Episode 128

Praveen Ananth on Mastering Mindful Decisions through Data in the Hiring Process

TIM: We are live on the Objective Hiring Show today. We're joined by Praveen. Praveen, welcome to the show. Thank you so much for joining us.

PRAVEEN: Thank you, Tim. Thanks for having me.

TIM: It is our pleasure to have you on the show today. We chatted a few weeks ago and. I immediately found you quite an interesting character, so I'm really keen to have this discussion today. And I'd love to start, or I start with all the guests, is just to hear a little bit more about yourself, because I think it helps our audience to understand who they're listening to today.

PRAVEEN: Sure. Thanks, Tim. So a little bit about myself. I'm originally from India. I spent half my life in the States and parts of Europe. From an education standpoint, I am both an engineer and an applied mathematician. With some courses in management as well, and from a professional standpoint, I think most of my 20 years in the professional arena have been in and around data. That means that I started my career writing probabilistic and deterministic models in the financial services industry. Then I moved along, went into fintech, and then From that point in time, I started venturing out to do things. In and adjacent to data. What that means is not only data science or advanced analytics and what you have in data, but also things such as project management, program management, managing data partnerships, and setting up new revenue streams. So a few different things, and these different things were, some might say, slightly not normal or slightly abnormal to a typical data expert. That said, I think that's enriched me in the form of understanding things from a more strategic perspective or the business dynamics of things programmatically trying to manage and orchestrate several factors that come in when we talk about data products and so on and so forth. Spend some time in finance as well. So understanding PNLs and opexes and balance sheets and so on and so forth, but all of those enrich me. The price of it would be that because I didn't mention that we'd not be doing justice to it. I think the price of it is, being a little removed from the, how should I say it, top of mind for a data professional would be things such as the metrics and how things work in terms of the various models, and so on and so forth. So for me, while it's there, it's a little bit in the back of my head. It's there somewhere; it takes a little bit of time to come about, but it's there somewhere. That's the price that one pays, right? When you start diversifying and doing different things adjacent to

TIM: As you say, you've been enriched by all these experiences, and I guess also enriched by the fact you've lived in so many different places in the world, and I wonder how that has helped you, how it's framed your view of the world.

PRAVEEN: Good question, Tim. I think for me, life gave me opportunities to live and work in different parts of the world, especially a company like eBay, PayPal. Back then, eBay and PayPal were together. So the eBay conglomerate helped me to not only be geographically diverse but also be different and be diverse in terms of the business units and the type of functions that we work in. What I mean by that is, for example, I've lived in the U.S. in different parts of the U.S. I've lived in Switzerland for a little bit. I've lived in the Netherlands for the last several years, and I'm originally from India. So on the one side, there is a lot of cultural diversity that's baked into me, if you will. And in terms of functions that I was talking about, it goes back to my earlier response about doing things that are within the sphere of data as we know it today, as well as adjacent functions like finance, FP&A, some amount of accounting, balance sheet reviews, and so on and so forth.

TIM: And one string to your bow, if we can call it that, is that you teach and practice yoga and meditation. And I'd love to somehow draw a connection between, yeah, learning that kind of mindfulness and your work and career and how it's helped you in your work. And if we could somehow connect it to hiring, that would also be interesting.

PRAVEEN: Sure, Tim. The short answer is it's a journey. I haven't reached the destination yet. It's a journey, and mindfulness is about every moment, right? And being human, we still are subject to things such as anxiety and stresses and ups and downs in terms of emotional waves or emotions, if you will. That said, I think practices that are in yoga and meditation, as well as in things such as Zen and other mindfulness practices, I think simply put, are about being aware. Be aware every single moment you try to be aware of every single moment of your thoughts, words, and actions. I think that's the simplest thing: being aware every moment of your thoughts, words, and actions now. Easier said than done. It's a constant practice, which is why you have mindfulness meditations. You have mindfulness walking; you have so many different practices that try to inculcate mindfulness into our daily lives. How does that help me on my career front? I think of a couple of things, and I don't think I'll be able to list them exhaustively. One of them is like we talked about mindfulness. Am I giving myself adequate distance between whatever stimuli there are and the reaction that I'm making or the response that I have to any particular stimuli? And I, by stimuli, people saying something or doing something or a situation going awry or a situation going that's unplanned or unforeseen, right? That is again a constant process. It's a journey, not a destination. But from that comes the ability to be more empathetic. And I don't claim that I've been empathetic all the time, every day in and day out. But it does help. Empathetic or having compassion for somebody else is Somebody is having a bad day. So they're going to react differently. It doesn't mean that we have to have a squabble as a result of that. So those are a couple of examples, or a couple of ways in which mindfulness, or the practices of yoga and meditation that I do on a daily basis, really helps.

TIM: I guess when it comes to then interviewing candidates, so you're saying, let's focus on being in the moment and really being present and being aware of ourselves. And then the empathy as well for the candidate; getting a job is a very stressful thing. Interviewing is incredibly stressful. And so maybe that mindful state. Could it also almost be passed on to the candidates? I know I've heard of some people when they're saying the first job is to make the candidate feel relaxed. So you have to feel relaxed. And I wonder if that's part of the trick.

PRAVEEN: Yes, I think you've said it really well. In any interaction. And in this case, an interview is a lot more stressful for one side than the other, right? So any person being interviewed, the candidate is going to have the need to be put at ease by himself or herself or by the person who's interviewing them, simply because they're anxious or they're tense. So they're on the edge of their seat, whatever you have it. Now empathy, how that helps is trying to break the ice in such a way that you make the candidate feel more comfortable. You make the candidate be able to access their own thoughts and their memories, right? Why I'm saying that about access is when we get stressed. Anxious, so on and so forth, we tend to lose our awareness or being in the moment, as a result of which things that we know very well over a long period of time also sometimes escape us, right? That immediate recall, that access to memory, is affected because we have these fleeting emotions or shortness of breath as a result of being stressed out. Now that's from an interviewer's standpoint, right? Sometimes, from the candidate's standpoint, my apologies, but sometimes the interviewer is also stressed or nervous or something because they've had a busy day or they've had less time to prepare or Whatever you have, a lot of people say break the ice really well when there is winter view. And there is very good reason for it, so that that conversation flows very easily, that conversation is productive, and the right questions have the right responses, or the best responses that the candidate can give, given where she or he is in their career.

TIM: And if I think back to my own career, particularly my early career, the first jobs I was going for as a graduate way back were investment banking and management consulting, notoriously difficult and competitive industries to get into. Now, back then, I wouldn't say top of mind for them was making the candidate feel relaxed. If anything, it was deliberately being obnoxious and having a stress interview to try to freak you out and see how well you could maintain composure under stress. And I guess maybe their theory was it was correlated to what you need to do on the job. If you're there in front of the CEO of a hundred billion-dollar company and you need to do some quick mental math in your head, you have to do it. You can't just melt away. So maybe there's some kind of method to the madness, but yeah, could you see any reason to advocate for deliberately stressing out the candidates?

PRAVEEN: I think more than the stressor, or the trigger for stress, what I've been trying to articulate here is how we deal with stress, right? We rarely have control over the trigger or the stressor. What we do have control over is how we respond to it. That's why putting a certain amount of distance in real time between the action or whatever you have, the stress or the trigger, and one's response is super important. What does that mean? That means taking a deep breath. Pausing to think about something before you're trying to respond to it, or just stepping back from this driver's seat and saying, Hey, you know what, Tim's having a rough day. So this is what it is, or you know what, Tim is being extra obnoxious today during this interview so that you know he can push my buttons. So it's okay. I can see it happening, and I'm going to take a little bit of a gap and try to respond to this in a more poised fashion.

TIM: And because this is a learning thing for myself at the moment as well, in general. So I'm trying to understand better people who are probably further along the journey than I am when it comes to this kind of thing. So part of the trick is to, in the moment, realize what's happening. And some are almost snapped out. So you're looking at yourself externally, and you are detached from it in some sense; is that part of it?

PRAVEEN: Yes, that is part of it. I think you've put it very succinctly, Tim. Yes, it is part of it. I have two points to say about that one: the reason a lot of masters are much more advanced for this, or yoga masters say that it is important that you meditate early in the morning as soon as you wake up, or as soon as you're done with your morning routine, is so that we inculcate or develop the habit of being calm and poised so that during the rest of the day we are able to stay that way, poised and calm. That's the first thing that I wanted to mention. The second thing I want to mention is there are different techniques for someone to extract themselves from the driver's seat so that they give themselves a gap. And you've seen a lot of people do this. Some people actually put their hands together and rub their fingertips. Some people have a rubber band around their wrist, and they're doing something, right? The applications of it are different. But in essence, what it's trying to do is it's trying to give you. That obviously the rubber band trick is not to inflict pain onto yourself, but it's just basically to stay aware and say, Okay, fine, this is happening. Let me take a little bit of a gap and respond to it.

TIM: Oh, that's a really interesting, like, mental trigger mnemonic where you can snap yourself out of it in a way. That's really cool. I hadn't heard of that before. I'll have to get myself a rubber band, and maybe if it somehow had some personal meaning to me, maybe that would then resonate better. But that's, I don't know. The name of someone, a loved one or something like that, maybe then that would add an extra layer. I don't know.

PRAVEEN: Yeah. There are so many other things, right? You have the stress ball, for example; you have a couple of magnets that you find people are flicking through your fingers or pens being twirled, right? That's basically it. Yeah, you might think they're distracting themselves, but with the proper intent, it's not a distraction. It's actually getting yourself to be more aware.

TIM: Yes. Okay. And stick with the kind of theme of interviews. Okay. So we've spoken about making sure we have a nice, relaxed environment. Candidates relax so they can access what's really in their brain, and they're not having a freak-out. That's essential. What about, how do you think about, so actually let me share a page from a book of a previous guest of ours. Because this explains better what I'm trying to say. So there's a book called Humanizing Data Strategy by Tiankai Feng. And on page 16, he has this spectrum. experience-based things. So there's no data. It's more like intuition and gut feel on the other side of the spectrum; he has data-driven. And I often think of the spectrum when it comes to hiring and interviewing. Where do you fit? Like when you do your interviews, are you doing a structured thing where it's measured as much as you can, or is there some kind of intuitive element, and how do you think about this process?

PRAVEEN: Let's map it to the two hemispheres of our brain. Okay. All of us have different levels to which we lean on one hemisphere of the brain. So we have the right hemisphere and the left hemisphere. And the right hemisphere deals with more of the left side of the body and the left on the right side of the body. So the left hemisphere, as we notice, has a lot more to do with logic and structure. So on and so forth. Whereas the right hemisphere, which is the left side of the body, the right hemisphere deals with a lot of the intuition and artistic, creative aspects of it. Now, as a result of our education, as a result of our conditioning, and so on and so forth, we tend to access one hemisphere more than the other, okay? And that's just natural. Some of us are more left- and some of us are more right-sided-brained from a brain perspective. It's, from my perspective, I think, depending on a couple of factors. So let me talk about first being a candidate for an interview and then as an interviewer as a hiring manager. So you get both sides of the equation right now as a candidate for an interview. I tend to try to stay calm and answer the questions mostly from a logical, rational perspective because I assume that the other person is having a structured thought process and has certain questions, and they have certain reasons for certain questions, so I'm trying to answer those questions in a logical and cogent manner. However, I am trying to access the creative aspects in my brain and the memory aspects, right? So sometimes it works flawlessly, and sometimes there are things where I might forget something because it's not on my mind, or I might misspeak something right because of the switching back and forth. That's just the way it works for me. Okay, when I am the hiring manager, then I try to come in a lot more from the creative side and the intuitive side because even though I prepared, I've read the candidate's profile, I understand their background to a certain extent, I understand what the job description is, and I understand what the requirements are. I'd like to get a good sense of how well this person will fit into the team or collaborate with the rest of the people, right? And collaboration is a lot more on the creative and intuitive side than it is on the logical side the way I see it. It's a mix. What I'm trying to say is, as a candidate, I try to be more logical and rational so I'm able to communicate with the other person. And as an interviewer, as a hiring manager, I try to be a little bit more on the intuitive side so that I am able to grasp what they're telling me logically and not stop at that but also try to sense, is this person nervous? Does this person actually know it and have forgotten it? Or does this person not know it and how well the person can fit into it? So it's a mix, and it comes with practice over a period of time.

TIM: Yes. And so there's a sense of that sort of intuition bit almost being more like experience anyway, because you must have interviewed hundreds and hundreds of candidates over the years for many different roles. And is there a structured element? Do you end up having a scorecard for candidates? Are you trying to grade them across different soft skills, hard skills, and values? Does it? Do you get a number at the end of the day or something else? Or what would you recommend?

PRAVEEN: It's a mix of both. And as a hiring manager, what I tend to do is give three to five maximum numbers of skills that we want to rate someone. Okay. Three to five max. It's a mixture of numbers as well as commentary on the person, right? Why this? Because as humans, we get a lot of information when we interact with somebody else, and putting that down as a number doesn't do justice to it because there are certain comments or certain, there is a certain commentary that goes along with someone's story or someone's thought process and so on, so forth. Long story short, there are three to five dimensions, which you can partly fill in by numbers, but also. With the commentary saying why or why not, or hey, you know This person's better suited for another role within the team or whatever. You may have it. The last thing I want to say is that as much as we, as much as many people, would like things to be black and white, Things aren't right, and if we are going to navigate the gray areas We do need to give ourselves room to be able to navigate set gray areas.

TIM: Do you think there's an so ? I'll, I think that the gray, the grayness could be faded away and be. More black and white if we measured more things well, and that part of the solution to the grayness is just better measurement of stuff so that, if you get to the end of an interview and you still have some kind of gut feel about the candidate one way or another, if you just meditated on and spoke through what you're thinking, probably you could come up with some kind of objective criteria. You could go back and measure them along.

PRAVEEN: That's true.

TIM: Am I onto something, or is there still just going to be this inherent element that is there?

PRAVEEN: Now that I agree with you, Tim, I think there's quite a bit of that gray area that we can try and rationalize and quantify. But there, in my experience, there is still some gray area that will be left at the end. We can reduce it, but we cannot make it go away. That's just the way we are. That's just the way we design. That's just the way, for example, the best example I can give you is ultimately when it comes down to making a hiring decision. And what I've seen is most hiring managers tend to make an intuitive call about a candidate as compared to others, right? It goes beyond looking at the CVs and knowing what they are and rating them and scoring them, if you will. But ultimately it comes down to, I feel this person will be better. Benefit from this.

TIM: And I myself have even done that. And I run a podcast called the Objective Firing Show and a skills assessment platform. So I would be like anyone else. I sometimes think I should be safe from myself, though. And that, my, my weakness is just to hire people that I like. I'm like, I really got along with this person. I can tell you if I ever have a candidate in the first five minutes, we're chatting about football. All right. And they're really passionate about football. We're talking about the Champions League this morning or something straight away. They're already three levels above anyone else. And I have to offset my known bias in that case to come back to rationality. But I wonder if there are other things I'm not even thinking about that I'm unaware of that lead me down the wrong path. Potentially. What do you think?

PRAVEEN: Yeah. There is this framework, and I forget who came up with the framework, but it breaks down biases into conscious bias and unconscious bias, and it gives us tools to be able to overcome them. Again, I'm not professing that by doing this, we'd be totally bias-free. We try to reduce the amount of bias in our decision-making and in our navigating our day-to-day life. We try to do so that it's more rational or it doesn't make sense, or it feels right. But all those answers come with certain bias. We try to minimize it, which is why I go back to saying, Okay, let's look at that conscious bias around conscious bias and make sure we can. correct for it to a certain extent. And there's the skill part, right? But there's also the will part. The real part of it is, am I okay just making decisions and not being conscious that I have a bias to begin with? Or am I willing to look at things differently? And with that, I can address one other thing: you made a nice point; you said you'd like to hire someone who's very much like you, and that's fine. Two pieces of response All five fingers of our palm aren't the same, and there is a reason for that. There is a utility. Okay, that's just a simple and anecdotal, funny, semi-funny kind of response to it. But the other thing is, when there are different approaches to solving a problem applied by different people on the team, right? Then the probability of finding a solution is higher than if everyone thinks the same way of solving said problem.

TIM: Yes, and I heard another guest describe this to me. That his view was that, okay, you have this kind of diversity of thought and mindset. Your odds of getting to the right destination are improved, even though it may take a little bit longer. Because inherently there's going to be more debate, a bit of back and forth, as opposed to just having this myopic view where you might just go fly straight to the mountain.

PRAVEEN: Exactly.

TIM: In interviews we've talked about the kind of structured unstructured approaches. One thing I always found difficult as an interviewer was trying to focus on what the candidate was saying, figuring out what I was going to ask them, taking notes on what they'd said, and also starting to almost make a decision in my head, score them, etc. Like, it's a cognitively complex thing to be an interviewer, an interviewee, I think. But there are now AI note-taking apps that get used for all sorts of meetings. That I think personally is a no-brainer in interviews because it could at least park one of those things off to the AI to do the summary, to do the transcription, to go, Yeah, the candidate did say that, to be a better memory than what we ever would be. Have you used any kind of tool like that in interviews yet? Do you think they should be used?

PRAVEEN: No, I haven't used a transcription feature or a feature that'll allow me to offload some of the activity. Then I see where you're going with this. And I understand how some of it can be offloaded, but short answer, I have not used it. Now, if I were to respond to, does it make sense? And do you think it is of use for us in this process? I think so. I think so, because then it allows the hiring manager to actually focus more on the response and how the person is conducting themselves and if the person is having a challenge in trying to say, for example, remembering something right from the past or trying to connect the dots and really trying to understand what question was asked. So then it's a more active and engaging conversation rather than You ask me a question, Tim, and I'm responding, and you're making notes frantically. And you're missing out on a simple thing like me smiling at you, or me telling you a joke, or whatever you have it, right? So yes, there is a balance that we need to strike. We can use it. There needs to be a balance. And that means that the hiring manager has the responsibility of being prepared before going in and knowing what rules and what value come out of it. Bottom line, ultimately, the hiring manager and the stakeholders, or whoever is on the panel, get to make that decision. The question is, are they being equipped well enough to take that decision effectively? That's the maximum value of that.

TIM: I am guessing that these interviews will be recorded and will be transcribed, and that will become a normal thing pretty soon, I think. And I think they'll just be like AI just edging into the hiring process gradually. Because once it's in there in the interview and it's done the recording and it's done the transcription, surely the next step is, Oh, here's the scorecard for the interview. How did you think the candidate went across these dimensions? I personally think there's a huge upside. Because of the things we're talking about, which is the bias, which is even, how many times would you have had an interview with two interviewers, and you go away and do, if people do this, do like your own separate scorecard, and then you come back, you're like, Oh, wow, you gave them a three out of 10, I gave them an eight out of 10, like, why? And so maybe it's even an extra opinion from the AI, superhuman, amazing, super being that might be helpful to the equation. What do you think?

PRAVEEN: Yeah, I think so. I think at the very least I agree with you, Tim. The very basic thing, any AI model or machine learning model, if you will, is trained over a period of time, right? It's trained on the various data sets, and how will you cut it? Now it can be a supervised learning model. It can be an unsupervised learning model. Whatever, but it needs to be trained. Now that model, as it gets more and more trained, gets more and more intelligent, right? And that's what AI is going through. Many of us have used a large language model and had chats with it and said, Okay, fine. I've already given you this information. Why didn't you access that? And answer this new query that I have. Some of it is designed to learn automatically. Why I'm saying that now is that model, once it creeps in more and more to the hiring process. It is going to be more effective and intelligent to help in that position, making it also going to get biases. This is just a normal process. Ultimately, the AI models are being written by humans, and we tend to pass on our rationality or the way we rationalize things to it. As long as we're able to correct for that and clearly define what kind of inputs we expect from the model, how much of the nuances that the model has. We are able to live with and what kind of recommendation we are going to leverage from the model. It's okay. Ultimately. It's a tool, right? We're using the tool to best help us resolve a question. So we need to know clearly what the limitations of it are and what value comes out of it. I think with that we can really improve the way we hire or at least interview and make a decision. The actual hiring process, I think, the pre-interview, all that selection, we can talk about in a second.

TIM: Yes, indeed we can. And I've spoken to a lot of people about the screening step because that's where the highest volume is; this is where the companies are getting hundreds or even thousands of applicants. I personally feel like if we can improve the accuracy of that step by even a bit, that's going to have such a big impact. If we can reduce bias there even a little bit, that's going to have a big impact. And I have spoken to a few companies that have started using some kind of LLM pipeline they've built to then do some kind of resume grading and matching. Only a couple, like it doesn't seem widespread at all yet. Have you tried to dabble with any of these tools yourself? And where do you think that kind of screening step is going with AI?

PRAVEEN: Sure. Any ATS is a very rudimentary form of an AI. Very rudimentary. Because it's trying to read, it's a machine learning. It's a, how shall I put it, in a very simplistic format. It reads the text from the CVs that go in and tries to put it into different categories in terms of work X and skills and so on and so forth, right? So it then tries to classify that and then tries to cluster the candidates into ones that are more qualified for this job or less qualified for this job or some in between, right? So any ATS is a very rudimentary form of such a model. It has its limitations, and we all know that. But it is set up to help the job of a recruiter as well as a hiring manager, right? So it's a tool that is set up to help them, but it has its limitations. So if you take one step further, you take one step back; the roles need to be defined very clearly by the hiring manager. And the recruiter and they both should really understand what is needed in order for anyone to be successful in the role as an individual contributor or as a team lead or a functional lead and so on and so forth, right? I'll be really clear as to what the requirements are. There is no such thing as a perfect candidate. Okay. And making sure we really understand that a candidate who is able to do the job to a certain extent, as they hit the ground running, and then that candidate should be able to evolve as the needs of that job evolve because no job is static. Okay, the job, the company's challenges, the questions that are being asked, or the problems that are being tried to be solved. They're all evolving. So the dynamic. So there is a part of it where you look at the history of the candidate and say for this role, do they fit into X percentage and obviously in the majority side, right? And then there is another part, which is how much of a growth mindset do they have, or how quickly are they able to learn, and how well do they collaborate with other people or different functions, and so on. So whatever you have, it is right, depending on the role. I think once we have a clear idea of that, and not fully and not always lean on, say, the technical aspects only for any role, then we as a hiring manager and a recruiter have a good idea, and our success rate is going to be better because now we have an adaptable process. The AI then can really help us do that process a lot more effectively and efficiently. I'll tell you why in a very short form, right? You find a lot of roles out there, and hundreds and thousands of people apply for them, but in any market for a particular role, you might not have that many qualified candidates. So how can we reduce that? Obviously with an AI tool. Obviously, we're trying to say, are we clear with the requirements and have we articulated that clearly to the job board or LinkedIn or wherever you have it? And thirdly, the duration for which that posting is there, right? So if you want to make a decision, let's not have it for three months. Let's not have the posting out there for three months. Let's talk about more in terms of a turnaround time of one week or two weeks, right? You have that posting out there for a week or two. Mention clearly on the posting that the deadline date is by this, and then you can run the process a lot more orchestrated. Not a lot well-orchestrated, right? A lot better, if you will. There's a fourth point to that. I want to make a mention because if I don't, we'd not be doing justice to it. Of late, there have been a lot of fake job postings on various job boards, right? For various reasons. There is, there is, fraudulent activity behind it. Some of that fraudulent activity is people who are building ghost databases of candidates in any market. Without getting into the ethical debate of it right now, Tim, I wanted to make mention of this thing happening because you find a lot of rules that are sitting around, you find hundreds and thousands, sometimes candidates applying to set rules, and it's time and effort. And when it, when the process is not run properly, then not only is the candidate's time being wasted, but the hiring team's time is also wasted. And ultimately, the brand value of the organization is being affected. Okay. And from that fourth point I made about these fake postings being around, it is muddying the waters. It is making this hiring process and job search process even more of a pain than it already is.

TIM: This is definitely something we should get into a bit more detail on because, yes, it's not a candidate-friendly market, and we should help them in any way we can. So you're saying that there's a spike in fake jobs driven by what, like some kind of recruitment startups trying to build up this model of candidates? Build up their own unique data sets, or is it more traditional companies that have just got fake jobs because they're pipelining for future roles or what? What have you heard and seen?

PRAVEEN: What I've fact-based on what I've heard and read about this, heard in the sense of reading about it. It's a mix of those two and a third thing. Yes, you have large companies who want to build a pipeline. And they may or may not have that job sanctioned by the finance teams or whatever you have, and then you have these recruiting agencies or recruiting teams or recruiting startups who want to build this pipeline of potential candidates, because as soon as a thing pops up. And I'm not going to get into the ethics of it. That's a much longer conversation. What I'm saying is that's happening. That's the second thing. And the third thing is there are a lot of scams that are happening where people are being approached by people who call themselves recruiters and try to get personal information, bank information, and so on and so forth, right? Yeah, we might think, why would you do that? Why would you give that when there are people who are? Who are struggling, who are in dire need, and who think that by doing that it gets them ahead in the job market? And it's that piece that's being What's the word? I'm looking for the right word. That's the piece that's being preyed upon by many scamsters, right? Fraudsters, if you will. So there are three aspects there.

TIM: For that last category, these people are scoundrels. That is absolutely shocking, and they should hang their head in shame. I think if that's what's going on Yeah, and I'm not sure how AI can help us solve that. I feel like if anything, AI might enable them to run their scams at a greater scale potentially.

PRAVEEN: I think it can work both ways, Tim. I think an AI tool can really help screen out such fake posts, right? You can put in a certain amount of diligence or rigor into whatever post is being published on whatever website, right? Whatever job board, before it gets published there, there is a certain amount of vetting that needs to be done. Is this legit? Is this coming from a company or person or whatever you have it, right? Or recruiting company, whatever you have it. Certain amount of rigor that needs to be there in that process. I don't think that's there right now. I think the model is more about you can use this job board and pay this much to list these many listings, and then there's the other thing: many people forget to delist it once they've made the decision, and you find roles that are sitting there for three months, six months, and then maybe those roles actually can't get hired. Can't find the right hire. Maybe you shouldn't be hiring for those roles. I don't know.

TIM: Yeah, someone mentioned to me a metric the other day that I would love to have access to, and that is, of all the advertisements that are placed, what proportion of those jobs actually get filled by a person? And we would be horrified at how low it is because you've just laid out three or four permutations of bullshit that happen. But then there's also just the roles that get pulled. Like I even know myself from working in recruitment is you'll get to the 11th hour and suddenly it's no, we don't have the budget for this anymore. Our new plans come out for the quarter. We're cutting this role that happens all the time, which seems bizarre to me that you couldn't forecast a few months into the future to know whether or not you're going to hire someone. And you'd run an entire hiring process with. 10 interviews and eight candidates and the hiring manager and everything. And they go, We're not going to need it. But that seems like you could have avoided that. I reckon

PRAVEEN: It goes back to the fact that the environment is dynamic, right? So approaching it from a very static position in terms of the process, in terms of requirements, is perhaps not the most effective way of resolving it.

TIM: You mentioned previously that for an AI or even without AI and hiring, you really need to think ahead about hiring, what skills you're after, and what you really need. I personally feel like a lot of hiring processes I've seen derail into failure pretty quickly; they have had that lack of forethought. But then you've also said, actually, sometimes it is a bit of a febrile dynamic scenario where you have to adjust on the fly. But yeah, in your experience, like, what should the hiring manager really be thinking about from the get-go? What is, and maybe does anything fall into the category of, oh, you can figure this out on the fly? Like

PRAVEEN: Yeah, I think so. I think and I'm guilty of making this mistake sometimes. Okay. But it's not only about filling an open role. Okay. It's about adding a member to the team. It's about adding a member to the organization, to its culture, to whatever you have it, right? You're adding a person, a candidate, or whatever you call it, a person or an entity, to this already existing entity, team, or organization. Now, you're going to be looking at very clearly what they're going to bring to the job in terms of their technical skills. But also in terms of their other softer skits, whatever you call it, right? Project management, cross-functional collaboration, strategic thinking—whatever you have. Now, are we clear on one? What are the requirements as of now? Today, most hiring managers want to make a hire for a long period of time, right? Someone who is with the organizer for a long period of time. So do we think, or have you done the thinking around how that person—or at least how that role—is going to evolve in the next year or two to the best of our ability, right? Many things that we don't know are based on the fact that there's one that is static, which is as of today, and then the other one is more dynamic, right? So have we done the diligence around clarifying what the role looks like or what the ideal candidate might look like and how well they're going to fit in with the rest of the team? That is super important as a hiring manager. Then that hiring manager needs to communicate that or articulate that clearly to, one, the recruiter and, two, the other people who are going to be involved in that panel of making the decision. I have personally, earlier in my career, made the decision of keeping that all in my head or doing less. Of that diligence and then learning that, you know what, if I really want to make my team more successful and add more value to the organization, I need to do this effort and really hone that or clarify that job description and the way we need to go about the process. Does that answer your question, Tim?

TIM: It certainly does. And you mentioned something I think is really essential there, which is sharing that with other people, because inevitably you're not the only one involved in the process. And I can vividly remember certain hiring processes I was involved with where it was actually a pretty reasonable scope, like we knew what we were looking for candidates getting through stage one, two, and three very well. And then comes Johnny-Come-Lately, a stage four interviewer with their own idea of the role that is completely disconnected from everyone else. And they come in with this bit of feedback or the candidate doesn't have X or they really need Y. And X and Y were never part of the brief to begin with. And so everyone has to be on the same page, don't they?

PRAVEEN: Yeah, Tim. I think many of us have had a similar experience. I'll respond to that with just one thing, right? The way we, the way our critical thinking works, is we tend to identify the gaps first, right? So that's a bias that we have, in terms of, where it's like finding a door. You go and search for a door because there is a gap between two walls, and that's the door. A simple example, very oversimplified, is that the way our critical thinking works is to find those gaps. But in the hiring process, it needs to be done the other way around. We need to see what candidates bring to the table. And do. Do they add up to, I don't know, 70, 80 percent, or 90 percent of what we're looking for? There's no one who's going to be 100, 110, or 120 percent to that role, right? So let's be realistic there. Let's be clear about it, and let's communicate and articulate that clearly both in the job description and to the recruiter and the hiring panel.

TIM: And so just so I've understood correctly. So let's say you have a job and the requirements, and you have a candidate and their skills and ability and some kind of crossover Venn diagram thing. And it's part of what you're saying that you can adjust. the job somewhat to suit the candidate once you see them leverage more of the skills that they have that you weren't even thinking about? Or would you still keep the job as is and just try to find the candidate that matches the job?

PRAVEEN: I'll put it this way. Not in the initial stages of the interview; will you change the job description based on the candidate? In your final three, if you've gone through the process in the final three or final four, whatever you have read in the final set of candidates, when you're trying to make a decision, then there needs to be some sort of flexibility, some sort of adaptability there. That adaptability will obviously grow over a period of time during the process, right? Because you realize certain things or certain things have evolved in terms of the problem statements that role is going to try and solve. That's what I'm trying to say. You don't have to change it right in the beginning. Obviously, towards the end, you'll see, okay, who is the best-suited candidate for this role? And don't, you needn't have to start this entire process all over again because our job description is set in stone.

TIM: Yeah. And that's a great way to get the most out of the person you ultimately hire. And it's good to be a bit flexible. Praveen, if you could ask our next guest one question, any question about hiring, what would you choose to ask them?

PRAVEEN: Yes. I'd ask them irrespective of the specific role, right? A data scientist is going to have certain different skill sets as compared to a data engineer and so on and so forth. So, irrespective of that specificity, right? What is the one or maybe two key skills? that you look for in any candidate that is going to be at the top of your list or a successful candidate. What does that successful candidate have as one or two skills other than the technical things that you think will make them successful?

TIM: That's a great question, and one that will go into one of our episodes next week, and I'm going to take a guess at what they're going to answer based on the data I've seen so far. I reckon there's at least a 50 percent chance they'll say something along the lines of learning new stuff quickly, growth mindset, or something in that space. That's what I predict they're going to say. How would you answer that question if you got asked that?

PRAVEEN: I'd agree there. I think someone who's agile in learning, right? So that growth mindset. None of us are perfect, so we're going to make mistakes; we're going to learn. So how willing are we to learn? That growth mindset is number one. Secondly is, I think, collaboration, right? How amiable are you to work with others? How amiable are you to, like, you like, we said, learn from others and adapt? Work with them and then ultimately add value to the team and the organization, right? That's, I think, those are the two things that really matter.

TIM: I would second that, and it's certainly what we look for. Praveen, it's been a great conversation today; I really enjoyed it. Thank you so much for sharing all of your insights with our audience today.

PRAVEEN: Thank you so much, Tim. Glad to have been a part of this. Take care.