What is the problem?
A list of trends is not a plan. Without a priority and a horizon, every trend looks equally urgent, so none of them changes a decision.
How does the model work?
Five steps, always in this order:
- Research. Collect weak signals. Look for at least three unrelated sources per trend.
- Cluster. Group the signals into a handful of bigger trends. One signal rarely matters. The trend ten of them form often does.
- Validate. Test each trend with people who work in the field. They kill the trends that only exist in reports.
- Prioritise. Place every trend on a 2x2: importance against certainty.
- Plan. Give every trend you keep a horizon and a date to look at it again.
The original cycle runs twice a year. I run it every quarter.
What does it look like?
The 2x2 asks two questions per trend. Importance: how much does it matter to us? Certainty: how sure are we that it is real?
- Act now. High importance, high certainty. Plan and budget for it this year.
- Keep a vigilant watch. High importance, low certainty. Watch for confirmation and prepare options.
- Informs strategy. Low importance, high certainty. Real, but not core yet. Let it shape the strategy without acting now.
- OK to dismiss. Low importance, low certainty. Park it until the next cycle.
Then the horizons: tactics for 1 to 2 years, strategy for 2 to 5 years, vision for 5 to 10 years, systems-level evolution beyond 10. The further out, the less certain, so the response gets broader: from actions, to a direction, to watching the system shift.
What did the first run teach me?
My first full run gave standard output: the trends every industry newsletter already carried, stated with more confidence than evidence. The process was fine. The inputs were not. A debrief led to three changes:
- Look across categories. A trend that shows up in technology, society and creative culture at once is hard to dismiss.
- Cap the AI trends. If half the board is AI, it is one megatrend in a lot of costumes.
- Look at the obscure on purpose. Standard sources give standard trends.
Reflection · 3 min readYou still have to know things.AI gives us access to answers in fields we know little about.And one rule: AI collects and structures the evidence, it does not pick the trends. A confident AI trend with round numbers is a yellow flag, not a finding.
How does it run in practice?
This model runs behind Movements. Daily, an agent logs datapoints from my newsletters in an evidence database. Weekly, I review the queue: promote, edit or dismiss. Quarterly, I run the five steps and publish a short read on four or five movements. Each quarter opens with a question: what got stronger, what changed direction, what no longer holds?
The noticing that feeds this uses a more intuitive method: Prime, converge, rationalise.
Why does it still matter?
AI made the scanning manageable. It did not make AI the judge. The work that is left is judgment: what matters, how sure you are, and when to look again.
Take the three trends your team keeps arguing about. Place each one on the 2x2, give each a horizon, and put the date you will look at it again in the calendar.
Origin: five steps and the 2x2 from my guest lecture on trends at Sogang University. Horizons adapted from Amy Webb, How to Do Strategic Planning Like a Futurist, Harvard Business Review, 30 July 2019. First-run lessons and the Movements workflow: my own practice, 2026.

