A History of Marketing / Episode 55
Kathleen Schaub spent thirty years as a marketing executive and CMO, and nine years running IDC’s CMO Advisory practice, where she counseled CMOs of the world’s most influential tech companies. Her book, Marketing in the (Great, Big, Messy) Real World, takes aim at a dream the industry has chased for over a century: marketing as a vending machine. Put a dollar in, get predictable revenue (or pipeline) out.
Kathleen argues it was never like that. She traces the pursuit of certainty back to Frederick Taylor, one of the first management consultants, who ran around steel mills with a stopwatch looking for “the one best way.”
Scientific management built the 20th century factory. But the stopwatch approach was never well suited to marketing, a function that sits where the company meets the messy real world.
That doesn’t mean marketers are off the hook for goals and measurement. Here’s my favorite excerpt from the conversation:
“Marketing influences, but it cannot control or predict.”
What you can hold marketing accountable for, she argues, is building the systems that give the company its best shot at turning intention into revenue.
We cover:
How marketing inherited Frederick Taylor’s stopwatch, and why the funnel still runs on it
Whether the marketers who promised certainty were fooling their bosses or fooling themselves
The CMO interview problem: why the candidate who promises certainty gets hired… and is often gone before measurement catches up
Judged numbers, attribution, and why the forecast that lands closest is the one you can’t back into the data
Listen to the podcast: Spotify / Apple Podcasts
Special thanks to Xiaoying Feng of Syracuse University for reviewing and editing transcripts for accuracy and clarity. And to Jon Miller, whom you may remember from episode 35 of this podcast, for introducing me to Kathleen.
The Book Schaub Wanted to Read but Couldn’t Find
Andrew Mitrak: I’m excited to speak about Marketing in the (Great, Big, Messy) Real World. So, I wanted to start by asking you what led you to write the book.
Kathleen Schaub: This is a topic that I’ve been thinking about for decades. I mean, I’ve been a lifelong marketer. I was a CMO and ran product marketing for a couple software companies. And then I was IDC’s CMO Advisory, and so I have a lot of background in this. But at the same time, I’ve always been interested in science and other things that are going on in the world. And very early in my career, I started learning about systems thinking, and I was easily applying it to marketing, but I noticed that very few people did. And so when I decided to leave IDC and I wanted to write a book, this was the topic that really jumped out at me because it explains so much—the whole complexity science and how to act in an uncertain world. It explains so much about the way that marketing works, and yet it is something that not a lot of people know about. And so I wrote that book because it was a book that I wanted to read and I couldn’t find it. So, that was what led me to believe that I could talk about this.
Andrew Mitrak: Running a CMO advisory sounds like a really fun, interesting job where you might learn things. And so, did some of that inspire the book? Or were conversations you were having with CMOs where they were planning things a certain way but it didn’t quite match up to reality—did some of that inspire what you wrote in this book and just sharing examples of that?
Kathleen Schaub: Oh, all the time. And the book is full of stories, both from my own personal experience as well as experiences that I got from clients. You know, I did a lot of consulting as a part of that book as well—or, excuse me, as part of the CMO advisory service, where we were transitioning from something that wasn’t working to something that worked better. And a lot of these themes always served as a sort of background for us. So, people’s stories are just a fantastic wealth of demonstration that, yes, the world is indeed messy.
Andrew Mitrak: And so IDC, for listeners who might not be familiar, is an analytics firm, an analyst firm, and sort of a market research firm that provides data.
Kathleen Schaub: Yes, yes. International Data Corporation. So, yes. And it was serving the tech industry, so we had huge, huge companies all the way down to startups as our clients. So the fact that I had all of this data that was available to me, and I had the opportunity to go out and get more data to answer specific questions, that was just like a treasure trove. But I always fed it in, and I think most analysts—most good analysts—do, is you feed it into this kind of humble view that you really don’t know everything, and tomorrow something’s going to pop up that’s going to change everything, and you just don’t know what it’s going to be.
Andrew Mitrak: That’s right. Yeah. And this gets to the heart of what a lot of the book is about, that the book is about this transition from—we use the term deterministic, seeing marketing as deterministic: you put dollars in, and you get revenue out or pipeline out. And the real world is something more complex than that. So before we talk about the complexities, and the book does a great job of breaking down how to think about these complexities, let’s talk about that deterministic era of why it became viewed as deterministic. So why do you think initially, as marketing was constructed, it was set up in this deterministic way? What was sort of the seeds that led to marketing as a function growing that way?
How Marketing Inherited Frederick Taylor’s Scientific Management
Kathleen Schaub: Okay, well, I’m going to go back a little ways, then, if you don’t mind. So back to the early 20th century with Frederick Winslow Taylor, who is considered to be the first management consultant. And he was brilliant. And if you think about what was happening around the late 1800s, early 1900s, that was the peak of the Industrial Revolution, and so many machines and everything were coming online, but work was not keeping up with the machines. So work was still being done in sort of a cottage industry way. And Taylor had this brilliant insight: what if we could treat work like it was a machine? And so for the first time—we’re talking about data—for the first time, things were being measured. And he used to run around to steel mills and things with a ruler and a stopwatch, and he developed what he eventually called the “one best way.” Or that was what he was looking for. And the efficiency absolutely exploded, and people all over the place—not just all over industry, it was just hugely, widely adopted, but also in our schools, the way our schools are with standardized testing and grade levels and all that kind of stuff, that was all scientific management. So Taylor and his—over the next few decades, there were people that became his followers. The reason why we could ramp up for World War II was because of Taylor. Hugely, hugely influential and had a lot to do with why the United States, but also other parts of the world, became successful during the 20th century. So marketing was part of that. And as companies, who were industrial powerhouses, wanted to become bigger and bigger brands, they needed to industrialize, if you will, or apply scientific management to their outreach efforts, to their go-to-market efforts as well. And so the—actually, what is now the American Marketing Association was founded for the purposes of bringing scientific management to the marketing world. So the idea of measurement and all that kind of thing in marketing became prevalent in the first part of the 20th century.
And that lasted for a long time, even though in the middle of the 20th century, science and math—so kind of maybe more tucked away into the more academic world—was starting to see that there were places where this didn’t really work. The closer that you got, or the farther that you went away from the very routine kinds of, like, assembly line types of factories, the more difficult it was to find this “one best way.” And finally in the ‘60s and ‘70s, there started to be—really with the advent of computers—we started to see the math and the science behind why things continued to fail. And yet, business in this case was really lagging.
The idea of complexity has started, maybe starting in around the ‘90s, started to be understood in things like Agile software development, where we get Agile, and all that kind of stuff, and even in manufacturing, where we had Lean manufacturing and things like that. But marketing just really didn’t keep up. I’m not throwing the marketers under the bus; this is a business kind of a focus that is just still working, for the most part, in that 20th-century way. We don’t want to throw away everything that—I mean, there was so much good about scientific management, but it just does not apply in all situations.
Andrew Mitrak: Yeah, that makes a lot of sense. So I’m not super familiar with Taylor. I looked him up a little bit prior to this episode. You don’t see a lot of his work on marketing specifically. But marketing at the time he was working wasn’t really called a job function. People did the work that we now consider marketing, like a lot of those activities were there, but marketing at this time in the 1910s, early ‘20s, there wasn’t usually like a marketing department per se at most companies. But then the AMA—sorry, American Marketing Association, I think—is that the ‘30s or something that that kind of gets started?
Kathleen Schaub: Around the ‘30s. And sales, too. Sales really started to really professionalize. And IBM, I think, was one of the very first ones to professionalize their sales force. So yeah, around the ‘30s.
Andrew Mitrak: Yeah. And I think a lot of Taylor’s work, you kind of mentioned it, within marketing, there’s sort of the supply side, the demand side—or the production side, then the consumption side. And you could measure a lot of like, how can we produce a little faster? How can we have these assembly lines structured in such a way? But then forecasting consumer demand is just a little trickier to apply those methods to. And that’s, I think, that’s sort of where a lot of the tension was, is on sort of the, how do you influence people, and how do you really gauge stuff? And is it as simple as put stuff into radio marketing or advertising or television, and then suddenly sales happen as a result? It’s a little more complicated than that.
Marketing Sits at the Edge of the Company
Kathleen Schaub: Oh yeah, it’s a lot more complicated than that. Because marketing and sales and customer experience, if you will, or customer service, all sit at the edge of the company, which is where the company meets the rest of the world. So, unlike other functions that started to get automated then during the latter part of the 20th century, where we’re talking about like finance and HR—those are, for the most part, although they do have some extensions into the outside world, those, for the most part, are internal functions. So marketing and sales, they meet the complex world in a daily fashion. So companies have always known that marketing and, to a certain extent, sales, too, had a lot of uncertainty around it. But there was this idea, I think, in a lot of companies that, “Ah, if we only had enough data, if we only had the right technology, then we could control it, we could predict it.” And so when marketing automation started producing all of this data, there was an expectation, I think, both in marketers and in their C-suite partners, that, “Oh, we’re going to be able to hammer this down now, aren’t we?”
Andrew Mitrak: Yeah.
Kathleen Schaub: But all it did was really show us, “Nope, it’s even more uncertain and more complex than we thought.”
Andrew Mitrak: Do you have like a specific, really concrete example that you point to where sort of conventional marketing thinking or viewing marketing as deterministic really clashes with the real world?
Kathleen Schaub: One of the most prevalent is in the way that the pipeline is measured. So again, going back to the fact that we have all this marketing automation, so there’s been a creation of the marketing pipeline, marketing sales pipeline, as being like a factory, right? So you’re going to manufacture demand that is going to be fulfilled. And we have made it into stages, and then there’s handoffs, and then you’re using very hard and fast rules like attribution modeling as to first touch, last touch, multi-touch, whatever, to try—and by the way, there is some value in the attribution data, but not the way that it’s being used in most companies. And so that factory orientation of the way the pipeline is managed, that has been instrumented by marketing automation, is failing. I mean, it’s been failing ever since, and people cannot understand. People are getting fired because of it, overcommitting, overexpectations, when the reality is that each one of those is always a probability. And they’re not—they’re not thinking about the way that the market really works and being focused on maybe too much demand, as opposed to building up the type of what I call market system health and agility that is needed in order to be able to act in that way. You can still use the data, by all means, but that would be a really prevalent place where that deterministic area fails.
Andrew Mitrak: Yeah, that’s right. I’ve had two conversations related just on this topic. Jon Miller, who actually is the person who recommended I speak with you.
Kathleen Schaub: Love Jon Miller, yeah.
Andrew Mitrak: He’s great, founder of Marketo and speaks a lot about the downsides of MQLs and the traditional demand funnel. And Kerry Cunningham, who was at SiriusDecisions, which was the company that basically invented the MQL and the demand funnel and all that. And as a B2B marketer, this is a place where I spend a lot of my time, and it’s just one of those things where, gosh, how do you unstick this situation? Because you have all of the things you highlight, and then on attribution, it’s sort of this weird all-or-nothing or multi-touch, hybrid, kind of fractional attribution-type thing. It’s like, because if you go to sales saying, “Hey, we, marketing, delivered this account,” and it’s like, “No, you didn’t, sure they downloaded some form, but I’ve known that person for years, and that’s like a personal relationship I have.” And they’ll laugh you out of the room. But then also you have to claim something, though. You can’t just say you’re not doing anything, because that’s not good either. I align with all the highlights of the flaws with the funnel. I haven’t seen a perfect solution that fixes them, though, and I haven’t been fully persuaded by, like, what is the best method to fix that.
Kathleen Schaub: I’m not sure that there is a best method. And the way that I present the book is, what I did was go out to the messy world, to other industries, as well as to the companies I know that are working at least at the edge of what we’re doing, and try to translate those things into what might work for marketing. So software development, healthcare, first responders, military places that are going—and there’s a bunch of books out that are about uncertainty and management in general, for business in general. So I tried to get a lot of those as well, and then translate those into marketing. But I don’t—I don’t say this is a recipe. I don’t think we’re going to get to a recipe where like, “Hey, do these five things and then you will be happy.” I think what I do is try to set up directional perspectives. If you start looking at the world in a way that’s compatible with its natural complexity, then you’re going to start seeing things differently, and every day when you make your dozens of decisions, you’re going to steer slightly towards that. You’re going to see opportunities or places that don’t work. And over time, it’s going to change. And I do give some specific—it’s not like everything is like, “Whoo just think about things in a different way.” But it’s that change in intent and the change in perspective that is going to five years from now, make a huge, huge difference. And the way that complexity works, if you start now, that’s one of the cool things about complex systems—this comes from the science—is part of their baseline of what they are is sensitive to initial founding conditions. So, that’s the whole idea of the butterfly effect. Right?
Were Marketers Unaware, or Just Playing Along?
Andrew Mitrak: If the old worldview was that marketing was deterministic and that was kind of the old mindset and framework, and in reality, the world is messy, volatile, and uncertain, it kind of implies that either marketers for a very long time were just unaware that marketing didn’t match reality, or that they were aware and lying or performing, and kind of pretending that it was. And I guess like which of the two do you think it is, or is there a third? Were marketers just somehow knowing, “Oh, we know that the world’s uncertain, but we have to behave in this deterministic way just because of that’s the way it is, and that’s how marketing’s been getting along for decades”? Or do you feel like this is a fundamentally undiscovered worldview that’s brand new, that they had never arrived at previously? How do you sort of think about that?
Kathleen Schaub: Well, I think I have to go to the reaction that I get from people as I get reactions to the book, as well as before, because I started a lot of these ideas before, and even my own experience. Every once in a while, you just hit something and you go, “Oh my gosh, that really explains why things are the way they are.” So, the reaction that I often get is one of recognition, like, “Oh my gosh, this is my world.” And so, I do think that pretty much everybody in the world knows that the world is complex. I do occasionally find people who still think that maybe somewhere out there there are rules that we just don’t know yet. And there are definitely lots of things—I mean, science is not going to stop, you know. We’re going to learn something in the next few years that’s going to blow us away again.
And by the way, I do not think this is an issue of “marketers are so wonderful they understand the world, and CEOs are stupid and they don’t understand the world.” Because I get the same when I talk to CEOs, COOs, CFOs, they’re kind of like, “How come no one told us this before?” It’s that kind of a discovery thing for—although there’s a fair number of people, particularly if they’ve been in Agile or systems thinking or something, that are already at the stage where they’re saying, “Well, duh of course the world is this way.” So, no, I don’t think anybody—it’s not crummy CMOs or liars or anything like that. I think it’s just the way of discovery. We’re just keep learning new things. And I think with all of the science and stuff that has been—and AI is going to help us, because AI is actually built on computers that work more like the real world than the old CPU and RAM deterministic kinds of things. So, I think AI may be a forcing factor to helping people understand the way systems and probabilities and things work.
No Marketing Plan Survives Contact With the Customer
Andrew Mitrak: One of the frameworks you introduce in the book is VUCA. Can you introduce VUCA for listeners, where you came across it, and kind of why you adopted the VUCA framework to sort of describe how marketing actually behaves?
Kathleen Schaub: Yeah, so I love the term VUCA. It comes out of the military, and I was first introduced to it by Stanley McChrystal, General Stanley McChrystal’s book, Team of Teams. And I think that’s maybe—it was, I don’t know, sometime in the mid-2000s. Anyway, great book. I really understand, for those people who love history and military and stuff, but it also explains how McChrystal took a failing adventure, if you will, a military adventure in Iraq, and how he reshaped it to make it more reactive. And the term VUCA, which is an acronym, stands for volatile, uncertain, complex, and ambiguous, came out of the US Army War College. And during the ‘90s, they were finding that the idea of this sort of mechanized tank-heavy, everybody marching in formation-type thing, never didn’t work. And so based on some of the business work actually that was done in the ‘80s, they came up with this term VUCA. It better described what reality was finding. I mean, military has always been complex. You know, it’s the famous German—I can’t remember what his name is—but anyway, he said, “No plan survives first contact with the enemy.” And so this idea that you need to be very agile and you need to be adaptive in order to be able to manage in a military situation, which is the same as what you have to be when you’re meeting customers—hopefully, they’re not enemies—but that’s where the—where VUCA came from. And Team of Teams is just an excellent example of conversion from a very factory-oriented, deterministic, heavy, planned—not that you don’t do planning, you still do planning—but handling of just like the metrics in a different way. So, that’s where that term came from, and it’s very evocative.
Andrew Mitrak: Yeah, for sure. I looked it up real quick. I would not have known this. “No plan survives first contact with the enemy” originated from the 19th-century Prussian military strategist, Helmuth von Moltke. So, I’m sure I’m not pronouncing that right.
Kathleen Schaub: Thank you. I did have that in my book, but I don’t always remember names.
Andrew Mitrak: Yes, I know, especially 19th-century Prussian military leaders.
How the World Gets Complex
Andrew Mitrak: So, it came from military, and then how does it apply to marketing? Why do you feel like marketing is volatile, uncertain, complex, ambiguous? What are kind of the mechanisms where that translates from the military or other areas into marketing?
Kathleen Schaub: Well, it might be useful to just talk a little bit about how the world gets complex, or how any natural system economies, ecosystems, beehives, whatever you want to talk about, neurons, is that they get that way because of interactions. And the interactions sometimes billions of interactions if you’re talking about an economy, create feedback loops. And those feedback loops then affect other things. And so, the rules and things that people make decisions on are not necessarily all that complex. But out of the simplicity of making some basic decisions comes this huge amount of complexity, and markets are semi-predictable within the confines of probability and time. They’re not—they’re not random in that sense, but they are more complex than anyone can, any brains or any group of brains can figure out. So volatility means how much sort of up and down it is, how extreme it is. Uncertainty, I think we know what that is. Complexity is what I was just talking about, about the way that complex systems work. And then ambiguous we communicate through language, whether it’s body language or spoken language, and there’s a huge amount of ambiguity in every kind of communication. So we all are interpreting things differently than perhaps they might have been intended.
Andrew Mitrak: I totally am persuaded by marketing being like VUCA. Like all those things, I think, describe both the real world, the markets, and how we have to adapt and understand it. However, I imagine that many of the CMOs I worked under, or CMOs I’ve seen outside, they need to be very confident, or they project confidence. And I also imagine that the system probably rewards confidence. And if, like by an example, if I’m a—if I’m a candidate and I’m interviewing for a CMO job, and I say in the—they’re interviewing me and I say, “Oh yeah, marketing, it’s—it’s volatile, it’s uncertain, it’s complex, and it’s ambiguous, and it’s—it’s hard, but I’m going to manage through it.” But then the next candidate comes in and says, “Oh, I’m going to make marketing a well-oiled machine. We’re going to hit targets predictably.” And that, I assume, the CEO who’s interviewing is going to like that second candidate. Maybe they get the job, and then maybe two years down the line, they get their next CMO job at some other company before they have to actually deliver on everything. And I kind of wonder if that pattern happens a lot. Do you see the system sort of rewarding the leaders who are overconfident, and are less likely to kind of acknowledge sort of the VUCA dynamics they’re really dealing with?
The CMO Who Promises a Predictable Revenue Machine
Kathleen Schaub: Well, I think it’s on a spectrum with any kind of worldview, if you will. And again, this is not—this is not my idea. I’m translating a more general movement, if you will, towards the understanding and acceptance of systems and complexity. There are people who, for whom this is like, “I never heard of this, this is ridiculous.” But I don’t think that’s—that’s prevalent. I think that it’s more kind of in between, in a middle stage where there is some general kind of knowledge or awareness. I think that if you have a CEO who’s completely rejecting it, then yes, the scenario that you described is probably true. I would never recommend for a CMO to walk in and say, “Hey, things are complex, so I can’t be accountable for what’s going on,” you know. You can’t make CMOs accountable for an outcome that they cannot control. Marketing influences, but it cannot control and predict. But you can hold marketing accountable for creating systems that give the company as many tools as they can to get their intention realized in the form of revenue. And I think if I was a CMO and I met the CEO who was completely in the deterministic camp, I’d probably walk away because, to your point, they’re going to—they’re going to be out on their, on their ear here in a year or two because they’re not going to be able to deliver that.
I would be looking for someone who is willing to work with me on how to create an agile system that is one that can provide the company with as many tools as they can, use that data to give it as much of a chance as you possibly can, with the knowledge that it’s all a probability. It’s—it’s not necessarily, it could be an easy conversation depending on the CEO, it could be a challenging one. But I think the natural next question, if you do start to talk about the fact that it’s—it’s a changing world and we have to be adaptive, the next question would be, “Well, how are you going to do that?” And that’s a question that I think, if you’re going to have the conversation about adaptability and complexity, you should at least have some idea about how you would go about managing that.
Andrew Mitrak: Yeah, for sure. I think that’s a natural next place to go to is like, some of the if a marketing department fully adopts the worldview in this book and kind of adopts like, okay, the world’s uncertain, but there are things we can do to influence it, sort of what—what should the goals of a marketing department be? Like, how do goals change or target setting or things like that change, or what—how does what they’re being held accountable to change? And then what sort of practices also change with that?
Transitioning to Agile Planning and Measurement
Kathleen Schaub: Well, I often recommend that you start with the measurement piece, because—well, there are really two. One is sort of more intentional and planning-oriented, and I give some specifics about how to, like, change your planning so that you are doing this giant, monolithic “Here’s our plan, we are going to stick to it no matter what’s happening in the world,” move from that monolithic kind of a plan into a pace-layered one, where you’re changing the flexibility as you get closer and closer to the market. Where certain things may last for five years, but then you might change other things every quarter. So you can start to change your practices so that the adaptation to the market becomes—becomes easier. And then, you also need to then start looking at your—your measurement in a less hard-coded way. And no change, and anybody who’s gone through—Andrew, you’ve probably gone through some organizational changes and some transformations and stuff, and I think we all have once you have at least a reasonable number of years of experience.
It never works to just like one day try to, like, cut over or anything. You have to do it at least somewhat incrementally, and that doesn’t mean the whole organization changes at the same time incrementally. You have pilots and you have work that you do in a—in a workshop type of a situation. You create enablers. And again, I talk about some of this in my book, including the last chapter, which is all about leveraging complexity. There are some cool things in leverage in complexity that allow change to happen in even a better way and a more sticky way. But using that measurements, and there’s a bunch of different ways that you can take measurements and start looking for things like, “We’re going to look for trends. We’re going to look for patterns. We’re going to look for—” like in the case of causal AI, “We’re going to look for the persistent, what is likely to persist in what we’re doing as a success factor, even though things are changing.” And so, you’re going to—you’re going to sort of do the bottom and the top, and work towards it. But at the same time, you may still have to keep the the old tires on the road while you’re—while you’re working simultaneously. There’s some overhead to this, there’s no question. It’s not a real efficient way to work. But at the same time, the least efficient way to work is to just keep banging your head against a wall that never gets you there.
Does Data-Driven Marketing Favor Short-termism?
Andrew Mitrak: You mentioned that it starts with—with measurement, and let’s talk about like the time frame for measurement, because on the one hand, I think marketing is more of like a long-term function. The activities I’m doing in the first half of the year turn into pipeline in the second half of the year, for instance, or maybe it can even go from one year to the next and so on. But then also you want to be adaptable, too, right? And having a shorter time frame target is—is useful for being adaptable and kind of adding—adding new targets in. And so how do you kind of balance—gosh, this is—you have these mindsets in your book, the—the navigator mindset and the investor mindset, and I feel like the investor mindset is a little more long-term oriented and might be helpful to have longer-term targets, and the—the navigator mindset’s probably a little more towards like short-term, like incremental targets. Gosh, how do you—how do you think about balancing those things within marketing organizations?
Kathleen Schaub: I’m going to fall back a little bit on some of the guidance that we see in—in data. So when you see very large—there’s been a few very large scale looks at what—and and even on the stuff that we were doing with at IDC when I was there, we did a lot of work on measurement, and in general, I think it’s probably a good just stake in the ground to start with like a 50/50. And that might be a little different from B2C, from B2B, and say invest half your budget in things that take a long time to go about it and half your budget for the incremental. Did you want to say something?
Andrew Mitrak: Oh, I was going to say there’s a long paper on this by, I think it’s Les Binet and Peter Field.
Kathleen Schaub: Yes.
Andrew Mitrak: Called The Long and the Short of It. And that’s what they—this is basically their thesis, like the—something like 60% in brand, 40% in performance, I kind of—or maybe, I forget which one’s which, but something like that, of that balance view, which seems a little bit maybe convenient, or maybe kind of a rule of thumb versus like a hard science. I’m not sure exactly where that landed, but—but that’s like—that was kind of the idea, is that sort of like, in line with sort of what you’re—sort of speaking to?
Kathleen Schaub: Yeah, I would say at the state of measurement today, that’s probably a good place to start thinking about it, but then you may want to vary it in accordance with what your specific business orientation is. In other words, if you’re a small company who is looking to be sold in five years, you might have a different goal than if you’re a mega brand that dominates the industry. You know, you’re going to measure things differently and you’re going to divide your budget up a little bit differently.
But there has been a move in later, in most recent years, towards an over-dependence on performance marketing, and you know, into that short-term kind of thing, and let me—I think people will respond, or you know, you know if you have a 401(k) or whatever the equivalent is in your country or whatever that—that if you put money in when you’re 30, it’s better than if for your retirement than if you put money in when you’re 60. Right? That you’re going to—that it compounds over time, and I explain in my book how that applies to marketing.
But if we go up to the adaptive piece of it, there’s—it’s a little bit more, a little bit more nuanced. So, it doesn’t mean adapting doesn’t mean just stay in your lane where you are right now and just keep shifting lanes, although to a certain extent it is. You have to build a platform, if you will, a way of working. Your organizational structure, the data that you have, needs to be primed for your ability to adapt. So, it’s not exactly a short term and a long term, but I think you’re accurate in the sense that investment, a lot of it has to do with making an investment and then doing things to make sure that managing so that it comes to fruition, and then that ability to act more in if not real time then certainly in close time. But they both require structure in order to be able to make those successful.
Andrew Mitrak: That’s right. I feel like a trend I’ve observed is that as measurement became like, “Oh, let’s be a data-driven marketing organization,” very often, I feel like that is biased a little more towards short-termism. Do you sort of—
Kathleen Schaub: 100%, I don’t think I could say it any better. So, yes. No, I agree with you, and I think it’s a pretty natural human thing that you—you want it to be predictable and you want it to be controlled.
Andrew Mitrak: Yeah, you want it to be predictable, you want it to be controlled, and you don’t want your testing to last forever, you know? And it’s like, okay, if you set up shorter-term testing, it’ll lead you to shorter-term activities. If you could do a multi-year brand study, sure, but that means like it’s going to—you’re going to have to do multi-year investments and all all of that as well, and in where it’s just such a quarterly or annual type of business rhythm, that it’s kind of hard to break out of that.
Smoke Alarms and the House That’s Already Burning
Kathleen Schaub: That is—that is the reality of the way that business is run today, and in some ways it’s helpful, and in other ways it’s destructive. I’m not going to deny that there is a little bit of faith in this. But I have tried to look at, again, the math and the science, and whatever I could find in terms of grounded studies, that—that the faith is not something that is just being made up, that there’s a reason behind this. We may or may not like the fact that that is true. You know, it may not—like I had one head of sales tell me one time that to tell him that the reason why he was having sales problems was because he had not made an investment several years ago in the reputation, you know, making sure that his customers had, that the company had a good reputation with the customers. And he said, “You know, Kathleen, that’s just like you’re telling somebody whose house is burning that, you know, they should have installed smoke alarms.” And it’s kind of like, “Well, yeah, that is kind of true. You still have to deal with the fact that, oh, the house is on fire.” You know, “You don’t have the revenue that you need in order to be able to make the—” you still have to deal with that, but it’s not going to prevent the fire. So it’s like, what is the old, you know, the best time to have planted a tree was 20 years ago, the next best time is today. You know, you end up with what you end up with, and there is a little bit of faith in it.
Andrew Mitrak: You could probably tell I’m very bought into the worldview of the book, that things are unpredictable, the dangers of short-termism, the flaws with attribution, and the flaws with traditional pipeline. If I was to kind of give the steel man defense of the other, or something that I have observed, is that when annual targets are set or quarterly targets are set for, say, a pipeline number, at every organization, even though, like, I don’t always trust the attribution model, I don’t always trust the data, I don’t fully trust like the demand funnel, somehow consistently the numbers always get pretty close. That you’re able to almost like, very often hit the number, and I suspect that there’s a lot of sort of individual actors, like kind of like sort of getting numbers sort of fudged at a certain—not fudging, but like, kind of getting things aligned in a certain way that map to the number, and and hitting it. But like, it is like there’s some alchemy to it that seems like, “Wow, even though this is really complex, even there despite all these flaws, even though it’s like a big organization, or even at a small organization, I’ve seen like usually like marketing can get kind of close to that pipeline number.” Which either leads me to think that something’s working a bit, or maybe that’s even more of a reason to distrust it because because it’s almost eerie how often we’re able to get to that number as well. And I’m wondering if you’ve ever kind of observed that as like a rebuttal that people like, “Oh yeah, I know it’s flawed, but it somehow kind of works.” And do you have any reactions to that?
Kathleen Schaub: Yeah, it actually does, and I think you—you kind of alluded to that, as you have a lot of individual actors. I mean, we don’t—we’re not like pulling the numbers out of thin air. And there are a lot of people, and in particular, I think I use an example of this with one job that I had where I was—my job was to sit down with the sales people and try to say, “Like, well, what can marketing do to make them more effective?” And sort of be a liaison between between sales and marketing. And sitting down and listening to sales managers put their projection together was just hysterical because of the, you know, it was all—each one of those sales managers had deep, individual knowledge about what was going on in their sales force, and who the people were, and who the customers were, so this was in a B2B company. And they always came up with a number which was very, very close. They call it a judged number. But they could never back that into the data. The CRM system and the judged number didn’t really ever really jibe. The same thing, if you have this very chopped-up, you know, “Oh, MQL to SQL and opportunity,” those kinds of things, at every level, you get somewhat of a disconnect, but people are not stupid. You know, your sales people are not stupid, your marketing people are not stupid, your product people are not stupid. They all have private information as well as public information, and collectively, the group can, to your point, get pretty close, unless you have a very, very volatile situation. You know, if you have a company where one sale, you know, makes the the quarter, and that moves to the next quarter, or it falls apart for whatever reason, or, you know, you have a supply chain issue that prevents you from delivering or whatever, those kinds of volatility things you can’t control. But no, you’re absolutely right. It sometimes works.
AI: Bringing Clarity or Pouring Gasoline?
Andrew Mitrak: It sometimes works. Works kind of in quotes. So you mentioned AI earlier, and I’m wondering kind of looking forward, how does AI fit in? Does it bring opportunities for clarity and making sense of the VUCA dynamics, or does it just pour gasoline on the fire of the VUCA dynamics where everything’s even more volatile and and even more ambiguous as a result?
Kathleen Schaub: Well, I think in the short term, probably more the latter, because right now, what AI is being used for is just to produce more stuff. And it’s being kind of, you know, like, “Oh, now I can do four emails instead of one,” or you know, it’s just—and it’s being done, I think, where we’re we’re using it to create the same old stuff faster and cheaper. So another thing that AI is going to add to is that as we start to introduce agents into the formula, and agents are going to be making decisions for buying or searching or whatever, with different criteria than humans. So I think there is going to be a lot of confusion as those get introduced into the whole commerce value chain. But I think in time, there are some really very, very interesting things that AI is going to be able to do. For one thing, AI can take these patterns of data and different kinds of data, and look at them in new ways. So we’re going to be able to see some trends, like we’ve been mentioning causal AI as a as a way to do this. I think we’re going to get some really interesting information. You’re going to be allowed to maybe go back in time, take data sets that are much bigger in time. So I think there’s going to be some cool things. I think that’s more of interest than in than some of the “create a new set of content.”
Andrew Mitrak: Yeah, for sure. I think coming full circle, too, I wonder if there’ll be some type of Taylorism-style rethinking of how businesses operate in the era of AI. I feel like we’re kind of entering that era right now. I think the tech is there, and businesses need to adopt to it. So, I think like almost having that Taylorism-style mindset of like re-measuring things, re-optimizing things, now that we have these new tools for us is kind of a an exciting era that we’re we’re entering into.
Kathleen Schaub: Yeah. And I do not want to say that we need to throw everything that Taylorism did or it’s the things that came after it. There are things like for example, you can—one of the things that makes you more agile is if you can break things into smaller components that can be reassembled like Legos. That came out of the Taylorist. So, it’s not—it’s not an either/or. I think the—the improv idea of “yes, and” isreally a better way than an either/or view.
Andrew Mitrak: That’s right. Yeah. “Yes, and.” Aside from buying your book, Marketing in the (Great Big Messy) Real World, where would you suggest that your listeners find you online?
Kathleen Schaub: Well, I do have a website, so kathleenschaub.com. But I’m also really active on LinkedIn. So, happy to link in with anybody and continue the conversation there.
Andrew Mitrak: That’s great. Kathleen, thanks so much for joining me. This is a really fun conversation.
Kathleen Schaub: Andrew, thank you so much for having me, and yeah, I look forward to staying connected and seeing what else is on the docket for you.
