Why I’ve tracked every single piece of clothing I’ve worn for three years
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Why I’ve tracked every single piece of clothing I’ve worn for three years
Olof Hoverfält
January 22, 2021
Have you ever wondered whether expensive clothes are worth their price? Or had that subtle feeling of guilt when buying something pricey, and then justifying it because you will wear it so many times, even if you have no clue if it’s actually true? If you thought yes, then this is for you.<br>I took a deep-dive into my closet to find out what my clothes truly cost, and learnt a ton about performance, sustainability, and myself in the process. In this blog post, we go on a journey of data-supported decision making. Even with small data, you can get big insights – and some nice shoes along the way.
I have kept a continuous daily log of the use of all my clothes for the past three years.<br>What started out as a simple question of whether it makes sense to buy expensive clothes has now turned into a rather deep discovery into the cost performance of clothes. You can explore my continuously updated wardrobe performance here.
My principles for more or less any consumption have for a long time been to buy what I need, use what I buy, and take good care of what I have. With clothes, however, I had no idea of how I was really doing.<br>The insights from this project have helped me improve the choices I make. I also ended up building an analytics platform for the performance of not only clothes, but any kind of durable good.<br>Three years into this journey, it’s time to reflect on everything I’ve learned and hopefully help others understand the logic, practices, and benefits of data-supported decision making. And if you’re only here for some wardrobe-perfecting tips, head over to the end of this post for a practical guide to clean out your closet and consumption habits.<br>Easy daily wear data<br>Let’s start with a brief look at the data, as it is the core enabler of everything to come.<br>My wear data is a continuous daily log of my use of each piece of garment since January 1st, 2018. To date, that is a total of 426 items, 1106 days, and over 300,000 data points of use and non-use. All items are divided into a simple MECE structure of 12 categories: jackets and hoodies, blazers, knits, shirts, T-shirts, pants, shorts, belts, socks, shoes, underwear shirts, and boxers. Sportswear is an additional category that is outside the portfolio of “daily” clothes.
My first version was a simple Excel that contained the wear data and a few plots. At some point, Excel started choking on my growing data set. I needed more powerful computing and data visualization capabilities, so I started building my own platform using R, a programming language for statistical computing. All computing and plotting is now automated in R. It took some 2300 lines of code. I also moved the master data from Excel to Google Sheets in order to make data entry as easy as possible and to keep all data in the cloud.<br>At the moment, the data entry UI in Google Sheets looks like this:
These are my jackets and hoodies that are active, aka items that are still in use now, as opposed to those that have been sold, donated or recycled, and are no longer available for use.<br>I count “wears” by day. Every evening, I open the browser tab and check the clothes I used that day in the list of active items. It takes less than a minute per day, which is roughly six hours per year. I spend four times as much brushing my teeth. Easy data entry is indeed critical to any voluntary, continuous, non-automated data collection. And yes, I have also played with ideas of RFID tags and image recognition to automate even that one last minute.<br>Once the platform and processes are set up, the data set itself is “cheap”, at least in comparison to the world of insights it unlocks.<br>Unveiling the real cost of clothes<br>Clothes are a form of durable goods. Therefore, a garment’s purchase price alone tells close to nothing about its actual cost performance.<br>To account for the costs of assets that deteriorate with use, the standard approach is to depreciate such assets over their expected economic lifetime. It works fine when the underlying estimated lifetime is acceptably accurate, as it is in most cases of continuous use of identical assets. As we shall see shortly, most of a wardrobe is nothing like that.
When I started looking into my clothes, I had no idea of what the lifetime of my garments might be. I of course tried to estimate my use for various items but later learned that nearly all of my initial guesstimates back in 2017 were way too high.<br>This is where daily use data corrects the distorted picture and lets you explore what the use really looks like, cleared of biases and wishful thinking.<br>Actual versus imagined use<br>Let’s start with the simplest thing: use.<br>The figure below shows the cumulative number of wears for all my shoes. The items marked green...