Metrics That Matter: Turning RevOps Data into Executive Decisions with Josh McClanahan

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Hello, everyone.
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Welcome to another episode of OpsCast, brought to you by MarketingOps.com, powered by all the MelPros out there.
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I'm your host, Michael Hartman, Flying Solo.
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Yo me and Mike will be back, I'm sure, at some point here and there.
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Today, I'll be talking about metrics, but not dashboards, tools, or attribution models for their own sake.
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To join me in this, my guest is Josh McClanahan, co-founder and CEO of Account AIM.
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Josh comes from a business operations background and works closely with teams on reporting, analytics, and helping leaders understand which numbers actually matter and why.
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In this episode, it is going to be about moving from reporting to decision making, understanding how your company really makes money and learning how to communicate data in a way that resonates with executives.
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Josh, welcome.
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Thanks so much for having me, Michael.
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Excited to chat here.
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Yeah, I love this idea of like not reporting just for reporting's sake, because I think a lot of our listeners that will resonate with them, right?
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They don't know the why behind it or how to communicate it.
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So, well, why don't we start this?
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Because you know, a lot of our guests come from a marketing ops or robots background, and yours is a little bit different, I think.
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So maybe walk us through your background, your experience, and then um how you didn't purely come up through marketing ops.
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Um, and I'm curious because you spent time in business operations.
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You even said when we talked before shop floor.
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So I mean how they like and then how that ties into how you think about the metrics stuff that we're gonna do.
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Oh, absolutely.
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Uh yeah.
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Uh so for me, my background, not marketing ops at all, um, actually did finance.
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So study finance in school, started my career in investment banking, uh, working and trying to basically sell software companies.
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So I was working with a lot of founders, and what I realized about doing that is I really enjoyed the operation side.
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Uh, as they were explaining their businesses and the challenges that they were solving, I thought that that was something that I wanted to go try.
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And so I joined a startup, uh, pre-revenue as the first finance hire.
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And it turns out that there is not a lot of finance to be done in a pre-revenue business.
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And so what I ended up doing was a lot of business operations.
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Um, and that was everything from finance and accounting, kind of more traditionally, to doing work in supply chain.
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Um, it was an e-commerce business.
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I then left and joined a Series A business called Sendoso uh in the corporate gifting space.
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And that was really where I'd say I had started to build out my uh operations chomps, if you will.
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Um really fun time there.
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Um, I ended up leading the business operations and the data operations team there and had an amazing time.
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Uh, I say today, it's my second favorite startup after my now uh current company account name.
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Um but that was really kind of where um I learned, you know, everything I know, you know, today about you know, kind of marketing ops, first getting exposure to that, uh, revenue ops more generally.
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Um just up being interesting in it's in the GTM tech space itself.
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And so just a lot of learnings there in a short amount of time.
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Um and a lot that we picked up um in now trade you uh kind of do on uh some of the work that we do here at accounting.
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Yeah, it's it's so interesting how people's careers sort of follow these random paths sometimes.
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We so many people we talk to, I find it rare right now.
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It's it but it's really interesting because I have children who are in college and you know, talking about where they want to go and they seem sort of focused, and I'm trying to make sure that they do that, but also be open to like things, be opportunistic, right?
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You know, but 100%.
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I like for me when I was in you know school, going back you know, over a decade at this point, RevOps was not even on my radar.
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I would say even when I was in investment banking at the time, like it wasn't even a thing that I knew of.
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Um like it may be occasionally in like one or two of you know the dozens of companies I worked with, that it was there.
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But uh it's interesting.
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I think sales is similar.
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Like it's not something you go to college for typically, um, but it's just an amazing career.
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Programs, yeah.
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A hundred percent.
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Um, but like these are just amazing opportunities.
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And so I'm hopeful, and I think you guys are doing a lot with like even things like this, so like promote it, get it out there.
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I think that uh as more people realize like that these are options, I think they're amazing options for folks that uh want to kind of explore something a little bit differently, have a huge impact in a business.
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It's a great mix of like qualitative and quantitative.
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So uh super glad and fortunate that I fell into it.
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Yeah, it's it's funny because I when I was coming out of high school, I wanted to be a chemical engineer at an uncle at OEM.
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Uh, but I ended up going to a college that didn't have chemical engineering.
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They had chemistry and they had several engineering programs.
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I ended up in engineering and how I like I never would have predicted I would end up anywhere in the domain of metric marketing.
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So yeah, I I think similar similar for me.
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If you had told me 10 years ago I'd be doing anything on the marketing front for a startup, I would tell you that's uh that's not right.
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It's crazy, right?
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Yeah.
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It is, but it's it's fun, um as I think most ops things are.
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Yeah, it's so it's interesting, but I think ops people do have some tendencies and that we can talk, can't get into about how they think about metrics.
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But it's interesting for me because you even though you said you haven't worked in marketing ops, like you've got exposure to to all those, including BizOps, different ops functions.
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And I'm kind of curious about what you see as uh maybe there's common themes across those that say like gaps where they go, like what are those teams producing uh versus what do those the leaders need for decision making that you're seeing where the like the biggest kinds of gaps you're seeing?
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Yeah, I think there's there's kind of two gaps uh in my mind here.
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There's the gaps for metrics that I'll call it have like natural start and ends with the departments that they're in.
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So as we think about like marketing separately from sales, there's a set of metrics that teams in marketing are focused on as like their full-time job.
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And that's amazing.
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And then you have sales doing the same thing, you have CS doing the same thing, and you've got other departments that are doing the same thing, right?
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The metrics that they own and operate.
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And I think the promise of RevOps has always been well, can we look more holistically across all of those metrics, at least for the GTM side, and have this like end-to-end view.
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My background coming from finance, like that was the view that I was used to.
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We're looking at you know entire companies to understand what is the value, the entire business.
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I needed to understand GTM.
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I also need to understand product and marketing, uh, or product and engineering rather.
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And so, like that for me was kind of always the natural piece.
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And what I still default back to is like effectively like a PL view of the business.
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So I think that like that's one of the gaps that we see is when these metrics kind of cross the chasm, if you will, between departments.
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And that's where you start to get into the fun questions of like, how do we stay aligned?
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And again, we can talk about how we, you know, might use metrics to do that, but it's also a really easy place for friction to start to enter, is when there isn't clear ownership or alignment in those kind of gaps.
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Then I think about it as like kind of going the other way, and that's kind of moving up and down maybe the hierarchy within a business.
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So, you know, what metrics are important to you as an IC, very different than the metrics that your manager probably cares about, very different than the metrics that your CRO cares about, potentially different than what your CEO, founder, or board starts to care about.
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And so I'm sure we'll talk about it, but I think understanding who your audience is, what is important to them, and what you expect them to do with it is table stakes for anybody that is in ops, uh, if you want to succeed in these roles.
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Yeah.
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I think I think that point about because I I I actually wrote a white paper about this in kind of the marketing metric space.
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Um, I guess was it last year or year before?
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I can't remember exactly when, but um that's one of the key takeaways I had is like the metrics that you're reporting.
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It's not that any one of those metrics, you we people would argue they're vanity metrics for marketing.
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And I'm not my point was like they're not necessarily vanity metrics, they are important, but it's the audience you that gets them that matters as much as anything else, right?
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So if you're going to directly go in, look at all the page views we get on our website, they probably don't really care.
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Now, maybe you should care because it's a leading indicator, legging indicator of your, you know, how well your brand is understood and known in the marketplace.
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But do you really this do the other senior executives really care about it?
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Probably not.
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Yeah, there's a soapbox I could get on very easily, which is the idea of vanity, vanity metrics.
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Uh, for for me, there's no real thing is a is a bad metric.
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I mean, there probably is.
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You'll probably get comments on like these are the absolutely terrible metrics.
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But for me, though there's almost always a use for some version of metrics.
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And I think that good operators are able to do is figure out what metrics really matter at certain points in time and in certain situations.
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And the ones that struggle, I think, are the ones that are either completely wed to a single metric for probably good reasons and good intent, but might that be relevant to the audience that they're presenting to, or they're in the other case, which is boiling the ocean and not really sure what to do now that we have all of these metrics compiled, and that's how you end up with dashboards that no one looks at, trusts, etc.
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Um, but I think at the end of the day, like you can find great uses for many metrics.
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And I think one of my sticking points is always like there's no reason why you can't walk and chew gum at the same time.
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Like you can look at multiple metrics.
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There isn't like a single metric that is going to solve all of your business problems.
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I wish there was.
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Um, but I've yet to find it at least myself.
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So if you if you if you do find one, send it my way.
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I'd love to know.
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Uh that that is like so true there.
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I I think of all the different times in my career, different domains where that I would agree, like that's the case, right?
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There's not a single metric.
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I mean, look, your finance guy background, right?
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Is there one kind of report that you that financial people look at to evaluate a company?
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No, there's at least three major ones, right?
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There's three major ones.
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There's cohort analysis that you're doing on the customer base.
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Like it's it's not endless, um, but it's also not one metric.
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And again, it depends on size, stage, maturity of the business, and focus area of improvement that you want to be focusing on.
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Um, and so I think this is where like, you know, what I always try to get to from like a metrics perspective is like, can we get a firm understanding and make sure everyone's on the same page?
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And then can we build a foundation that allows us to explore and click in when we need to?
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And again, the best operators are figuring out ahead of time and being very proactive, but these are the areas we need to go click into, and this is why, and this is what we're gonna go do about it.
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And to me, like that is the fun of ops.
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Like, that's what all of this eventually gets you to is like what actions to take.
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And I think you know, being in the driver's seat is like what I enjoy the most of ops.
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Um, and where I think data can be a great way to just level set, regardless of level you're at.
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Um, it's one of the few things that can get you into a conversation with a CEO when you are in your first year of business.
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The data doesn't change.
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The judgment does, probably.
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Um, but that is always gonna be constant, and you can always lie or rely back on that.
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So uh I think it's kind of like the great equalizer.
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Um so so okay, so I think you described sort of two ends of a spectrum.
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Like one is like all signal, but only one signal.
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The other one's like maybe a lot of signal, but also lots of noise, right?
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There's like too many things.
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How do you how do you how would you guide our listeners or audience to go like how do you think about like which metrics matter, especially metrics that matter for specific audiences?
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And since that's probably the one that's the hardest for most of the operators listening, is like executives.
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Yeah, I mean, a couple different ways I'd approach executives.
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The first one, ask them what matters to them, and then ask them why it matters.
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And you you'll end up in two situations.
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One is like they're not sure, in which case, like that could be great for you because now you can be seen as a trusted advisor and you can actually bring metrics to them that you think matters.
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I always tried to take an ownership uh kind of mindset when I was in ops, even you know, now a little bit different as a CEO myself.
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But uh before that, even you know, I I wanted to be effectively the GM of the business, is how I thought about my role.
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And so like I wanted to be that thought partner.
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And so if we're at situations where they weren't sure what to look at, like I'm coming with a recommendation every time.
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Now, is it right every time?
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Probably not, but like I want to be in that conversation.
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That was just something that was important to me.
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So that's a situation where like they don't know.
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The best case is like they actually know exactly what they're looking for, and they're able to articulate to you why.
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And I think in that case, what you'll find is like these are gonna be great metrics, probably.
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Hopefully, you have trust in them and you know what they're recommending at a certain point in time.
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I think the mistake is when you don't adapt over time because metrics will become stale.
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And so it's not that they become bad metrics, it's not that they become vanity metrics necessarily, it's that it's really difficult to look at the same metric every single week and continually do something with it.
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And so I think what we find is like the best operators are able to figure out what metrics we should be looking at when versus uh kind of anything else here.
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So um having to double click, but that's kind of how we uh I at least think about it.
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Oh, you said something that I caught my attention here.
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You said like if you sometimes it's hard to keep the same metric when you're looking at it for a week and know what to do with it.
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Um I actually went through this recently where someone you know, we had an executive team asking for updates on something on a daily basis, a little bit of a crisis situation.
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So understandable, but it was not a metric that would like the fluctuations day to day could be pretty significant.
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And so the the team that was kind of chartered or tasked with providing that was really struggling with how do we go tell them like we can give you this every day, but we don't want you to overreact or what like how have you like are the do you think about that too?
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Like how frequently, like if say we've got a metric we think is solid, but you know, reporting on it weekly doesn't make sense, but maybe it's monthly, quarterly, but maybe there's something that's every day we should be looking at.
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100%.
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I I think for me, this is kind of like hits on a couple of different pieces.
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One is that oftentimes when you are asked to produce a metric, a report, a dashboard, and someone says, you know, Michael, this is what I need.
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What the best operators are doing is double clicking in because you will often be told things that are needed that are actually not even solving the problem that the person requesting it is actually asking for.
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Like they're they're trying to get this metric for something that they're trying to either do, decide, or change in the business.
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And you really need to understand what that is to then decide on the frequency of it.
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I think if you're just approaching this as a list of tasks for you to do, someone asks me for this dashboard or this report or this metric on a weekly, daily basis, pick your time period and you just produce it.
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If you're a junior analyst, that is probably okay.
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As you move up in the business, though, and you want to have a real impact on it, you need to understand the why behind it.
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And the harsh reality is sometimes the people requesting it actually don't understand the why.
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And that is really, really challenging to be in.
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And that's probably a whole different episode that you go deep into.
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Um, but I think the more that you can really understand like what are they trying to get to?
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What are the specific actions that are gonna be done?
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And I always try to break it down to like the simplest terms.
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Metrics are gonna go up, they're gonna go down, they're gonna stay the same over some period of time.
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Do we have ideas of what is gonna happen in each of those three scenarios?
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It's only three.
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It should be possible for us to get to at least that.
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And if they're really clear cut, then amazing.
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Like that's the perfect scenario.
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Usually they're not.
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And so that's where you know you can either again rely on the people that are requesting it, ask for advice from others that have been in similar situations that might be able to help guide you, or come with a recommendation yourself.
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And this is where I think like, you know, you can start to trust your gut a little bit.
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Like you, as an operator, have access to a lot of other data points too.
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Can you use those to inform a recommendation on like what we should be doing here?
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Um, and again, this is I think one of those things where it is easier said than done.
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I've been in situations, I probably requested it myself for like the hey, can I get the daily update of this?
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Um, but what you find is like the half-life of these things is not very long usually.
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Um, and so I think I'm always just trying to anchor back to like, are we really getting done with this what we wanted to originally?
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And just having touch points, like maybe end of the week, the first time you do it, even like, hey, is this still relevant?
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Is this still actually helping us?
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And if someone can't articulate exactly what those actions are, then you know, maybe it's time for uh for you to look at a new metric or you know, maybe take a different approach.
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Well and and I think um not everyone is great at to say they may be great at describing this is what I want, but they may not say, go like, I just needed this one time.
00:16:26.250 --> 00:16:34.889
Like I've got a new decision I need to make or change I need to make, versus uh this is something I want to see for the foreseeable future.
00:16:34.889 --> 00:16:45.370
But then you're I like your point, like on a regular basis, uh it it not only doesn't make sense, I think you should proactively ask, like, is this still something you need?
00:16:45.529 --> 00:16:45.769
Right?
00:16:45.850 --> 00:16:46.730
Because 100%.
00:16:47.289 --> 00:16:56.089
Um it's easy it's easy to just add to that list of things when it may not be relevant and that people aren't always great, kind of like the government, right?
00:16:56.089 --> 00:16:58.490
When something comes into place, right, it doesn't go away.
00:16:59.289 --> 00:17:04.730
Yeah, you don't you don't find a lot of obstinates coming in proactively cutting the number of reports that are being generated.
00:17:04.730 --> 00:17:07.529
I mean, usually to your point, it's just adding to it.
00:17:07.529 --> 00:17:10.329
But I think a lot of folks would do well by doing these resets.
00:17:10.329 --> 00:17:22.170
And again, pick the time that makes the most sense for you is something that we try to do at least annually at my last business, where we're looking at, you know, are these dashboards, are these reports, are they being used, are they actually like helpful for the team or are they outdated?
00:17:22.170 --> 00:17:27.049
One kind of like framework that I like now use is like the idea of like projects versus programs.
00:17:27.049 --> 00:17:31.450
It's a program that's gonna be ongoing, you know, we need it for you know extended periods of time.
00:17:31.450 --> 00:17:33.690
Within part of that, you might even have Evergreen.
00:17:33.690 --> 00:17:36.970
These are the metrics we're gonna be tracking every single time forever.
00:17:36.970 --> 00:17:40.009
Revenue growth, customer logo counts, net retention.
00:17:40.009 --> 00:17:42.009
These are metrics I'm always gonna be looking at.
00:17:42.009 --> 00:17:43.289
And then there's the projects.
00:17:43.289 --> 00:17:44.809
This thing is on fire.
00:17:44.809 --> 00:17:46.170
I need to put out the fire.
00:17:46.170 --> 00:17:48.970
This is my indicator for why it is on fire.
00:17:48.970 --> 00:17:52.329
I probably only hopefully need this for a day.
00:17:52.329 --> 00:17:54.250
Um, in the best case scenario, maybe.
00:17:54.250 --> 00:18:06.250
Um, but it's something where, you know, that should eventually be, you know, kind of archived, move on, um, and you know, kind of now you're gonna be shifting your focus back to the probably million other fires that you have going in uh the fun world of ops that we live in.
00:18:07.129 --> 00:18:25.690
Yeah, but I I think it I get I I see a lot, and I've done it myself, where I get caught up in conversation and I take uh I take an executive saying something as big, go do this, whereas what they were really thinking was this is an idea, right?
00:18:25.690 --> 00:18:29.690
It wasn't necessarily they expected you to go run with it and do something.
00:18:29.690 --> 00:18:36.569
Um and I think that's an easy it's really hard in my experience, it's hard to know when that's happening, right?
00:18:36.569 --> 00:18:38.089
Which scenario in.
00:18:38.089 --> 00:18:44.250
And I've been told a lot recently, like you ask a lot of questions because I do.
00:18:44.250 --> 00:18:46.490
I like ask a lot of questions to get clarification.
00:18:46.490 --> 00:18:52.329
It's not because I'm trying to be a passive, I want to make sure we're saying the same thing and agreeing on what we're gonna do and when.
00:18:52.889 --> 00:18:53.369
100%.
00:18:53.369 --> 00:18:54.889
I think like finding the balance, right?
00:18:54.889 --> 00:18:56.329
It's like very individualistic.
00:18:56.329 --> 00:19:03.690
One thing that I tried to do in any of the analytics or optionals that I did is like really build strong relationships with the stakeholders that were requesting things from me.
00:19:03.690 --> 00:19:09.210
Um eventually my last company where I was running a bigger team, like and they were doing a lot of the analysis themselves.
00:19:09.210 --> 00:19:12.410
What I was actually spending almost all of my time doing was just that relationship building.
00:19:12.410 --> 00:19:18.089
So if somebody asks me for a report or asked my team for a report, I could go to them and you know, ask them like, is this really what you want?
00:19:18.089 --> 00:19:19.849
Is this really high priority?
00:19:19.849 --> 00:19:25.129
As we think about, you know, putting this in the list of other requests that we have, like, where does this rank for you?
00:19:25.129 --> 00:19:30.649
And just like diving in that way, I found it'd be a really helpful way for us to like avoid some of it.
00:19:30.649 --> 00:19:33.049
And again, it's not always going to be avoidable.
00:19:33.049 --> 00:19:36.170
Um, it's definitely still one of those things where it is easier said than done.
00:19:36.170 --> 00:19:47.690
But um I think the more that you can just like kind of build those relationships, the more you'll start to you know be involved in like the decision making, which is ultimately what I wanted to get to as an operator, and I think most operators want to get to.
00:19:47.690 --> 00:19:51.529
It's you know, the analytics, the reporting, the dashboards, these are like a means to an end.
00:19:51.529 --> 00:19:54.970
To me, the end was I want to get into the decision-making conversations.
00:19:54.970 --> 00:20:03.049
Um, and so you know, this is kind of a great way to do it, but to your point, it can also be really challenging if you become just overwhelmed with building and building and building and building.
00:20:03.529 --> 00:20:03.849
Right.
00:20:03.849 --> 00:20:04.649
Yeah.
00:20:04.649 --> 00:20:23.289
Um so you talked about well, I guess any of these metrics, um, and especially the ones you talked about, the the the those chasms between departmental kind of stuff, um, one of the I think one of the sands in the gear, if you will, that causes problems sometimes.
00:20:23.289 --> 00:20:26.089
Different definitions of metrics, right?
00:20:26.089 --> 00:20:27.369
Both reporting metrics.
00:20:27.369 --> 00:20:29.930
We use different ways of getting to them.
00:20:29.930 --> 00:20:34.009
Um how do you think about that?
00:20:34.009 --> 00:20:35.210
Like what have you done for that?
00:20:35.210 --> 00:20:40.009
And I know you and I, when we talked before, you talked about things like life to value and CAC and those.
00:20:40.009 --> 00:20:44.649
I don't know if there are others that you think about, and maybe you have even specific definitions that you go with.
00:20:44.649 --> 00:20:48.649
But how do you how do you handle that or how have you handled that kind of thing?
00:20:48.649 --> 00:20:50.649
Just to be aligned on those.
00:20:50.970 --> 00:20:53.690
Yeah, I I I've honestly really struggled here.
00:20:53.690 --> 00:21:04.170
This is like one of those uh challenges I'll say that I come across that like I can intellectualize why it's challenging, but I can never get myself to understand why it doesn't take 30 seconds to solve this problem.
00:21:04.170 --> 00:21:13.369
It's one where it feels like what the answer is is like, well, why don't we just have like a metrics dictionary that everyone uses and agrees on and goes off of, right?
00:21:13.369 --> 00:21:18.730
Um and if it was as easy as that, uh there'd be a lot less LinkedIn content, probably.
00:21:18.730 --> 00:21:31.690
Um, but I I think what what I found it to be to work in the real world, I'll call it, is it's just consistent um kind of overtime reinforcement of what these definitions are.
00:21:31.690 --> 00:21:38.649
So the earlier you start with this, the earlier you start with data generally, the earlier you start with like clean Ingrid reporting, the easier this does become.
00:21:38.649 --> 00:21:43.769
But in any case, it's going to take work to continually keep people on the same page.
00:21:43.769 --> 00:21:48.490
Even if the definition hasn't changed, the people in your org probably has changed.
00:21:48.490 --> 00:21:50.329
Parts of the business probably have changed.
00:21:50.329 --> 00:21:55.690
And so the definitions that you had six months ago, a year ago, you know, again, pick the time frame that makes the most sense for you.
00:21:55.690 --> 00:22:04.970
They probably have changed at least slightly, or folks don't know where to look because it's only a portion of their day that they're spending thinking about this thing.
00:22:04.970 --> 00:22:15.930
And I think that's like one of the harder parts for ops, where 100% of your time and energy could be focused in this one area for weeks, if not months, if not years, that takes up 1% of the time of an executive.
00:22:15.930 --> 00:22:21.769
And so it's crystal clear to you that the definition of lifetime value to CAC is in your business.
00:22:21.769 --> 00:22:25.289
And for them, they're spending next to no time thinking about this potentially.
00:22:25.289 --> 00:22:30.089
Um, and so like being able to bridge that gap, again, it just takes consistency.
00:22:30.089 --> 00:22:32.170
There's like really tactical things that we try to do.
00:22:32.170 --> 00:22:42.490
I would build a metrics dictionary, I would try to build definitions and tool tips and dashboards and reports that you're doing just to continue to reinforce, even if it seems like so basic.
00:22:42.490 --> 00:22:44.329
What is a customer?
00:22:44.329 --> 00:22:47.289
Seems so basic, but it can have different definitions.
00:22:47.450 --> 00:22:49.690
No, that's like one of the hardest questions to answer.
00:22:49.690 --> 00:22:50.329
I ran.
00:22:51.049 --> 00:22:51.289
Yeah.
00:22:51.289 --> 00:22:54.250
And so uh I again, I think just like continually reinforcement.
00:22:54.250 --> 00:22:59.129
I have been thinking a lot more recently about just like how much enablement is really needed here.
00:22:59.129 --> 00:23:05.289
I think it's like one of the bigger gaps in analytics and reporting, is just not treating it like a good, again, like an ongoing program.
00:23:05.289 --> 00:23:07.210
It's this like one and done thing.
00:23:07.210 --> 00:23:09.289
That's just not the case in analytics and reporting.
00:23:09.289 --> 00:23:16.250
It is going to be continued energy and effort needed to keep consistency, to keep alignment across these teams.
00:23:16.250 --> 00:23:22.250
Um, but I think I had yet to meet a company that has not told me they have some form of misalignment somewhere within the org, right?
00:23:22.250 --> 00:23:28.329
Um, it's just one of those ever-present uh challenges that you'll have um that hopefully you can just reduce over time.
00:23:28.329 --> 00:23:30.970
But um I don't think the goal necessarily should even be zero.
00:23:30.970 --> 00:23:33.930
Um, or maybe it should be the goal, but I don't know if you'll get there.
00:23:34.730 --> 00:23:48.649
Yeah, I so it's I I really love this because I think most people would go the real the answer is just we just need to document it and make it visible to the right people at the right time.
00:23:48.649 --> 00:24:04.009
I think your point about the amount of time that certain people have to access you know that are spending with this is so small, and they're like relearning every time that uh we can't assume that they should know it and understand it.
00:24:04.009 --> 00:24:09.609
And we don't want them to make assumptions incorrectly about what the data is telling them if because they don't understand it.
00:24:09.609 --> 00:24:12.809
And so it's incumbent on us to make sure that we're reinforcing.
00:24:12.809 --> 00:24:14.250
I mean, I really like that idea.
00:24:14.250 --> 00:24:15.849
Think of it as an enablement one.
00:24:15.849 --> 00:24:21.369
So that um I think that's a great tip from for for just for everyone listening.
00:24:21.369 --> 00:24:31.289
Like, yes, you should document this, yes, you should figure out ways to do it, but and you should also be reinforcing it on a regular basis with the stakeholders that matter the most.
00:24:31.769 --> 00:24:33.450
Yeah, I think that's exactly right.
00:24:33.450 --> 00:24:40.569
And like I said, the documentation doing a day, the enforcement enablement, it's gonna take you probably the rest of your career.
00:24:40.569 --> 00:24:43.690
So uh yeah, just uh just baby steps.
00:24:44.569 --> 00:24:46.009
Yeah, that totally makes sense.
00:24:46.009 --> 00:24:53.210
Um, okay, so another thing that I've seen, and I've probably been guilty of this too, is kind of over-engineering.
00:24:53.210 --> 00:24:57.930
And I I hate to throw something under the bus, but we'll take attribution as an example, right?
00:24:57.930 --> 00:25:02.889
I get I get asked it's a great example, like which what kind of attribution model do you like?
00:25:02.889 --> 00:25:04.809
And I was like, I really don't care.
00:25:04.809 --> 00:25:10.170
Um as long as you use the same one consistently over time.
00:25:10.170 --> 00:25:11.849
Because to me, that's the real value.
00:25:11.849 --> 00:25:18.649
So it's easy to get like I don't even remember all the different versions anymore, like because I just sort of stopped paying attention.
00:25:18.649 --> 00:25:34.329
But like, do you think that there's value in trying to simplify some of these things versus making them more um I'll I'll use the word robust since it's it seems to have a more positive connotation, but like the complicated.
00:25:35.369 --> 00:25:48.329
Yeah, I I actually think this is one where um I probably maybe in the middle one in the sense of yes, metrics should 100% be simplified if they're going to be used for enablement of other teams.
00:25:48.329 --> 00:26:05.769
Like it's just much easier to explain a single metric to someone than a you know Black Shooles model that is overly complex or you know, a machine learning-based model that you hope that your data scientist understands, but you're not really totally sure, right?
00:26:05.769 --> 00:26:10.170
Um what I try to think about is like what action are you going to be taking with it?
00:26:10.170 --> 00:26:14.889
And I think if like human in the loop is needed here, simplicity is gonna win almost every time.
00:26:14.889 --> 00:26:20.089
It's kind of interesting now because there's definitely you know decisions and actions that can now be taken without humans in the loop.
00:26:20.089 --> 00:26:28.490
And at that point, I might argue having more better, you know, maybe not over-engineered, but you know, more sophisticated modeling can actually be very, very helpful.
00:26:28.490 --> 00:26:31.289
And so it's very situationally dependent.
00:26:31.289 --> 00:26:36.809
Um, one thing that I always try to do is I never want to be the limiting factor in getting to an answer if possible.
00:26:36.809 --> 00:26:46.009
So if there's complexity to be had, like I want to be, you know, at least understanding internally what the answer is for things that are very complex.
00:26:46.009 --> 00:26:56.889
But I then want to use my judgment on what is the right level of simplicity or you know, sophistication that needs to be given to the team based on who the audience is, what the request is, what the impact is.
00:26:56.889 --> 00:27:07.609
So one way of answering the question, I err towards simplicity for the most part, uh, but I do think we're entering a place um today where actually more come like more sophistication could be a good thing.
00:27:07.609 --> 00:27:11.210
Um, but it's definitely a two-sided uh or a double-edged sword a bit.
00:27:11.210 --> 00:27:12.809
So you have to be careful about it.
00:27:12.809 --> 00:27:19.289
Um there's definitely ways to unlock it today that I think could you could not have done pre-2023, probably for most teams.
00:27:20.089 --> 00:27:20.569
Yeah.
00:27:20.569 --> 00:27:38.329
I am I see what you're saying, but I still lean towards I would lean towards like if if I had to all other things being equal, I think I would lean for something that's simpler for at least two reasons.
00:27:38.329 --> 00:27:42.649
One, it's easier to understand what the output is.
00:27:42.649 --> 00:27:52.089
Because you kinda the second is it's easier to explain to somebody who's less familiar with the details of how the sausage is made on the other end.
00:27:52.889 --> 00:27:56.089
Um yeah, I I think this this goes back a little bit to me.
00:27:56.089 --> 00:28:04.410
Sorry, I think I'm about a half-second delay, but um I was gonna say I think it goes back to me of like how good of relationships do you have and like how much enablement are you doing with the teams?
00:28:04.410 --> 00:28:06.329
I think in a vacuum, I totally agree with you.
00:28:06.329 --> 00:28:10.730
And I think like for most teams, 80% of the time, simplicity is going to win out.
00:28:10.730 --> 00:28:13.129
It probably should win out more often than not.
00:28:13.129 --> 00:28:24.490
Um I think if you have the ability to build more robust models that are more predictive, for instance, I would build those and use those internally.
00:28:24.490 --> 00:28:28.089
Now, I'll take an example of this, could be customer health scoring.
00:28:28.089 --> 00:28:36.170
You can build very, very lightweight customer health scores using two metrics and some weighting on there that don't really matter too much, right?
00:28:36.170 --> 00:28:43.769
But your data science team could build a 100-factor model for predicting customer health.
00:28:43.769 --> 00:28:46.250
And that model might be 5% more accurate.
00:28:46.250 --> 00:28:50.649
Now, your CSD might not take a ton of different action between those two models, right?
00:28:50.649 --> 00:28:57.289
And it's going to be certainly easier to enable them and to explain to them what a customer health score is if there's only two components, they will more likely take action with it.
00:28:57.289 --> 00:29:09.129
But I want the answer to understand what is the customer health based on this more predictive model because me as an operator needs to understand what that is so that I have the visibility at least into it.
00:29:09.129 --> 00:29:13.609
And then we're making the judgment call that simplicity is going to win out in this case.
00:29:13.609 --> 00:29:16.410
And so I think there's like two sets of metrics that you can have.
00:29:16.410 --> 00:29:25.450
There's the metrics that you're actually using to take action with, but there's metrics that you should be looking at to monitor the health of the business that you don't necessarily need to share with everyone else.
00:29:25.450 --> 00:29:27.210
And I think this kind of goes back to what you were saying earlier.
00:29:27.210 --> 00:29:29.690
It's like, what are the stakeholders who needs to be involved in this?
00:29:29.690 --> 00:29:36.809
Um, and so again, I'm actually fine with having different sets of metrics for different folks, uh, depending on like their sophistication levels.
00:29:40.730 --> 00:30:01.930
You know, you know, I I I'm gonna walk myself back a little bit here because I think what you just described is what I would argue for in general, which is you've got your simpler version of a model, the say it's a predictive model, and there's a level of effort to get to one that's five, ten, fifteen, like a much a more accurate one.
00:30:01.930 --> 00:30:16.730
And I think the question for me is do we think that the level of effort uh to add an additional sophistication, complexity, whatever, is going to yield enough benefit to warrant that additional effort?
00:30:16.730 --> 00:30:18.410
Right, that's a great question.
00:30:18.410 --> 00:30:20.009
Initially and ongoing.
00:30:20.250 --> 00:30:23.609
Yeah, that that's a question I I wish more operators were thinking about.
00:30:23.609 --> 00:30:29.690
Um I think that's that's actually the heart of a lot of ops is making those calls on when does it make sense, right?
00:30:29.690 --> 00:30:34.730
And this is where I think you can start to add in, you know, what is the revenue lift that we would get from this more predictive model?
00:30:34.730 --> 00:30:37.289
Is it worth the, you know, how many hours is it going to take?
00:30:37.289 --> 00:30:40.809
What is like, you know, are are the actions going to be different?
00:30:40.809 --> 00:30:45.930
If they're not, like, then yeah, maybe default to the single, you know, the simple version every single time.
00:30:45.930 --> 00:30:55.930
I think as you get bigger and more sophisticated and you have more people and you can go roll out, you know, kind of more nuanced workflows, I think you probably start to make that call more towards the complex model.
00:30:55.930 --> 00:30:59.049
Um, but again, it's very situationality dependent.
00:30:59.049 --> 00:31:00.889
Um, I I would say so.
00:31:00.889 --> 00:31:02.250
Uh I love that question.
00:31:02.250 --> 00:31:07.289
I think that's uh such a fun, like those are the types of questions I love just like focusing on as an operator.
00:31:07.289 --> 00:31:08.490
Those are the fun ones.
00:31:08.730 --> 00:31:09.210
Yeah.
00:31:09.210 --> 00:31:15.210
I I mean, I won't say like I I think as Thomas Sowell, economist, right?
00:31:15.210 --> 00:31:21.769
If people are could go look for it, he I think he's the one who's attributed to saying like there's no answers, there's only trade-offs, right?
00:31:21.769 --> 00:31:23.369
Some or something close to that.
00:31:23.369 --> 00:31:30.170
And I think it really that's how I think about this stuff now is like what's the trade-off for that like 1%?
00:31:30.170 --> 00:31:37.450
Is it is that incremental cost, effort, even benefit gonna be be worth it?
00:31:37.450 --> 00:31:51.289
But I think the other part, like this is where there's there's a there's a point at which the complexity probably doesn't yield much of more value, but falls into what I would call the clever space, right?
00:31:51.289 --> 00:32:06.410
Where it's there's a for sure, like it's the kind of thing like you get really excited about if you're really into this kind of stuff, and you go like, this is so cool, but at the end of the day, like it's actually not much more predictive or helpful from a decision-making standpoint.
00:32:06.410 --> 00:32:12.970
I think that's the that's where I get stuck, is like I don't I don't want stuff that's clever, I want stuff that's useful.
00:32:13.529 --> 00:32:13.930
Yeah.
00:32:13.930 --> 00:32:18.490
Which I think like until you do some of the work, I think it's hard to know which of those it's going to be, right?
00:32:18.490 --> 00:32:21.529
So I think there's always gonna be some form of like having to, you know, kind of figure that out.
00:32:21.529 --> 00:32:25.049
And like I think there's good benefits of to exploring that creativity.
00:32:25.049 --> 00:32:49.049
But I will say I think you're hitting on a really good point, which I think a lot of times if you do come up with even a clever solution, call it that is actually helpful, even I think one of the challenges that folks have when they're connecting the dots between the data work that they're doing and the reporting work that they're doing, and how it's taken action is an executive, unfortunately, probably doesn't really care about the process that went into coming up with the cut the clever solution.
00:32:49.049 --> 00:32:54.170
And that can be a little disheartening for a lot of operators, where like that's where I like it.
00:32:54.170 --> 00:32:55.450
That is the most fun part.
00:32:55.450 --> 00:32:59.609
It's like, hey, I spent so much time and energy and I figured out this really cool solution.
00:32:59.609 --> 00:33:04.889
And again, it might be impactful, but like executives only care about the impact for the most part.
00:33:04.889 --> 00:33:06.250
And again, it'll be rare.
00:33:06.250 --> 00:33:12.649
And you might find a case where you know you can go explain exactly what you did to everyone in the in the business, but those are rare, it's gonna be small.
00:33:12.649 --> 00:33:22.889
Um, and so you know what I always do in those situations, and what I ran an ops team myself is like what we would do is like we're gonna share the clever solutions internally with our ops team, give you the forum, present it out.
00:33:22.889 --> 00:33:24.250
We're interested in it, it's super cool.
00:33:24.250 --> 00:33:26.569
Explain it like, hey, or you know, it's awesome.
00:33:26.569 --> 00:33:32.569
To the exec, I'm probably gonna give them 30 seconds of what was just explained in 30 minutes, uh, because that's what they care about.
00:33:32.569 --> 00:33:38.569
Um, and so that's kind of that's kind of one of the challenges I always came across in ops is uh just don't know what the right level is.
00:33:38.569 --> 00:33:41.609
Um, but uh other operators will appreciate it at least.
00:33:41.609 --> 00:33:42.730
Just know that.
00:33:42.970 --> 00:33:43.529
Yeah.
00:33:43.529 --> 00:33:46.089
So celebr celebrate within the team, right?
00:33:46.089 --> 00:33:47.849
Because it's like yeah.
00:33:47.849 --> 00:33:53.210
So people who get it will understand what it took to get it to get to that totally.
00:33:53.210 --> 00:33:58.889
So but so but you said you would reframe things with the the executives, and I'm with you, right?
00:33:58.889 --> 00:34:03.690
They don't most executives are not going to care about all that kind of detail, that kind of stuff.
00:34:03.690 --> 00:34:08.809
How like in your experience, like what are the kinds of things that the executives care about?
00:34:08.809 --> 00:34:10.250
What are the metrics?
00:34:10.250 --> 00:34:17.130
And then think about how would you tie what you're you know, an ops person might be reporting on.
00:34:17.130 --> 00:34:19.050
How do you tie that to what they care about?
00:34:19.450 --> 00:34:25.289
Yeah, I mean, I I think at the end of the day, like we're in the business, at least, you know, somewhere not a nonprofit and making money.
00:34:25.289 --> 00:34:29.050
And so you think about your executive team, like ultimately that's what they care about.
00:34:29.050 --> 00:34:31.690
It's are we making more revenue than we did before?
00:34:31.690 --> 00:34:39.930
And are we retaining it if we're in, you know, it called a traditional SaaS business, but even still, um, are we able to retain um that business?
00:34:39.930 --> 00:34:47.130
Like again, uh partially a bias because of my background, but it ultimately does come back to just the financial profile of the business.
00:34:47.130 --> 00:34:49.530
And there's exceptions out there for sure.
00:34:49.530 --> 00:34:52.090
Um, but that's really what executives are tasked with doing.
00:34:52.090 --> 00:35:01.930
Like their job is for the company to make more money, um, either from a top-line basis or from you know a profitability basis at the eBaDL level as you get you know uh kind of bigger and more sophisticated.
00:35:01.930 --> 00:35:06.650
Everything that you need to be doing is needs to be able to be tied back to that.
00:35:06.650 --> 00:35:10.410
And in ops, like look, it might not be the completely linear path.
00:35:10.410 --> 00:35:17.769
Like everything that you're doing, you know, the customer health modeling that you're doing might not be directly attributable back to net retention, but hopefully it will.
00:35:17.769 --> 00:35:20.810
And hopefully that they're you know, you can at least paint that picture of it.
00:35:20.810 --> 00:35:33.370
And I'd say like, if you can't figure out how you're contributing to increasing revenue, increasing profitability in the business, you might want to take us a second to pause and think about why are we doing what we're doing?
00:35:33.370 --> 00:35:37.530
Because that's really what the job of hops is, and in my opinion, is is driving that.
00:35:37.530 --> 00:35:40.730
And again, I think it's you know, wear that like the GEM kind of hat.
00:35:40.730 --> 00:35:43.769
You are the owner of the business, like is that what you would care about?
00:35:43.769 --> 00:35:47.769
And I think you know, in 99% of cases here, it's that's what it's gonna be.
00:35:50.090 --> 00:36:00.090
So one of the things that I say regularly on the podcast to our listeners is if you don't know how your company makes money, right, you should go figure that out.
00:36:00.090 --> 00:36:02.330
I mean, is that is it as simple as that?
00:36:02.330 --> 00:36:05.930
And if so, like it sounds way simpler than it probably is.
00:36:05.930 --> 00:36:08.250
Like, how how have you gone about doing that?
00:36:08.250 --> 00:36:16.730
You have the benefit of having a different kind of background, I think, than some of the people who are listeners, but no, I think you're I think you're spot on.
00:36:16.890 --> 00:36:19.769
Um I I was uh talking to someone earlier, and I think this is totally true.
00:36:19.769 --> 00:36:28.570
Where like, you know, in RevOps, I think sometimes the the revenue gets lost a little bit, and we think about it as just ops, but like the revenue is actually the the important piece here, right?
00:36:28.570 --> 00:36:30.650
Um understanding how your company makes money.
00:36:30.650 --> 00:36:34.890
Look, it can be really complex, especially if you're working in like a very big enterprise that has multiple product lines.
00:36:34.890 --> 00:36:39.130
Um, but like that is some of the homework that I would be doing day one as an operator.
00:36:39.130 --> 00:36:47.370
Is like I really just need to understand that because again, like the finances is the common language with across the business with how you understand what is happening.
00:36:47.370 --> 00:36:57.210
And if you can understand it, and again, you don't need to become a financial analyst, you don't need to spend years and years going through it, but you should understand like how does your company make money?
00:36:57.210 --> 00:36:58.410
Who are you selling to?
00:36:58.410 --> 00:36:59.610
Why do they buy from you?
00:36:59.610 --> 00:37:01.050
What is the price point of it?
00:37:01.050 --> 00:37:06.170
Like, all of those things are within the grasp of everyone in operations to really understand.
00:37:06.170 --> 00:37:13.690
And again, I think just like reminding yourself and refreshing on a periodic basis can be helpful because it's really easy to do that as part of like onboarding.
00:37:13.690 --> 00:37:15.610
It's like, oh yeah, of course, this is how we make money, right?
00:37:15.610 --> 00:37:21.530
And then a quarter goes by and you're knee deep in a CPQ implementation, and you might not really be thinking totally about it.
00:37:21.530 --> 00:37:27.690
Although CPQ may be a bad example since you're in pricing and food quoting, but um, you know, you're building a customer health tour, right?
00:37:27.690 --> 00:37:30.170
It's like, how are we making money again?
00:37:30.170 --> 00:37:34.090
Um, and so I think just like consistently reminding yourself can be really helpful.
00:37:34.090 --> 00:37:37.370
Um, truth be told, you could probably go talk to your CFO.
00:37:37.370 --> 00:37:47.130
Um, your CFO would probably love to share with you how is your company making money or your VP of finance, uh, depending on the size of your business, like they would love for someone to be as excited about it as they are.
00:37:47.130 --> 00:37:53.290
So uh I would I would go to them um if you can, and they will talk to you for years and years about it.
00:37:53.450 --> 00:37:54.890
Um Yeah.
00:37:54.890 --> 00:38:14.570
I I mean I've I've had a lot of interesting conversations with financial leaders, CFOs, FBA leaders, whatever, that um have really helped me understand how they um make decisions or make recommendations to the CEO for decisions.
00:38:14.570 --> 00:38:26.490
And when I've gone to go pitch ideas, I generally now lean towards I go to them to kind of go like, does this does this make sense?
00:38:26.490 --> 00:38:28.330
Does this like what am I missing?
00:38:28.330 --> 00:38:28.650
Right?
00:38:28.650 --> 00:38:33.530
Because they they will ultimately be a part of that decision process, whether you like it or not.
00:38:33.930 --> 00:38:34.410
100%.
00:38:34.410 --> 00:38:40.330
I think it's the most closely related role to many operations roles, is this the CFO.
00:38:40.330 --> 00:38:45.850
Um, and again, it's again company dependent for sure, but like they care about a lot of the same things that you care about.
00:38:45.850 --> 00:38:47.450
Like they care about how the company makes money.
00:38:47.450 --> 00:38:49.450
So they care a lot about pipeline.
00:38:49.450 --> 00:38:55.130
They want to understand who is buying, why are they buying, they want to understand what that means for profitability.
00:38:55.130 --> 00:38:56.890
They want to know are you retaining these customers?
00:38:56.890 --> 00:38:58.250
Again, very similar.
00:38:58.250 --> 00:39:04.330
I think in ops, you're probably gonna go click in layers deeper than they ever will because that's only a portion of their job.
00:39:04.330 --> 00:39:08.970
But I think like building that really strong relationship between the two can be just so mutually beneficial.
00:39:08.970 --> 00:39:12.010
And it doesn't mean that ops needs to report into the CFO.
00:39:12.010 --> 00:39:13.769
That again, hold other discussion.
00:39:13.769 --> 00:39:16.490
Uh, but you speak a lot of very similar language as is.
00:39:16.490 --> 00:39:20.650
Like, I just encourage folks to uh to chat with them more frequently.
00:39:20.650 --> 00:39:26.890
Um, and I think shared learnings across both will be make literally everyone's job easier, uh, even when it comes to something like board reporting.
00:39:26.970 --> 00:39:27.210
Yeah.
00:39:27.450 --> 00:39:28.730
Makes it so much simpler.
00:39:29.050 --> 00:39:29.690
Yeah.
00:39:29.690 --> 00:39:33.130
It's so it's interesting as you were talking about this.
00:39:33.130 --> 00:39:44.090
There's I think for the for the people who are in here still sort of scratching their heads about how would I go have that conversation to have that like language, and why should I care about how the company makes money?
00:39:44.090 --> 00:39:54.650
It seems intuitively obvious, maybe to me, but I think one of the things that many of the people who who are listening will say is like one of their jobs should be the advocate for the customer.
00:39:54.650 --> 00:40:01.370
So when they get a request to go do something, put something in the market, change something on the website, whatever it might be.
00:40:01.370 --> 00:40:06.410
One of the things I always say is like, I my job is to advocate for the customers too, right?
00:40:06.410 --> 00:40:08.330
Make sure that we're doing right by them.
00:40:08.330 --> 00:40:12.010
And if if you think about it that way, right, that should be a part of your job too.
00:40:12.010 --> 00:40:20.970
Like if you're being asked to go do something, invest in a tool, it's whatever, part of your job should be am I using the company's money wisely?
00:40:20.970 --> 00:40:23.130
Even though I was asked by somebody senior, right?
00:40:23.130 --> 00:40:24.890
So It doesn't mean you say no.
00:40:24.890 --> 00:40:34.890
It just means like you should think about that in the process of whether or not you think you should push back, challenge, ask questions before you just go off and do.
00:40:35.450 --> 00:40:36.330
I couldn't agree more.
00:40:36.330 --> 00:40:36.570
Yeah.
00:40:36.570 --> 00:40:38.650
I don't think these things are mutually exclusive at all.
00:40:38.650 --> 00:40:41.930
Um it's just a it's a question of time horizon, I think.
00:40:41.930 --> 00:40:50.170
Um so yeah, I think you know, if you take a customer-centric approach in the longer term, like you are probably going to be driving towards a more profitable business, which is ultimately great for everyone.
00:40:50.170 --> 00:40:51.610
So yeah, I don't think about those two.
00:40:51.610 --> 00:40:52.570
It's like separate things.
00:40:52.570 --> 00:40:58.730
To me, they're uh directly interrelated, even though it might not show up in the PL in that uh yeah specific period.
00:40:59.530 --> 00:40:59.850
Yeah.
00:40:59.850 --> 00:41:03.850
I mean, I was thinking of them more as analogs as opposed to opposing forces.
00:41:04.090 --> 00:41:05.130
Oh, totally.
00:41:05.130 --> 00:41:05.930
Yeah.
00:41:06.410 --> 00:41:07.050
Yeah.
00:41:07.290 --> 00:41:07.530
Yeah.
00:41:07.690 --> 00:41:10.170
And so like and so that's that's really what I was thinking about.
00:41:10.170 --> 00:41:13.130
So just real quick, I'm curious now.
00:41:13.130 --> 00:41:21.690
Um when you were presenting numbers, or if or if you were like had somebody coming to you, like, how should I go take this stuff to my MOPS person?
00:41:21.690 --> 00:41:24.410
I'm gonna be taking numbers to our leadership.
00:41:24.410 --> 00:41:31.690
How what are some general principles or guiding guidance you would give them as they're preparing for that?
00:41:32.090 --> 00:41:32.410
Yeah.
00:41:32.410 --> 00:41:37.370
One thing I've come back to every time in my career has been the idea of a one pager.
00:41:37.370 --> 00:41:48.890
If I can't create one PowerPoint slide, it doesn't have to be PowerPoint, but a slide that has everything summarized and synthesized, and they can't get it or grok it in 20 seconds.
00:41:48.890 --> 00:41:50.650
I haven't done my job well.
00:41:50.650 --> 00:41:57.370
Now I want to have and I will likely present more than just a single slide, but that was always what I kind of anchored back to.
00:41:57.370 --> 00:42:02.090
It was can I just get all my ideas across in this one super easy to digest way?
00:42:02.090 --> 00:42:07.769
And anytime I wasn't able to do it, and you know, you share it with somebody else in your team, they're like, What are you trying to get here?
00:42:07.769 --> 00:42:09.210
That was a disaster.
00:42:09.210 --> 00:42:10.970
Those presentations never went well.
00:42:10.970 --> 00:42:13.769
Um, if I didn't have that one behavior, they never went well.
00:42:13.769 --> 00:42:22.090
Um, I one of the things I I mean, I used to sit in meetings all the time, and like you'll cut, you know, you build a 50-page deck and you'll see people flipping through it, and they'll literally stop and like slide two.
00:42:22.090 --> 00:42:28.810
It's like people don't have the time to go through layers and you know, as deep of analysis as you ever want.
00:42:28.810 --> 00:42:30.170
Again, even if it's interesting to you.
00:42:30.170 --> 00:42:32.810
So that's something I've always come back to is like get the one page.
00:42:33.450 --> 00:42:35.290
Don't bury the lead, is what you're saying.
00:42:35.610 --> 00:42:36.410
Absolutely not.
00:42:36.410 --> 00:42:39.130
This is not storytelling, like for an executive.
00:42:39.130 --> 00:42:43.530
This is like this is what is happening, this is what we should do, this is why we should do it.
00:42:43.530 --> 00:42:48.970
And then if they want to double-click into how you got there, that's where you have your support.
00:42:48.970 --> 00:42:52.170
Um, but that's what I found to be very helpful.
00:42:52.170 --> 00:42:54.410
Um, and again, I can't say that it's foolproof.
00:42:54.410 --> 00:43:01.290
Like, I've been in situations where I have like what I think is an amazing one pager, and like, you know, it we end up in rabbit holes or you know, completely off track.
00:43:01.290 --> 00:43:10.250
But um I think if you can do that and just like, you know, I think it's similar to maybe like the idea of like writing a memo instead, um, I think it can just be really helpful to like just synthesize all of this stuff.
00:43:10.250 --> 00:43:12.010
Um, but personally I found it really hard.
00:43:12.010 --> 00:43:21.050
I I found it really difficult to do the analysis and spend the hours, weeks, months building it only to summarize it into one page.
00:43:21.050 --> 00:43:25.690
Like really hard, I think, to see forest for the trees, um, because you're so deep into it.
00:43:25.690 --> 00:43:31.690
And it's funny when we did banking, we used to say like I knew every model in or I do every number in the model tied to each other.
00:43:31.690 --> 00:43:34.010
I couldn't tell you what a single number even was.
00:43:34.010 --> 00:43:40.570
Um, and it's because you just get so laser focused on on that piece of it that you forget what's really important, which are what are the takeaways.
00:43:40.570 --> 00:43:43.290
So uh I think if you can start there, that's usually helpful.
00:43:43.290 --> 00:43:45.050
But um again, varies.
00:43:46.410 --> 00:43:49.050
Yeah, I I think that's one of the things I've learned over the years.
00:43:49.050 --> 00:43:53.610
It's funny because I was taught to do presentations in a storytelling format.
00:43:53.610 --> 00:43:54.410
Totally.
00:43:54.410 --> 00:44:08.250
And it took me a long time to realize after going doing keep going through that experience, like you get to page two of the lead up, and people are questioning that, and you never get to here's what I recommend, or here's what I want to do.
00:44:08.250 --> 00:44:13.850
Um, so I tell people like, do a little bit of that up front, like very quickly get to this is the point.
00:44:13.850 --> 00:44:18.010
And then if you, like you said, like have the supporting stuff and be ready.
00:44:18.010 --> 00:44:20.490
But that's what they're looking for.
00:44:20.890 --> 00:44:23.290
Almost nine times out of ten, that's what they're looking for.
00:44:23.290 --> 00:44:26.810
Um, and again, there's a time and a place for storytelling, uh, for sure.
00:44:26.810 --> 00:44:35.610
I think if you're trying to build and convince someone of something to you to do that's like completely different, like maybe you do want to paint like a little bit broader of a picture, but if someone's just asking you for like, what's your recommendation?
00:44:35.610 --> 00:44:37.370
Like, I just want to give you my recommendation.
00:44:37.370 --> 00:44:51.290
What I found when you do that for me personally was that I could spend almost all the time just debating and going back and forth on like judgment calls versus what I never wanted to do, which is diving into the numbers and being like, are we sure that this is the right number?
00:44:51.290 --> 00:44:54.170
Um, and like, is that what matters here?
00:44:54.170 --> 00:44:58.090
Um, and so it's really easy to get down that rabbit hole I find if I if I don't do that.
00:44:58.090 --> 00:45:03.130
So uh anyway, um definitely situationally dependent as as all things are in ops.
00:45:03.130 --> 00:45:04.010
Yeah.
00:45:04.330 --> 00:45:05.290
Of course, right.
00:45:05.290 --> 00:45:07.690
And if you know your audience, you have to learn and adjust.
00:45:07.690 --> 00:45:28.970
I mean, I think the one thing I when I coach, especially well, both teams I've had, um, or when I do coaching with um leaders too, is if you're presenting, especially if you're presenting number, you are presenting numbers, say a chart or something, and there's something that um is out of phase with the rest of the pattern, right?
00:45:28.970 --> 00:45:30.970
There's some anomaly somewhere.
00:45:30.970 --> 00:45:33.690
You be prepared to answer that.
00:45:33.690 --> 00:45:35.130
Like, why is that there?
00:45:35.130 --> 00:45:41.210
Because guaranteed 100% every time someone is going to ask, why does that say that?
00:45:41.690 --> 00:45:43.130
I absolutely love that.
00:45:43.130 --> 00:45:44.490
Um, that is a great addition.
00:45:44.490 --> 00:45:46.330
It's something I would highly, highly recommend.
00:45:46.330 --> 00:45:51.130
It's like once you start to work by someone, you you know and can anticipate the questions that are coming.
00:45:51.130 --> 00:45:56.570
That's how you build trust is if like you're seeing something, they ask it right away and you have that answer.
00:45:56.570 --> 00:45:59.769
Like that is the fastest way I've ever found to build credibility.
00:45:59.769 --> 00:46:04.730
It's the when they ask the question and you haven't really thought about it or you have to get back to them.
00:46:04.730 --> 00:46:09.130
It's not to say the trust immediately is derailed, but like it's where it starts to chip away.
00:46:09.130 --> 00:46:12.090
And like that's where you know the longer it takes for you to get the answer.
00:46:12.090 --> 00:46:14.810
This is where these things just like completely go off of the rails.
00:46:14.810 --> 00:46:16.410
So yeah, it's a really good ad.
00:46:16.410 --> 00:46:20.090
I think like having the idea, like what are the two or three questions that are likely to come here?
00:46:20.090 --> 00:46:26.330
Like, if you know those, that's where you can spend all your time, which is what you want to happen in these situations for the most part.
00:46:27.050 --> 00:46:27.610
Yeah, yeah.
00:46:27.610 --> 00:46:35.769
I mean, that's another like it's another tool to avoid going down a rabbit hole that is away from the main point of what you wanted to cover.
00:46:36.090 --> 00:46:36.970
Yeah, I love that.
00:46:36.970 --> 00:46:38.410
Just avoid rabbit holes.
00:46:38.410 --> 00:46:38.810
That's it.
00:46:38.810 --> 00:46:40.090
Yeah, it's it's so simple.
00:46:40.410 --> 00:46:41.610
Yeah, yeah.
00:46:41.610 --> 00:46:51.370
But I I think a lot of people, what they do, um and it's true that everyone's busy and they're just trying to fulfill the request, right?
00:46:51.370 --> 00:46:57.210
We need a report, I got the report done, they're not looking at the report and going like, why is this off, right?
00:46:57.210 --> 00:46:59.690
Or what like what is this trend telling me, right?
00:46:59.690 --> 00:47:11.930
If you do that extra step of anticipating those kinds of questions, then that will go a long way to like so you can either build trust or lose trust in those scenarios.
00:47:12.490 --> 00:47:16.570
100% for me, like likewise, and that's like for me, I go right.
00:47:16.570 --> 00:47:20.010
I find like that's the that's the interesting part of ops is like those pieces.
00:47:20.010 --> 00:47:21.050
Like, what do we do with it?
00:47:21.050 --> 00:47:21.930
Why is this happening?
00:47:21.930 --> 00:47:23.690
Like those those are the questions I want.
00:47:23.690 --> 00:47:27.850
Uh whether the number is you know 100 or 105, like I don't care.
00:47:27.850 --> 00:47:30.170
Um, I want to know what we're gonna do with about it.
00:47:31.050 --> 00:47:34.650
Uh I almost never say exact numbers.
00:47:34.650 --> 00:47:39.530
I talk about that's the other part with it, especially in the marketing and sales space.
00:47:39.530 --> 00:47:43.130
This is not finite, this is where it's different, right?
00:47:43.130 --> 00:47:46.970
This is not financial data that has standards and controls and all that kind of stuff.
00:47:46.970 --> 00:47:48.170
It just doesn't.
00:47:48.170 --> 00:47:48.810
Totally.
00:47:48.810 --> 00:47:55.050
So I don't go, this is exactly you know 2543.
00:47:55.050 --> 00:47:58.090
It is somewhere around 2500.
00:47:58.490 --> 00:47:59.450
It's a great point.
00:47:59.450 --> 00:48:04.570
Knowing when to use specificity, very, very big unlock for for folks.
00:48:04.570 --> 00:48:06.970
Um, yeah, there's there's a time and a place for it.
00:48:06.970 --> 00:48:11.130
Um, and in most startups, it's it's probably not the right time.
00:48:11.130 --> 00:48:17.769
Um, and so that's kind of the the fun of being in the earlier stages as like the the numbers aren't gonna be all directional um and they're not gonna matter.
00:48:17.769 --> 00:48:23.930
And then you can worry, let your CFO worry about being uh audited, and like you know, they'll go they'll make sure that that'll that's all clean.
00:48:23.930 --> 00:48:26.810
But uh yeah, pipeline's not in there, so you're good.
00:48:28.890 --> 00:48:30.890
Josh, tons of fun.
00:48:30.890 --> 00:48:32.170
I know we can keep going.
00:48:32.170 --> 00:48:35.210
You and I like I think we're like on the same page on this stuff.
00:48:35.210 --> 00:48:35.930
So I appreciate it.
00:48:35.930 --> 00:48:36.490
Totally.
00:48:36.490 --> 00:48:39.050
Thank you for joining us uh in in sharing the time.
00:48:39.050 --> 00:48:45.450
If folks want to learn more about how you think about this stuff or more about what you're doing with account name, what's the best way for them to do that?
00:48:45.690 --> 00:48:52.410
Yeah, uh email me anytime, josh at account.com, come to our website, come to account n.app if you want to just uh test it out yourself.
00:48:52.410 --> 00:48:58.570
And uh I'm on LinkedIn, so yeah, if you ever want to chat anything, metrics, analytics, reporting, rev ops, marketing ops, uh I love it.
00:48:58.570 --> 00:49:00.250
But uh Michael, thanks so much for having me.
00:49:00.250 --> 00:49:02.490
This has been uh a great job, and obviously, yeah, I think you're right.
00:49:02.490 --> 00:49:04.090
We could uh we could get this going for weeks.
00:49:04.090 --> 00:49:06.010
So uh really appreciate it.
00:49:07.210 --> 00:49:08.010
Yeah, of course.
00:49:08.010 --> 00:49:11.690
Well, uh as always, uh we appreciate you you joining and sharing.
00:49:11.690 --> 00:49:14.090
It's um it's a lot to take out of your day.
00:49:14.090 --> 00:49:15.130
So appreciate that.
00:49:15.130 --> 00:49:21.130
Thanks as always to our listeners and audience out there for your continued support.
00:49:21.130 --> 00:49:30.890
Uh as always, it also if you are have an idea for a topic or a guest or want to be a guest, you can reach out to Naomi, Mike, or me and we get the ball rolling just like we did, Lajosh.
00:49:30.890 --> 00:49:31.850
Till next time.
00:49:31.850 --> 00:49:32.890
Bye, everybody.