Steely Seamstress

Sewing for life

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Me-Made-May 2022 Summary and some graphs

It is nearly the end of June and high time that I wrote up my observations from Me-Made-May. . I find the more I invest in recording and analysing the data from this challenge, the more interesting and informative the results. Unfortunately this year I have had some real pressures on my time and well-being and so I haven’t been as organised as I would usually try to be. Never mind! I’m sure there will still be some take homes from the month.

First of all, due to my circumstances I have been quite restricted when it comes to what I could wear this month and it became clear early on that living in trousers with reasonable pockets was best for me, so this will be a very “jeans-heavy” month.

First of all, the spread of wears per pattern company. Unsurprisingly, the largest slices are for Burda (21.4%) and Grainline Studios (17.1%). More than anything this reflects just the quantity of times I use their patterns. I make a lot using Burda’s patterns simply because buying a magazine can work out quite a cheap way of acquiring patterns and I don’t worry if I only make one or two things from each magazine. I have made three Driftless cardigans and as these are firm favourites the repeat wears of these show up as a large slice too.

The last company that makes it into the top three is Scout Patterns . I wore the Navy blue velvet Lulu cardigan so many times this month (10.0%).

I usually make a comparison of the RTW to me-made worn in the month and this year is no exception. The percentage of me-made dropped slightly this year (78.5%) compared to last year (84.9%). I think this was due to my reliance on jeans in the month and had circumstances been different I suspect the figure would have broadly been the same as last year. But, those RTW garments I do wear are well-loved key items in my wardrobe and I cannot stress how important it is to make good use of our wardrobes, whether RTW or me-made.

This all brings me on to a new category I decided to document. I was intrigued to categorise all my garments according to age. This isn’t a problem for the me-mades as these are all documented on the blog or Instagram and I can quickly look up when they were made. For the older items I can only roughly guess their age, because some were bought as far back as the nineties!

I am really pleased with the results shown on this graph because I can see clearly that old and new get equally worn. Yes, I overdosed on wearing my new Lander trousers (made in 2022), but then it made a successful pairing with an RTW shirt from c. 1992 (early university years). This is definitely the outfit of the month:

I have also included some of my older me-mades too; specifically the Bicycle blouse, which dates from 2015, and my first jersey t-shirt from 2015. Looking at the graph I wonder whether the age of the clothing correlates to particularly productive years; I can see there are a lot of items worn from 2017 and 2020. It would be interesting to compare my usage with someone (of the same age) who wears exclusively RTW clothes. Would their clothing age profile be the same?

Number of items for each age grouping. RTW items all bought in 1990s, 2000s and 2010s.

As a final note, I wonder whether this is just an exercise that is useful to me. I know I can thoroughly geek out on data and graphs! So, if you like to do likewise I have a MMM-template that you are welcome to use!