Most moodboards explain what a trend looks like. Very few explain why it's showing up now and not five years ago. That second question is where the useful stuff is, and it's almost never answered by looking at more pictures.

PESTEL is a good tool for forcing that question. It's old, it's a little boring, and it works because it makes you look where you weren't looking.

First, what kind of research this is

Trend spotting is qualitative research. Qualitative research tries to understand the meaning and the why behind a behavior, instead of counting how often it happens.

Counting how many people bought secondhand clothes last year is quantitative. Finding out what they think they're saying about themselves when they buy them is qualitative. The first gives you a number. The second tells you what to design.

Qualitative doesn't mean subjective or "less rigorous." It means the rigor lives somewhere else: not in sample size, but in traceability. Anyone should be able to follow where each claim came from. That's why every observation you record needs a date, a place and your own evidence.

A quick word on coolhunting

You'll hear trend spotting called "coolhunting." Malcolm Gladwell popularized the word in "The Coolhunt," published in The New Yorker on 17 March 1997, following trend scouts hired by sneaker brands. Peter Gloor and Scott Cooper later treated it as a method (Coolhunting, 2007): trace a signal back to its origin and to the community where it started, instead of stopping at the visible surface.

It's worth knowing the critique too. Jim McGuigan ("The Coolness of Capitalism Today," 2012) argues that "cool capitalism" aestheticizes products and hides the material conditions behind them. In short: when a brand turns a subculture into a product, the subculture loses what made it interesting and the brand keeps the profit. You can coolhunt knowing that, or you can be an extractor. The method is the same. The ethics aren't.

What a framework is (and isn't)

A framework is a fixed set of categories you use so you don't forget anything while analyzing. A grading rubric is a framework: it makes you check every criterion even when your first impression already gave you a grade.

A framework doesn't generate knowledge by itself. It organizes the search. Filling in all six PESTEL boxes isn't an analysis, it's a list. The analysis starts when you say which of the six forces is really doing the pushing, and why the other five matter less.

On the name: Francis Aguilar proposed environmental scanning in Scanning the Business Environment (1967) with four categories he called ETPS. PEST and PESTEL came later, as the strategy literature piled on letters. Credit Aguilar for environmental scanning, not for the acronym.

The six letters

P, Political. Public policy, stability, trade agreements, government priorities. In Mexico, for example, nearshoring of manufacturing and the relaunch of the "Hecho en México" seal have both shaped what "made locally" means.

E, Economic. Buying power, inflation, exchange rates, new business models. The steady growth of clothing resale is an economic story as much as a cultural one.

S, Social. Demographics, values, ways of living, platform use. A good reminder here: the platforms designers assume are dead are often the biggest ones. In Mexico, Facebook still reaches an enormous share of the population, far more than most design students would guess.

Those three rarely appear on a moodboard, and they're usually what explains why an aesthetic appears right now.

The three designers forget

T, Technological. What became possible, for whom, and since when. Until fairly recently, image generators mangled any text inside an image. By late 2025 several models could render readable text reliably. That changed what can be produced cheaply, and what no longer sets a professional apart.

E, Environmental. Climate, resources, waste, circular economy. The textile industry is a permanent case study here; the Ellen MacArthur Foundation's A New Textiles Economy (2017) is a good starting point.

L, Legal. Rules, obligations and deadlines. It's the most underrated letter and the most useful one, because laws come with dates. A few that affect designers directly:

• Mexico's NOM-051 front-of-pack warning labels, which forced food and drink packaging redesigns in phases.
• The European Accessibility Act, which started applying on 28 June 2025.
• Article 50 of the EU AI Act, whose transparency obligations apply from 2 August 2026. It requires AI-generated or manipulated content to be marked in a machine-readable way, and deepfakes to be visibly labeled. It applies to anyone offering the service in the EU, wherever they're based.

That last one is worth a moment. A European rule is likely to set the de facto global standard, the same way cookie banners spread everywhere. If you design for a brand with a European presence, disclosing AI use stops being a nice practice and becomes a requirement. That's a legal driver, with a date, that arrived before the trend did.

How to write a driver that actually helps

This is the single most useful habit in the whole method.

Doesn't help: "Social media." "The pandemic." "Artificial intelligence." "Sustainability."

Helps: "Since 28 June 2025, digital services sold in the EU must meet minimum accessibility requirements, which turns contrast and text size into a purchasing requirement instead of a designer's preference."

The rule: a driver has a subject, a verb and a date. If you remove the date and the sentence is still true, it wasn't a driver. It was a topic.

The test: read it out loud and ask, "was this just as true five years ago?" If yes, you haven't found the engine yet.

Signal versus noise

PESTEL helps you explain a signal. But first you need to know whether you have one.

Elina Hiltunen ("The future sign and its three dimensions," 2008) breaks a signal into three parts:

• The signal: what you observe. A photo, a sign in a shop window, a behavior, a post. It's the only thing you actually hold.
• The issue: the underlying change the signal supposedly points to. You don't see it directly; you infer it.
• The interpretation: what you and others decide it means. It changes depending on who's looking.

The key insight is that these can come apart. A signal's strength and the strength of the change behind it are independent. You can have a very loud signal about something that doesn't exist, and a nearly silent signal about something huge. Noise isn't a small signal. Noise is a signal with nothing behind it.

A practical test

Here's a rule of thumb built on Hiltunen's idea:

• Probably a signal if it makes people laugh, gets a "that'll never happen," most people haven't heard of it, and it feels a little embarrassing to say out loud.
• Probably noise if everyone nods, a big outlet already covered it, the algorithm recommended it to you, or you can explain it with a word that already exists.

The cost of being wrong isn't symmetrical. Writing down a signal that turns out to be nothing costs you one line. Not writing down the one that turned out to matter costs you the chance to date it later. H. Igor Ansoff, who coined "weak signals" in 1975, described them as incomplete information that arrives before certainty, useful only if you act before you're sure. Waiting until you're sure means arriving late, by definition.

The mistakes that sink a signal

• No date. It can't be verified.
• A screenshot with no origin. An image with no author or link isn't a source. Neither is a repost.
• "I see it everywhere" as an argument. Replace it with: who else is doing it, what need does it meet, and what force is pushing it.
• All from the same feed. If every signal came from one app, you documented your algorithm, not your surroundings. Get at least some from the street, shops, transit, a classroom.

All four are the same mistake in different clothes: confusing what reached you with what's happening.

Try it

Pick the one signal you think has the most future. Run PESTEL on it, one line per letter, with "doesn't apply, because..." where it doesn't. Write each driver with a subject, a verb and a date, plus a source you can link to. Then write one paragraph ranking the six forces: which one is really pushing, and why the others weigh less. That paragraph is the actual analysis. Everything above it is prep.

Further reading

• Aguilar, F. J. Scanning the Business Environment. Macmillan, 1967.
• Ansoff, H. I. "Managing Strategic Surprise by Response to Weak Signals." California Management Review 18(2), 1975.
• Hiltunen, E. "The future sign and its three dimensions." Futures 40(3), 2008.
• Gloor, P. A. and Cooper, S. M. Coolhunting: Chasing Down the Next Big Thing. AMACOM, 2007.
• Gladwell, M. "The Coolhunt." The New Yorker, 17 March 1997.
• McGuigan, J. "The Coolness of Capitalism Today." tripleC 10(2), 2012.