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Case study 02 · Entertainment · A decision story02 / 05

The hardest ticket on Earth is 3,000 years old.

Christopher Nolan's The Odyssey just opened. Fans joke that getting a seat is harder than anything Odysseus survived. They are not entirely wrong.

Opening weekend

A monster at the box office.

$123.5M
US opening weekend
$264M
worldwide in three days
$52M
on IMAX screens: the biggest opening in IMAX history
7.5M
tickets sold in the US alone
The catch

Only 41 machines on Earth can show it the way he shot it.

Nolan shot the film for a rare projector that has not been manufactured in decades. 25 of them live in the United States. The rest are scattered across the planet.

Fixed supply, furious demand. Tickets went on sale a year early and vanished. Even the 3 a.m. shows in New York sold out. Scalpers moved in the same day, flipping seats for hundreds of dollars.

The real problem

Every showtime is a decision. And nobody agrees on the goal.

Which city gets a print. Which slots it plays. What tickets cost. When they go on sale. Nine different companies own those 41 screens, and each wants something different.

How it's done today:one planner, one spreadsheet, one eye on the past. The usual method is last year's numbers plus instinct. But nothing like this has ever happened, so there is no last year. History cannot tell you how people behave during a first.

What we do · part one

Ask in plain English. Let the math find the best schedule.

Describe the goal the way you would say it out loud: fill every seat, keep prices fair, respect what each theatre wants. Our software turns that into precise math and searches millions of possible schedules for the provably best one.

The catch with perfect plans

A perfect plan is a wooden horse.

Flawless on the outside. What decides its fate is what is inside: people, and what they actually do. The Greeks understood that 3,000 years ago. Most planning software still does not.

What we do · part two

We build the crowd, then let it attack the plan.

Thousands of simulated moviegoers, each with a life of their own, rush the schedule the way real people would.

The plan fails in private, before it fails in public. The simulation shows exactly which showtimes get scalped, which families give up, and which seats sit empty, before a single real ticket is sold. Every fix goes back through the math, then back through the crowd, until the schedule survives everything the simulation throws at it.

The whole loop

Optimization for the answer. Agent simulation for the truth.

Plug into the data you already have. Ask the question in plain language. Get a plan that has already survived contact with people.

Have a decision like this?

We take on a small number of design partners. Bring the plan you are afraid to run.

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