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What’s up everyone, today we have the pleasure of sitting down with Kathleen Schaub, Author, Strategist, and Advisor in Marketing Management and Organizations.

Summary: Marketing has spent a century pretending it’s a machine you can feed cash and read like a receipt, and Kathleen is here to take that apart. She makes the case that markets behave more like weather than vending machines, walks through her 4 mindset shifts for leading in the chaos, and explains why a single north-star metric quietly wrecks your decisions. Along the way there’s a butterfly in Brazil, a cucumber garden in Canada, a poker champion, and a COO who begged for the book on a cruise. If you’ve ever had to defend marketing ROI in a boardroom and felt the ground move under you, this conversation names what’s really going on.

In this Episode…

• Why Marketing Behaves More Like Weather Than a Machine
• The 4 Mindsets Marketing Leaders Need for Complex Markets
• Why ROI Doesn’t Work as a Marketing Measurement
• What Causal AI Can Actually Tell You About Marketing
• Why Your Marketing Budget Works Like an Investment Portfolio
• What Marketers Should Actually Be Held Accountable For
• Why a Single Marketing Metric Always Fails You
• Why Marketing Managers Should Create Conditions Instead of Commands
• How to Make a Marketing Budget Adaptable With Pace Layering

About Kathleen Schaub

Kathleen Schaub is an author, strategist, and advisor focused on marketing management and organizations, working through KathleenSchaub.com. She spent 9 years leading IDC’s CMO Advisory practice, where she advised hundreds of technology marketing leaders, and she’s a longtime contributor to leading martech publications including CMSWire.

Her work argues that markets are complex adaptive systems rather than predictable machines, and her book (Marketing in the (Great, Big, Messy) Real World: Rewire Your Marketing Organization to Navigate Anything) lays out 4 mindset shifts, investor, navigator, statistician, and ecologist, for leading marketing in a volatile world. These days she splits her time between writing, advising, passion projects, and being a grandmother of 2.

Why Marketing Behaves More Like Weather Than a Machine

Every marketing leader has sat across from a finance executive who wants one thing. Put a dollar in, know what comes out. Budgets get built on that promise. Forecasts get defended on it. And every year, the results wander off somewhere the model never predicted.

Kathleen has spent more than a decade explaining why that keeps happening. Her line is that marketing is not a vending machine. A vending machine is controllable and predictable. You put your money in, you press the button, you get the exact thing you chose. Executives, she says, would give almost anything for marketing to work that cleanly. Marketing never has.

“Sadly, we all know that marketing is a lot more like the weather.”

The weather comparison is a humbling one. We carry supercomputers in our pockets, we have decades of atmospheric data, and we still can’t say for sure whether it’ll rain tomorrow. Marketing runs on something messier than the atmosphere, which is people. Buyers, brands, influencers, partners, and the economy, all reacting to each other at once. Kathleen calls the result a complex system, the kind scientists study, where every interaction feeds back into the next and quietly introduces unknowns into every situation.

That’s the part most measurement frameworks skip over. Marketers, salespeople, and customer experience teams all work at the edge of the company, the seam where the controllable inside meets the uncontrollable outside. Their whole job is to manage, predict, and measure a world that refuses to hold still. No amount of dashboard polish changes the fact that half the inputs live outside the building.

Kathleen keeps the parts of the old factory toolkit that still earn their place. The shift she wants is smaller and harder to swallow. Accept that markets are what the military calls VUCA, volatile, uncertain, complex, and ambiguous, then adopt measurement practices built for that reality instead of pretending the reality is something tamer. The methods already exist. Other fields use them every day. Marketing just hasn’t bothered to translate them yet.

The uncomfortable implication is that a lot of the dashboards marketing teams present with total confidence are measuring a machine that was never really there. The teams that win the next decade will be the ones who stop apologizing for uncertainty and start building for it.

Key takeaway: Audit your current reporting for any number you present as a guarantee. Rewrite each one as a range or a probability, and rehearse saying “here’s what’s likely and here’s what could move it” before your next budget review. Present every forecast as a weather report, a set of ranges you can actually defend.

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The 4 Mindsets Marketing Leaders Need for Complex Markets

You can buy a new attribution platform, restructure the team, bolt on a dozen dashboards, and still land exactly where you started. Kathleen thinks she knows why. You changed your operations without changing the thing that steers them, which is your mindset. She treats mindset as the director of every action a team takes. Leave it untouched, and every operational upgrade delivers roughly the same results you’ve always had.

Her favorite way to explain this comes from Buddhism. Your mind is the ox, and the cart is everything the ox drags behind it, every outcome your marketing produces.

“Your mind is like the oxen pulling the cart, and the cart is what delivers all of your outcomes. If you don’t change the direction of the oxen, then your cart’s just gonna keep following in the same direction.”

The leverage is quieter than it looks. Change your mindset and the dozens of small decisions you make every day start bending, even slightly, and over enough decisions you end up miles from where the old direction would have taken you. That’s why the mindset has to move first. The 4 she recommends all come from worlds that are genuinely volatile and complex, but they’re worlds anyone can picture, and each one maps onto something marketing leaders already wrestle with.

• Investor: stop treating the budget like a cost center you spend down, and start treating it like a portfolio you risk for a better future return.
• Navigator: change the relationship between your plan and your measurement, adapting like a pilot or a sailor who reads the conditions in front of them instead of clinging to the route.
• Statistician: give up the hunt for certainty and accept that everything in the human and natural world runs on probability. Kathleen calls this the hardest of the 4 because our brains hate it.
• Ecologist: manage the conditions people work in, because behavior arises from the intersection of an individual and the context around them, so managing the person by themselves only covers half of it.

Read them together and a pattern shows up. Every one asks you to trade the illusion of control for the ability to adapt. That trade is where most transformation efforts quietly die, because swapping tools is easy and swapping beliefs is not.

Key takeaway: Before you approve the next platform or reorg, write down the belief driving it in one sentence. If that belief still assumes marketing is predictable and controllable, fix the belief before you spend the money. Pick one of the 4 mindsets and name the single daily decision it would change for you this quarter.

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Why ROI Doesn’t Work as a Marketing Measurement

Ask a room of marketers what keeps them up at night and ROI lands near the top every time. It’s the question waiting in every board meeting. What drove revenue last month, and how much will this next bet add? Kathleen has been chasing that question longer than most. Running IDC’s CMO advisory practice for 9 years, she kept asking leaders whether they were actually getting ROI, and the answers always came wrapped in so many caveats that the number stopped meaning anything. That’s what sent her down this whole path.

The problem is structural, not a matter of effort. ROI only works when you can cleanly separate the parts. Build a machine and you can swap one component, source another differently, and watch the return move in response. Marketing has no such parts.

“Instead of treating your inability to get deterministic answers as a failure, you treat that information as, well, deviations are information.”

She uses a purchase everyone has made. You buy a new car, and someone asks you to isolate exactly what tipped the decision. Was it the brand, the review you read, the thing your brother-in-law swore by, a commercial, an influencer clip. You can’t pull those threads apart, because in a complex world they’re all wired together. That doesn’t let marketers off the hook. You should still work out which influences move buyers the most and pour your effort there. You can gather real information about ROI. You just can’t measure it to the decimal.

The reframe is where it gets useful. When your numbers refuse to give a clean answer, that gap is data. Every deviation between what you expected and what happened tells you something about the system, and you use it to get closer and closer to the truth. You never hit it exactly. You do get better every cycle. There’s real math underneath this, the same math that governs any complex system, and pretending it isn’t there is how teams keep promising precision they can’t deliver.

The honest move for most teams is to stop reporting ROI as a single confident figure and start reporting it as a direction of travel. A leader who can show the system trending the right way, and explain what the deviations mean, earns more trust than one defending a number everybody quietly knows is invented.

Key takeaway: Stop presenting a single ROI figure you can’t defend. Identify the 2 or 3 influences that move your buyers most, measure whether they’re trending up or down, and bring the deviations to the table as signal instead of hiding them. Frame the conversation around getting closer, not around being certain.

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What Causal AI Can Actually Tell You About Marketing

The correlation versus causation fight has been running in measurement circles for years, and it usually splits into 2 camps. One camp says causation in marketing is basically hopeless. No real randomization, too many confounding variables, confidence intervals too wide to act on, so accept correlation and move on. The other says correlation only describes what’s already happening, and causal AI is the thing that finally tells you whether your actions cause the result. Kathleen refuses to pick a side, and once you hear her reasoning, the fight looks like the wrong argument to be having.

Her starting point is that both camps can be fanatical about measurement and both use the same data. What separates them is how they treat it. In a complex world, you use data to find patterns and trends, because the noise isn’t random. How much signal you get depends heavily on your industry. Work in a large, mature category with established brands and rare innovation, and the patterns tighten up fast. She points to the consumer world, where a diaper brand can track how many babies are born and how many diapers each one goes through, and get remarkably close to the truth.

Now flip to high-innovation tech and B2B, with tangled buying groups and constant disruption, and your ability to predict drops through the floor. Both worlds are probabilistic. One is just far more volatile than the other. That’s why lifting a consumer-marketing playbook and dropping it into B2B produces such bad forecasts, because the underlying volatility isn’t remotely the same.

“Causal AI tends to tell you what persists. If you have a change in context, what are the elements that persist and are most likely to get you there?”

This is where causal AI earns its keep, and it’s a narrower claim than the hype makes it. The upside is scope. You can feed it far more data and build far more sophisticated models than older tools allowed. But it obeys the same law as everything else in analytics. Good data in, interesting results out. Crappy or incomplete data in, and no amount of causal modeling saves you. What it does well is tell you what persists. When the context shifts, it points to the elements of your program most likely to keep working and carry you forward. It won’t promise that a specific deal closes. As Kathleen half-jokes, maybe it even could, but never in a deterministic way.

The real value of causal AI isn’t certainty, and teams that buy it expecting certainty will be disappointed. Its value is durability, telling you which of your plays survive when the market moves under your feet. That’s a better question than the one most attribution tools are built to answer.

Key takeaway: Before you invest in causal AI, grade your data honestly, because weak inputs waste the whole exercise. Then aim the tool at the right question. Ask which parts of your program persist when the context changes, and fund those, rather than asking it to prove a single campaign caused a single deal.

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How Industry Experience Shapes What Marketing Can Predict

There’s a reason a brilliant B2C analyst can move to B2B and suddenly feel lost. In consumer marketing you often swim in data, thousands or millions of users, enough to predict behavior to a high degree. Cross into B2B and the data thins out while the guessing goes up. Kathleen sees experience, or at least awareness, as the thing that decides how well someone reads that difference.

“Marketing more than any other function within the company is context related.”

She’s careful not to lock people into a single lane. Nobody is stuck in consumer products forever, and plenty of skills carry across. But the trap is real. She’s talked with analysts and marketers who moved between B2C and B2B, knew intellectually that the 2 behave differently, and still couldn’t figure out what to do with that knowledge. Marketing sits closer to the messy outside world than finance or HR, so the context you’re operating in shapes what you can measure and what you can only estimate. Knowing which is which comes from having lived in that industry, or from paying enough attention to learn what actually matters there.

Key takeaway: When you hire or move into a new category, treat the industry’s data density as a first-order question. Ask how predictable buyer behavior actually is here before importing benchmarks from your last role, and give yourself a ramp to learn what signals the category rewards.

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Why Your Marketing Budget Works Like an Investment Portfolio

Most marketing budgets get treated as money to spend and then justify. The investor mindset flips the frame. A budget is capital you risk for a better future return, the way an investor risks money in a portfolio rather than spending it. Darrell put it in poker terms, which Kathleen liked, and it turns out one of her big inspirations for the book was Annie Duke, the former professional poker player who writes about thinking in bets. Diversify the portfolio, size the bets, accept that some will lose. That’s the posture.

Then she adds the part that reshapes how you’d actually allocate the money. Complex systems are sensitive to their starting conditions. Most people know this as the butterfly effect, from the 1970s paper asking whether a butterfly flapping its wings in Brazil could set off a tornado in Texas. Tiny changes early in a process can cause enormous, unintended swings later, good or bad.

“In complex systems, the work that you do early makes a much bigger difference than you would think.”

Compare it to a machine and the difference gets obvious. Press the gas a little and the car speeds up a little. Press harder and it speeds up more. Machines are linear and deterministic. Markets aren’t. A random conversation with someone at a conference 3 years ago, where they simply remembered you, can turn into a huge deal that lands in 2026. Or the same tiny input can cost you a deal you never knew you were in.

This is exactly where measurement goes wrong. Teams fixate on what happened yesterday, or which campaign generated last month’s leads, when the things actually moving the outcome started far earlier, and sometimes other people started them. In B2B, the buying group often assembles 2, 3, or 4 vendors right at the beginning, and then the deal is theirs to lose. A new brand trying to break in later faces long odds. Ask any salesperson and they’ll tell you the same thing. The moves that matter usually began a long time ago. So when you set the budget, investing early takes a real amount of faith, because you can’t fully measure the payoff. Kathleen has collected proxy measures over the years that get you close on whether branding is working, but close is the ceiling, and pretending otherwise is how early investment keeps losing budget fights to last-click reporting.

The measurement obsession with last month’s leads is measuring the wrong end of the timeline. A marketing team that can defend its earliest, least-attributable investments is protecting the exact work most likely to compound, and that’s a harder and more valuable argument than defending a tidy monthly number.

Key takeaway: Split your budget into bets and label each one by time horizon. Protect a portion for early, hard-to-measure work like brand and relationships, and defend it with proxy signals instead of demanding last-month attribution. Judge the portfolio on how it performs across cycles, not on any single line item.

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What Marketers Should Actually Be Held Accountable For

Marketers love to complain that theirs is the only department forced to prove its worth over and over. Phil has pushed back on that story before, and he’s right to. Sales gets scrutinized just as hard, carries quotas, and gets cut just as fast in a downturn. The difference is the kind of spend. Marketing controls growth capital it can throw at ads and bets, tied directly to revenue, and that makes every dollar feel like it needs a defense. So the honest question is whether marketers should just be trusted to allocate that capital like any other investor, instead of justifying each line.

Kathleen doesn’t take the bait. Marketing, sales, and customer service all sit at the edge of the company, and all of them need to be accountable. If she were the CEO, she wouldn’t hand people money and say spend it however you like. That’s not good practice. The real question is what you hold them accountable for.

“Marketers can’t be held accountable for things that for which they have no control.”

What they own instead is the quality of the decisions they help the whole business make, and how well they steward the money they’re given, all while knowing they can never be pinned to exact outcomes. She won’t throw anyone under the bus, because most people are doing as much as they can with the tools and conversations they’ve got. Often the breakdown is upstream. Marketers sometimes don’t know what the company is actually trying to do, or whether the goal was ever realistic. Sometimes that’s on the marketer, sometimes on the company.

Her evidence that this lands comes from outside the marketing bubble. She met the COO of a large Texas company on a cruise, told him what her book was about, and watched his eyes widen until he asked her to put the book on his phone so he could hand it to someone back at the office. CFOs tell her the same thing. Why did nobody explain this sooner, it makes so much sense. A few are strict penny-counters, and she has sympathy for anyone stuck working for one. Most are knowledgeable businesspeople who don’t find any of this shocking. They just want marketers to understand the reality, bring the data that helps them decide, and be a trusted partner in the conversation.

The accountability fight stays stuck because marketers keep accepting responsibility for outcomes nobody could guarantee. Shift the contract to decision quality and stewardship, and marketing stops being the department on trial and starts being the one finance actually wants in the room.

Key takeaway: Renegotiate what your team is graded on. Propose accountability for stewardship and decision-quality information you provide, not for revenue outcomes you don’t fully control. Walk into your next leadership review with the 2 or 3 decisions your data improved this quarter, and position yourself as the partner who informs the call.

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Why a Single Marketing Metric Always Fails You

Every marketer has been graded on a single number. Hit the pipeline target, hit the revenue target, and that one figure becomes your whole performance story for the year. Darrell asked whether a smarter review might split the difference, half tied to a hard metric like pipeline, half reserved for the fuzzy stuff like brand and community. Kathleen’s answer went somewhere more useful than a fifty-fifty split. In a complex system, no single metric pays off, no matter how you weight it.

The name for the failure is surrogation, and her blog post on it is the most-read thing she’s written. Surrogation is when one metric quietly becomes a stand-in for the performance of the entire system. The map becomes the city. You start managing the roadmap instead of the actual streets, and before long the number is the goal and the thing it was supposed to represent gets forgotten.

“I really cringe when I hear people say like, I’m just totally on leads, or I’m just totally on revenue. Because I don’t care what you pick, it’s not going to be adequate.”

Her fix isn’t a mountain of metrics either, because a bazillion numbers just freezes everyone and no decision gets made. She wants a small set that pulls against itself, so managers have to work through the tension instead of gaming one dial. Here’s what that set looks like in practice.

• 3 to 6 metrics, no more, so people can actually hold them in their heads.
• Metrics that are somewhat in conflict with each other, so keeping them all healthy forces real trade-off conversations.
• High-level numbers connected directly to the business, never low-level vanity counts like website hits.
• Reviewed on a live dashboard, not saved up for the annual review, so there are no surprises.
• Measured all along the buyer’s journey, the external view, not the internal funnel.

That last distinction carries more weight than it seems. The funnel is how the company sees itself. The buyer’s journey is how the customer actually moves, and Kathleen is adamant those are very different maps. She also wants the whole exercise aimed at making the entire company more effective, not just the marketing function, which is why the metrics have to be diagnostic. When a number deviates from expectation, that deviation is information feeding the higher-level decisions, and it should be a running conversation rather than a once-a-year verdict.

The single north-star metric that so many teams brag about is a surrogation machine in disguise. Any organization that can hold 3 to 6 conflicting measures in productive tension is closer to managing reality than one chasing a clean number it will eventually start faking.

Key takeaway: Replace your single north-star metric with a set of 3 to 6 measures that deliberately pull against each other. Put them on a live dashboard tied to the buyer’s journey, review them continuously, and treat every deviation as diagnostic information rather than a reason to blame someone.

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Why Marketing Managers Should Create Conditions Instead of Commands

You hire someone brilliant, hand them clear targets, and they underperform anyway. Most managers respond by tightening the grip, more oversight, more direction, more control. The ecologist mindset says the grip is the problem. In a complex system, individual performance comes out of the intersection of the person and the context around them, so managing the person alone leaves half the equation untouched.

Kathleen reaches for gardening to make it concrete, and it fit the conversation nicely, since Phil has a cucumber patch going. Anyone who has raised a plant, or a child, knows you’re really in the business of creating conditions. You can’t command a living thing. You can’t order a plant to grow or a child to become a specific person when they grow up. You pick the right plant for the spot, put the right person in the right role, and then your real job starts.

“If you create the conditions for people’s success, they will thrive.”

She’s managed hundreds and hundreds of people, and the pattern held every time. Take someone out of a top-down control setup, drop them on a tiger team, and just let them go, and the results can be startling. Talented people do it, and so do perfectly average people, once the situation stops fighting them. We’ve watched this happen over and over, and we still keep believing we can control our way to better output. The lesson isn’t to stop coaching individuals, because picking people and developing them stays essential. The lesson is to stop treating that as the whole job.

What that changes day to day is where a manager spends their energy. Instead of pushing harder on each person, you build the links and the network conditions that let a whole community of people work better together. Kathleen fills a good chunk of her book with those mechanics, because the shift is easy to nod along to and genuinely hard to operate.

The org chart is a control fantasy that keeps managers busy managing the wrong variable. The teams that consistently outperform are usually the ones whose leaders got quietly good at engineering conditions and then got out of the way.

Key takeaway: Pick one underperforming role and diagnose the conditions before you diagnose the person. Redesign the surrounding context, the links, the autonomy, the team structure, and see what changes. Spend your next month building conditions for the group rather than issuing directives to individuals.

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How to Tell a System Problem From a Person Problem

The gardening analogy raises an obvious hard question. What do you do when a plant won’t grow even after you’ve gotten the conditions right? Phil pushed on it directly. Is that a system problem or a person problem, and can you design a role so it’s structurally set up not to fail? Kathleen wouldn’t hand over a clean escape. You can’t guarantee anything against failure, and sometimes the problem really is the individual.

“You’re not doing them any favor or anybody else any favor by keeping somebody who’s just not performing.”

Her sequence is to investigate before you assign blame. Check whether the person is in the wrong role, or whether something environmental is dragging them down, or whether it’s one of the personnel conflicts every manager eventually meets. Making accountability a squad rather than a solo act helps here too, because integrated teams hold up better in complex conditions, and she spends real pages in the book on why the old silos should be softened and blended. But once you’ve genuinely worked the options and the person still can’t perform, keeping them helps no one. Sometimes the job is to make the hard call.

Key takeaway: Before acting on an underperformer, run a short checklist: wrong role, bad environment, or a real personnel conflict. Rule out the system causes first, and if none of them explain it after an honest look, make the hard decision rather than dragging it out for everyone’s sake.

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How to Make a Marketing Budget Adaptable With Pace Layering

The navigator mindset treats the plan as a compass instead of a contract, and it runs straight into a wall every marketer knows. The budget gets set in January, it can’t move much, and that’s exactly why teams default to rigid annual plans. Darrell named the tension, because he’s tried to run sprints and faster iterations against a budget that simply won’t flex. Kathleen thinks this is one of the areas where you can make an immediate change.

She sets one thing aside first. She’s assuming a relatively stable budget, since she’s worked at places where marketing was the only big pot of money and got raided the moment the CEO needed to hit a quarterly number. Put that case aside, and her tool is pace layering, borrowed from another field. You split the budget into pieces that get adjusted on different clocks. The annual number still gets set along the financial plan, because companies need that for legal and planning reasons. Committing all the spending on day one is the mistake.

“Some parts of the budget should be rented, not owned.”

The logic tracks how close the money sits to the customer. Long lead-time work like big events has to be locked early, sometimes 2 years out. As you move closer to the customer, you allow more and more degrees of freedom. So you might give your field marketers a set amount, then reserve the right to pull back a percentage and move it as conditions change. If Central Europe suddenly booms, you shift field money there from North America, and everyone understands why, because the reallocation runs on transparent, well-known priorities rather than a quiet grab. Even those enormous events work this way underneath. Certain line items get committed years ahead, and others get decided almost on the day, because that’s where the changeability lives.

What this really breaks apart is the image of the whole budget roaring down the freeway together, locked in one lane from January to December. Kathleen wants you to see it as layers moving at different speeds, each with its own tolerance for change. Plenty of companies already run this way. The mindset shift is refusing to treat the plan as a single monolith and starting to manage it across different horizons of time.

The locked annual budget is a relic of the factory era, and it quietly punishes any team trying to respond to a market that moves weekly. Layered capital, with a portion explicitly rented and reallocated in the open, is what lets a marketing org stay accountable and adaptive at the same time.

Key takeaway: Break your annual budget into layers by how close each dollar sits to the customer. Lock the long lead-time commitments early, and mark a clear percentage of the customer-facing spend as rented, reallocated quarterly against transparent priorities. Tell your teams up front which money is theirs to keep and which you may move.

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What Planning Is Actually For When the Plan Is Always Wrong

Phil raised the question every marketing ops person has muttered under their breath. He’s been at companies where planning was a brutal monthly ritual, stop everything, review last month, comb the backlog, decide the next move, and then ditch the whole thing 2 weeks later when conditions shifted. So what’s the point of pouring effort into a plan you keep throwing away? Kathleen doesn’t flinch on this. Planning is essential, and the reasons have little to do with predicting the future.

“The plan itself is wrong the moment that it’s released, so we just have to accept that.”

The value lives in the act, not the artifact. Planning forces you to think problems through, and you’ll catch at least some of what’s coming even if you miss the rest. It creates alignment, brings people together to reason through hard calls, settles everyone down, and makes coordination possible. What she rejects is the monolithic plan that tries to predict what the field will do in September while the ink is still drying in January. Some things genuinely need long lead times and deserve real planning. The rest should be modular. You don’t lock everything on day one. You set the pieces that must be set in advance, headcount and a rough budget distribution, and you keep the near-term pieces loose, telling a team you’ll confirm in 6 weeks whether the money stays theirs. Plan as a living practice, and the plan being wrong stops being a failure and becomes the point.

Key takeaway: Keep planning, but stop grading the team against a static plan set months ago. Run it as a modular, recurring practice: lock only the long-lead commitments, hold the near-term choices open, and measure the quality of the thinking and alignment the process produces rather than the accuracy of the document.

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How Intention Decides What Deserves Your Energy

Deciding what deserves your energy is its own kind of complex system, and most people never build a method for it. Kathleen has. She stopped her paying job a few years ago, and her days now run on writing, passion projects, volunteering, and being a grandmother to 2 grandsons. When the closing question landed, how she chooses where her attention goes, she pointed straight at intention.

“Over a lifetime you kind of learn, if you really pay attention, what does make you happy and what doesn’t.”

She’s been a meditator for a long time, and she credits it with a specific skill, the ability to listen to her own body and read what it’s telling her. What does joy actually feel like, what does disgust feel like, and then you steer by those signals. There’s a nice symmetry to it. The same woman arguing that marketing should sense and adapt rather than force certainty runs her own life on exactly that logic.

The other half is pure marketing ops, a field she helped establish years ago. She’s a planner who keeps lots of lists. She doesn’t track data on herself, but she uses those lists to make sure she’s giving real time to health, relationships, and purpose, so none of it slips by haphazardly. She still adjusts, still learns, and keeps a lot of intention behind the steering. Sense the signals, hold the intention, adjust as you go. It’s the navigator mindset pointed inward.

Key takeaway: Build a short, standing list of what actually matters to you across health, relationships, and purpose, and check your time against it on a regular cadence. Pay attention to how different work makes your body feel, and use those signals to steer instead of letting your calendar decide by default.

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Episode Recap

Kathleen Schaub makes one central argument, and everything else in the conversation hangs off it. Marketing is not a vending machine. Markets are complex adaptive systems, closer to weather than machinery, and the industrial habit of demanding predictable outputs from predictable inputs is the root cause of most measurement pain. Once you accept that markets are volatile, uncertain, complex, and ambiguous, the job changes from forcing certainty to sensing and adapting.

The tactical thread runs through her 4 mindsets. As an investor, you treat the budget as capital to risk across a portfolio of bets, protecting the early, hard-to-measure work that compounds later. As a statistician, you give up clean ROI for probability, reading deviations as information and pointing tools like causal AI at what persists when the context shifts. As an ecologist, you manage the conditions people work in instead of commanding individuals. As a navigator, you break the annual budget into layers that move at different speeds, renting part of it so you can reallocate as the market moves. Underneath all 4 sits her warning about surrogation, the way a single metric quietly becomes a stand-in for the whole system and starts getting gamed.

For practitioners, the implications are concrete and a little uncomfortable. The dashboards many teams defend with confidence are measuring precision the data can’t actually support. The fix is a small set of conflicting metrics tied to the buyer’s journey, an accountability contract built on decision quality rather than outcomes nobody controls, and a planning practice valued for alignment instead of prediction. None of this throws out rigor. It moves the rigor to the places where it can actually hold.

Kathleen is honest about the limits too. Causal AI won’t manufacture certainty, and weak data ruins the whole exercise. Some underperformers really are a person problem, not a system problem, and sometimes the humane move is the hard decision. Even her advice to think like an investor comes with the admission that early investments take real faith, because you can’t fully measure the payoff. That willingness to sit with what can’t be known is what makes the framework usable rather than just clever.

Follow Kathleen’s work and read more on her mindsets, measurement, and complexity writing at KathleenSchaub.com.

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Intro music by Wowa via Unminus
Cover art created with Midjourney (check out how)

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