In this interview‑style discussion, Dom Monkhouse and a guest explore why many scaling companies lose millions by mishiring leadership. They argue that early‑stage founders often need to replace themselves with seasoned professionals once the business outgrows the founders' skill set, and that the timing of this pivot is critical. The conversation highlights how most founders under‑invest in hiring and rely on ad‑hoc interview processes, leading to hires based on likability rather than functional expertise. They propose using AI tools like ChatGPT to craft a complete interview pipeline—from job description to assessments, behavioral questions, and a 90‑day plan—tailored to the specific pain points a company faces. A striking McKinsey statistic is cited: in highly complex roles, a star performer can deliver 800% more output than an average performer, translating to up to a 9× return on compensation. The guests note that top‑performing CEOs achieve this talent advantage not by expanding budgets but by reallocating existing capital, moving funds six times more frequently than average CEOs to high‑return people and projects. The discussion warns against siloed budgets and emphasizes systematic, data‑driven hiring and budget reallocation as essential levers for scaling profitably.
Chapters
The people you had at the beginning, were they the same leadership team at the end? And if not, why not? And what lessons did you learn building leadership teams?
Yeah, well, I forget who said it, but there's a quote, something along the lines of, if you think a professional is expensive, wait until you do business with an amateur. You get what you pay for when it comes to leadership. And there's a time, of course, in the beginning when you kind of have to make do with whatever you have. But you have to very, very quickly pivot. And you've scaled, I know, a few businesses yourself. You have to very, very quickly pivot. You need to know when is the right time to invest in a professional.
Right.
who is really skilled within their function, rather than trying to get everyone to kind of chip in and just make it all work.
Mm-hmm.
And I think that's a critical point. I think the interview process as well, AI makes this so much easier. Everyone should be asking themselves, especially if you experience a situation where you really struggle with a particular function, let's say, in your leadership team. You just pick whatever it might be. We've tried finding a director of operations or a COO, and we're on the 4th one now, or the 5th CFO, or whatever it is, because every company will typically have one of these roles that they really, really struggle with. And if you just have a conversation with ChatGPT, open book, about here's all the things that we're struggling with, here's all the things that I want to see in this role. Can you please help me design an end-to-end interview process from job description to assessment to their first 90 days that will allow me to course correct on the historical here and finally get the right person? And even down to what are the behavioral-based interview questions based on the pain points that you've heard me share that will help uncover the degree to which this person is a good fit or not? What are the right assessments? All of that, super, super critical to find those right people. But I think the biggest problem with leadership and getting that right, I think very often is at the very front end where people underfund the role and/or have a very poor process for identifying the right talent.
Yes. We were helping a client hire a head of revenue. And I got asked to do the final interview.
And I went, no.
And I think because the recruitment process had been done by the team, if you're not an expert in the function, the only thing you can hire for is likability. And so the guy was quite likable, but didn't— was never going to be able to take this company from $1 million to $3 million in the next 12 months, let alone, you know, $10 million the year after. So It's just, you know, have we got the right people? Are we asking the right questions? And, you know, nobody's ever been hired. Nobody's ever been trained to do interviewing properly.
Yeah. And so there's another—
they wing it.
And there's another fascinating stat too, uh, that comes from McKinsey's Global Talent Survey. So this is especially relevant the higher the complexity of the role, but when you compare star performers versus average performers, In very complex roles, a star performer will have 800% more output than an average performer. Now, this is especially relevant when you think about, well, a star performer might be 2 or even 3x market rates, which might make the person squirm. But what the research shows is that—
Yeah.
But you're going to get a 9x return potentially if it's a highly complex role that you're hiring them for. So that's, I think, another— and then one more thing, because it's all related to this, getting the right talent. What that doesn't mean is that you need to suddenly expand the budget. Because if you look at the top-performing CEOs as well, what they're very, very good at is making sure that they constantly reallocate. And the best CEOs will actually reallocate 6 times more on a percentage basis, their annual budget to get it flowing to the highest return people or projects than an average CEO. So meaning the best performing CEOs don't create extra capital to hire star performers, they reallocate the capital.
Yeah. Yeah, yeah, yeah. Well, and so often you have these, you have siloed budgets and no reallocation. In average-performing companies, somebody's going, no, this is my budget. Leave my budget alone.
Yeah. And they keep doing it and they stay on with the same people. Well, because they've always been there and they forget the whole adages and sayings. They exist for a reason. And the whole, what got you here won't get you there applies to people as well.
