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Quantified Self

I like numbers. Maths was always one of my favourite subjects, and I went on to do Maths with Maths (and more Maths) at university. Part of the appeal is measurement, because it can lead to insights and optimisation. Things like Nicholas Felton’s amazing annual reports fascinate me. This led me towards Quantified Self, and it sounded like something interesting, and like something I wanted to do.

For quite a long time I used Daytum. It’s pretty easy to enter data, and its output options are simple and appealing. The entering of the data was a little too time-intensive, though. To get the most value out of it, you need to track a lot of things, which means investing a lot of time.

So I dropped Daytum and used Moves for a while, but found it a bit limited. I took the (monetary) plunge and acquired a FitBit (The One, since it seemed the smallest and least dorky). In the end, it was much like Daytum, though. It track some things easily, but most of the data was fairly long-form manual entry, and it gets dull after a while.


When Mr Felton released Reporter the other day, I decided to give the whole QS thing another go. The thing that interested me the most was Reporter’s approach to gathering data: short, randomly timed bursts, with simple answers. Logging every single thing that happens might give you some deep insights, but it’s a pain to do.

I’m also finding that I don’t mind being interrupted by it. I’ve turned off just about all notifications on my phone, except for personal, just for me, ones like Twitter Direct Messages. I found myself spending too long playing with my phone, and wanted to remove some of the temptations to pick it up. Reporter somehow goes under my radar for, though.

I’m intrigued to see if I stick with this, and what extra little questions I’ll add myself. I’m not quite sure what I want to track, but I suspect a pattern will emerge after using the app for a while: blank spots that I want to fill, or things I’m recording that I actually don’t care about.