Before I ever planned a range, priced a collection or ran a business, I learned how yarn is spun and fabrics are built.
Yarn, construction, weight, hand, how a fabric behaves after the tenth wash. It wasn't glamorous. It turned out to be everything.
I didn't study merchandising. I studied textiles. At the time, that felt like the long way round. More than thirty years later, it's the reason I can do the job at all.
The first job was reading fabric
My first role at Ralph Lauren was at Chaps, graphing intarsia. Every sweater began as a grid: one square per stitch, one color per square. If the graph was wrong, the sweater was wrong, and no amount of styling could save it.
I learned to read a sweater backwards: from the finished piece to the grid, and from the grid to every decision someone had made along the way.
That's where I learned the rule I've used ever since. The product's truth lives in how it's made. Everything else, the story, the price, the floor, has to be built on top of that truth, not around it.
The degree kept showing up
I moved from product into retail, then into running whole businesses. The textile degree came with me every time.
At Burberry, we scaled the first core-replenishment platform, but only after restoring Made in England trench and quilt capacity. You can't plan a replenishment business on a make you don't understand.
At Temperley, we moved sourcing from about 90% Asia to 65% Europe in three seasons. That's a fabric and construction decision long before it's a spreadsheet one.
At Wrangler, our Women's Heritage line used laser-etched all-over herringbone, a first for the category. Knowing what the cloth could take is what made it possible.
Each time, the decision started with the cloth and ended in the numbers.
Why it matters more now
Every tool I've used has changed: the fax machine, Excel, PLM, Shopify, and now AI. The cloth hasn't.
AI can write a product description in seconds. It can't tell you why a jersey twists after washing, or why a fabric that photographs beautifully will pill by the third wear. That knowledge has to be put into the system by someone who has it.
That's how I work with AI now. I don't ask it to know cloth. I give it what I know: construction notes, fabric specs, fit comments, why a style sold or didn't. With that context, it helps me write faster, spot patterns across a range and keep one version of the truth. Without it, it just guesses, beautifully.
The context is the craft. AI is how it travels further.
The brands that get the most from these tools will be the ones whose product knowledge is deep enough to feed them. That knowledge starts somewhere very old-fashioned: a person who understands how the thing is made.
Construction, taste and math
People sometimes ask why I describe myself as a merchant rather than a planner or a designer. It's because the job needs all three in one person: construction, taste and math.
The textile degree gave me the first. Ralph Lauren's teams taught me the second. The business taught me the third.
If you're starting a textile degree now, don't let anyone tell you it's the long way round. Learn how things are made. Every tool you'll ever use will need someone who knows.
Will
