(39) The New Rules of Executive Recruiting in the AI Era (Asad Zaman, CEO @STA) - YouTube https://www.youtube.com/watch?v=yosoGOJrj7E

Transcript: (00:00) Acid Zaman is the CEO at STA, a world-class sales recruitment agency overseeing over a thousand placements a year, most of which are at a senior executive level. So he's got a bird's eye view of what's happening in the GTM talent market that very few people possess. The best firms in go to market are trending at about 45% offer acceptance rate. (00:23) That is a hot hot market. We discuss why the case study is no longer an effective interview tool and acid shares the new teach me test which VPs are failing left and right. >> I swear to you the amount of people that will fall apart in that step. You cannot hire a VP of sales who doesn't even have that basic understanding of how to teach something. (00:40) >> And if you're currently hiring ACE knows where most teams will go wrong. >> No one does the process. Everybody shoots from the hip. They haven't thought through the scorecard and how to operationalize it. But that's also why we talk through a clear and actionable game plan that you can use to find and secure the very best talent. (00:58) The way you operationalize a scorecard is you do a couple of things. The first thing is Welcome to the Revenue Leadership Podcast. Here's a familiar scene. A deal's in commit and the buyer says, "Can I talk to somebody like me?" Next thing you know, sales reps are asking CSMs after hours. Five people are in Slack trying to remember who helped last time. (01:19) And that one customer who always says yes is getting burned out after three requests in a week. That's why this episode's brought to you by User Evidence, the platform that turns customer proof from chaos into a repeatable GTM system. With advocates, references, and real customer evidence all in one place, your team can share credible proof instantly and keep deals moving forward instead of stalling. (01:40) Companies like Gong, Ramp, and Wiccado already use user evidence to capture customer proof, build buyer confidence, and shorten sales cycles. See how at user evidence.com. That's user evidence.com. Today's guest is Asa Zaman, who is the CEO of SalesTalent Agency and has been there over a decade in sales recruiting and executive recruiting for over 10 years now. (02:07) And uh STA, for those of you guys who don't know, it's one of the biggest, highest volume recruiters in North America. They do now a ton of executive recruitment. He's one of the most thoughtful people in the space that I know. Somebody that I lean on uh for insight when it comes to hiring and also hosts the Topline Podcast, which is uh the sister, brother, cousin podcast to this one. (02:28) >> Yeah. >> Relative. Yeah. Yeah. So, appreciate you joining and uh looking forward to this. >> I'm excited to be back. Which episode is this now? Give and take. >> No idea. 50ish and change. Something like that. >> I did episode one or two with you. So I I was here for the first few and now I'm here again. (02:49) Every 50 episodes I'll be back. >> Exactly. And and our first episode was about uh sales hiring mostly on the IC level because it's a thing that I get asked about all the time. Um, and today we're going to talk about leadership hiring because it is incredibly fraught. I've personally found it difficult to hire senior leaders. (03:08) I know this is uh this is something that is felt across the market. It's just so difficult. And so we're going to get into how to approach leadership hiring. Uh also talk about how to think about when is the right time to layer or promote from within structuring a senior leadership hiring process. uh who should be involved, how do you what do you look for? How do you look for it? Uh and all sorts of good stuff. (03:34) So, uh I'm curious as just a warm-up question, how many senior leaders does STA place now? So, we do about a thousand searches a year. It's Ze and leadership is about 50 to 60% of that >> and the other 40% is IC. And on the IC front, we've always done a lot of IC. IC used to be 100% of the work that we did. Um, and of that things like SDRs were a really large percent. (04:07) Whereas right now, even the IC work that we do is more so on the complex IC side. >> And so, in a way to think of it is that we've re-engineered business over the last couple of years to focus on the hardest problems when it comes to grow. You know there's that Alon saying I think he said it where you get paid in proportion to the difficulty of the problems you solve in life and so that actually informed some of this and so we focused on the hardest go to market problems in tech which are executive leaders and then complex IC roles makes (04:42) sense so hundreds of senior leaders a year you've been doing this for a long time I want to talk about what's different before we get into unpacking the process But what is different today in hiring and we're predominantly talking about like VP and up >> specifically I think like my cohort sort of CRO are looking at their SVP and VP layers being the most challenging. (05:08) So what's changed uh in hiring those positions more than uh more than anything? I think the biggest change that has happened is driven by AI and is to me around how much harder it is to interview. So there are things that we all used to do that were pretty high signal in an interview process. An example would have been a case study. (05:36) We were big believers in case studies and pre- AAI a case study was a a good way to have a forensic test at the end of your interview process. You know, if the if the perspective is that commercial people are hard to interview because the worst candidate you interview still has characteristics that lend well to interviewing and they have lots of practice and so you can't just talk to them. you need more. (06:02) And so you you're very thoughtful about the interview process and how you're going to layer in the scorecard through that process. And then towards the end of it, you're going to have some sort of forensic test. And so you could do a business plan. You could the worst version of it would be a 30 60 90day plan. (06:18) Some companies would ask for business plan. We thought those two were low signal and case studies were high signal. And as soon as AI has become as used as it is today, it's got a long way to go, but it's still pretty powerful today. Those case studies have become low signal. And the reason for that is that the friction that used to be there before is gone now. (06:41) You can use the AI to do a lot of it. And that in a way teaches you something about the person, but it's not teaching you as many things about them as before. And so we've switched completely to doing live whiteboarding sessions instead. And so that's a pretty big shift in terms of today versus even just 2 years ago. (07:01) I think another shift that is at a different stage of the process is when you think of the number of sales people that you would have had to hire per $10 million of revenue. >> Mhm. Pre AI you would have had to hire more people and now you have to hire less and if we are believers in AI we believe that it will keep improving over the coming years then that number will go down even further. (07:35) There are companies right now you and I know some of this uh people at these organizations where the AEES are doing twice of what they traditionally would do from a quota perspective for a company at that stage >> and I can think of one specific company where the quota is double and 80% of the team is hitting and so that company has about 35 salespeople for about 150 million in ARR it's a much leaner team than before >> and so The design of that team has changed. (08:08) The importance of getting hires right has changed. So that CRO needs to make sure that the people underneath them from the VPs to the second and first line managers that they miss a lot less. And that is a huge shift that's happened. And it's it's an uncomfortable shift because we have to change how we believe about hiring. (08:30) Before it would be I made five hires. If I can get two really right and one that's good and I miss two, that's okay. If you're making half the hires before, you have to miss a lot less and that's that's hard and that's different. One of the things that I've been advocating for in sort of a AI native leader is is an ability to be a systems engineer as opposed to like a people manager. (09:01) I think the era of the pure people manager is is ending. Disagree, agree. How do how do you think about that? >> I think 100% agree. I think there was a world in which in a way like you could say that the game is just getting harder and harder at the leadership level. >> Like before there were some people that were really good at the people part and not at the rest and there was I think more room to run for them and I think there's less room to run for them right now. I would say the very best people. (09:35) One of the things I think about a lot when I think of VP SVP hiring is this idea of we're trying to hire someone who's a really good teacher. So much of the job is teaching. >> Mhm. >> Right. And you need somebody who's good at teaching one-on-one and then teaching through systems. >> Mhm. (10:00) That's the best VP is somebody who can be like, okay, directly I'm working with the second line manager. So, I'm going to teach them one-on-one and I'll spend some time with maybe the first line management layer, but underneath that, I'm not doing a lot of one-on-one stuff across dozens of reps. And so now I'm teaching through systems. I'm enabling an organization to be good at teaching people how to do things the way we want them done. (10:26) And if I can match that with really good hiring, I can have a really powerful output from this thing. And so I think those have always been the very best. And I think those people are going to be in higher demand. But I think before what you would have is if one had one or the other, they had better careers, then I think they'll have the potential to have from now on out. (10:51) >> I think in a way the game has just gone a lot harder. And you you see this across multiple layers in the stack, this sort of flight to quality. You see it in venture capital, more dollars going to fewer great companies. You see it with talent, more great people concentrating around fewer exceptional companies. (11:13) And and same thing here, the the sort of power law of it with the leverage of AI just gets like greater and greater. We see this we see this very much in our business too and like in in advisory stuff, you know, the the great companies break out faster than ever conceived of before. >> Yeah, >> it the rates are staggering. (11:36) And you know, an interesting exercise these days is so I use I I like to think of I'm an analyst more than anything. So a lot of times I start by like looking at these the the setup the the the game on the field. So if you think about talent specifically, let's say go to market talent, you'll be like what's happening at the demand and supply level >> and for the first time since I've done this. (12:01) >> I don't think those numbers tell you the story because you could go and have a couple of conversations and come away feeling very different things. You can talk to some people who are looking for a new job today and you talk to them and it feels like the toughest market ever. Ever. This is a crazy job market. (12:23) Then you talk to some other people who you would put in the top 2 3 4% of that craft and to them they've never had this much demand knocking at their doors before. And I think that that's a really interesting bifocation in the talent market and kind of speaks to what you're saying which is the way that it is right now. (12:48) If you are part of that five maybe 10% who are really really good at something the market's never been hotter. Demand's never >> AI engineers being a great >> AI engine CRO growth growth people like demand genen people who are really good. It plays out across all of these roles and then you go to the rest of them and the market feels like we're still in 2023. That's really interesting. (13:14) I hear the exact same thing. We have a mutual friend who is in that top top tier who was swimming in cool opportunities and turned down a bunch of really great ones and landed on something awesome but like felt like he had just like unlimited potential in this market. And then I also talk to people. (13:35) It's like, "Man, it's so hard out there. The market's so tough." D I was like, "Dude, the market's the market's not bad." Like there >> I've never been this busy in my life. You know, people tell me like, "This is such a bad job, Mark." I'm like, "We've never been busier." >> Yeah. >> Can't keep up. And there's some interesting signals like there's the while the demand and supply data is less interesting these days to me, there's some data points that are very interesting. (14:00) One is that the number of layoffs that happened in 2025 in tech in the US are down. The total number is down and the number of companies that have laid off is down. But what is up by more than 80% is the average number of layoffs per company that did the layoffs. So >> that's up 80%. And so what that tells me a little bit is that we we wrestle with AI and because we wrestle with it, we understand how hard it is to get the ROI from it, but how real that ROI is. (14:32) But you have to put in real effort. It's not as easy as I buy something off the shelf and I get it and I use it and I get the benefits. We're also at a stage where the intelligence and capability of the people using it has a huge impact on the output from it. And so I think there are and then there's that MIT data point of 95% of AI pilots at the enterprise are leading to no ROI and people read that and they say it's all about the AI the AI is bad >> and it's like sure there's a lot of improvement to go in the AI but getting (15:06) the ROI is a combination of AI and organization >> and I think that number speaks to how few companies are able to digest and get ROI from AI as much as it says anything about the state of AI. And so I think the companies that are getting the benefits are cutting quite a lot deeper and wider than they have in the last four or five years. (15:29) But those benefits are hard to find. And the reason I think this is more AI than anything else is when you click into these layoffs and you see who's been laid off, it's all most of them are concentrated where the use cases of AI are actually quite good. support, edge, design, all of these roles where we know AI is somewhat decent right now. (15:50) So I think that's a really interesting data point about the market. And then the other one is very anecdotal, but when you speak to search firms that are focused on tech and are working with the fastest growing AI companies out there, one of the things I'm always wondering is what is your offer acceptance rate? because an offer acceptance rate tells you the state of the market a little bit. (16:14) >> How hard is it to close top talent? And the best firms in go to market and in uh engineering are trending at about 45%. From what I hear >> wow that's pretty bad. Like that is that is a hot hot market. Um and so for the top hot market on the other side layoffs layoffs layoffs. And I think next year is going to be this exasperated out >> and is is the 45% like a general market number. That's not the good companies. (16:48) >> It's the search firms that are working. This is why it's super anecdotal. I'm hearing it in the market from search firms that I know are working with good AI companies and are heavily concentrated with venturefunded fast growing AI companies. And so what they've seen is nice. >> Yeah, we were proud of our offer acceptance rate for engineers and now I'm absolutely thrilled. (17:14) >> Yeah, if you can have somewhere above 75% offer acceptance. If you're above 75%, it's as good as you can be right now. >> Wow. >> If you're like in it trying to fight for the right people, like if you're in the fight, right? Like 75 is really good. >> Yeah. One of the other things that could be driving driving the layoff number is it because I don't know if you successfully adopt AI, I don't know if you're going to cut engineers like it's it's the Jevans paradox thing like you're just you're probably going to (17:44) want to ship more support. you would cut support >> sales I don't know if you cut um if product you would cut a bit design you would cut a bit >> but a lot of it is also it's not just cutting and not replacing it's there are certain people that are good at using AI >> and are open to using it and certain people that aren't and there's a presence of those people in engineering like you know the purist s who want to do everything by hand old school style who existed >> they exist anymore >> yeah a few of them and they're getting (18:23) laid off left right and center and if the ones that are not adopting these tools they're getting left behind relatively quickly and what you find is in the startup world we see less of those people you see the progressives in startup right like startup is edge of the ecosystem so you see the most progressive version of everything there >> like your go to market infrastructure is far more progressive than the infrastructure at some multi-billion dollar revenues large tech company. (18:52) >> In those organizations, you will find the less progressive versions of a lot of these roles as well. So, you will find engineers that feel that that are resistant to change. And what will happen in those organizations is the company will say okay we'll get rid of those people and we'll replace them with we'll fire five of them and replace them with one person who's going to be really good at using these tools whose throughput is going to be massive. (19:20) Um, so I don't think they're looking to cut engineering indiscriminately the way they might be in some other function if they get the advantage, but they are fixing for high adoption rates. And if they don't see it, that's what they want. And and going back to sort of what this means for leaders, you you know, if you're in this environment, I just keep coming back to the word leverage, like the leverage on a person, the leverage on a decision. (19:43) It it really comes back to a place where the good leaders versus the great leaders have like a dramatically different outcome. Because if you if you can make, you know, slightly better decisions, if you make >> five really high leveraged decisions a year as as a senior leader, maybe it's not even that many, but if if the quality of those decisions is is better or the quality of the decisions, you know, four out of five is good versus three out of a five is good and the leverage of those decisions is 10x, you know, like if every rep or or it's 2x to (20:20) be more conservative, then then I understand it. And so what tell me about the from your client's perspective like what's the language they use to describe what they're looking for in a modern leader? I think clients have I think this is pretty across the board. I noticed this that you start with a very broad understanding of what you're trying to do and then it's through the process that you develop sharpness with it. (20:54) So it starts similarly right like I've got a business problem and I need to hire this person. Usually a hire is made by a CRO and the CRO is looking for time back essentially. Or you have a series A company that's hiring a VP to be everything for them. You're >> going to do the CRO stuff. You're going to do the frontline manager stuff. (21:14) You're going to do everything in between, etc. And so those are kind of like the two buckets of VPs that you see play out in in our world more and more. And so it usually starts with if you're a startup, we have no one. We've we've gone from founderled sales. We've done what Lmin said. We hire two AES. (21:33) They're hitting some decent numbers. It's time to invest into this and create some repeatability, predictability, scalability. And where they come with is they usually say something like, I've gotten this as far as I could get it. Now I need somebody who can live breathe this thing and do it really well. Who can offer me some glimpses of repeatability, predictability, and scalability. (21:55) And then you want to work with them to develop sharpness around all of this. We'll talk a lot about how you do that and how you implement though that thinking across a process. And on the other side, it's usually a CRO who is like, okay, I've been doing this thing for a while and the company's getting bigger and bigger. I need time back cuz I need to spend more time doing the CRO things that I need to do cuz the decisions are getting fewer and the magnitude is becoming bigger and it's pulling my attention, my time. (22:24) I need to spend time on that and so I can't be doing this thing that I'm doing right now which is playing this VP role. So I need to bring somebody in to do that >> and they'll have a very clear understanding of what they're trying to do. They're trying to buy time back and so that's great. Both of those make a lot of sense. (22:43) And then you have to take that thread and pull it and create sharpness around it and create an offering around it and then learn how to operationalize what you're trying to do across a process to give you the highest probability of making a successful hire. And those are really the really hard things to do. (23:03) I think uh one commonality between everyone these days is that there is a much a very clear focus early in the conversation that we're looking for somebody that has the capability of helping us gain advantages from AI in our go to market team. This is becoming clearly called out at the front of the conversation and the reason for that is that AI is early. (23:30) The advantages are there to be found, but they're not easy to be found. >> You have to do a lot of experimenting and hacking and trying. You have to swim through a pool of inefficiency initially to gain the efficiency. You've spoken about this, how when you first start trying to use AI to do something, it takes you a little bit longer and then it takes you a lot less time. (23:54) And so we need somebody who's going to help us get these advantages >> and who's excited to help us get these advantages. They're calling that out more and more because they understand how few of their peers when founders and CRO are all sitting with other people in market. One of the glaring things that we all realizing is how few companies have real substantial AI advantages in market. (24:23) So it's like but Kyle does I want what Kyle has. I want those advantages and I need people at all levels and all layers that are going to help me get those advantages because one of the lessons has become quite clear. You don't get them by advocating it to one person in some part of the old. You don't get to say let's hire a really good revops person and they'll do this for us. (24:44) It's a combined effort where everybody has to work together for it. And so this has now been called out for all the key hires companies. I'm making. >> Yeah, I couldn't agree more. And so, one of the threads that you'll be pulling on, I would imagine, is like what are the specific skills and traits? And so, how much are you bringing a scorecard to bear for people versus are you trying to pull that out and like what are the skills and traits that you think are the the most important ones for a CRO to be to be trying to uh identify in a VP (25:16) level person? I think what usually I like doing is somebody reaches out. Let's say we talked specifically about a company kind of at your the owner stage, right? Where you are you have a CRO who's hiring somebody to work under them. And so where I spend more time than what I have been told my peers internal and external spend is actually on the problem first. (25:44) M >> I think it's really important to start with what's the business problem we're trying to solve for which we want to hire this person. Let's get really sharp and clear about that. And so we spend a lot of time trying to distill that down. And from there you have to ask a question as to what are signs that so what are the jobs to be done when we hire this person? what are the jobs to be done to get this business outcome that I'm looking for and you get really specific and clear about those jobs to be done and then from there you say now (26:24) you are in a position to start thinking of profile against the jobs to be done because the jobs to be done are different and the problems are different based on companies and stages and types of companies. is if you are a well here's some fundamental differences to just paint the picture of how different the same title or the same job can be at different sorts of companies. (26:54) M >> if you look at a private equity owned business private equity a lot of the playbook is you buy these dumplings you do reduce some of their cost structure down one of the places where you cut cost a little bit is R&D >> and if you think back to the SAS era we were at a in a really mature part of that era meaning that the ATS system released at the tail end of that era was probably only incrementally ally better than the ATS system released 5 years before that. (27:26) >> Isn't that a painful truth? >> It's a painful truth. It's like slight improvements. And now that model of PE cutting R&D costs of somebody that played in that space, the delta between that product and the most cutting edge version of that product in the market wasn't that much. Right now you have AI. Now compare that the that game is still being played but now you're being compared next to this like super fancy out of YC nextg ATS system at a time where every buyer is trying to stay relevant for which they think they have (28:04) to buy AI right it's a way to maintain relevancy more than anything there's a status to the purchases we're making in market and so that's exciting and fancy and this other thing where the R&D cost has been cut down a little bit. The delta is exasperated. So what does that mean for go to market? For go to market, it means things just got a lot grindier. (28:29) And the leader you bring into an organization that has to grind out its wins is a different sort of leader with a different sort of wherewithal and style and skill set than the person you bring into your fastest growing AI company who's there to capitalize on the momentum that is there. You know, in sports there's some players who do really well. (28:54) If the team has momentum and you put that player on from the bench, they can kill it. But when they have to grind out a win, that's not for them. That's somebody else's game. And so you kind of need to know what games are being played where you are. And then you have to define profiles accordingly. So not enough work is done usually on what's the problem and jobs to be done. (29:13) What usually happens which shouldn't happen is it all starts with like a feeling of a problem I need to solve and then you start talking to HR who's like let's start writing a job description. >> And that is the worst thing to do. But job description comes much later in the process does not come at this point. (29:30) Job description is a marketing document. The the thing you have to get specific about is the problem and then the jobs to be done in service of that problem and that starts becoming a mandate and then you have to say what does good look like across one two and three years. M >> so here's the problem here are the jobs to be done and here's what good looks like 1 2 3 years down the line if I bring somebody in to focus on this so once you have that now you get to say what type of skills characteristics and experiences do I think I must have for a (30:11) person to have the highest probability possible to do all of this and now you start pulling that thread out and start thinking about essentially your scorecard and you're really focused on the musthaves. What's the critical stuff that will have the biggest impact on probability for success? Yeah. And you will have certain things that are classical. You should put them in there. (30:36) You know, you're going to have um a stage related element there like I need a person who's done this to this has taken a has been part of a journey going from 50 to 150 million. There's going to be a lot of learnings and nuances and things that we can pull out of that. So we want stage based experience is one of the things in our scorecard. (30:57) We're looking for a person who is proficient at doing this job at a company of this stage. We want go to market alignment. Uh dynamic alignment. So we want somebody who's dealt with this deal size and sales cycle and style of deal. You want culture fit. These are pretty basic and everybody can put them into their scorecards. (31:16) What's the stuff that is like >> what are the other ones? This might not be obvious for everybody. So like what are the other like uh non-starter things in a scorecard that people should be building against? >> The the thing that I think most people don't have in scorecards that should be that is what are the problems that you've got in your organization. (31:39) We we kind of like forget that we all have problems and our problems are somewhat our problems and somebody else's problems are theirs. So I like to spend a lot of time trying to understand what are the problems and I want I need a person who has shown signs of being effective against those type of problems. (32:01) Ideally I'm looking for past experience having dealt with it. And if I can't find that for whatever reason, I want the characteristics that lend well to dealing with a problem of that sort. So I think that's the it's obvious, but for some reason isn't a place where people spend a lot of time. And so I would spend a lot of time in the scorecard getting an understanding of the organizational problems, the go to market problems that I have that this person is going to be wrestling with and put that in there. (32:31) The other one is we put into that that we want a person who's good at hiring which scoreard for a VP doesn't have that. >> Mhm. >> And I think that is obviously a fair thing to have. You need to have something around forecasting because a VP should own the number and help you build the team to get to the number and be able to teach individually and through systems the people the things they need to know to be able to do these things. (32:58) Those are like the core responsibilities, right? And so they need to be good at forecasting. They need to have owned the number across these stages. They need to know how to hire effectively. They know need to know how to teach people individually and through systems. And so you start like filling out your scorecard with all of these things. (33:18) From there, you have to ask a really important question that everybody skips. 90% of people don't ask this question. What constraints are we dealing with? that are going to impact our ability to get all of this. So, we've just put our wish list together, right? We've essentially developed an understanding of the problem. We've mapped out the jobs to be done and we've said if a person has all of this stuff, then they have the best probability of being successful against this. (33:45) >> Mhm. >> What's holding us back from getting that person? >> Maybe you can't afford them. You can't win them. Maybe you are looking in a very specific location. So very specific scoreards in very specific locations. There's a tension there. You and I are from Toronto. >> You don't have to make a bunch of compromises when you meet certain hires in Toronto. (34:10) Toronto is not an ecosystem that has a lot of enterprise sales startups. Hence, you don't have a lot of people that have that skill. So you don't have >> dev or dev like devops engineering and centric sales people. Yeah, it's a different Yeah, for sure. That's an interesting con. >> So, geography is a constraint. In office can sometimes be a constraint. (34:29) Like, hey, I want a person 6 days a week in office. Great. That's a constraint. That's going to impact the supply of talent available to you. I need this person to travel 90% of the time. So, you just like you have to pull this thread and say, okay, what are the constraints holding us back? Usually, the constraints are geography and compensation. (34:46) >> Mhm. And then once in a while you get the nuance stuff like some knuck CEO who's like I want a low ego sales team and so I want a person who doesn't care about titles so I want a CRO who's willing to be a VP or a head of and so you see like nonsense like that that you have to kind of like click into and push back on. (35:06) But the logical fair constraints are compensation geography things like that. And so then you say okay so now I know what's holding me back. What am I going to do? I'm either going to have to at this point think about the compromises on the scorecard that I'm willing to make. What compromises can I make? Or I'm going to have to give in on some of these things. (35:29) So if compensation is one of them and it's a surprisingly common one by the way like even in companies that are well funded that are doing well for some reason we in certain situations will create these constraints for ourselves where we'll put ourselves in a situation where you know 30 40 $50,000 constraint on compensation holds us from getting somebody in the top 5% and now we're shopping between the 6 and 10% range which is a huge difference. (35:59) It's like it makes a huge difference. It happens often >> and so you say >> why why would a founder or like a team >> put that constraint in? >> I think some of it is just the psychology of people you know some people like being costconscious in certain ways. I think there is this they want people to show flexibility in cash compensation to join their dream cuz they've had to make so many sacrifices in cash compensation to be on this dream and they forget that that person at best will get.5 to 1% and you own 25%. (36:40) So if this goes well millionaire and this person will at best be a millionaire and so they kind of forget that. I think people put on their CFO hat often when it comes to numbers like this and they start like trying to make a good deal happen. But the common one that we actually wrestle with is at the start of the project people are willing to pay anything to get the best and then when they have the best at the end of the search they want to make a good deal happen >> and it's that I think is you go from your founder CEO let's get the best (37:11) person and I understand the delta between a 1% and 5% candidate let's get the 1% and then at the end being like yeah but they asking for 75% % equity and I don't want to give more than 0.5% and the deal is almost about to die over like 0.25 and you're like good grief guys like what are you guys do? >> And I give this advice like I give this advice a lot. (37:37) I'm like if they're amazing if if they're really good you're going to be so glad that you gave them the extra 0.25% cuz you want to lock them in and if they're not good they're not going to make it to the 12-month cliff anyways. >> Yeah. They're like like this is the nature of the beast with with you get a lot of this happening and I think this is where good investors make a huge difference. (37:59) This is where they make the biggest difference. >> They help you get past some of your like psychological I think tendencies and orient you in a way that is designed to win the game that you want to win. >> And so they help you understand no you're thinking this the wrong way. Think of it like this. And I think investors and advisers together can play that role for a founder because we're all imperfect people. (38:24) We come into these things with, you know, preconceived notions and tendencies and all of this stuff. And some of those are the things that will help us win the game. And some of them could screw us up along the way. And it's the it's your cabinet of advisers who will be able to help you, I think, miss some of those potholes. (38:45) a company I was trying to do a favor for lost out on a really good candidate, like a good CRO candidate because they couldn't make the comp work. And it was more than 30 or 40 grand, but it wasn't egregious. And I'm a real snob about CRO because I get to talk to a bunch of the best. And I talked to this person. (39:05) I was like, this he's great, gets AI on the cutting edge, like you know, like slam dunk. You should hire hire them. and they couldn't make the comp work. And uh I was sort of baffled. I couldn't I was doing it as a favor. I didn't really want to like come in with a strong opinion saying like I don't care what the comp is, just pay this guy. (39:25) Like you don't understand how wide the dispersion is on CRO, head of sales quality. Like you can go. This is also one of the things we're trying to solve for with our methodology to making these highs. I think some of this and we we'll talk about some of the rest of the things people have to care about. One of the things that plays out at the back of everyone's mind when you're making hires is so every every hire is some sort of trade-off, right? You're making trade-offs in every which direction. (39:58) You start with this like perfect thing of like you perfect job description of everything you want and then the reality is you're dealing with humans and the market and there's trade-offs that you're going to have to make. And so one of the things that plays out is hm I wonder what else is out there. >> H you know you start thinking like should I budge on compensation this much? Maybe there's somebody else out there who's really really good and who will be within my comp range. (40:29) There's a there's a lack of understanding of something very important that creates the confusion and gives you some false reason to not do the thing you have to do in that moment. And it can play out both ways. It can sometimes make you make a hire and it can sometimes make you screw up the hire. And that is something that we try to get away from by using the scorecard to actually here's something that was not possible before. (41:02) You couldn't know 100% of the candidates that match your scorecard for these type of roles before. You can know 100% of it now. You can have complete precision in terms of here's my scorecard. Here's every human being out there that matches this scorecard. >> And you're doing that with like not >> Yeah, just research. You have the tools. (41:27) You have LinkedIn, you have Pitchbook, you have all these things. You just have to do the heavy lifting now and like map the market out. >> And so what we do is once we've got the scorecard mapped out and we talk to them about constraints, you get to a point where you've now got a really good understanding of what your scorecard is. (41:44) You've looked at the constraints. You figured out where you want to give and where you want to not give and you land up with this scorecard. The next step is operationalizing a scorecard. >> Too many people say scorecard, but it's just a list of things that they want. And that's not what a traditional scorecard should be. (42:06) And so the operationalization of the scorecard is the next thing. And by the way, till now we've not written a job description just as a call out. So now we're thinking of the operationalization. The way you operationalize a scorecard is you do a couple of things. The first thing is the scorecard tells you all the types of companies that you should be looking to pull candidates out of. (42:30) And so you start there. You map 100% of those companies out. Then you stream their orgs and you map out 100% of the candidates that match my scorecard. And then you go through all of those candidates and you see which ones look like they have the caliber to be viable. And so you get this really good understanding of your market. (42:55) Total number of companies, total number of candidates to total number of viable candidates. And this is really important information because now what one of the things you're solving for in a search is saying there's some candidates in this viable group. That's the group you you should be making the hire out of is these viable candidates. (43:17) So now I know how many there are. Maybe there's such few that I need to think differently about my scorecard. We had that recently on CRO search where there were 11 people that came out as viable. >> Yeah. >> And the company's board and the company wanted to make the hire in New York. There were two people in New York that matched the scorecard >> just to this was very very small town pool. (43:41) So we now have to go back and be like let's try to get those two people but this isn't enough. So we have to give on something. And it's a really interesting exercise to do up front rather than later. You don't want to be shooting in the dark with these things. So this helped us at the front end be like, "Oh yeah guys, there's two candidates in New York. (43:59) >> There's 11 in total across the US." Do you want to give on location a little bit and start there? Because you are saying that the probability of this profile being successful against this scope and this mandate is much higher than once we start making adjustments. So if you don't want to make adjustments, we then need to give give up on location a little bit. (44:20) And they ended up giving up on location. They're like, "Yeah, we do like this profile more than an a version of this profile. So now let's go after the so you find out all these candidates and some of these candidates are just not looking for a job. >> Open AAI calls them chief commercial officer looking for one. (44:41) " They're going to say no. They're that closed off. Okay. So those people are off. The rest of them fall on a spectrum between aggressively looking for a new job and slightly open to a really interesting next step. >> Mhm. >> And I want to engage 100% of them. Each person who's anywhere between this open to a next step to I'm I'm looking what's out there. I want them in my process. (45:11) And that gives me the ability to have an understanding of my market. So I have now spoken to lots of candidates I've brought into this process. If I'm doing this correctly, I have a pretty good funnel coming in. And so now I have everyone in here. So when I get somebody to the end of the process, I'm not wondering what else is out there. (45:34) I know what I'm not finding I'm not letting dark spots in my understanding convince me to do something silly that's going to hurt the potential future enterprise value of my business cuz I'm fumbling something at the end cuz it just feels uncomfortable to give somebody an $800,000 cash compensation or something, right? Or or to have to give somebody 1. (46:00) 5% of the business to do what? to sell this product that I built that is so amazing. What? Because no one thinks they have an ugly baby. No founder thinks the product shouldn't sell like hot gates and so give you so much to sell this. You should give me something to sell this. And so you you get yourself away from that. (46:19) So that's the first thing is you you map everything out. The second part of operationalizing the scorecard is looking at those elements and saying what's the how do we stack rank this because we want to give them a weight right not everything is equal one thing is more important than the other thing um and so let's now give it let's start uh ranking these things and giving them a weight and let's get specific about how we're going to test for this thing. (46:49) So, if we're looking for their ability to make good hires, how are we qualifying that? Something that blows my mind that we're starting to do this right now, it's wild that it's it's not done, is if you hiring a VP of sales, you should get an email from whoever is helping you on that search, internal, external, etc. (47:13) Here's everyone that person has hired in their career. M >> little Excel file, Google sheet, everybody they've hired. What do you think? Here are the five best they've hired. Here are some disasters they hired. And that's I would spend a lot of time looking at that and having conversations around hiring over there. (47:32) Right? So that's one way to figure out if the person's good at hiring is who have they hired. Rarely is this done. this is this very new like we're doing it like we're thinking of like what is the best dossier that we can send you to help you make good decisions. We were resistant to doing things like intelligence tests and personality tests before but because we knew how flawed they were and the bad habits that people would create around using them. (48:00) They would they would almost abdicate to these things and so we thought that's a flaw. We weren't big fans. Where I am now with it is yes, there are some of those flaws in there, but you can you can work around those and there's still a lot of signal to be found. And so there's a 4% correlation between the level of intelligence a person has and their performance at pretty much anything in life. (48:29) Intelligence is a really uncomfortable thing that for humans to talk about. Mark Andre was saying this where 4% 04 correlation >> point4 okay >> yeah point4 not point4% so it is highly correlated with affairments science and but intelligence scares us as a thing to talk about like some people are smarter than other people are naturally smarter than other people naturally that's an uncomfortable thing and then that natural intelligence impacts their ability to do certain things better or worse than other people and so but it is (49:08) the truth. It is as as real as black and white is real and so >> people taller. Yeah. Or people taller faster like these are gen Yeah. Yeah. I get what you mean. >> These are real things. So you have to take it into account. So you should test for intelligence. You should do a personality test. (49:26) Like you should start thinking of how am I going to test all of these things. What's the best way to test each of these elements on my scorecard? Now, let's talk about the interview process because the interview process materializes out of that. You decide on who's going to be part of the interview process and you decide what steps you're going to have, but then you overlay this score part and how you're testing these things across those steps. (49:50) And so, what you get is this really elegant process where everybody has a role, everybody's got some consistency with what they're doing and the steps that they're managing. And every minute of the interview process has been used efficiently. And all of it is being used to develop uh a sophisticated understanding of whether or not we think this person is showing us good, bad or somewhere in between signals against this thing. (50:23) And that's how we're trying to develop a interview process that helps us go from problem to scope to scorecard to then the interview process and the people's roles within it. And in this we have candidates only coming in who are deeply aligned with our scorecard and everyone else is out for now. >> We don't let distractions come in. (50:48) The worst thing that can happen to an interview process sometimes is somebody from outside of the scorecard, left field, comes in who's actually a really good leader, >> is objectively a good p good leader, talented, dynamic, just not a fit with our scorecard. That's confusing as hell for founders. (51:08) These are not founders who've hired 30 CRO in their careers. Like this is sometimes the first or second time they're making this hire. Let's not confuse them. And so we stay very disciplined against the scorecard and then operationalize it like that. >> And so then how different is an interview process for an early stage vertical SAS CRO versus a series E enterprise CRO? Like are the core components of that interview process similar and you're just you know asking different questions? You care way more about forecasting for one than the other. Like (51:43) just maybe paint the picture there. I think depending on the problem you're solving, what you're testing for is different. Your scorecard has materialized differently. Um, if you're looking for a CRO versus a VP, it's different. And so you might have a similar number of steps in an interview process and some of the things you're looking for might have some sort of consistency across those but there will be significant differences between hiring a VP of sales at a series A company versus hiring a VP of sales at a (52:14) series C or D stage company. But is the structure is the structure the same but the questions are very different or would the structure like oh I'm not even going to do a hiring manager screen I'm going to do this other completely different thing for for late stage versus early stage the way I like to do it is there's actually quite a lot of consistency across the the number of steps in a process >> there is a lot of consistency around what I think is the ideal time frame to conduct those steps within >> there it there is to some extent (52:53) consistency around these core things that I think we should try to do an example being the whiteboarding session I think it works across all of this stuff so we're asking clients on CRO's VPs directors all of them to do whiteboarding sessions Something new that we're asking people to do is teach me something. (53:21) >> Teach me something. >> You you're going to be responsible for teaching the next 50 people that we hire in sales uh through your systematic approach to teaching and then the frontline managers and second line managers through your actual individual interactions. Teach me something. Show me you're good at teaching something. (53:41) I swear to you the amount of people that will fall apart in that step. This is a new one that we've added in. So the we've been doing whiteboarding sessions for a couple of quarters now. This is a brand new thing that we're adding in right now is teach me. >> This is this is something I've done for a while and instead of like a I I've felt similarly about case studies like I I think the signal is pretty wishy-washy. (54:06) I I haven't done three 30 60 90 a day plans in a long time. >> But uh part of the the senior level case studies for me is I'm going to give you a bunch of a bit a bunch of calls for you to review and then run me through the experience as a rep. Not like come in and present your findings and give me a score. No, no, no. (54:27) Like come in and coach me as if I'm the rep. And when I was hiring a VP of sales 18 months ago or whatever it was, it was really interesting to see how many people like completely failed that step. And then I would give them feedback. I'm like, "Oh, so actually here I don't want you to coach two things two or three things in one coaching interaction. (54:47) Just coach one thing, but let's go deeper on that thing." >> But the fact that you're having to tell this person that itself basically disqualifies that candidate, right? Because you cannot hire a VP of sales who doesn't even have that basic understanding of how to teach something. >> Oh. Of Yeah. (55:03) I mean 90% of VPs of sales don't know that. >> Exactly. >> That that would get on a call and like try to coach multiple things. It's it's but it's not really their fault. And I I >> when I do this with manager hires, >> when I do this with manager hires, >> it's almost always done wrong because nobody's being taught the right way. (55:21) And so I'll give them the feedback and watch them do it again and see how fast they can. >> No one taught I don't know about you, no one taught me this. I learned this that how you teach people things, right? >> I learned it from sport. Yeah, >> I learned it from sport as well. And then there were couple of books that spoke about this. (55:37) I think um the talent code. >> Talent code. Yeah. Yeah. My go-to recommendation. >> Exactly. And so it's also what you're trying to see is how depend how downstream of the people that have led you are you versus there's more to your development than just that. Like I think if people were to look at you, you're not just downstream of the people that were your leaders early on. (56:00) Obviously, there's a lot of impact that they had on you, but I would say in talking to you, there's so much you've gained through the time and energy you've put in towards learning things academically for yourself. You read, you you go and have conversations, you're listening to things, and you're processing it, and you're trying to include it into your game. That's a big part of it. (56:23) And so when a leader doesn't know this piece at the VP level, it's kind of a big problem for me where it's like, okay, you there's there's enough out there for you to have figured this out. And if you haven't figured it out right now, >> I'm sure you can and I'm sure there's a place for you to go and be effective, but if I'm you hiring for the company you're at, I'm looking for a top 1 2% person. (56:47) And so I don't have the space to bring that type of incompetence in. And in the context of this, that is incompetence. you're at the VP level and you haven't gone and figured out something that's fairly basic to figure out. >> Yeah. I want to hear about live whiteboarding before we run out of time. So >> tell me about the how how you run that process. (57:05) >> So with whiteboarding, so why do we do this? We do this because AI has made doing homework easier irrespective of your age. And so it is making case studies for leaders and reps and whoever just less signal for us. >> It's brought the performance dispersion very narrow instead of a wide dispersion of good versus bad in a case. (57:33) Now nobody's really going to mess it up because it's Chad GPT can give you so many of the answers. >> Exactly. They give you something good enough. You kind you play around with it a little bit. Spend like two hours on a Saturday. You drive it. >> That was clean dashes. >> Yeah. Get rid of the M dashes. Forget get rid of the it's not this, it's that. (57:50) Take out the word flop. You're done. Right? Like that's the editing what we're doing. And so the we we can't do that anymore. But we still need to do some sort of testing. So then what were we really hoping to understand with the case study? We were trying to figure out how does this person's brain work? How much effort did they put into it? what's the output of the the processing that they did? Um how well did they present this information? Were we able to see signals of collaboration when they were presenting it and I clicked in on (58:23) something? So, okay, there's other ways to figure that out. Let's just get rid of all the homework part and just make it a live thing where we say let's pick a problem. If you're hiring a leader, maybe the problem is something like we want to open, we want to go mid-market. We've been SMB, we want to go midmarket. (58:40) And it's as broad as how would you think through this in 2026 for us to hit our number? We probably need to do a mid-market as well or we need to enter a new geography. One of the two we cannot do either. How would you think through this? And what your job as a leader is to have figured out the problem and bring to the conversation some relevant data that is easy to access if the person asks for it or says I would need to see that data. You have it. (59:10) You know what the poor things are. That's it. Now you let them drive and it's literally that. You just let them drive and you see what happens. Like you see where they go with it and you book yourself an hour and a half and you see >> h what's good versus not good in that scenario. I think good is showing you is a brain that is able to logically think through break down the problem and build back up with it. (59:42) Right? Like a what good leaders are systems thinkers. A systems thinker can take something and break it down into its pieces and then use that ability to work back towards something else. Right? So here's the problem. Here are the pieces. Here's how. And so that's really the number one thing you're trying to understand is they can take a systemsbased approach to this because what you can't be affording at with hires of this sort is an over reliance on gut and intuition and the lack of intellectual rigor put towards what are really meaningful and (1:00:20) expensive bets. So you're looking for does this person have the natural ability to use intellectual rigor to understand this problem from a systemsbased perspective. Another way to say that is take state of first principles-based approach to wrestling with this problem. That's the first and more important than anything else. (1:00:39) You're trying to figure that out. And when you think of how important that is and how effective this exercise can be in figuring that out, it's kind of crazy that we didn't do this before and we ever did case studies. This is far more high signal than than the case study for this. (1:00:55) The the second thing what I'm really trying to get from there is that there is a a calmness to them. >> There's a temperament. I need people whose temperament is suited to the job. It's intense as hell building these companies. We're going to be working hard and tired or like do you know how to like calm yourself down? Do you know how to like control your temperament a little bit? So I'm testing for that in this. (1:01:19) It's like what was your temperament during this time? Did you feel frazzled? Did you feel like what was it like? Were you level? And then what was my collaboration with you like? Did I enjoy it? Did I like working with you here? Cuz if I enjoyed it and you were somewhat, you know, level set and you were be able to be first principles and how you thought through this, that's pretty solid for a VP of sales coming into the organization. (1:01:47) It tells me that this person has the ability to be a future CRO. And I think it's really hard to hire VPs of sales who you do not think have the potential to be a future CRO. There's some questions you should probably ask yourself at the end of a process to help you figure out if you are making the right decision or not. And one of them is that that would I do I see this person being a future CRO? Number one. (1:02:14) Number two, another question I think is super important to ask towards the end is commercial people's careers are very much like sports people's careers. You have a period where your raw potential. I I used to watch football but I imagine this analogy works for other sports where like you see the legends of today when you were growing up and they were young and entered the team. (1:02:36) I think of Ronaldo when he was in his early 20s. You knew he was high potential but he was bloody crazy. like he was not a finessed player yet. He would take shots that would go flying into the seats. He would have a tough time controlling the ball. He wouldn't pass enough. He wanted to show a lot of flare. (1:02:55) You watch him five years later >> and all of that has he's become extremely disciplined and sharp and finessed. And so he's he reached his he started entering his peak and then he had a run and then now he's on the tail end of it. he's past his peak. These people are like that. You want to get them right before they hit their peak. (1:03:18) >> You want to work with them when they're at their peak and you want to avoid the people that are past their peak. And the hardest one is at the tail end of their peak. That's the hard one to figure out is is this person at the tail end? But how many CRO's How many of the legends did like four or five CRO gates? >> Yeah, they had two. (1:03:39) >> Yeah. hard. Yeah. >> All right. I one more question before we we wrap cuz I'm getting the text messages that we have to go to dinner. What's the biggest blind spot just like a CRO? It's mostly CRO that listen CRO's hiring specifically VPs of sales. What's the number one blind spot that you think if you could give them one piece of advice like don't miss this? I think it is, funny enough, a taste for what great is in that role. (1:04:11) M >> an over reliance on thinking of themselves a few years ago or thinking of the best person in that role that they worked with ever but not going out and developing a much broader understanding of what the top 1 to 3% or 1 to 2% in that role actually looks and feels. you know, one of the one of the top investors out there came to me and they were like, they were asking a bunch of us, what would you do to help an early stage founder who's got no sales experience, who's not got like natural tendencies over there, but they need to now go (1:04:48) start making these hires. How would you help them? And the first thing I did, my my first idea was I would spend a lot of time making them meet the best, >> develop taste, what's the what does the best look like? And then you can go do a lot more. So I I find that and it's a strange one because you wouldn't think that's the case with commercial leaders but I find that that is the common problem. (1:05:11) >> Makes a ton of sense. >> And then the last thing I would say is no one does the process. Everybody shoots from the hip. So they don't know their complete understanding of the market. They haven't thought through the scorecard and how to operationalize it. They start by writing a job description, sending it to HR. HR post a job up. (1:05:32) They get a bunch of inbound applicants from left, right, and center. They stream them badly. They send them to the VP of sales. VP of sales spending insane amount of time or CRO is spending a lot of time looking at VPs of sales that make no sense gets disheartened at the state of the market and their ability to attract somebody good and in a disheartened states ends up making a very compromised decision because their their understanding has been I think manipulated by a bad process and the output of a bad process. (1:05:59) That's great advice. This was great. I feel like I'm better I'll be better at this moving forward. And the next time I need to make a senior hire, I'm going to call you and ask you some more questions. But, uh, yeah, appreciate you jumping on. Uh, I think people are going to get a ton from this one. So, appreciate it. (1:06:14) >> Always fun. I'll be back again in another 50 episodes. >> Thank you for listening to the Revenue Leadership Podcast. If you enjoyed it, don't forget to subscribe and you can find a link in the show notes. And be sure to leave a fivestar review, share it with your network, and please join me next Wednesday for another great conversation.

The New Rules of Executive Recruiting in the AI Era (Asad Zaman, CEO @STA)