I've been trying to work out for years why so many good decisions arrive late.
Not wrong, exactly. Late.
Because the people making them are usually careful and properly smart. Wanting more data before you commit is a perfectly sensible instinct. Most of the time.
And then the window closes while the team is still polishing the slide that would have opened it.
Beautifully argued. Slightly too late.
I say this as someone who has, more than once, researched a decision so thoroughly that it went and made itself while I wasn't looking.
For me, that is what learning agility training is really for. Learning fast enough to act while it still matters.
So this programme puts your managers somewhere the data is never complete and the ground keeps moving. Then it takes one real decision of theirs and gives it a date.
How the change happens: play, then EPPA
Every session runs on one loop. I call it EPPA - Experience, Patterns, Principles, Application.
- Experience. The game itself. Probing, guessing, arguing, and occasionally crashing.
- Patterns. The room names what kept repeating. The debrief is built to surface who waited, who probed, and who defended the first plan long after the planet had moved on.
- Principles. The room connects those patterns to how they handle the unknown at work. In their own words, because it lands better when they get there themselves.
- Application. A named behaviour, a real situation and a date. This is where people usually stall, so it's the step I've built the most around.
Application is also the only place AI comes in.
The game at the heart of it: Planetfall
In Planetfall, your managers are a crew in orbit around a planet nobody has mapped, trying to land in one piece.
Their probes come back half-legible. Some readings are exact. Some only give a range.
Every action in the game does one of two things. It buys certainty - probe the planet, decode a reading. Or it commits against what they still don't know - gather supplies, build an upgrade onto the ship.
And there are never enough actions to do both properly. That gap is the whole game, really.
No single person can run it, either. Every player except the Commander takes one cube a round and decides what it does, so a confident voice can advise but can't steer the whole crew. The Commander holds no cube and runs the round instead.
Then, late in the game, a sealed forecast is built to open a hole in exactly the system the crew trusted most.
Which is a bit mean of me. But it's also quite a lot like a normal quarter.
What the game is designed to bring out
The game is built so every crew starts with a plan that looks good. And then the planet turns, and the plan is wrong.
That's the moment Planetfall is built around. Here is what it's designed to make visible:
- The prober and the waiter. Who spends an action to learn something, and who holds on for a safer moment that is never going to arrive.
- Why the person who announced the plan first is so often the last to let go of it, and what the game is built to make that cost.
- The meta-decision. When do we stop debating and act? The game is designed so a beautiful position that arrives too late costs the crew.
- The decision rule. The game is built to reward crews who agree early what would make them act, and reach for it every time the conditions move.
- One shared picture, or five different readings. Whether the crew builds a single view from the same face-up data, or splits into people politely reading it different ways.
I won't tell them any of that. The game is built to, which I think lands far better than me saying it.
Where AI comes in, and where it doesn't
There's no AI on the planet. The game is probes, partial data, a lot of argument and the occasional crash landing.
AI only shows up at Application, after the room has named its own patterns. And it works on a real decision from their actual job, not on the game.
- Each manager brings one real decision that's stuck on "we need more data".
- They frame it first, using the Double Diamond, so they know which problem they're actually deciding before anyone opens a chat window.
- AI sorts what they know from what they don't, and drafts a decision rule. "We act when X."
- The manager sets the date to act.
What stays human: when to stop debating and act.
AI is good at sorting a messy pile of facts and guesses into two neat columns. Deciding that the columns are good enough is still a person's job, and I think it should be.
What your managers walk out with
- One stuck decision, unstuck. Framed, sorted and dated, before they leave the room.
- A decision rule they wrote themselves, in plain words. The same move the game is built to reward.
- An honest read on their own lean, toward action or toward analysis, from a made-up spaceship rather than a questionnaire.
- Imagine the next meeting where someone says "we need more data", and someone else asks, quite kindly, "what would X have to be for us to act?"
- A shared vocabulary for the team. Probers, waiters, and the plan from round one.
What I can show you
I'll be straight with you. Planetfall hasn't had its first client room yet. So everything I've said about it above is what it's designed to do, and it has no score of its own.
What I can tell you is how the rest of my work has landed.
I've been training founders and leaders since 2019, with founders in the US, Canada, Australia, Singapore and India.
On one programme at a Fortune 100 company, across six session-days, the satisfaction score came to 8.82/10 from 113 respondents.
Across every session-day I've had scored, it's 8.40/10 from 244 respondents. Which is probably the more useful number of the two, because it includes the days that went less well.
Who it fits
- Managers in fast-changing environments, where the data is never complete and the deadline doesn't wait for it.
- Organisations in the middle of a transformation, which is most of them.
- High-potential groups, where learning agility is the exact thing you're trying to build.
- Teams whose post-mortems keep landing on "we knew conditions had changed, and we stuck with the plan anyway".
Who would probably get more from something else
- Groups too small to split into crews. The patterns need a few people at each table to become visible.
- Leadership teams whose real problem is political rather than cognitive. I have programmes that get closer to that, and they're on the programmes page.
- When the real issue is who gets to decide, not how well they decide. That's a structure question, and a game won't fix it. A good conversation with your HR partner will probably get further.
- Anyone who'd rather buy a game with a long track record. That's a completely fair preference, and some of my other programmes have one.
A few fair worries
"How is this different from a normal business simulation?"
Most simulations I've seen score the outcome, and that's useful in its own way. Planetfall is built to watch the process. How did the crew behave the moment the right call stopped being obvious? In the debrief I walk back through the decision points instead of tallying results.
"Our people have played simulations before."
Fair, and it should help. They'll be past the mechanics sooner and quicker to spot their own patterns. It doesn't need novelty to do its job.
"It's new. Isn't that a risk?"
A bit, honestly, and I'd rather say so than hide it. What isn't new is the loop around it, or the person running it. I design every game I run, so if something at the table needs adjusting, I can usually adjust it on the spot.
"Can AI really help with a decision like this?"
Honestly, it can't make the decision, and I'd be worried if it did. What it does well is the sorting. Separating what you know from what you're assuming takes most of us an afternoon of arguing. AI gets you a first draft of that list quickly, and then the arguing can be about the right things.
Worst case? We have a conversation and you come out of it with a clearer brief.
Let's find out if it fits your managers
Your managers, the decision that's been waiting for more data, and a straight answer on whether this is the right programme.
Or just tell me what you're trying to fix
I went back and forth on whether to put a form at the end of this page.
Because a form asks you to be tidy about something you are probably still working out. And the enquiries I enjoy most tend to arrive as three messy lines, written by someone who has not finished deciding what they want yet.
So there are two ways in, and I genuinely do not mind which one you use.
Write to me directly at arvindh@puttheplayerfirst.com and say roughly what you want to change. Three lines is plenty. I read my own email.
Or fill this in, if that is easier. It lands in the same inbox.
I answer these myself, usually within a day. Two if I am in a room somewhere with my phone in a bag.
And you are not committing to anything by writing in. Worst case we have a conversation, and you come out of it with a clearer brief than you had this morning.
And if it turns out you really do just need the data... that's a perfectly good answer too.
With love from Bengaluru, this is Arvindh saying over and out.