Anthropometry is not as simple as alpha numeric sizing
August 1, 2016 — San Francisco, CA
How do we define fit?
Fit is a vaguely defined, complexly intertwined technical and emotional topic; especially as it pertains to garments. Each individual has a different definition of how they want their clothing to fit. The way that we use words to describe fit even varies from one person to another. ‘Baggy’ to one person may look like something very different to someone else. Brands often use words like: athletic, skinny, curvy, classic, or slim, to describe the style of a garment as it may relate to fit or to a body type within their customer base.
Some people’s preferences for fit defy rationality and are embedded in the sentimental. The sentiments are often left overs from previous necessity. One example of this sentimental effect is in garments like denim, which was once made for durability and has become an icon, worn by almost everyone, regardless of age, demographic, or gender. Another example is in the sagging jeans preference. It’s most recent appearance was popularized by hip-hop celebrities. The look is rooted in necessity, the tradition of handed down garments that didn’t fit properly. Its popularization is a sort of optimism about the situation, turning a symbol once associated with poverty into a powerful statement, voiding it of its original context.
What do we currently use to describe fit?
Sizing systems are an alphanumeric organization of fit, created to simplify the process of finding garments that fit individuals. This simple-looking concept becomes overly complex as brands tailor their own systems based on customer. Resulting is a severely bastardized concept based on relative measure, not concrete measure. The idea is deceptive; the current sizing system is deeply entrenched in an unspoken language based on several layers of funneling. Finding a garment that really fits can be an overall complicated process.
Here’s an outline of the funneling that happens when a consumer is shopping, each level narrows their search until they're able to find their unique fit:
- Brand Selection; different brands cater to different demographics and psychographics and will handle the fit of their garments based on their customer. This has many benefits to both the consumer and the brand, however, can be frustrating to shoppers who are excluded from the average customer base or to shoppers learning about new brands.
- Style Selection; this is a layer of fit that is frequently seen using the nomenclature discussed above: athletic, skinny, curvy, classic, or slim, to describe the style of a garment. These descriptors indicate that there might be more or less room in the seat of a pant, or the waist of a shirt, etc. They a lot to do with fit preference, but for some become a utility of finding garments to fit their body shape.
- Size Selection; the obvious alpha numeric system for choosing within a brand and style which set of measurements fits best.
The most common sizing is based on a simple mathematical system, called a grading rule. This method increases all key measurements by 1” for smaller sizes up to 2” for larger sizes. Grading rules account for body shapes that follow the rule of the original proportion, but do not take into account proportions that differ from that rule. For example, someone with a large waist and small hips, or small bust and large waist, may have difficult time finding garments within this system. A sample of a standard grading rule is pictured in the chart below:
What are the economics of fit?
How brands use fit
Brands cater to their particular customers. Their brand’s fit profile is often characterized based on race, culture, economics, and trend. The defined fit of a brand is an important service to their customer base. The consistency of a brand’s fit is useful for finding or re-ordering garments and helps build brand loyalty. On the flip side, this can be marginalizing to those who desire to be their customers, but are outside of their defined set.
The economics of sizing
There is a benefit to offering the least amount of sizes possible, while still serving a targeted customer base. Decreasing breathe can help to cut costs on stocking inventory and decrease end of season waste on styles that were less popular for a particular size. Brands have long been tailoring their fit based on customer. Let’s take Japan for instance, where brands offer smaller sizes based off averages and distributions.
How is it that so many brands are driven by sales of smaller sizes when the average American woman is a size 14? How is it also that while 60% of women are overweight, plus-size sales account for only 16% of the total? How many women are wearing the wrong size or are creatively finding clothing that fits that is labeled smaller than it is measured?
How can we improve?
No size at all, you are you
As we improve our methods of making and return to customized garments; the experience walking into a store won’t be defined and tainted by a randomly assigned number. You will be size you.
Large companies and startups have been trying since the 90s to offer mass customization of sewn products. There have been some successes, like Nike’s sneaker design customization, which accounts for 20% of their sneaker business. There have also been some abandonments, like Levi’s custom-fit program, launched in 1995. As off-shoring became more and more popular, companies needed to prioritize their initiatives. Focus on customization did not match goals of manufacturing overseas, turnover was too slow to satisfy customer expectation.
Startups attempting fit customization are mostly on the basis of customer self-measurement. Generally speaking, these companies, end up with a business model that simplifies into what looks more like traditional retail as they de-emphasize customization over time. Manually measuring, even when professionally done, is messy and inaccurate. On the flip side, asking people to come into a physical location to be measured is an expensive and cumbersome buying experience.
We know that anthropometry data is far more accurate when taken from 3D scans than from manual measurements. Manual measurements, even when taken from skilled professionals, can be up to 2” off in accuracy. The question stands: how can we navigate around the problems of physical location and buying experience in order to provide value to customers shopping for garments?
This essay is a brief overview of why fit is a problem and what issues are playing into the problem. If you're looking for more information about fit and sizing systems, check out some of the research at Cornell University on Sizing Systems and Body Scanning.