This is a quick visualization I made last year, but recently updated with current data to show at a glance where my capsule wardrobe was made.
Where was this really made?
It's extremely difficult to get precise data about where most clothing is made.
And even more, many brands won't list where their pieces were made on their websites, but instead just list "Imported" which I've come to find out (what I already assumed) generally means China. When I was first creating my wardrobe inventory, I emailed brands to see if I could get any more specific information on the origin, but never got anything more than a country name.
The good news is that some clothing brands like Everlane, American Apparel, and VETTA do provide the actual city of origin - so where available I do track that data, but it's not represented in this visualization. For example, most of my clothing that was made in the United States was actually made in factories in Los Angeles and New York - two cities on the opposite ends of the country, but the dot looks like it's placed somewhere near Montana.
Trends in geography
I was a bit surprised to see so many dots scattered across Europe when I first loaded my data into this visualization, because I assumed most of my wardrobe was from China and other parts of Asia. When I took a closer look, I realized that a lot of my shoes (generally the more expensive ones) were made in Europe.
This got me thinking about how geography plays into my wardrobe. Are more expensive pieces made in certain parts of the world? Do some countries specialize in specific types of clothing? Anecdotally, I read that a lot of basic clothing items like underwear and socks have moved from production in China to Bangladesh.
My shopping habits have changed significantly since I started tracking my wardrobe in early 2017. I've become more selective about the brands I shop from and while I don't typically check where an item is made before I buy it, I do have a preference for ones that have a transparent supply chain. This visualization is very simple and a bit surface level, so I'm looking forward to do a bit deeper of analysis as my data set grows.