Most of us, sadly, fail to embody a platonic ideal in our physique. I certainly don’t. I’m vertically challenged and stocky (I prefer to use the term ‘muscular’).
That means for the vast majority of humanity, clothing ourselves is a challenge — an unhappy compromise resulting in tradeoffs among bagginess, pinching, too short or too long sleeves, etc., etc.
When it comes to jeans — the sartorial lingua franca across the globe, happily worn by students and billionaires alike — the situation is miserable. The largest brand, the ubiquitous Levis, offers a bewildering variety of different numbered styles characterized by terms such as skinny, athletic, narrow, and so on, all costing around $50. In my experience, the only way to determine whether a particular number type fits you is to physically check it — go to a store, take several number types in a range of sizes, try them on, and find the least ill-fitting one to buy. Even that is problematic, as I’ve found that two pairs of the same number type jeans in the same size can vary in actual fit, so thinking you can find the right style with a physical store visit and then order online from then on is sadly mistaken.
An alternative is to look more upmarket to designer jeans. They cost on the order of $200 and purportedly offer more customized fit than plebeian Levis, although I speculate that the ‘customized’ fit is more commonly due to the liberal use of spandex in the cloth rather than better tailoring. In any case, many people might be reluctant to wear such an expensive item for prosaic daily duties like gardening, taking out the trash, and so on.
Given my jeans travails, I was primed for a different approach and was pretty intrigued when I came across a company called MTailor via an ad on CNN. Its pitch is that its smartphone app measures the customer in seconds and results in a custom tailored pair of jeans delivered to the door two weeks later, all for around $100, with a money back guarantee. I figured it was worth a try.
I downloaded the app and went through the measurement process. It involved putting the phone on the floor and leaning it against the wall at an angle specified by the app. After that, you position yourself a few feet away and do a complete spin so that the app can capture your measurements. The capture takes approximately 10 seconds. Once that is done, you use the app (or website) to select color and leg style (e.g., bootcut) and order. Here is an MTailor ad depicting the process:
Ten minutes after I started, I submitted my order and began my two week wait.
When the jeans finally arrived, I immediately tried them on — and it was revelatory. They slipped on and were just right. For me. No tight places. No baggy places. They just slid on and fit.
So, you’re thinking “Great. I’m happy for you. But so what?” Some of you might be thinking “Yeah I know about MTailor. It was on Shark Tank. It’s not a secret.” To the latter, I would just offer the obvious: I’m not very engaged in fashion and definitely not a leading edge follower of fashion trends. It took MTailor getting on CNN for it to come into my ken. But this post isn’t about me and my clothing options.
It’s about cloud-native jeans and how MTailor symbolizes the way technology is disrupting long-established industries (Levis got its start 170 years ago during the Gold Rush when a San Francisco-based French immigrant created durable pants for miners). With the confluence of a number of separate technologies like cloud computing, machine learning, and global high bandwidth digital connectivity, IT is moving from manipulation of digital representations of physical processes to being used to transform physical processes, to the disadvantage of incumbents strongly entrenched in traditional industry processes.
Let’s look at what makes up MTailor’s offering:
The net result of these technology innovations is that MTailor has been able to reimagine an important consumer domain. What has MTailor done by recreating the jeans buying experience?
All of this is not to say that MTailor’s future is all roses and champagne. I see three areas of concern that could affect the company’s prospects.
An obvious question is why wouldn’t Levi develop such a system? It could extend its product line with “Levis — just for you” or somesuch. It’s coming off a hugely successful year, has lots of money, and MTailor is a tiny flyspeck in terms of comparison. That may contain its own answer. The TAM for MTailor is unproven (and unknowable) today, and large companies tend not to invest in small unproven markets — they aren’t large enough, in the common parlance, to “move the needle.”
This is, of course, Clayton Christensen territory. His theory revolves around why large incumbents miss shifts in technology, and a common reason is that big companies underestimate potential demand for a new way of doing things.
One shortcoming in his theory is that it is based on a belief that existing technology in a given market evolves to meet the needs of the most demanding customer segment; this incumbent technology ends up ‘overserving’ a large part of the market for whom a less-capable and -expensive offering would be sufficient. A new disruptive innovation is introduced that meets that overserved need at a lower price point; eventually the new technology evolves to be just as capable as the existing offering and proceeds to wipe it out because the innovation is just as capable while being cheaper. From Christensen’s point of view, disruptive innovation is fundamentally based on lower prices; it’s a single factor view of customer adoption.
This perspective misses the power of removing friction in an existing market and the potential convenience holds in building a new customer segment. For example, many people assert public cloud computing is more expensive than on-prem infrastructure. Notwithstanding this, public cloud computing use has skyrocketed, which could be a reflection of how much easier it is to obtain computing resources from a public provider.
Based on this, despite the fact that MTailor jeans are more expensive than the incumbent, it is very possible that its market could be significantly larger than might be expected, based on price alone. The superiority of fit, married to the convenience of custom measurement and doorfront delivery might overwhelm the drawback that MTailor costs more than the incumbent.
MTailor represents an interesting development in our economy: restructuring an existing market segment by applying cloud-native technology. While jeans seems like a trivial, unsexy category, they have the virtue of ubiquity — everyone wears them and many customers find the existing offerings inconvenient with more attractive options too expensive. In other words, jeans are a legacy industry ripe for disruption via the application of information technology.
Looking with fresh eyes at how this industry operates, MTailor recognized that it reflects an outmoded approach to operation — delivery of large quantities of standardized designs that actually fit only a subset of the total market. This approach was originally based on the constraints imposed by the need for standard designs to be amortized across mass production and distribution; this makes perfect sense when the cost of customization is extremely high. MTailor removed those constraints by substituting computing for key elements of the supply chain and was able to bring to market a more satisfactory product that can be economically delivered to customers.
MTailor gives a glimpse of the kind of restructuring we’ll see across our economy and society over the next twenty years. As fresh sets of eyes are cast over legacy products and services, assessing how they can be updated with computing substituted for inefficient and/or expensive elements, we’ll see an explosion of new offerings made possible by reconfiguring value chains. It’s more dangerous to be an established industry participant today than ever before in history and many powerful incumbents will be brought down by small companies leveraging force multipliers.
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[…] I wrote about one such example a few weeks ago — MTailor uses a smartphone app, machine learning, and a global supply chain tuned for customization rather than mass production to deliver tailored clothes at an attractive price point. […]