A decimal can blow up a book.
Years later I'm building a glass IKEA display case with a bag of random tools in the basement of North Hall at Expo West, staring at the Siete booth, questioning if a HotProducts booth was really the best $20K use of a $50K annual marketing budget.
More calibration.
Two decades navigating markets where risk modeling and compliance collided between the SEC, FDA, and FTC. Where faulty assumptions survived because speed trumped patience, action was mistaken for success, and outside noise often drowned out common sense. The question was always the same: is this model practical or aspirational, and how does this actually make money?
As an IC committee reminded me weekly through our budgeting cadence, awareness doesn't pay the rent.
The pattern is consistent.
You already know something is off. The team's working hard, the campaigns are running, and revenue may even still be growing. But something is underperforming and nobody can explain exactly why. That's the pattern. Every time.
I reviewed a top-tier consulting firm's $12M year-one revenue forecast for a regulated healthcare business. Problem was the pharmacy throughput capped the math at $1.7M; a factor of seven gap. An assumption no one considered before presenting the forecast to investors. The symptom looked like weak execution. The actual issue was structural.
It is when a marketing team with P&G credentials is executing against a $10,000 monthly budget, all the brand could afford, and seeing no traction. Or someone has dropped $130,000 on a six-month PR retainer before market validation, purchase data, or consumer stories to tell. The agency work was as good as it could be, but catastrophically wrong for a pre-revenue company.
Five or six ECRMs ago, a category buyer came to my meeting room for our scheduled twenty minutes. It took her six minutes to eviscerate our pitch and walk out. Not because our deck or product was bad, but national accounts almost never drop an unproven brand into their assortment. That was $20,000 in registration, travel, and booth fees spent on aspiration, not reality. Execution got blamed. Nobody questioned the model.
Not every failure is commercial. I've told stakeholders the problem was governance, not growth. You don't win Walgreens or CVS on vibes. You don't build national retail distribution against a $5K monthly budget. You don't launch four products with the budget for one and blame the operator when the math doesn't work. The right GTM, the right product, and still dead on arrival because the expectations were an exponent of reality. The people running the campaigns were never hired to question the underlying model. That is a different mandate. It is the one I operate under.
Most people are trained to see the symptom, not the system.
See momentum
See throughput
See frameworks
See downside
I've spent twenty-five years operating across categories that rarely share a language. That makes structural failures easier to recognize when everyone else is still debating the symptom.
On the trading floor, bad assumptions were punished immediately. In DTC and CPG, the same mistakes took months and millions to surface. In regulated healthcare, compliance becomes a commercial constraint long before it becomes a legal one. In early-stage venture, every dollar deployed against the wrong model accelerates cash burn.
The framework is the same across all of them. Identify the assumption the model depends on. Stress it. Find where it fails. The trading desk called it risk management. Founders call it a commercial diagnostic. The math is identical.
I've walked into CAC assumptions nobody pressure-tested against public category economics. Revenue forecasts that collapsed under five minutes of throughput math. Pricing models built from COGS up with no room for real distribution costs. Omni-channel GTM plans that required twenty assumptions and a lotto win.
Most businesses think their problem is unique. Usually it isn't. I've just seen the same structural failure from enough angles to recognize it faster.
What kind of operator this is.
Analog markets to electronic infrastructure
Single-system expertise to cross-category pattern recognition
Revenue leadership to enterprise operating systems
Commercial execution to regulated infrastructure
I started in markets where trades were written on paper and mistakes were punished before lunch. Over twelve years, I helped modernize a brokerage through the shift from analog execution to electronic infrastructure, compliance automation, and institutional workflow systems before most operators had heard the word SaaS.
What followed was not a straight-line career. It was repeated adaptation across fundamentally different operating environments: early-stage venture, consumer growth, retail distribution, enterprise systems, asset-heavy manufacturing, regulated healthcare, and telehealth infrastructure. Different systems. Different industries. Same question every time: what breaks first?
AI makes the diagnostic faster.
It does not make the judgment easier.
Of course AI helps me. The analytical work that once required teams, analysts, and weeks can now happen in hours, if you know what questions to ask. Category benchmarks, three years of public filings, ZIP-level demographic segmentation, competitive pricing models. Access to information is no longer the moat. Judgment is.
Recently I built the full commercial infrastructure for a regulated telehealth platform as a single operator under active compliance scrutiny. The execution speed would have been impossible five years ago. The leverage came from AI. The judgment did not.
AI can aggregate data. It cannot tell you that the number in the filing invalidates the assumption in the pitch deck, or that the assumption in the pitch deck is the crux of the entire campaign.
This work is not for everyone.
The companies that get the most from this work tend to look familiar. Revenue between $2M and $50M. Growth that looks healthy on paper but is not producing the margin or unit economics the model promised. Capable teams stretched thin. Boards asking sharper questions. Agencies already hired. Consultants already paid. Still no clear answer.
The quiet version is the company doing $50M in revenue with $49M in cost, where everyone is too busy executing to ask whether the execution is pointed at the right problem.
The loud version is the founder who just watched a six-figure campaign underperform and cannot get a straight answer about why.
I have seen both. The budget is real. The margin for error is thin. The next decision actually matters.
What has to be true for each of these numbers to be true, and who owns each assumption?
Describe the business, what's not working, and where you need clarity.
Five questions. One business day. A direct answer. Initial diagnostic review is no-cost.
If there's a real issue worth solving, I'll tell you where it is. If there isn't, I'll tell you that too.