The size-16 2019 woman is confronted by a bewildering array of sizing, grading, labeling and other confusing solutions

Plus fashion sizing – help or hinderance?

In 1960, the average US woman weighed 140 lbs, so in the mid-twentieth century, most US women took a dress size between a 6 and a 14: anything larger than that was often dubbed ‘Outsize’.  A size-16 woman at that time was considered rather a large person, and with the particular pressure to conform that existed in that era (which was even more severe than it is today, hard as this is to imagine), she may have felt freakish, embarrassed or even ashamed to admit to not fitting into a ‘regular’ size.  If she was guilty about her own body, she had low expectations as to what clothing she would be able to purchase, which was just as well, because the choice was dire.

By 2010, the average US woman's weight had grown to 166.2 lbs, and has been on an upward trajectory ever since.  Roll forwards to 2019: if a woman were a size-16, she would probably not feel embarrassment, and almost certainly not shame.  But then again, today's size-16 woman may not believe this is her size: actually, she might not have any idea what size she really is.  As the population has grown heavier, the standard sizes being retailed have stretched their seams and become more generous, and some brands have gone even further and adopted so-called ‘vanity sizing’, whereby they have been sneakily moving their sizes upward, in tune with the waistlines of their customers.  They have capitalised on the fact that virtually all people would prefer to think they are a smaller size rather than a larger one, and that a size label can be used as a subtle tool of flattery.  Indeed, some women will not even think of trying on a garment if it is labelled as larger than the size they relate to.  So, for some brands, what would have been a size-14 in 1960 has unceasingly crept upwards and would fit (an already stretched) size-16 today.



This explains why a 2019 standard size-16 woman (who is already larger than a size-16 lady of the 1960s), often wears a 14.  Such a person, when she takes a selfie in a crowded place, notices that she looks like everyone else in the background: she certainly doesn’t appear to be ‘plus size’, if that's supposed to be larger than everyone else.  She looks ‘average’, she feels ‘normal’, and she relates to being a size-14 – why shouldn’t she be wearing a ‘mainstream’ size?  Her expectations for fashion are not as low as her grandmother's, and she’s wondering why she – an average person (an ‘everywoman ') – is having such difficultly finding something to fit her properly.

But then again, is she really a size-16?  If we examined this particular woman, she is revealed to be a size-14/16 bust, a size-14 waist and a size-18 hip (a ‘pear’ shape).  Her sizing mismatch is entirely normal: very few women have what is called the ‘perfectly proportioned’ body shape (one size all over), and that matters a lot more for larger women than it does for smaller ones. This is because as female bodies put on weight, the extra mass is not usually evenly distributed.  Each woman possesses a particular body shape, meaning that, for example, if a woman is destined to wear her extra flesh on her bottom (a typical pear shape), by the time she has grown to a larger size, her derriere will have increased far more than anywhere else on her body.  This is in contrast to her friend who stores her weight on her bust, giving her an extra cup-size or two as she gets bigger, although her bottom stays relatively svelte.  By the time these different body shapes reach the top-end of the sizing scale, their bodies have radically diverged, meaning that they need to wear differently sized apparel on different parts of the body, and – crucially – although they are the same height and weight, they cannot wear the same size clothing as each other.  The busty woman, for example, may end up wearing size-24 tops, whilst still slipping into size-18 or 20 trousers, the exact inverse of her pear-shaped friend. 

It is often mentioned that our population has changed size: the critical fact that it has largely changed shape is rarely referenced; yet this has had the greatest affect on the fit and size requirements of this generation of shoppers.

Some plus-size brands have reacted to this diversity of shape by developing grading to fit a particular version of woman, their ‘muse’.  When consumers find a brand that tailors to their own body shape, this will usually become a firm favourite, while those for whom the fit doesn’t work will often learn the hard way never to order from this range again.

This is not to say that the plus-size sector has made concerted attempts to find out the body shapes of their consumers and match them with a proportionally correct array of diverse gradings.  In fact, it is extremely difficult to gather body data from this cohort (who dislike being analysed and sized) – and it has not yet been achieved anywhere near satisfactorily.  In any case, until the correct fit technology has been developed, targeting a very diverse inventory to the correct sections of the customer base at the point of sale would be impractical.  Many of the brands that have adopted a grading based on a ‘non average’ body shape have just opted for the ‘hourglass’ figure: probably one of the rarest of all the variants, and hardly a breakthrough for fitting ‘everywoman’: it simply replaces one impossible ideal (ultra-slimness) with another (perfect hourglass).  Doubtless this body shape has been singled out because the fashion has embraced the myth of the 'curvy' woman: a sexy uberwoman, who exudes an exaggerated femininity and makes 'body positivity' more palatable for an industry that finds the sight of extra female flesh very difficult to stomach – if it is in the wrong place, such as, for instance, the stomach.

But the variations in cut in larger apparel are not always deliberate.  Occasionally, the plus-size sector suffers with the same trouble that afflicts each sector of fashion: instances of random variability.  Sometimes there are technical problems in the production of garments, meaning that items are cut too small, too large, or a strange shape.  This is exacerbated by the sheer difficulty in correctly grading larger garments. 

When the pattern cutters struggle with those plus-size issues (which is surprisingly common), this also muddies the water with some consumers' understanding of their size.  The person trying on a garment may believe that the size is too small when a pair of trousers is not long enough in the rise, for example, or, if there is no bust darts in a particular blouse, she may conclude that all that loose fabric is evidence that the garment is too large.  She may choose a different size the next time in the mistaken belief that she has learned something about her size.

Retailers have also had to grapple with a greater – internalised – level of plus-sized customers’ own ‘size acceptance’ issues.  The problem of garments being rejected because they are labeled with sizes that consumers find unacceptable or depressing has driven some in the sector to alter their whole system to make it less obvious.  Some have sized their garments S (16–18), M (20–22), L (24–26), and so on; others, L (18), XL (20), XXL (22), XXXL (24), etc. – actually, the permutations of these are mind-boggling and the antithesis of standardization: the actual object being to make the sizing more opaque and anonymous.

A traditional industry response to this 'size resistance' conundrum has nothing to do with sizing or grading, but nevertheless brings a little more confusion into the scene.  For generations, many specialist plus-size designers have resorted to force majeure, and used fabric tech or design to bear on the problem.  Fabrics with extreme stretchy qualities are used to create ‘easy fit’ (‘fits size 16–22’) apparel, or drapy, baggy, or wrap-around styles (‘one size fits all’) creations to offer amorphous sizing.  Women who wear these garments can live in a twilight zone of perpetual ‘size denial’, sometimes losing all track of what size they really are, which can be a problem when they need to buy something else (say, formal workwear for an interview), where their latest sizing requirements come as a source of dissonance. 

So our size-16 2019 woman is confronted by a bewildering array of sizing, grading, labeling and other confusing solutions or missteps.  There may have been logical reasons as to why these diverse systems evolved, but there is none in trying to understand and navigate them: those that are not deliberately opaque are simply too complicated, random or impractical to be helpful – the long forgotten reason why a sizing system was developed in the first place.

Look as hard as he can, my little dog is never going to find the ball if he is seeking it in the wrong place

The key to solving the fit problem that ‘dogs’ e-commerce fashion

Dogs do all sorts of things that humans are far too intelligent to do.  For example, I have a little dog that loves to chase after a ball that I throw, running to fetch it back to me, most of the time.  However, if the ball accidentally lands in a prickly bush, he just stares at it soulfully for a couple of seconds, then sets off cheerfully to search for it elsewhere.  He clearly sees where the ball has ended up, but because it’s somewhere that he doesn’t want to go, his decision about where to look is governed, not by common sense, but by wishful thinking.  That’s not something a human would ever do, surely? 

How does this shaggy dog story help to illustrate one of fashion’s biggest problems?  E-commerce fashion companies want to send out garments that are correctly sized so as to avoid the main reason for customers to sent them back: poor fit.  The problem is a huge one; returns rates range from some twenty per cent in ‘mainstream’ sized fashion, up to an eye-watering seventy per cent in the more problematic plus-size sector.  Clearly, this rate is unsustainable.  There are millions – possibly billions – of dollars ultimately to be saved (and made) in dealing with the issue of finding a reliable way to make sure apparel fits e-commerce customers.



One way of preventing all these returns is with fit tools.  Some e-tailers rely on the time-honoured system of offering customers a ‘size chart’ of clothing measurements with which, should he or she have access to a measuring tape, a customer can compare his or her body metrics.  Clearly, this method, which actually employs nineteenth Century technology (and which bristles with all sorts of problems), does not do the job very effectively.  Elsewhere, e-commerce has adopted more up-to-date tech of varying degrees of sophistication (but none with perfect success), and all eyes are now on the IT industry to see if they can come up with a solution that will carry all before it.

There is a varied field of fit innovations jostling for dominance.  Some rely on scanning or clever mobile phone camera developments, whilst others are still based on consumers being asked to input various body measurements or sizes.  The tech business appears to be doing its best to find the remedy for badly fitting apparel – by looking in the places that it wants to look.  As befits the activity of very clever technically minded people, the emphasis is being laid firmly on developing a lot of very clever technology.  Thus IT will – if it continues to develop at the rate it is going – be extremely effective in establishing a good fit between the spec for a piece of apparel on the one hand, and body data from the customer on the other.

Hereby lies the nub of the problem: data.  At present, some, but not yet all, manufacturers supply the comprehensive level of garment information necessary for these fit tools to feed on.  Some businesses feel that they don’t really need to go to the bother of providing the spec, and worse, some act as if their garments' measurements, grading, construction and fabric details should be some kind of industrial secret.  However, these out-dated attitudes will soon be swept away.  In a very short time brands that expect their apparel to be sold online will automatically produce data packs that will enable their product to do just that.   The tech developers will then swoop down on this kind of information, as it tends to be clean, accurate and clear.

But how do we provide the other half of the equation: the information from consumers?
  Will this be clean, accurate and clear?  Every fit tech system relies on accurate customer metrics, be they measurements, scans, and/or stated or unconscious preferences (and repeatedly re-obtaining them, as measurements change on a regular basis during a customer’s lifetime, whilst preferences can change over the course of a trend).   Surely, it is therefore to be expected that, first and foremost, all the tools being developed are focused on obtaining customer cooperation, motivating their actions and gaining their trust, as well as the biggest issue of all: reflecting their will. 

Customers (also known as human beings) can be difficult, apparently illogical, contrary, seemingly unpredictable, variable, and wilful.  They have every right to be any or all of these things, and there is no evidence to suggest that they are going to change just because they wish to buy a shirt, regardless of how well fitting it is (or how lovely the print). 

Obtaining their data in a predictable form promises to be a rather prickly undertaking. Many of those who are presently tasked with developing the tech to serve these people (because the ultimate client will not be the retailer, but the consumer), are relying on some somewhat shaky assumptions.

Take, for example, those who in the UK and US make up about half of all womenswear consumers: plus size women.  It is often taken for granted that this cohort, due to their severe fit problem, will be only too happy to provide all sorts of information.  The majority of fit tools ask for height, weight, bust (or bra size), waist and hip measurements, among other metrics.  But there is no evidence that this cohort finds it anywhere near as easy to provide these figures as those who design fit tools assume.

Many larger people, living, as they do, in a judgemental society that sees ‘overweight’ almost as the worst sin, are extremely sensitive about their bodies. They are often unwilling to go through the process of measuring themselves, do not possess the equipment to do so (many bigger people do not own a weighing machine, for example), dislike knowing their metrics (and avoid doing so at all costs), hate reporting them, get disheartened when they change 'detrimentally', and are very worried about having their measurements accidentally revealed in some way. 

So it is likely that the majority of larger people will avoid situations where their measurements can be taken, and, when they have do have access to their data, will immediately contaminate it.  The idea that every plus-size woman will happily go through a thorough physical revelatory experience (even in the privacy of her own home) in order to obtain better fitting apparel is an exercise in wishful thinking – and one not based on any study I have seen.

With the billions of people on the planet, it is all too easy to undertake an online survey of plus-size women and find many who are happy to supply their measurements.  Some of these will be perfectly accurate – and will be supplied by an assiduously self-selected group of un-selfconscious women.  Other measurements gained the same way will be inaccurate due to the contamination process outlined above: however, in the midst of the Internet, it is very difficult to understand which data is correct, and which is corrupted.

Nor can it be automatically assumed that the scanning tech as it exists today will fare any better: such devices can trigger all the sensitivity to self-revelation that exists with a measuring tape – occasionally more.  Another assumption – that the consumer's emotions will change to adapt to this new system – has got a lot more going for it.  Based on past evidence, consumer behaviour alters all the time, and each generation has its own attitudes.  However, predicting that the next generation will grow-up devoid of sensitivity about their bodies (and, even less likely, predicting that those who are already in the customer cohort will suddenly change) is quite a stretch, and based on no available evidence.

In order to understand each technology’s exposure to the problem at hand, every fit tool should have self-monitoring element, carefully picking up data as to whether consumers are providing correct or incorrect information, if they are being deterred by questions as to their size, and the chances of whether they will accept the tool’s findings or not.  And every tech specialist working in this field should be diligently concentrating on improving the vital subject that has such a profound effect on the efficacy of their tool: that of customer participation.

It is important not to spend time and resources developing tech that requires consistent data from a consumer who is simply not prepared to provide it with any degree of accuracy. The perfect fit tool, not only for the plus-size woman, but also for all fashion consumers, would be non-revelatory, unconscious continuous monitoring of body data.  The tech, working with the consumer’s full knowledge and permission (but with only passive participation and minimal personal input with no revelatory feedback) needs to absorb the consumer’s needs without intruding on his or her sensibility. 

It is rewarding to use expertise to chase down complicated and clever solutions; to produce feats of technical virtuosity.  However, it is always best to be realistic from the start, and, if ultimate success can only be hoped for by looking into more prickly, difficult, unsexy and unpredictable areas – to step well out of one’s comfort zone – then this is the course of action that should be taken. The tech industry is going to have to pause, take time to look at what the consumer is prepared to do, and reverse-engineer all their technology to utilise what they will actually have to work with.  They may find they have to develop a different approach altogether.

Look as hard as he can, my little dog is never going to find the ball if he is seeking it in the wrong place: he’s going to be disappointed, and no amount of wishful thinking is going to alter that.

Larger women are spending less than half as much as expected on their clothing

Plus-size fashion: the new Gold Rush?

This is a copy of an article written for WhichPLM.

In today's guest post, Emma Hayes, womenswear customer fit expert and founder of At Last, explores the many issues around today's 'plus size' market, and what we can do to better this. Emma has worked in retail for over three decades, with a specific focus on womenswear and lingerie, and is fascinated by bodyshape diversity.



In the UK we are often told that the average woman is size-16 (a difficult fact to prove, lthough it's known that larger women make up around half the population), yet the percentage spend in the plus-size fashion sector lags at around 22%.  So it looks like larger women are spending less than half of what they might be expected to do.

There is no consensus as to what constitutes the size range for 'plus-size', but it's clear there is a dearth of choice of apparel offered from size-16 upwards.  In Britain, premium brands like Marina Rinaldi and fashion-forward Anna Scholz, stand among the few honourable exceptions to the rule that there is no top-end in plus-size fashion.  Mid-pocket fashion fares little better: European e-tailer, Navabi, is one of the few that can use the words 'quality' or 'design' about plus-size without hyperbole.   The vast majority of British apparel in this size range rests firmly in the non-designer, value sector.

The same applies in the US, where a few brave brands have created fashion-forward outposts in a largely underwhelming landscape.  Most American women are forced into the same, fairly narrow price-point as their UK counterparts, having to put up with a similar lack of design creativity.  In both markets the vast majority of plus-size apparel is made from stretchy, cheaper fabrics, modified for a non-specific fit. It's shocking to find that tracking down a classy, well-made and functional business suit that fits a size-24, for example, is a big ask for these women – regardless of the fact that there are businesswomen aplenty who are asking for just that.  Fashion's disappointing offering to one half of the female population means it would be easy to fit a list of all of the main plus-size players in this one article, yet would be difficult even to calculate the length of such a list of 'mainstream' sized brands.

The logic is clear: arguably 50% of the population is not being offered anything like a satisfactory breadth of choice on which to spend their money.  Admittedly, this market is projected to grow an extremely healthy 7.1% in the next few years, yet even at this rate it is unlikely ever to catch up.

The logic is clear: arguably 50% of the population is not being offered anything like a satisfactory breadth of choice

It doesn't take a long time browsing through 'size acceptance' social media to get the feeling that plus-size womenswear consumers are not happy.  On one hand, they've noticed that they are being offered nothing like the choice of the fashion-forward looks they aspire to, and, on the other, these women also make persistent complaints about ill-fitting clothing.   It does appear that this cohort is suffering from considerably worse grading problems than their 'mainstream' sized equivalents.

Thus resonates the persistent drumbeat of bad news about the fit-related returns that are plaguing this sector.  Brands can be very secretive about their failures, but there are dark places in plus-size e-commerce where returns rates of up to 70% (far worse than the already abysmal returns rate of 'mainstream' sizes) are whispered about, the lion's share of which is reported to be due to 'fit problems'.

All in all, something is very wrong in the state of plus-size.

Could fit be at the root of all plus-size fashion's woes?
The answer to this question is that it would appear so.  Women come in a range of bodyshapes.   To name a few: 'apple', 'pear' and 'busty' (men's physiques are less diverse).  Among slimmer women these various types are often evident, but it is in the plus-size cohort that they become really exaggerated.  Put simply, each female body stores its weight in a particular pattern (it's fairly rare to have it spread evenly all over), meaning that, as a woman puts on weight, whichever part of her physique was comparatively large to begin with, continues to grow, while other areas become proportionally smaller, exaggerating the shape.  Therefore, the larger a women becomes, the more likely she is not able to squeeze into apparel that is made for her size, but not her shape.

The fashion industry has largely soldiered on trying to ignore this inconvenient fact.  Sending out apparel in standard grading and sizing to a market that is anything but standard is like throwing mud against a wall and hoping it will stick.  The resultant slurry of returns is clogging up the industry.

The chronic fit problem particularly plagues e-commerce, because it doesn't presently offer consumers the opportunity to try garments on prior to buying them.  This has meant the industry has been forced to ignore designer, tailored, fashion-forward and expensive clothing, or anything else that relies on a very specific fit, which would probably stand no more than a one-in-six chance of hitting the mark.  Faced with the tidal wave of returns, most of this sector has had to wriggle its way right down to the bottom of the price, variety and quality scale, so much of the offer comprises 'easy-fit', cheaper, predictable garments.

The result of the fit problem spreads out like an oil spill, polluting the whole scene: the plus-size fashion industry's margins are damaged, it's even more ecologically unsustainable than the rest of the fashion industry, lacking in maturity, lacklustre and suffering from galloping customer dissatisfaction.

The sizing system also needs a radical re-think

Yet those with imagination look at a stunted industry and see only a huge, exciting opportunity, with billions just waiting to be disgorged by digital disruption.  Apparel businesses are still using sizing systems that were developed for last century's technology. With present-day advancements, so-called online 'fit tools' will soon be capable of identifying a consumer's individual bodyshape and match it with the corresponding apparel.  It's like California just before the first prospector struck gold.

A radical re-think
The requisite garments are not yet in fashion's inventory: clothing will have to be graded specifically for an individual's body shape, dictated by a feedback loop of data gleaned from a large enough sample of consumers just like her, using those same fit tools.  Apparel will be manufactured in a series of differing, niche shapes (mass, rather than individual customisation) in shorter runs using advanced digital systems at every stage.

The sizing system also needs a radical re-think; it has to be far more comprehensive to take into account the wide range of consumers' diverse metrics.  The consumer will be largely unaware of her new clothing size, which will be applied to her automatically using AI technology working intuitively, immediately, confidentially and non-intrusively.  All she will know is that she is ordering a piece of clothing that will fit her.

If this sounds seductively easy, it shouldn't: is very complicated, and as with all such situations the trick will be to simplify it as much as possible from the start.  The industry will initially use judgement and subtle customer knowledge to cluster the metrics into meaningful groups.   There will be a trial and error period at the beginning where the data (which has never been so widely mined for this cohort, or any other) is gathered and analysed.  This process has the added complication that a woman's bodyshape dictates more than just the metrics of her apparel; working along with her own taste, it has fit and style preference implications, too.  However, understanding these aspects just represents yet another way of better serving the consumer.

And this is just the beginning.  The bodyshape data will ultimately be used to create better-fitting apparel for people in all sizes and shapes (the slimmer cohort will also end-up getting a better fit), and achieve a more equal, diverse clothing offer to everyone, whether they are minority groups, fitness junkies, disabled people or have otherwise outlier bodyshapes.  It will allow the development of curated apparel offers, enabling brands to benefit from increased sell-through, and individual customisation for specific purposes (say, bridal wear, occasional or, indeed, that smart work suiting). It will slash fashion's shameful carbon footprint and boost the bottom line.   It will market all aspects of the fashion industry (from top luxe at one end, to budget fast fashion at the other, and everything in between) to the neglected half of the female population.  This will open up billions of dollars in increased commerce.

The first step is the development of the fit tools and associated input technology (like handheld scanning, for example, as relying on customers' willingness and ability to input their own measurements will not be scalable).  It will not be an immediate process, and the fashion and tech industries have to come together to dig-in for a long haul, being prepared to invest time as well as resources. Researching, acquiring, partnering and developing these advances should be the number-one priority for those fashion brands that do not want to be left behind by the next great leap forward in digital technology.

All the costs are ultimately added on to the price of those garments that end up being sold to customers, meaning that as if the ecological crime was not bad enough, this process also victimises the consumer

e-Commerce fashion fit and the 1p levy

On 19 February 2019, the UK Government Environmental Audit Committee released a recommendation that the Government make fashion retailers take more responsibility for the waste they create.  Committee Chair Mary Creagh MP said: “In the UK... we get rid of over a million tonnes of clothes, with £140m worth going to landfill, every year.” 

To encourage a more responsible approach among UK fashion retailers, the members suggested a levy of one penny per garment on fashion apparel producers. 



However, there is doubt as to whether such a tax would have any meaningful impact on the actions of the apparel industry.  The subject of waste is a huge one, spreading into every aspect of the manufacturing and retail of apparel, but by drilling down to a single example of what can go wrong, it is possible to show why this is so. 

One issue in the matrix of problems that plague fashion today is that of garment fit.  e-Commerce customer returns are running at an unsustainable rate, with online retailers often seeing 20% of their garments being sent back for a refund, and many return rates topping a whopping 50%.  Over two-thirds of these retail returns are reported by consumers to be ‘fit related’, meaning that sizing is a huge problem.

Most of the garments that are returned as unsatisfactory are placed back in the inventory (adding processing and often postal costs to their engorged carbon footprint) awaiting resale.  Some, having already gone through this process before, are damaged or have deteriorated due to the caustic ‘sale and return’ journey, and consequently can no longer be re-stocked. In addition, after a series of aborted transactions, the fit of certain items will be flagged up as faulty and they are withdrawn, or reduced in price in the hope of a quick disposal.  Of these failed items, some newly manufactured fashion even finds its way into landfill.

The whole process (manufacturing, distributing, promoting, retailing, taking payment, packaging, consignment, delivery, collection, processing, re-stocking) does not happen for free.  All the costs are ultimately added on to the price of those garments that end up being sold to customers, meaning that as if the ecological crime was not bad enough, this process also victimises the consumer. 

But, of course, brands suffer also.  Nothing could be more financially punitive than creating a piece of stock whose lifecycle consists of a litany of expense, ending in a total waste.  Loading the price for their failures on to the rest of their range is highly damaging in a market that is super-competitive.  This is a tax on failure that is paid every minute of every day.

There are many on to whom this extra ‘tax bill’ is being pressed. The added reduction of margin is one reason why fashion production is often exported to countries where low wages and staff welfare keep costs down.

That the fit problem still endures despite the substantial monetary penalty, is evidence that expense alone hasn’t delivered enough motivation to find a solution, so it’s doubtful that adding an extra penny on to the price of each garment will make any difference.

Part of the problem is that is difficult for brands to understand what needs to be done to help them develop the range of stock and the tech suited to their fashion consumers.  Today (much more than when the first standardised sizing was developed in the 1950s), UK consumers range in size extensively, and there is also a wide age range, a broad racial mix, and width of differing preferences.  The diversity of people who now have the right to expect material gratification has seen social justice meld with commercial interest to create a lucrative but highly complex potential customer base. 

These discrete groups have diverse sizing and fit needs, as their body shapes and preferences range widely.  As yet, from a sizing and grading point of view, much of the fashion industry has been trying to pretend this diversity doesn't exist, and has adopted the technique of throwing mud at a wall and hoping it will stick.  A mass of clothing is sent out to consumers in the hope that it will be ‘all right’, with what ‘doesn’t stick’ possibly ending up as waste. The returns evidence suggests that not nearly enough has been achieved in fit tools and appropriate choices of grading, meaning that hundreds of thousands of wrongly sized and/or graded garments are being sent out to ultimately disappointed customers.  It looks very much as if the fashion industry is floundering on this issue.

When it comes to fashion fit, it’s my belief that we should look at history to think about how government intervention can work successfully. In the mid-twentieth century, during the development of the first mass-produced fashion, national governments in the developed world worked with their respective industries to develop standardized sizing.

Fashion is facing a similar challenge today: starting with the advent of the Internet there has been a complete change in the apparel business, with the new consumers making the old sizing systems increasingly obsolete, and retailers needing to develop techniques of selling garments without the use of a changing room.  It’s time to see the fashion industry as a whole – internationally and with the assistance (or at least encouragement) of all interested governments – take up the challenge of developing the sizing solutions and fit tech that are suitable for today’s apparel commerce.

I am not talking about regulation or compulsion here; the suggestion is for leadership and co-operation, perhaps backed-up with academic and business expertise and positive tax incentives.  Tech solutions can be found to the fit problem, and, if this particular source of waste in the fashion industry can be solved in this way, it will serve as a template for politicians and industry to work together to help tackle other preventable environmentally damaging practices. 

This approach would be much more constructive than just putting another tax on an already financially stressed industry, knowing who will ultimately pay that levy.

When it comes to fit, the most challenging sector of fashion ecommerce is plus-size womenswear...

Fashion's imaginary consumers

The fashion industry risks creating an inventory – and a set of fit tools – designed for a largely imaginary consumer base.  If this sounds unlikely, it’s worth remembering that it is something that has happened before.

Fashion e-commerce is suffering from an unsustainable returns habit that damages profitability, ruins customer loyalty, upsets shoppers, is wasteful and extremely damaging to the environment.  The majority of these returns are reported to be due to ‘fit issues’.  It’s a no-brainer that the industry needs to find a way to send out clothing that can be relied upon to fit its consumers.



One flank of the battle is for the fashion industry to ensure that the apparel being manufactured is ‘fit’ for purpose.  To do so, it’s necessary to understand exactly what clothing sizing and gradings should be produced in order to reflect society and satisfy demand.  This will entail a study of one of the most complex entities in the universe: the human consumer, both body and brain.  Due to the considerable variability of the population, it is going to result in a much broader range of sizing offers than has been produced up to this point.

The battle’s other flank involves tech companies developing the tools that solve the myriad technical issues involved in targeting customers with suitably sized and graded garments, a task made more difficult when involving the more comprehensive range of apparel that will be on offer.  For this to be achieved, it’s necessary not only to match the level of population metrics expertise of their fashion colleagues, but also to acquire their thorough technical knowledge about all garments being retailed – the matrix of measurements, fabric characteristics, relevant construction specs, usage information and designer preferences. 

When it comes to fit, the most challenging sector of fashion e-commerce is plus-size womenswear, which is what I will be addressing in this post.  Here, the rates of return can be swingeing: much higher even than in ‘mainstream’ fashion.

The legacy of plus-size fashion’s sizing (and the root cause of its inflated fit problem) is that the grading has been ‘extrapolated up’ from 'mainstream' sized women, where historically, sizing research tended to originate.  The idea that curve women are simply larger versions of smaller women may be true to a certain extent, but this is far too reductive: these larger consumers have much more exaggerated body shapes than their smaller equivalents, so, where they have been graded on a false premise of conformity, it's all too easy for garments to completely miss the essential fit points.  It would actually be more informative to create a range of diverse cuts based on the physiques of larger women, and shrink these down to their smaller counterparts, who would, in all likelihood, be delighted with the subsequent advances in the fit of their garments.

Historically, the plus cohort has been underserved by the clothing industry, of which this lack of specific research is an example.   It was long assumed that larger people are not as valuable to fashion commerce as their ‘mainstream’ counterparts, partly as they have traditionally averaged a lower spend, but also because their association with a brand was considered negatively.  Putting it bluntly, many companies did not like the aesthetics associated with larger people. 

With the growth in the proportion of fuller sized individuals in the population, both these considerations are fading away: the younger generation no longer balks at seeing brand ambassadors who vary from the traditional models’ slender bodyshape, whilst it has come more widely accepted that any shortfall in the spend associated with plus-size women is caused primarily by the poorer offer available to them – which actually represents an opportunity for forward-looking companies. 

Now that these reservations are being removed, in order to develop this sector to its full potential, the industry will need to reduce fashion returns significantly, necessitating a specific and comprehensive study of female bodies – from the smallest to the largest – in the kind of depth that has never been achieved or attempted before.

There are two general methods of collecting consumer body metrics: those undertaken by professionals, and consumers' self-reporting.  Some enquiries have involved experts who have reached out into the population to weigh, measure, scan, take surveys and live-test volunteers.  In others, subjects have been asked to either measure themselves, fill out surveys – or allow their bodies to be scanned in some way.  We already know that far fewer plus-size women are willing to participate in such studies, yet we are relying on this work because we will not gain a complete understanding of the customer base without it.  Is there a particular group of larger women that is more likely to step forward to provide data?  Is this going to have an effect on the quality of the information collected?

When designing anything for larger people (be it tech or clothing), it is advisable to think about people holistically, and consider, not just their physiques, but also their preferences, personalities, emotions, experiences and thinking.  This is particularly relevant to the prickly subject of how to go about finding a realistic plus-size sample of the population to study.  Many larger people (with good reason) are resistant to having their bodies categorised, scanned, analysed, measured or observed. Putting aside the differences brought about by the vagaries of personality types (which varies across all women of every size and body shape), there are particular reasons why the body confidence of certain groups of larger women is more resilient than others. 

A clue can be seen when observing the shapes of larger women who are happy to exhibit themselves, and compare them to the rest of the population (who largely don’t).  ‘Curve’ fashion models are women who make a living out of the fact that they (and society) find their bodies aesthetically pleasing, and these women usually tend to have certain features in common.  They are young, with a balanced physique, tall with smooth lines, and usually have either ‘perfectly proportioned’ or ‘hourglass’ body shapes.  They usually tend to share a European physical type.  These women are not at all representative of the plus-size population as a whole.

Larger women come in a range of highly distinct body shapes, the rarest types being the 'perfectly proportioned' and 'hourglass'.  This should come as no surprise to anyone: we don't really expect models to represent an ‘average’ woman.  What may come as a shock to the uninitiated is how resistant most plus-size women (who do not share this ‘aspirational’ shape: indeed, they vary from it considerably) are to being accurately measured.  When calling on the population to volunteer body metrics, it is necessary to be extremely careful not to end-up with a highly self-selected, un-representational sample.

It could be that a survey of plus-size consumers finds that 90% of them have hourglass or well-proportioned body shapes, when in fact, only 10% of the general population shares this profile. 

If this happens, the industry will be creating a fashion inventory – and a set of fit tools – for a largely imaginary consumer base.  Leaving it in exactly the same highly unsatisfactory situation as it is now, in fact.

There is evidence, possibly because they vary from the ideal to a more exaggerated degree than their smaller equivalents, that those who are not ‘conventionally attractive’ or 'balanced', physically, are far less likely to come forward to be tested by a professional, nor can they be expected to enter correct measurements into any fit system, even in the privacy of their own homes.  They may be slow to volunteer to be scanned, and extremely reluctant to want to know their own metrics.  They are likely to be very concerned about privacy, and many of them will not even possess the tools (a tape measure, or a weighing machine) with which to gather their data, choosing to enter invented measurements if pushed.

If developers are not careful, this is a situation that may be carried forward into the new generation of e-commerce retail fit tools and scanning devices, causing a diminution of effectiveness.

It’s not all doom and gloom, however.  Forewarned is forearmed, and, with anticipation of these issues, strategies can – and will – be put in place to collect an accurate, representative sample of fashion consumers, and the development of effective fit tools.  In order to do this, it is necessary to abandon the wishful thinking, the 'common sense' (that is not backed-up by empirical knowledge), the prejudice, myths, or the incorrect extrapolation that has plagued the plus-size fashion sector for too long.

Most of all, we should see the end to imaginary plus-size, standardised female consumers, and replace them with the rich diversity of real women.

We can only solve the issue of apparel fit by rising above simply thinking of it as returns problem

Apparel fit and inclusivity

With consumer apparel purchasing increasingly moving online, the subject of apparel fit is at the heart of fashion e-commerce.  In this article, four industry insiders come together to merge their differing viewpoints: 

Mark Chalton:

‘Diversity inclusion’ is a term used frequently by corporations intending to ensure everyone has a voice and that there is equal representation of gender, race, religion and other human variations. Equally important is diversity of thought.



So how does this concept relate to the fit of apparel?

Each week brings fresh potential technical solutions to bear on the current apparel fit problem.  This is a Good Thing, as the tech geniuses are recognising fit as an area where technology can offer a significant contribution.

It’s our opinion that most of these advances are instigated and developed within the somewhat rarefied environment of the tech industry – employing one very specific way of thinking.  We note – not as a criticism, but as an observation – that there is an opportunity to redress any imbalance of reasoning by introducing some art into the science.

This observation is not a novel one: for example, it is supported in principle by The Medici Effect (Harvard Business School Press, 2004), which explores why the most powerful innovation happens at the intersection where ideas and concepts from diverse industries and disciplines collide.

Apparel fit is part art/emotion and part science/tech
Think about the last time you purchased a garment that fitted amazingly... how did it make you feel?  Apparel fit speaks to, and stimulates, the senses.  It creates an emotional connection greater than the sum of its parts: much more than mere body dimensions and garment measurements.

So what’s raising the age-old problem of apparel fit among the tech solutionists?

E-commerce apparel return rates are eroding brands’ and retailers’ margins and profitability.  As e-commerce continues to grow, this erosion can no longer be sustained... or masked.

But as a consumer, what do I care?  If I don’t know what size I am, know for certain that I will like a certain product, or that it will suit me, I have the option to order it anyway – perhaps in multiple sizes – hoping to figure out for myself whether it will work.

We all know that so-called ‘free shipping’ and ‘free returns’ are, of course, nothing of the kind.  It’s these delivery costs, coupled with the task of processing returned products back into inventory, and attempting to balance stocks when over half of demand is returned, that are causing margin erosion and higher prices to the consumer.

Reasons for high returns
Apparel e-commerce return rates on average hover around the 50% mark –  70% of which are attributed to poor fit.  It’s a cliché, but for such a tiny word, ‘fit’ is a very complex process!

To put it in a nutshell, ‘fit’ is where individual consumers’ body measurements meet brands’ sizing and garment specifications; designers’ fit ideas meet consumers’ fit preferences; real-life material properties meet consumers’ fabric expectations; and designers’ styling decisions meet the pace at which consumers are willing to adopt trends. 

Emma Hayes:

Many of us are aware that in future we will be able to take 3D scans of ourselves from our mobile phones or similar devices.  These will generate accurate avatars of our bodies, complete with all our measurements, upon which we will be able to virtually ‘try on’ potential purchases – checking our images on-screen in three dimensions for how good the fit is, and whether the style suits us.

At the time of writing, all over the world, many apps, devices and methods are being developed that are advancing rapidly towards this dream.  For example, there is an app on which you can see a three-dimensional avatar of your body – complete with measurements – after simply taking front and side view photographs on your phone.  Another app allows you to upload pictures, and your virtual-reality self will then try on the clothing of your choice – draping naturalistically.  There is a clever hand-held device that takes your measurements by scanning you.  There are even smart body suits and scanning pods, which offer the promise of the gold standard of human measurement: a perfectly accurate rendition of your entire body in three dimensions. These all exist today at various levels of development.

Such devices are exciting and headline-grabbing, but it’s unlikely that most of the companies selling us apparel online will opt for them quite yet – partly for technical reasons, but also because they need to be integrated into the systems currently employed in the fashion industry.  In the early stages, retail companies will need to ‘grow out’ their operation to merge with the technology – and many changes will be required.

Fit tools are clever online algorithms that work out which sizes of apparel need to be ordered, based on ‘inputs’ – and it is these tools that are making the big inroads right now.  Inputs are various pieces of customer information – weight, height, age, perhaps body measurements, ordering/returns history, and body shape – which the consumer loads into the tool.  In the near future these will also include personal preferences. A vital ingredient of these tools is profound apparel knowledge, allowing them to match the consumer with the optimum garment.

Even at this early stage, this tech is proving to be effective – the best tools boasting a considerable reduction in the number of product returns.  They also have the advantage that they are already doing a lot of the heavy lifting required for the digital transformation of the fashion industry.  This is what is building the infrastructure that will plug into all the extra data that’s collected.

The human angle
However, like all new technologies there are going to be issues surrounding adoption by the public.  Predictably, the tech people may think that the problems are all centred on the technology, but there are considerable social, psychological and emotional difficulties to overcome.  As consumers, we have to learn how to travel around this new technology.

Whatever tools we use, we are asked to take some time gathering – and inputting – information.  But there are problems with asking people to do this, and they fall into two categories... 

The measurement problem
Studies show that our measurements are in a state of constant flux, so measuring will not be a one-off activity.  We are being asked to continually monitor our measurements and weight – possibly on a monthly basis – regardless of whether we use a tape measure or scanning device.

There are confidentiality issues to think about. If we are not going to have to keep repeating ourselves with every company we buy from, we will have to develop methods whereby our information can be shared between various organisations.

Our experience is that people only substantially change their behaviour and attitudes when there is something in it for them, and that something often has to be more important to them than a new pair of jeans – even if they fit beautifully.

The phrase 'conform to new habits' fills consumer experts with a mixture of dread and concern.  Can we consumers really be expected to be 'educated' into new habits?  In our leisure time (and shopping is supposed to be that) most of us want to undertake enjoyable activities with an instant reward, rather than toiling through worthy chores in the hope that something better will come along later. 

We need to create usable, enjoyable tech that will draw everyone in from the inception; ideally, fun tech that we don’t even notice we are using.

The revelation problem
The second problem is revelation.  Many people don’t know, don’t want to know, don’t believe and/or would never tell you their accurate measurements. 

We need tech that is 'unconscious': having given our permission for the data to be collected, we should have the right not to have to have any interface with our body metrics unless we choose to do so. 

Jessica Couch:

The future of fit technology
Fit is becoming a buzzword and everyone has an answer to the online returns problem, but the best solutions have two qualities:

1.   Ease of use – How simple and convenient the solution is: mobile phones vs. specialist devices for example?
2.   Ease of integration – How easy it is for brands to integrate the technology into their current systems?

The best technologies do not try to train users to have habits that are not simple or natural.  They allow end-users easily to add technology into their everyday lives. Accuracy is key, and the less effort required the better.

Neither do the best technologies try to do everything.  Instead they connect to existing technologies and enhance outcomes.

Many smaller brands find it difficult to integrate fit technology because their current 'solutions' are unable to connect to other solutions, and buying an entire suite of IT products is not an affordable option.

Expensive, rigid technologies are out.  The best technologies are those which integrate easily with existing platforms and create more efficiency.  Because tech has not existed in fashion in the past, many departments are siloed and are not properly integrated for it.  Great technology companies have to take this fact into consideration before they can succeed.

How fit is your competitive advantage?
Fit and fit technology are customer experience tools – A lot of brands believe that implementing more lenient return policies can somehow impact the quantity of returns.  In our view this is similar to putting a Band-Aid® on a gash... it simply doesn’t treat the real issue of customer expectation. 

According to an article on online apparel returns myths:
  • Most returns are made by one-time buyers.
  • Good returns policies do not affect sales.
  • Most shoppers don't think about returns before buying.
  • Most people are not concerned with free return shipping.
  • Bad returns policies don't affect sales, and a returns policy won't impact  future sales.

By the time a customer has had to return an item, you have lost them for future opportunities.  Customer expectations must be met and returns avoided. This can be done through building confidence with consumers, whether in-store or online, and helping them understand what to expect in regard to fit.

Fit and fit technology are loss management tools – Implementing fit technology helps to increase consumer confidence in products. $62.4 billion worth of apparel and footwear is returned every year due to incorrect fit. That works out to about 57% of footwear and 64% of apparel purchases, according to a recent Footwear News study.  The same study found that if fit were not a concern, 51% of respondents would purchase footwear more often, both online and in-store, while 58% would purchase clothing more frequently.

Excellent communication around fit is important because it helps build confidence with the shopper – increasing sales and generating fewer returns.  Implementing fit technology tools that create directive shopping experiences and manage expectations can help to reduce the amount of unsold inventory.

Fit can help reduce fashion’s carbon footprint – A recent op-ed piece published in The Business of Fashion revealed that dead inventory (unsold clothing) costs the US retail industry $50 billion a year.  Although brands may be able to absorb some of these costs through write-offs on the balance sheet, the environment (through landfills, toxin pollution, etc.) cannot.

Newsweek published an article stating that Americans alone produced 15.1 million tons of textile waste in 2013 and around 85% of that ended-up in landfill, according to the Environmental Protection Agency.

Fit technology allows brands to create better-fitting clothing for shoppers, and helps to match them to their products – so clothing is not created unnecessarily, quickly ending up in landfill.  Although changing the shopping habits of consumers is a difficult task, brands have to take more responsibility for their impact on the environment.  Implementing fit technology can help to fix fashion’s misaligned supply and demand issues.

Fit is inclusive: more people shopping equals more money – In a survey conducted by Fung Global Research, some 72% of respondents did not believe that fashion designers create their designs with the average American woman in mind.

Approximately 78% of people would be willing to spend more money on clothing if more designers offered plus-size options.  Some 68% are interested in participating in fashion trends, but 67% feel that there are not as many fashionable clothing options available in their size as they would like. This isn't just a plus-size issue.

According to a Business Insider report on petite people, over 70 million US women fall into the 'special' size category, and 50% of the population is under 5' 4" tall, but brands' size offerings do not reflect this.  In addition to these categories, there are also tall women, big and tall men, petite men, and people with physical handicaps that are also opportunities for brands to target.

Richard Irons:

Fit tool desired output
When thinking about creating a fit tool, firstly it’s necessary to think about what is needed from that tool.  For instance, whilst producing a custom-made dress, a pattern with all the correct measurements will be required from the outset. 

However, in this piece we’re not talking about bespoke garments, but clothes that are already manufactured, and are available in a finite number of sizes.

Best size
When shopping in a store for clothes, most consumers who are not sure what size to pick opt to try them on – and when a size doesn’t fit correctly they may examine different sizes until either finding a good fit, or deciding that none of the available options is suitable.  It’s this process that we want to duplicate in a fit tool – essentially the algorithm 'tries on' every available size on a body, selects the best size for that body, or concludes that none of the sizes are any good. 

So really what is being asked from a tool is 'best size, if any'.

Ideal garment measurements
In future, if manufacturing processes change so that fit plays a greater part, we may want the tool to provide us with a list of 'ideal' measurements for a garment.  This could, for example, be used as input into some sort of electronic manufacturing system that makes every garment to order. 

But perhaps this is jumping ahead.

Required inputs
In order to get the best results from a tool it needs consumer information to work with. To return to the analogy of trying clothes on in a shop, there are two things involved: a body and a garment. A tool needs information about both.

Clearly, a fit tool needs the body-in-question’s measurements, and the most obvious way of obtaining them would simply be to measure with a tape, the way a tailor would. This is actually the best way to get accurate metrics, if it were a professional who was undertaking the measuring. However, for a customer at home, it’s not a great system. Firstly, the subject needs to possess a tape measure, and secondly, they need to be willing to stop in the middle of shopping in order to take measurements.

These issues are problematical in themselves, but worse, the majority of people don’t know the correct measuring method, so will ultimately supply inaccurate metrics. And if the data is inaccurate, there’s no way the tool can give a good result.

AI method – 'pertinent questions'
An easier and more reliable way to get the information needed is to ask the customer some pertinent questions – age, weight, height – simple information that people already know about themselves. Once it has this information, the tool can use a neural net, armed with a great deal of knowledge that has been previously collected, to deduce that user’s measurements surprisingly well. This method is usually significantly more accurate than asking consumers to measure themselves.

Garment info
The information that is required about a garment is a little more complicated. It’s not enough to simply know the physical dimensions (although these are necessary), since other considerations, such as how closely the garment is meant to fit at certain points, and how stretchy the material is, must be taken into account.

The easiest place to get this information is from the manufacturer. All the details about the apparel’s dimensions, the fabric’s 'handle', and the design’s 'preferred fit', are known to them, because this information is needed for the manufacture of the garment.  However, sometimes the retailer doesn’t have a direct relationship with the manufacturer and won’t have access to that information.

Without these details, it’s necessary to use one of a number of methods. The most accurate would be for a garment technologist to acquire the apparel in each size and undertake accurate measurements, using their expertise, along with product photography to judge the preferred fit.  However, with a large number of products, this approach becomes prohibitively expensive. Other available methods include generic size charts, information from similar garments, and artificial-intelligence inference from product descriptions and photography.

Ideal future
Manufacturers who want to make sure that an accurate fit could be calculated for all their products would be best advised to make all the measurements and design information easily and freely accessible. 

If this became an industry norm, customers would find obtaining a good fit much easier, and the level of expectation and competition would ultimately cause manufacturers to raise their game with regards to fit.

Checks
To make sure a tool is reliable, developers need to check that the results make sense. There are certain ways to do this.

One simple method is for a specialist to test tools by entering lots of different measurements and then see if the recommended size 'looks right'.  Of course, this method can be subjective and inaccurate, as, for example, it depends on the manufacturer’s idea of 'size 10' broadly agreeing with the technologist’s.

More accurate testing can be done, albeit more expensively, by buying garments in the recommended sizes for many people of different shapes and sizes, and judging the fit when trying them on. Information from this process can then be fed back into the tool to improve its accuracy.

In conclusion... Mark Charlton:
The diversity that exists across the human race meshes with the complexity of each fashion brand's design aims, layered to the multiplicity of fabric properties and fit preferences, both of designers and consumers. These issues create a mind-bogglingly intricate problem of achieving the perfect fit.

But this is only part of the challenge: for example, optimal fit can also differ across POMs (points of measurement). An instance of this would be where stretch jeans would require greater elasticity in some areas than in others, so that there is flexibility on the hips, but a snug fit on the waist: a combination of variable body shape, but also of preference.

No individual company, however great their resources, can solve the fit question in isolation: one brand can hope (at best) to supply a solution for their own apparel – which only represents a fraction of their consumer’s overall fit needs. 

We need the vision to collaborate with fit solutions across the entire fashion industry, whilst still competing in this space.  A necessary step towards this is to understand that we must solve the issue of apparel fit by rising above simply thinking of it as returns problem.  It is far more important than that.


 

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