Ask most attraction operators what a rainy day does to their numbers and they'll tell you confidently. Outdoors? Bad. Indoors? Good. Simple, right?
Except it isn't. A rainy weekday in summer behaves differently to a long weekend in winter. The wet can improve auxiliary per caps, even if visitation is depressed. The confident answer is often a false belief, one many operators are running decisions on, every day.
This is what I think about. Not software or dashboards, but decisions. How we make them, what gets in the way and what it would mean to make them better. Sometimes they’re small decisions (that sneakily add up), like responding to the weather forecast. Sometimes they’re big decisions, with significant consequences, like changing pricing models.
Sometimes, they’re the decisions that aren’t made. Here's something I've seen more than once, and it never gets less striking: an attraction publishes its visitation figures, puts them in the annual report, presents them to the board. If they’re publicly listed, a non profit, or a government organization, they’ll go on to publish them publicly, often as a point of pride. And the number is wrong. Significantly wrong. More than once, I’m talking about over a magnitude of over a third - all down to wrong assumptions, or how it was being calculated.
What makes this remarkable isn't the error, it happens. It’s that often, people inside that organization had known for years, said nothing. Or more accurately, decided to do nothing (and not realized that was a decision). The number had become institutional fact, referenced in enough reports, repeated in enough meetings, that challenging it felt impossible. The elephant in the data, sitting quietly in every boardroom conversation. Maybe those board members knew it too. Maybe they didn’t. I’m not sure which is the more uncomfortable truth.
I've been there as brave leaders have made the hard decision to call it. Every time, the conversation that follows is difficult. Every time, once it's done, the relief is palpable. Because you can't make good decisions on information, let alone insight you don't trust. Somewhere, beneath the silence, everyone knew that too.
That moment, the calling of the thing everyone knows but fails to say aloud, is one of the most important acts of leadership. It's also, almost by definition, not something AI does for you (it will quietly tell you, it just won’t stand up in said board meeting and be the true bearer of that news). It takes judgment, courage and the willingness to live through the discomfort.
Which is exactly what I want to talk about.
We are entering an era where analytical work gets done faster, more thoroughly and at lower cost than ever before. AI finds the pattern in ten years of data split between silo systems that no analyst would spot. It surfaces anomalies, finds nuance, runs scenarios, synthesizes signals. The work of insight is becoming abundant.
Which means the scarce thing, the thing that determines outcomes, is what you do with that insight once you have it. That work is irreducibly human. Messy, contextual, relational, hard in ways no model captures. I think about this as the difference between what we know and what you feel. What's in the system are things that can be documented, measured, modeled, now at a level previously unattainable by human hand. Then we have what you've absorbed from all your years as an operator: what you read in a room, what you sense beneath what a stakeholder is saying, what your community means in ways no dataset will fully capture. The partnership between human and AI isn't human versus machine. It's knowledge and intuition in conversation, each doing what it does best.
But that partnership only really works if the human side shows up with its full potential. And in my experience, there are a lot of ways we don't - speaking from personal acquaintance with most of them.
The decisions we don't know we're making. The most dangerous ones. They live in habit, in process, in assumption: the way the weekly report gets read, or doesn't; the implicit judgment that this audience matters more than that one; the merch we order on repeat. Nobody calls these decisions, we don’t really notice we’re making them, so data never gets near them. They run on autopilot, accumulating consequence quietly. That visitation number, calculated wrong for a decade, could be one version of this. So is the pricing structure nobody has questioned since 2018, the queue trade off we’ve come to accept, or the season pass model that's slowly eroding your most loyal fans.
Managed by the torrent. You arrive without a plan and the day swallows you. By five o'clock you've responded to forty things and decided nothing of significance. That's not leadership, rather management by inbox. It isn't just unproductive, it consumes the cognitive resource you need most for the decisions that actually shape your organization’s future. Decisions become reactive - consequentially inconsequential. The team burns out around you, busy treading water.
The false binary. A team works hard, reduces a problem to a choice, presents it upward: do you want A or B? The answer is often: a lot of A, some of B, plus something neither has named yet. The binary frame strips out the nuance that would let a good leader find the third way, that thread the needle moment where you can serve multiple objectives at once, rather than feeling forced to sacrifice one for another.
Opportunity cost blindness. The other day, I watched a customer executive deny their teams access to a mainstream AI assistance tool to save budget. The actual cost in time and capability was likely in the millions. The saving didn't show up on any balance sheet, so it never got counted. The decision looked fiscally responsible when it was actually expensive.
Lost in the analysis. More data, more dashboards, more meetings to discuss the data from the last meeting. Another three weeks, scrap that - months - for the consultants to come in. The analysis becomes the work. The actual decision, that act of choosing and committing to change, keeps getting deferred. We're in our heads, when we need to be looking up.
Procrastination dressed as prudence. A close friend of analysis paralysis - the need for more information, time, alignment. Sometimes that's true. Often it's fear wearing sensible clothes. Not deciding is itself a decision. It’s often the one people will agree with easily, but usually the most expensive decision to make.
The elephant in the data. The thing everyone knows and nobody names. The inflated visitation number. The churn nobody wants to report upward. The happiness scores quietly declining for three years, or the voices underneath them which reveal deeply uncomfortable truths. Inside the organization, people see it. The data sees it. But naming it requires courageous leadership.
Then, there’s my personal favorite that I’ve humbly learned more than once.
When the decision you fear the most is the one you really need. Twice now I've faced a decision that divided life into the 'before' and the 'after: once personally, once professionally. Both times every instinct in my body screamed to avoid it. Both times I (…eventually) made the hard call anyway. Both times, what I feared the most turned out to be far less damaging than the weight of playing not to lose. I would even go as far as to say it turned out for the better. Good things came from the hard thing, those gold nuggets found at the bottom of the well. On the other side wasn't just relief, it was clarity, freedom and the ability to move forward differently.
Those who finally called their false visitation metric found something unexpected afterwards: insights and culture that gave way to the growth they'd been chasing for years. The decision wasn't the hard part, the avoidance was.
The question that drives our work at accesso Intelligence is what good decision empowerment actually looks like in practice. Is it autonomous agentic analysis running quietly in the background, surfacing only when there's something worth deciding? Is it the way the stories of insight get told, the framing, the ability to help someone see the forest through the trees, or realize they're in the wrong one entirely? Is it the people work: the messy, relational, deeply human act of bringing the right stakeholders into a decision, challenging the assumption, holding space for change?
I think it's all of these and more. The rain isn't just bad. The visitation number might not be what you think. And the leaders who will thrive in this era are the ones who invest in getting to superior insight faster - so they can spend their energy where it matters most.
Because as it turns out, it’s not our insights that matter the most. It’s your judgment.
That's the work. That's what we’re here to figure out, together.