully that gets them motivated or invested enough to stick around.

TIM: And yeah, this transparency I think is so important on both sides. And part of the issue of hiring is that it's not that common on the candidate side to be brutally honest in your own CV. This is part of the reason why CV screening is so inaccurate, why everyone's complaining about getting inundated with random CVs. It's like I spoke to someone just an hour ago who put up a job for a data scientist, got 2,000 applications within a day, 99 percent of them are fundamentally irrelevant, like getting applications from teachers, from chefs, from people with no, not really any crossover in advanced data science skills at all, because it's an open job market, because anyone can just hit that quick apply button on LinkedIn or whatever. So I feel like, yeah, candidates obviously need to be honest as well. I can think of someone I interviewed recently who said that they had hired a data analyst. said they had advanced SQL skills, gone in on day one, and said, Yeah, nah, I don't know SQL at all. So we're going to have to deal with this problem together. Now, to the credit of this candidate, they actually upscaled very quickly because they were motivated and interested, and they played a game, and I'm going to lie to get this job. But once I've got it, then I'm going to make the most of it. So it worked out in the end, but yeah, surely if we were just more honest with each other, we'd all be better off.

HOA: It's definitely a personality type; I don't think I could ever black my way into a job like that. I wouldn't have the nerve.

TIM: Neither would I, and that's when I hear about some candidates. In fact, I saw a video just yesterday, someone tagged me in it, of a candidate doing an interview on Google Meet, where they had some kind of tool to implant their face. On the face of the person doing the interview. And it was very obvious because, as they moved their heads slightly, the face was imperfectly over their face, the avatar. I don't think I could do that either. Like I, I don't have the balls of steel to try to fake my way through that kind of process. I'd rather just be honest with people.

HOA: Yeah, props for creativity, but yeah. Definitely not.

TIM: Yeah. And I see other candidates yet using clearly an LLM model on another monitor where they've got the audio coming out of the computer, and then it's trying to answer, and they're looking back and forth to me. That also makes it more complicated. It's pretty hard to focus on an interview and their question and then solve the problem. If I'm now introducing a stream of texts from an LLM, it's God that's another input. This is just making my life harder as a candidate, not easier.

HOA: Yeah, it's that thing too, because I guess in the day job, people will have access to tools like that. And so there is that question about, is it bad to be using those tools? What I would say is that someone who's preoccupied with using such things in an interview comes across as less engaging; they have less rapport. I don't think it helps them.

TIM: So yeah, it's not even purely about the quality of the answers to the questions. It's the metadata almost of, as you say, their focus or lack thereof and building that relationship. Probably, it is at least as important a factor in getting the job or not.

HOA: And it's that thing we keep coming back to, but I 100% I'm like a people-first type of recruiter in that sense, where I'm looking for people who will be a good team fit, and I think in reality, I spend more time with my team than I do with my own family, so I need to be able to get on with him. Yeah. They need to be happy where they are. It's that sort of situation.

TIM: And how do you evaluate that? I assume that's mainly in the interview stage where you're looking for that team fit.

HOA: Just looking for the right kind of dialogue for people who have a certain level of experience that, when you talk to them, you know that, yeah, they've dealt with similar things before. They know what I'm talking about. They also know what the role entails. Should they take it? Should they be successful?

TIM: And you mentioned team fit. So is it, do you think, Do you think of almost having a portfolio of skills you need in your team overall and then finding people to add the bits that are missing?

HOA: Yes, so I think Team Fit comes. There's a skills and a functional aspect to it, but then there's also a personality and EQ element to it. I think the best example I had is, it was actually my first role at MBNA/Bank of America, but my manager at the time is also probably the most influential person in my career. And he had that these three team values that and he used to repeat them all the time. And in this instance, it was conscientiousness, diligence, and fun. He was talking about, like, your conscientiousness; you need to be willing to do the right thing. Diligence was around working hard and taking care of the results that you deliver and fun. I guess it was his. way of talking about team fit from a cultural perspective, and that's not just about being polite and being nice to people, but it was about putting energy into actually contributing to make it a better place to work. And it's funny because, decades later after that role, I still see posts from people who I used to work with, and they always say those were the best days of any career. So there must be something to it.

TIM: Yeah. And who was this manager? I feel like we should give them a shout-out.

HOA: Oh yeah, shout out to Ian Grime. Definitely probably the most influential person in my whole career. He gave me my first job.

TIM: You gave your chance and your start. And it sounds like you had a very clear vision of how he wanted his, like the environment of his team to be. And it sounds like that's something you've also carried forward into your team.

HOA: Yeah, I think about it every day, as bad as that sounds.

TIM: That's good. It's not bad. That's good. Yeah. As you say you're a people-oriented hirer and manager, one challenge with that, I think, is. Like, in general, when we talk about hiring for values and hiring for a cultural fit, sometimes I think that could almost be at odds with diversity of thought in the sense that you could almost start to look at people who, yeah, have this consistent set of values. But sometimes you might want someone who's, like, just out of left field, who's going to come in and cause a bit of a ruckus, who's maybe going to ruffle a few feathers, who's maybe going to operate in a very different way. Is there any value to that? Or would you rather have people who have that kind of common alignment of values?

HOA: Oh yeah, so it's funny that, because when I talk about a team fit, I guess the way I see it, it's not to the exclusion of people from that left field. We actually have quite a diverse team, no matter how you slice it. In terms of the whole people coming from different backgrounds, different career experiences, and different walks of life. We have a few that have made a big impact. One of my senior analysts, or the senior analyst in my team, came from a retail management role, and it turns out he's absolutely fantastic at dealing with tough stakeholders, and he's really organized. It stands to reason. The second example is I have a lead BI specialist who's from a different industry altogether, so it's not financial services, but I find that she approaches her analytics from a storytelling perspective. It's quite refreshing and she brings a lot of discipline and rigor to the planning and design phase up front.

TIM: And so you've really tapped into some of those. Kind of unique backgrounds and leverage them in the team. Which is awesome. One thing I think is also tricky once we start to get into these almost subjective areas. So we start to get away from just evaluating. XYZ skill. I've measured your SQL skills. I've mentioned your Python, your stats, knowledge, and whatever; you can measure it pretty well. It's black and white-ish, but then you start to get into, let's say, softer skills like communication or some of these values, and it's just inherently a bit more subjective. Do you try to measure any of these things in the hiring process or do you, is it a sort of intuitive feeling around the person's skills or values fit?

HOA: It's because I haven't actually tried measuring it, though I guess there are ways. Around, there are ways that exist that do that sort of thing. What I find is that I think candidates who I find promising, so it's almost like they need to pass the technical component to be in consideration, but then it's a point of having that competency, values, and behaviors type conversation with myself, with members from my team. But I also like to have interviews with them, getting to meet some of our key stakeholders in wider organisation. It's just about how quickly you can build that rapport and when people feel like they want to be a good person that they'd want to work with.

TIM: And so you get this quite holistic view of the candidate then if you've gotten all these different people's views on them.

HOA: Yeah. I think it's that. There's that two-way benefit where the candidate also gets a feel for the culture of the company and whether they want to work with those people too.

TIM: Yeah, it de-risks it for both sides, doesn't it? If you meet more people,

HOA: Yeah. And then, should they join the company, they also come into a more familiar environment because they've already met these people.

TIM: Yeah, that's right. A few friendly faces don't hurt, especially for introverts. I know if I joined a company and I'd already met 10 of the people, it would make it a lot more comfortable for me then. Going into a room full of complete strangers.

HOA: Yeah. And I think it speeds up that kind of going up the learning curve.

TIM: Yeah, 100%. What about broadly speaking about making hiring a little bit more fair, a little bit more objective? Are there any ways that you have to do that throughout your hiring process?

HOA: It's one of those where we have a standard set of exercises, of questions for the technical element. We'll have a standard set of questions that we'll go through for the competency-based values and behaviors section. But then I think a lot of that conversation is organic in terms of depending on the responses that we get from the candidate, or their particular experiences will probably go down different paths of that conversation. And I think that goes back to the sentiment I have around the application process needing to be fair, but not necessarily the same. Fair doesn't mean the same.

TIM: And for example, that might mean someone who, let's take an example. Someone is vision impaired. Giving them some kind of online test or some kind of online thing that requires them to do that would clearly be unfair. So you can change the process to accommodate them.

HOA: Yeah.

TIM: Rebalance it. Is that a fair example?

HOA: 100 percent Yeah. I think it's for me, and it goes back to my point about being as people-oriented as would make sense: How do we make the conditions for someone to show their value?

TIM: So it's really about unlocking that. Yeah, it's hard to do. I feel like you're running those structured interviews and doing it a consistent way does make it. easier to compare candidates, and you've given everyone a similar opportunity, arguably. But then it's also, there's almost like a constraint to it inherently, like the structure to it, then sometimes it might prevent someone from really shining. And if you didn't have a really free-flowing conversation, it'd be hard for them to show that little spark of amazingness.

HOA: Yeah. So it's that thing where we have standard interview structures, which act as the guardrails; we just ad lib at times as well.

TIM: So you've got a bit of both, almost the best of both worlds in some ways. HOA: Hopefully. Yeah. TIM: If you could ask our next guest a question about hiring, what would you choose to ask them? HOA: I'd say that What is your go-to interview question, let's say?

TIM: Nice. We'll level that. Do you have a go-to interview question, one that we can discuss, and you wouldn't consider it being leaked?

HOA: So yes, to be honest, mine's probably pretty boring, but it really is. Just tell me about yourself. There's, I think, it's sufficiently open-ended that it puts the onus on them to add the structure, literally to make something from nothing, but it also hopefully starts the interview on the right foot. About you showing interest in them.

TIM: That's a good one. Nice. Okay. Hello, I might start my next interview with that very question with our next guest and see how they answer it. I'm looking forward to what they say. It's been an interesting conversation today. Thank you so much for sharing all of your thoughts with our audience.

HOA: Thank you, and I appreciate your time, Tim. Thanks for having me on.