Episode 57

Pier Martin on The Evolution of Data-Driven Hiring and Overcoming Interview Challenges

TIM: Here, welcome to the Alooba objective hiring show. Thank you so much for joining us.

PIER: Yeah, Tim, thanks for having me. Actually, I'm really excited to talk to you today.

TIM: I'm pumped to speak to you we're thrilled to have you on board one area I'd love to kick off with is a bit of a a bit of your curiosity that I found over the years in working in the kind of data recruitment space and so let me lay it out for you to get your thoughts on it so I must've spoken to maybe a thousand analytics leaders over the past six years and these are leaders who spend their day helping businesses make data driven decisions in product and sales and marketing and operations they're like deeply embedded in this way of making data with decisions and yet I'd say probably 80 percent of them when it comes to hiring and making hiring decisions they abandon a lot of that kind of data driven decision making and go for a very intuitive gut feel based approach do you have you seen this pattern can you explain why it might happen what are your thoughts on this

PIER: 100% I think I've seen that pattern. I'm probably even guilty of it myself. I think ultimately you humans are just biased creatures in my mind. Like, if we like the person we're talking to, we're more than likely to refer them forward. I think there's an element for sure that comes in there. I also think that it's hard to quantify a lot of the things that we're looking for in the people in this space. I think it used to be easier to quantify if I go back 10 years ago. Oh, can you use SQL? Oh great! Do you know Python? Oh wow, amazing! Right away you're already ahead of the curve, but now those two skill sets are mainstream. And so the things that you're looking for are more like the intangibles of how do you think, how do you communicate, how do you relate to the team, and can you handle change and incomplete requirements? And so to me that's somewhat a little bit harder, especially with the tools that we have at hand or the legacy systems that exist from our recruiting that I think nowadays it's just you have to use your gut more, and there's less data to say, like, how do you say Oh, this person will handle adversity really well with the way that the system is set up now with the way that we look at the interview process. You just go into the interview, and you chat for 45 minutes. There's no real data that comes back out of that from a standard historically the way we used to interview. So yeah, absolutely, I'm definitely guilty of that too, and we shy away from that data-driven approach.

TIM: That's a really interesting lens you've added there, so basically part of what you're saying is the technical, the basic technical skills have almost been commoditized, so everyone's on a similar playing field. It's not a distinguishing factor anymore. Is it also maybe then a maturing of the market that now we are thinking about more specific things in candidates rather than just a simple technical test

PIER: Absolutely, yeah, for sure. Look, so in Europe the candidates I have put a job offer for an entry-level role are looking for someone with maybe a year of experience, something like that. They all have a master's degree. We at a prior role were looking for four interns. Interns are quite a big item here in Europe. We hired four of them. They all had master's degrees; one of them had a PhD. The market is saturated in that space, and the overqualification of skill sets in the data science world, but I think that, or even in analytics, to me the big differentiator is exactly that if you put a roll-up on the internet here, you get 250 candidates within 24 hours. How do you differentiate? Yeah, you can do those SQL and like Python tests, and yeah, you can do case studies, but with the invention of AI, now those are even easier to do. We don't expect people to be experts in anything specifically, but what has remained constant, in my opinion, is a lack of data literacy within the organization, a lack of true, clear requirements, ambiguity across what we're trying to achieve, etc. And the pressure on the data team is higher than ever again. Five years, 10 years ago, you built a dashboard. You're the company's hero. Now you build a dashboard, and you're just another analyst who doesn't understand the greater context of the business, and so, like that, that also has matured as well as the expectations, which is great in my opinion.

TIM: Yeah that is a good thing because I remember that kind of slightly earlier days of the first or maybe not the first but a wave of kind of AI machine learning projects 10 years ago my sense was when I spoke to people is there's a lot of money being spent with very little actual tangible benefit which hopefully we're past that That kind of growth curve or what have you so maybe we are okay maybe not but yeah hopefully we're thinking about the candidates then in a more mature sense so then you're saying that the types of things we would now evaluate and care about are inherently a bit more subjective a bit less easy to measure so it's only fair in a sense that we would use more intuition rather than a data driven hiring approach basically

PIER: Yeah, absolutely. I think mature organizations have a way of quantifying what is good communication versus what is not good communication, but I think that those are typically the organizations that are larger or have the capital to invest in those sorts of things. If you look at a startup with 100 employees where they're making up processes as they go along, They have no real way of quantifying evaluation between multiple candidates about what is communication; they often rely on the hiring manager's gut instinct for who will be a fit for the team from a cultural perspective, so I think you take the data; you definitely take the data out of it. In that space, unfortunately, I think that's a part that we need to figure out how to quantify that because ultimately that is the make-or-break. You go and talk to a candidate; you really like them; you think they're going to be a great fit. Technically they're fine, no challenges, but they come in, and they can't write an email without aggravating somebody, or they can't run a meeting the right way. and then you realize that investment, especially here in Europe, is a three-month commitment, so what I mean by that is when you hire somebody, there's a three-month notice period, and so you have to wait three months for them to resign from their job. Start with you, you give them three to six months to integrate into the organization. and if they're not the right fit, you've lost a year, and so that person that you were trying to recruit a year ago, you have to start over again, and it's another year, so one bad hire can cost you easily 15 months of lost productivity, so it's an expensive—it's a very expensive mistake if you do it the incorrect way. and I think that right now we're relying too much on gut, and we are making those mistakes when we do that hiring.

TIM: I feel like one way to make the evaluation of these subjective things a little bit more objective is to have at least some kind of scoring rubric, so let's say, for example, communication skills are probably going to be something you're looking for in every single candidate irrespective of the role I feel like there's a difference between just getting to the end of the interview and going yes or no versus here's how we're defining good communication. He is like a five out of five; here's a one out of five. Here are specific ways they might communicate that would be indicators they're five or one. If we boxed it in that way and got people to evaluate it in an interview, I feel like we'd make it more accurate. What do you reckon?

PIER: Absolutely. For sure you've seen different organizations. The fad of the last couple of years I've noticed is the star system. The situation is trying to remember exactly what it is, yeah. something action something result or something anyway, so I wish I had come up with that on top of my head, but that became the new mainstream way to figure out how someone can storytell and communicate what they actually did and the task and what they achieved and all those elements. but then again, like everything else that became a mainstream way, so now everyone's prepared to answer questions in that format, so I think there's also this element of every time we introduce a new way of trying to evaluate something, people do master it and then know how to gamify it in a certain way, but yeah, I think, yeah, absolutely A very mature company would look at that and say, Okay, on a 1 to 10 scale or 1 to 5 scale, whatever it happens to be, how do you rate this candidate? And you should. I think that's just the only way to do it. I've worked in many organizations as well where they focus on different areas. So you might have one interview that's focused on overcoming adversity, and there are questions around that; there's another one that's talking about how to navigate stakeholder conversations. But again you're leaving one individual to ask those questions around that topic and to make their assessment of whether Tim can handle adversity. I think he can be okay, great, but maybe five other people would say, Actually, no, Tim cannot, but it's, again, it's very suggestive of the flip side of it, and I'm speaking a lot here. You do these panel interviews, but then there's also a lot of studies that show that if you put someone in front of five people, it's a very intimidating situation also, or you're really getting the best out of them. and how often would that happen where this candidate talks to five people at once and has to answer questions right? It's not a common occurrence in the business world.

TIM: That must be one of the fundamental flaws with the way hiring is done; the process doesn't really mirror or reflect the job the closest is in. Technical roles are probably that kind of take-home task or project that's normally quite correlated to the real job, especially when it ends with some kind of presentation back to that audience. but even then it's still a little bit contract I feel like interviews are a long way off real work; again, there's that pressure element. There's also just that kind of mask that both sides have on where you're not really being yourself; it's like this weird charade, this act, so I really I am fascinated to see where we'll get to in five, ten, or fifteen years. Is there a way that we could get to someone's true behavior sooner? Because you really only discover it after, like, your first night out together drinking; that's when I noticed a lot of the reality comes in, you know what I mean?

PIER: I think the process is inherently flawed, and definitely in the recruiting process, and I think you touched on it right here with the case study. Again, five years ago there weren't many case studies that were being sent out, and then all of a sudden now there's a huge phase where everybody was sending out a case study. The challenge is that they're like, Oh, just send out the case study; it's a low cost to the company. There's no, Oh, the resume seems interesting; let's send a case study. The candidate then spends however many hours, say, four, five, or six hours; some spend 10 or 15 hours preparing for a case study that then gets put through maybe an automated check that fails, and then they're... Or it's a lot of investment of time for something that is not necessarily a commitment on the company side, so I'm also cautious about that, and now with the advent of the invention of AI, you can just upload GPT, ask it to give you the answers, and tweak it a little bit to make it look like it's not AI-driven. And there's your case study, so are you really getting something out of it? A couple of years ago we started doing live coding. Part of that was you spent an hour together, so there's not much more than a one-hour commitment. It was, Here's a task. How would you go? Obviously, it's a little bit more pressure because someone's watching you while you're coding, but try to create an environment where it was more like a collaboration where we're solving a problem together. We're working on it together and really seeing how they ask questions and how they challenge that, but again, every process has pros and cons to both life coding and being very stressful. Some people said it's an anxiety-inducing environment, which I also get; they'd much prefer to work on their own. They do work on their own day to day. How often do you have to work with your manager on your shoulder? so pros and cons, but it's an evolving space for sure. Yeah.

TIM: necessarily one better or worse way to do it often, and I know if I can remember back to the last job I had in an office, if someone came across to my desk and said, Hey, can you just chop this SQL code for me? I think I'd lose the ability to use my fingers; that's how clumsy I'd become. I couldn't do a select star. I don't think with someone staring over my shoulder, that level of pressure would get to me, but then, yeah, as you say, the take-home test is just such a huge time suck. Then how do you compare those results really

PIER: Absolutely, and most people aren't applying to one job anymore. That's the other thing: applying for a job is easier than ever. Most candidates can apply to five to ten jobs in a day, depending on what career level they're at. If you're sending five to ten take-home tests, it's an easy step for the company to weed out who's interested. You've got some candidates who might be spending 40 hours doing 10 take-homes to get no traction; that becomes demoralizing really quickly as well.

TIM: Yep, yeah, it's such a tricky market at the moment, I think, as well, and you touched on candidates using AI sometimes to take those take-home tests. We have certainly seen candidates optimize or create CVs using AI. What about from your end? Have you started to dabble in using any AI on the company or the hiring side, and are there any things you're thinking of using AI for in terms of hiring?

PIER: Not specifically at this stage, I think there are many things that I'd like to see what we can do with it, especially around creating more realistic scenarios in the moment. I think one of the challenges that we have when you are having conversations with somebody, a lot of the time, I'm sure everyone's seen this data set, but there's a New York or New York City bike rental case study that it became like everyone was using it for a while before, you know, you're like, okay, it's the same data everywhere. I think that's the part where I think there'll be some use cases there to create a scenario that no one is familiar with so that you can work truly work together right. I think that's part of the ways to leverage AI to create What would be a similar day-to-day environment within the organization? Versus this, and that's been, I think, a big challenge too if you hear all these candidates that they talk about, Oh, I did this boot camp; I'm now a certified data scientist, and it's a lot of what they experienced in those courses is very good for the fundamentals, but that data is so clean, and they nudge you towards a certain outcome, versus the reality of our day-to-day is that our data is dirty, that this new integration did not work well, that we are solving something for the first time because otherwise it would already be automated and running as a dashboard or a report or a tool. And so how do you use AI to potentially create those situations where it's a similar outcome and then work with the candidate in that moment if we do live coding or so they can't just use AI to cheat if you want to say cheat right from a fairness perspective, but in my opinion, we've also this idea that candidates need to be thinking on the spot off the top of their head, and they can't leverage the internet during an interview process is also antiquated. We live in a world where if I don't know the answer, I google it, and if I don't know the answer, I ask ChatGPT. It's all at the end of the day these are tools that are available to us. Why would I not let a candidate use them for the process of the interview as well?

TIM: Yeah, that's a fair point, and you mentioned cheating and adverted commas. How do you personally view candidates use of AI? Is there anything in the hiring processes that you feel is off-limits that you feel like Oh, I'd rather they not use ChatGPT for X, or do you think it's completely fair game?

PIER: Yeah, to me it's like if you notice it and you can see it when someone's looking at a screen above them or if they're typing the question to see what answer they get back again, it's like you either know it or you don't. and I think that's part of the thing is that let's say I talked to somebody about using a neural network for certain analysis, right, and they go, Yeah, I know what that is, and they read off a pretty scripted answer, then you know that they don't know what that is, right. Or you say, Okay, how would you apply it, and what happens when this happens? Or there's when you're having a conversation with somebody and truly spitballing the problem, then you end up in a position where you'll know if they know it or not. I think that's part of it, so if they want to use chat, I use it too. I use it to get an understanding about certain contacts about a company or thing, or how would I use this, and then how do you then actually implement it based on my knowledge and my skill set? So yeah, I think there should be no limits, and if you create limits, then you create opportunities for cheating and lying. and I think in this case, why would you create that? Of course they're going to use it, so let's just embrace it and figure out how they use it and what they can do with it. No

TIM: Because why would you want to in any way discourage candidates from using a groundbreaking bit of technology that could make them like 10X more efficient on the job? Would it make sense you'd be sending the wrong message? I think I guess it's just because the technology has developed so rapidly that it's broken so many hiring steps that we don't quite know what to do with it now as you said take home tests that can probably get by on that an online test yet the CV now is dust as far as I'm hearing in terms of how relevant or accurate it is and so now we're just struggling to come to terms with how are we actually going to evaluate people how are we going to choose out of these 500 applicants who is the one we need to hire and so I guess companies are just grappling with that let me throw one particular scenario at you which I had recently and I thought Oh I'd rather they not have used Chattopadhyay so it was a part of the application process for some of our sales roles one of the questions we asked them was imagine it's day one for you at a Alooba What are the three things you need from us to give you the best chance of being successful in your role? And so it was a very personal question where I wanted their opinion as an individual. I didn't give a shit what the OM said on that particular day, but so many candidates had clearly just whacked it through ChatGPT and given us the pasted answer, which was just annoying. Because then I didn't have the bit of information that I needed, what about something like that? Are there any bits that you would suggest not using if you were a candidate, let's say?

PIER: Yeah, but so that's a data point for you, right? So that tells you that in the case where they have to think on their own for something that is personal, they're still going to use something that is inherently not personal, although granted now you can make ChatGPT know a lot more about you and can give it a personal spin. But yeah, again, that's a data point for you that tells it to me. Would they look at that and go, Okay, that's a pretty scripted answer; probably not the fit for us ? Is that how they're going to operate here, or are they just nervous or unsure what to put or unsure if they can be their true self or things like that as well? That's the part that you as a hire manager need to evaluate what that looks like for me. I think I always look at this as it's a data point either way, so I don't think there's any You're right that I think anything where it's a personal question of what you enjoy about your job, if they put that through an AI I think then you can see how the answer is formatted, but I'm also cognizant that some people are not great at writing, and so they might just type a bunch of buzzwords or words that are important to them into an AI language LLM. And then get it to rewrite it for them as well, and then it looks a little bit more polished. Which I think is a lot of the use cases that most people use these things for nowadays, right? So cognizant of that, but no, ultimately I think for me the only thing would be Hey, don't use it when it's asking about a personal thing about you when it's talking about your ambitions, your goals, your beliefs, your values, and things like that. Don't just get a generic answer out of it, but if you use it from the perspective of helping me reframe this in a more positive light or helping me use words that will make it more cohesive or things like that, again, that's fine, but for me, I believe no limits are barred, especially around that interview process. I think we get more into trouble when we talk about data privacy if you're ingesting company data into it, but that's a whole different story.

TIM: I think even in that interview process where you mentioned if you had a candidate using it, it becomes fairly obvious, and I would have thought for a candidate it If you actually knew what you were talking about, it would be more difficult to be running ChatGPT and having an interview at the same time. I would find that cognitively very difficult to read the output of AI, put that back into my words, and give an answer rather than just giving the answer, but I wonder if the meta thing here is that if in general in hiring I feel like if companies and candidates could be more brutally honest and transparent earlier on, the better the hiring process would run. I feel like This is another example of that where it's like you can use ChatGPT or Claude or whatever you want. I'm now more interested in the next levels: how you're using it and why you're using it. Let's now investigate your prompts as your prompt code, and you can almost just get past that superficial first layer What do you think?

PIER: Yeah, 100%, but I think that also speaks to the maturity of the people on both sides of that conversation. I think companies feel overwhelmed with the hiring process. You have, like I said, you might have 250 candidates apply for a data analyst role. How am I making the right decision? The cost of making the wrong one is so high. And oftentimes the people who are doing the hiring don't often get to hire very often. It's not like they're professional hirers, especially when we talk about data and analytics individuals. They don't necessarily, most of the time, have the highest caliber soft skills, right? They're technical people for a reason; they went down this path for a reason, so they don't like interviews to begin with, and they definitely don't like running interviews as part of the process. It's a very different vibe; you're asking someone to, in a way, say, Look, let's be real. Let's be honest: we like you; you like us. Let's see how this works together to treat this as a real relationship. No, a lot of the time it's, Let's not show that we're too keen because we don't want them to negotiate with us too hard at the end, and then the candidate goes, Let's not show that I'm too keen because then they'll know that they can have me for free. and then you got this dance that you're doing when in reality it's let's be grownups about this, let's have a conversation, let's see if this is a fit for both sides and truly how we would work from day one, but that takes a maturity both from the candidate from experience and the company as well from their processes. and I don't think we're there yet in many cases

TIM: I feel like now that we've described that the owners should really be on the company to set that tone, especially if we're talking about individual contributor candidates who are maybe in their first, second, or third year, maybe it's a bit of a stretch to expect them to have that level of maturity, but the company should have almost company-quality recruitment even if each hiring manager maybe isn't that experienced.

PIER: Oh, absolutely, I agree with that, and the companies do need to set the tone. I've interviewed at companies where, you know, at my level, most of the interviews are conversations now, right? And rightfully so, like we're talking strategy, we're talking about how we would build teams, and how do we develop people. it's not necessarily Hey, here's how you do a SELECT FROM statement right. I think there are elements now where there's more of that, yeah, but still I've interviewed at some companies where it's incredibly rigid, like we want—they ask a question, we need the answer in this format; this is how we're going to do it. And then you realize that actually if that's the way that you interview, is that the way that you're going to operate as an organization, right? And so I think that's part of it too: is that just the way that they are interviewing because they are then using a scoring template in the background to say, Okay, a four is a four? We know for sure that four is accurate because we followed our strict process, and there's, again, like I said earlier, pros and cons, right? That might be good for them to make an evaluation of me, but then I'm walking away going, Wow, if that's the way that we're going to interact with each other, then I'm not sure if I'm interested. So it's both sides.

TIM: So the hiring process itself is an advertisement or an anti-advertisement, in some cases, for the business and the role and the people involved.

PIER: Yeah, it has to be right. It has to be nowadays as well. Like, it's me. It's a huge red flag when you start jumping jobs too many times in a span. It's now it's not like our parents generation, where they worked at one company for 35 years and retired. Now Yeah, you're jumping around maybe every three, four, or five years max; in Europe, it's more like every two years you have to move to make that career progression, but then you start to get this reputation as a job hopper, so what you try to avoid is making a mistake. I don't want to join an organization to realize in month three that this isn't what I thought I signed up for. and why am I here, or what is this sort of culture that I've signed up for that I don't believe that I'm part of? And then having to switch again costs both sides a lot of money and a lot of time and a lot of energy, so for me, yeah, it's more than ever now; it's a dance on both sides; it's not just, Please hire me. It's now let's see if there's a fit for both of us together to make this work.

TIM: The way you framed it then makes me think that I feel like one of the unlocks in hiring then in the next few years might be the creation of new data sets to make better decisions because at the moment at that initial application stage we have a CV and an application and someone's reviewing that but the CV is just someone's opinion about themselves very subjective it's now apparently even less accurate than it used to be because people are working through check TPT it's now optimized the job so they all look amazing this is what I'm hearing constantly and so from the company side they've got very little to go on at that initial stage and then as you say from the candidate side once they go to hiring process sometimes you're still really none the wiser you've had a bunch of interviews with people who've bombarded you with questions you've maybe had five minutes to ask your own questions but you've really what is this job actually going to be I feel like often people are still signing contracts without truly knowing what's about to happen. I can also think from personal experience of some of the shit shows I've walked into in my earlier careers without maybe knowing what questions to ask, so I wonder if we just need better data and what that data would be. like even hypothetically What would a company love to know about a candidate? What would a candidate love to know about a company if you've got any thoughts?

PIER: I'm trying to think off the top of my head here, but yeah, that would be great. Yeah, again, you hit something right there that's happened to me, right? You join a company like, Yeah, we're using Looker to do this, and we're really established. We've got a modern data stack, blah blah blah, and then you realize, Yeah, okay, you come in, you join, you've got a modern data stack, but you're not leveraging it the right way, and your data is garbage in whatever you're putting in, and you're not really using Looker; you just have it there, but you're not actually using it. So there's always this element of you have to weed out what the truths are and what the stretch truths are. I don't think anyone ever lies in an interview process because it's obvious when you get in, but everyone stretches a little bit in terms of, Yeah, our team is really well-matured. and then you come in, you realize actually the team is quite junior and they don't understand, so I don't know how to solve that. I think that's just a matter of similar to the interview process. What I often advise the people that I coach in this space is if you do get an offer at the end of this process, if you do get an offer, ask for an extra call with the hiring manager to ask them a ton of questions, right? How do you think you will manage me, and how will you do this and show me your tech stack? Because at that point, you've got an offer on the table. It's not you have to do your due diligence, and I think a lot of people don't; they feel Oh, if I don't sign the offer today, they'll renege it from me, and I won't be able to work here when, in reality, I would really appreciate it if a junior analyst came and said, I'd love to sit down with you for an hour and ask you some questions that would, in my mind, be like, wow, this person is really putting a lot of thought into this to make sure this is the right fit. but I think a lot of people are worried that, Oh, that's another touchpoint where I might slip up, and they might realize that they don't like me anymore, and they'll renege my offer, but I think in this space we're also seeing There's a lot more information about every company's tech stack on the internet. You can see a lot of public, a lot of these analysts, and/or some releasing things publicly on whether it's on just Stack Overflow or things like that. You can see some things, but it's never again a truly complete data set.

TIM: That's a great suggestion and shout I hadn't heard before then, so you basically add your own step once you have the contract in your hands because, yeah, then you've got leverage, and hey, they'd be a pretty psychopathic company if they reneged at that point, and surely that would tell you everything you want to know about that company. and you've almost dodged a bullet if they do that right.

PIER: Exactly, exactly, and you're only asking for an hour's time that you're asking for an hour to ask 20 questions and whatever it happens to be. Now, obviously, don't come in and say, What's your promotion process look like? although that might be a fair question, right? But think about it; I think it's a good opportunity to do that and good due diligence on top of that, especially if you haven't had the chance if they're giving you five minutes to ask your questions at the end of every interview most of the time, right? You're not really getting into the depth of it. They've, like you said, interviewed you. Can you flip the script? I think now we're seeing a lot of companies are actually asking the candidate, or it's been happening to me in some instances where they will ask me upfront if I have questions at the start of the interview, and we'll use that first 20 or 30 minutes to go down that path. but again I can't. I don't know if I want to compare where I'm at in my career and say that's a market trend either, so it all really depends on the level of career.

TIM: I wonder if you've heard from your mentees any feedback around When they've done this extra step at the end and had the opportunity to ask the hiring manager questions, I wonder if the kind of truth serum cut comes out then, and I wonder if the hiring manager has become a little bit less on guard and they're just being more honest with the candidate. I'm not sure if you've heard any feedback along those lines.

PIER: I haven't, but in the times that I've done it, I found that I definitely get more because by that point, it's like the I love you has come out or the I like you has come out, so now everyone's a little bit more like, Not as guarded anymore, and so I think there is a little bit more about, Hey, we like you; here's a bunch of information. Let's help you make your decision, so I think it's been positive in the times that I've done it in the past. Again, you don't always get every like you may not get; you can still be lied to in some way, but I think, again, it's an opportunity depending on which questions you ask. If you ask similar questions in different ways, you can get an idea as to what it looks like, but definitely the guards are more down by that point, which is also great. Yeah, it feels like again for companies and candidates it's almost tempting to keep your guard up and play your cards close to your chest, but I feel like that's such a short-run strategy because what could be worse than hiring someone or joining a role and realizing in the first week Oh my God, what mistake have I made here?

TIM: Okay, because that's just going to be if you overpitch a role and oversell it and the candidate comes in, they're going to quit in one week, and as you say, in a market like Germany, that's just you've just lost half a year, so then start the recruitment process again; someone's got a three-month notice period. That's just a disaster, so I feel like surely it's in your best interest, even if it's a bit uncomfortable to do it just to really get the facts away in the interview process itself.

PIER: Yeah, I think that, to me, again, we talked about maturity earlier; ego plays a part. I think a lot of companies are—we have to showcase that we were—we've got it together, that everything is super great here and that they love it, and in reality, I think a lot of candidates, if you came to me and said, Hey Pierre, I have this job for you; you can take over this team, They're fantastic. They're all high performers. Everything's sorted; there are no problems. I'd be like, okay, that's not that. Seems boring; all I can do is wreck it. Is what you're telling me you're already super thrilled with them? What? Why would I join that versus if you come and say, Hey, we've got these problems, and we need to solve for this, and we're missing this, and we have huge gaps, and this is a problem." Okay, now you've got me; now I'm interested. Now I know that's not for everybody, but to me it's okay. Now, as a leader, I can come in and help make something better, help turn it into a high-performing team, help do something not just Hey, be a babysitter and keep this team happy, and I think that's the same case for many analysts. People want to come in and do valuable work that has a high impact that is changing something for the better, and so I think companies need to shy away from this idea of Everything's fantastic; we're fantastic; we love it; we're a family. No, there are challenges. Our data is not good. We have these products that we're building. It is time sensitive. It's very, and then get the candidate that comes in that is excited by that, not just, and I think that's part of it. By being truthful, you're going to also weed out someone who looks like, I don't really want to work in a time-crunched environment. I much prefer when I'm more calm for me. So I'm going to opt out of this process. This is not the role for me, and someone else was like, No, this is for me. I love this. This is where I thrive. Okay, welcome aboard, and then you get the candidate that is going to fit the role of what you need versus this rainbows and unicorns and then everyone's lying to each other.

TIM: I think this is one of the benefits of running a startup because it's such a specific environment that you have to be very honest and transparent from the get-go about the ups and the downs because probably 99 percent of people would hate it, but there's this 1 percent of people who would love it. and for them it's the perfect job, and so if you don't get that clear from the get-go, it's just you're going to have a horrible time; everyone's going to have horrible times: the hiring company, the hiring manager, the candidate if they joined, and oh, there's no documentation. there's no process There's no there's like where's my X Y Z? X Y Z doesn't exist, so you do it.

PIER: And the flip side, the other way, right? Oh, I'd love to join Microsoft; I'd like to join Facebook or Meta and work for them. Okay, great, and then you realize you join, and you're only working on a small subset of a piece of their product that they have, and that's all you can do. but I have an idea for how we integrate with WhatsApp, and they're like, That's not your jurisdiction; stay in your lane; do your thing, and I think that's also the flip side of it: some people love to be able to touch everything and do everything and push their own code to production within 12 minutes. And if that's what you want, don't go join a thousand-person company; don't go join a meta with their checks and balances in place. Imagine going to Commonwealth Bank and telling them that you can change the code in 24 minutes. Like, good luck with that; that's not happening without a formal review process. So I think everything has every job has again, and if you're not honest about that, then you end up with a candidate that joins day one and says, I want to change this, and they say, Did it go through this process? No. Okay, we'll come back to us in six months after we do the next prioritization process. Yeah.

TIM: Inflation then on both sides, like the companies are inherently marketing their role above and beyond what it is, and then the candidates are kind of marketing themselves and bullshitting a bit on the CV. I wonder if then maybe both sides fear that if they were really honest, then people would look at it and go, Oh no, that's not—oh no, your job looks much worse than these other 50 jobs. I'm looking at they're telling me everything's amazing; you're telling me some things are amazing and some things are shit, and so it's almost like we're stuck in this on both sides in economics; you've got like a bad equilibrium of sort of misinformation and almost exaggerations that we need to get out of somehow.

PIER: But you also got that publicly Oh, everyone, every company, especially if you're looking at your competitors, when they put job descriptions up, you're looking at your competitor across the street and saying, Oh wow, they don't have their business together; look at those guys. They're saying that they've got problems with their data quality. Wow, what a mess! I think that's also part of that, right? You're putting a public persona out there of, Yeah, we're hiring for this; we're good as well, so I think that's definitely part of it. The reality is that everyone has data quality issues. Everyone has problems. Everyone has everyone like when you go to these here in Europe, we were really big on these meetups and these roundtables where you sit with eight or 10 other data leaders from the city or the country, and you realize very quickly that everyone has the same problems. Everyone has the same challenges. Everyone's struggling for the same exact things, but we all publicly say we're doing great until we go behind closed doors in a safe environment and then actually realize that not so good here, not so good there.

TIM: I feel like then we need, like, a company therapist or something—someone who's seen behind the curtain and has spoken to people or candidates or companies, and they know the reality, and they just need to say, Hey, come on, seriously, nobody's that perfect, so don't worry about it; just relax; just be honest.

PIER: Yeah, but I think also on the candidate side, right, the market is so competitive that if I'm not this ideal, perfect candidate, I don't get this job. I think that's It's the same. You go back to the university application process, right? Are you doing it? Do you have a—I can't remember this scoring system in Australia, but in Canada it's do you have a 98 percent average? Did you also do 17 extracurricular activities? Are you volunteering in six countries? If you're not doing that, then don't call us, and I think part of the jobs here too is Oh, do you have all of these? This master's degree: Do you have 15 years of experience in some language that was invented 10 years ago? like it's almost impossible to meet the requirements, but people, as a result, will stretch the truth and expand their… they do so, yeah, it's a dance; it's a nice little relationship dance at the start.

TIM: And it feels like we're in this weird scenario where, from what I'm hearing, companies are getting inundated with all these CVS candidates seeing each job ad on LinkedIn and going, Oh wow, there's already been a thousand applicants in two days. Are you kidding me? I thought I had to apply to 10 jobs, and now I feel like I have to apply to a hundred to give myself a chance of getting a job because my conversion rate, my odds of getting the job, have just gone down. which is then causing everyone to apply for more and we're in this kind of weird vicious loop thing, and I'm hearing that a lot of companies are saying I have too many good candidates on paper based on their CV So many of them seem like a good match, but then they're getting the candidates into interviews, and they're finding out that it's not as good as it seems on paper. It seems like that process is broken. Are there some other tools? some of the data sets some of the way that you think we could be doing screening in those early stages to decide who to interview that could be better than just a CV and an application

PIER: I think there are elements where we could get the candidate, especially nowadays if you think about how easy it is to record yourself doing speaking or doing something, right? There's an element where you could do something like, Here's a question; answer this question and record yourself on the screen. I went through this process earlier in the year where they basically gave me a question that I had to answer in less than three minutes, and I could try to record myself three times. It's a platform that they built themselves, obviously, or a tool maybe they're using in the market. And yeah, the first time you go to answer this question, you make a mistake, and you flub, and then you start over again, but by the third time, you've got your answer down pat. You also had something like 10 minutes to record yourself once you hit that window, so you could still do a little research if you wanted to. You still had a little bit of time to get your thoughts down on paper and do it, but I think there's an element there where, for example, that three minutes is a much faster way of scanning through maybe, say, 10 to 15 candidates as a hiring manager instead of having to schedule 10 to 15 30 to 45 minute interviews. If you consider the 15 minutes before and the 15 minutes after, now everyone's wasted an hour of their time when in reality you could easily weed out that candidate and say, Look, that resume looks great, but the way that they communicate, they would be and it's really easy for a recruiter to just say, I don't see a fit for us, or The way that they thought about the problem is not at the level that we expect, or whatever it happens to be. You at least get a little bit more insight and a small window that might help you make the next decision and say, Look, I'm unsure about this candidate, but I saw enough potential. Let's move them to the next stage. There's also that, so I think we can start to leverage some of the things that we have at our disposal that aren't just CV interviews and job offers. There could be some things in between that will reduce the time on both sides but still create an opportunity, and I'll just say your point is valid. We're seeing when we put a job application up, I'm seeing about 150-200 applications. Once you started scanning through it, there are about 60 or 70 that you're like, Wow, these are fantastic; they look really good, and then you realize very quickly that out of those 70, you might have five that actually are able to communicate or think or logic the right way or even understand the business. the amount of candidates I don't even spend five minutes researching what we do as a company, like little things like that, but by that point, I've invested 15 or 20 hours of my time interviewing candidates to realize that I have maybe two or three that are good. Could I not have gotten to the two or three earlier on and then spent more time with them to figure out which of the two or three is actually a better fit for us and a better fit for them? I would rather do that time than spend 20 hours on people that I'm never going to talk to again.

TIM: Yeah, I think anytime the market's balanced this way, which is very much in the favor of employers, normally the screening step becomes a little bit more aggressive, like a little bit more effort for candidates, and see if that ends up being a video, a one-way video interview, some kind of AI interview, a test, something like that. I'm sure companies will have to use cause; otherwise, you'll end up interviewing way too many candidates because the CV ultimately just doesn't predict performance that well.

PIER: An AI interview would be quite interesting, and I think we're close to that. I think the AI interview would be pretty interesting.

TIM: Yeah, yeah, the products are definitely emerging, and I think GPT Colloids are at a state where their ability to interpret answers and do grading and those kinds of things is pretty close to there, and in this kind of use case you're talking about, it might be a no-brainer because it's not like instead of doing all human interviews, it's just this in-between step where you're trying to get from X hundred applications to the higher touch higher costs, higher value, higher signal interview with a human, so yeah, maybe it's that intermediate screening layer I suspect that will be the norm in the next year or so, probably. One thing I'd love to chat with you about is your career coaching, and in particular, I'd love to get your thoughts on what the biggest gap is that strong technical data candidates have to develop or overcome to get to that data leadership role and how you help some of them bridge that gap.

PIER: I know, thanks for asking about that. I think that's so the area that I focused on is helping data and analytics leaders create or develop that soft skill to take them to the next stage of their career. I identified I was thinking about this a lot a few years ago, and I started to figure out that there was a pattern that we're now seeing largely for the first time. In this space, people who had graduated with Masters of Data Sciences or Bachelors of it used to be, yeah, you had software engineers, and they were buried in the back room working on the, and no one talked to them, and no one saw them, and they ran the back end right, and now The expectation, especially in data and analytics, is that you're not only able to understand what the business is doing in the context of the business but you're also able to be technical and to actually build your own data products and pieces like that. So what I've seen is we have these really incredibly smart individuals who do a great job of being individual contributors, and yet they aren't mature enough yet. Some are like Facebook and Google and the big tech companies that have a high-level individual contributor that really can showcase the value that they drive. Most companies don't have that, so you get to a place in your career where it's like, You have plateaued, or, Would you like to become the team leader? Most say, I think it's only natural that I become the team leader; that's what history has shown that we want to become a leader; we get more money, etc. But then we give them the team leadership, and we say good luck, and the example that I attribute is imagining having a Michelin star chef and then it's saying Hey, yeah, you've been a chef for a while. You want to make more money; it's time for you to run the restaurant. You can now be the manager of the restaurant. The chef who's used to making fantastic food is now expected to be in charge of payroll and staffing and sourcing new glasses and plates and doing the marketing. That's not a skill set they've ever done before, so why would we expect that they would be magically successful? because they're a Michelin-rated star, a Michelin-rated chef, and so I think that's the same approach here, and so for me, my coaching business helps those new leaders or people that want to transition into leadership to understand those soft skills and things like how do you create effective storytelling. How do you think about building a strategic plan? How do you engage stakeholders at different levels? How do you manage your own boss in an environment where you're no longer just showing Hey, here's my code and how good it is now you're thinking. How do I manage my boss to help them unlock things for me? And those are just skills that they don't learn as an individual contributor, and so for me, that's where I believe the gap is in this industry: helping develop those softer skills, but I think more along the lines of just effective management and leadership.

TIM: Yeah, if I think back even to my own career, I just fell into data and fell into data management. and then was just doing it, and obviously I wouldn't know what I didn't know, so I was probably making a lot of mistakes along the way, yeah, without any real guidance at all, just floundering around and figuring out as I went along. But yeah, surely there's a more efficient, more effective way to do it if you had a little bit of an understanding that, okay, you're going from, I don't know, senior data analysts to head of data analytics or something; here's your current skill set that has served you well; here's a myriad of new skills that you're going to need, maybe half of which you don't have at all. So, like, how can we help you then get to that next stage and in filling in those skills gaps, because a lot of them are not technical or largely not technical? How do your mentees, how do your clients fill in those gaps? Is that like through networking? Is it like, Yeah, how do you help them navigate those gaps?

PIER: Yeah, the big part is having a lot of it is having a buddy that you can talk to, so part of what I offer from coaching is I've been at this for 18 years. I've been a leader now for over 12 of that space, I think, so for me it's about a lot of the times they know the answer. They just need someone to bounce the idea off that isn't their peer. Most people don't want to go to their boss and say, I don't know how to, and they don't go to their peers because their peers don't really understand what we do, so it's a completely different kind of sector, especially in a company where you may not have four or five data leaders; you might be the only data leader. So for me, it's about using coaching frameworks to ask questions so that they can come up with the answers themselves, giving them some tips and insights from my own career. Again, I'm not saying that what I do is right, but I'm helping them navigate that and think about it from a different perspective. The ones that often seek coaching or seek mentorship are often the ones that have growth mindsets, and they're already thinking about it. They just need someone to validate that with and to put that into play with soft skills, especially since you need a lot of repetitions, so a lot of the things that I do with my clients is look Here's a framework. Here's how you might apply it. Go test it out. See how it feels. You may like it; you may not like it. And then come back, and let's talk about how it went and what went well and what didn't go so well so that we can tweak it because every company has its own quirks and nuances. There's no one size fits all. Otherwise, we'd all read a book, and we'd be expert managers. I think part of it is giving them the framework so that they can navigate different ambiguous challenges as they face them.

TIM: Pierre, as one final question I'm wondering if you could ask our next guest one question. What question would that be?

PIER: To me, the question would be, It's very similar to what we talked about today. It's like, how do you know you've got the right candidate? Like, how do you know? And I think even I, every time I meet someone like, I had it; they're great, and yeah, most of the time they are, but I don't know. And so I'm always curious as to how others are finding how to staff it and grow and develop, so for me that'd be my question: How do you know you've got the right fit for you? I think that that's what I would love to see.

TIM: Pierre It's been a great conversation, wide-ranging, very interesting, and thank you so much for joining us on the show.

PIER: Thanks, Tim. I really appreciate it.