Peter Drucker noted that what gets measured, gets managed. Other iterations evolved to suggest what gets measured gets done.

My take is that what gets measured becomes addictive and compulsive.

I received a FitBit many years ago, as a gift from a good friend, and used it slavishly for months until it stopped holding a charge. I never did replace it. I remember one summer when I was relaxing on the sundeck with my daughter. She would, every once in a while, leap from her chair and pound the 85 feet of deck from end to end a few times before throwing herself back into her lounger and picking up her book. She had set her FitBit to remind her whenever she was indulging in a lengthy period of inactivity and when it buzzed, she jumped to the pump.

Depending whose research you access, fitness tracker abandonment runs anywhere from 33% after a few months to 75% within a year. Researchers point to various reasons for abandonment, among them adherence to technology, lack of results, inaccuracy of tracker information or politics. (When Google purchased FitBit, many users switched to something else, believing Google would downgrade the tech in favour of promoting its own product.) Perhaps it’s the relentlessness of the tracking which induces guilt and remorse when targets aren’t met or results are less than had been hoped for.

I’m not just making up this addictive appeal; I’ve been there and recently at that! For two weeks last month, I wore a CGM, a continuous glucose monitor. Once the sole domain of people with diabetes, you can now order or purchase one without a prescription, simply to learn how different foods and activities affect your blood glucose or just to add to your arsenal of physical measurements. Having moved to a ketogenic eating regimen several years ago, I was interested to see if the assumptions on which I have been operating, were sound. In the early days that required a finger prick onto a test strip and a blood glucose reader. Needless to say that activity didn’t last more than a week.

So what did I learn? Partly what I wanted to learn and partly something that hadn’t occurred to me when I launched this experiment. First, for all you blood glucose aficionados, the biggest blood glucose spike I saw in two weeks came after dim sum, largely thanks to all the rice based dishes and their gluteny carbs. The biggest meal I had, a lovely steak with about a dozen spot prawns and drawn butter, had ZERO impact on my blood glucose. The fastest drop in blood glucose came thanks to 20 minutes of walking the deck of the ferry on my way home after a sushi dinner (moderate spike, rice again!).

A friend recently told me of her vague sense of guilt and disappointment when, upon awakening in the morning, she found her blood glucose high-ish, despite having “fasted” all night while sleeping. Ah hah, I observed, having noticed the same thing and researched it to find “dawn phenomenon” whereby the body, wanting to set you up for a productive day, infuses your person with cortisol and human growth hormone which elevates blood sugar. Otherwise we might languish abed all damned day and forget to head out to forage for berries and kindling.

And now for what I learned about this whole measuring, data collection and interpretation thing.

Towards the end of my two week experiment I couldn’t wait to be done. Much as I valued the insights and confirmations of my eating and exercise regimen, I was tired of being glued to the screen, watching for any fluctuation and analyzing it based on intake and output.

I know various people who measure glucose, whose watch or other device measures the length and quality of their sleep, tracks their food intake and analyzes its nutritional value, that monitors blood pressure, heart rate and blood oxygen. There is talk of a wearable device to constantly monitor our hormone levels so we can decide if it’s the hormones or if we’re just being really nasty and irritable for GOOD SOLID REASONS, DAMMIT!

Data is useful in so many endeavours: market analysis, product uptake, segmentation, advertising, research spending and on and on. What we’ve also learned over the years, however, is that we can make data dance to whatever tune we choose to play so I wonder if we’re truly learning anything new, or just hunting around in the sock drawer, looking for support for something upon which we’ve already made up our minds.

Because I’m such a fan of anecdotal, completely not empirical, information, I’d love to hear what tools, devices and apps you use to figure out who and what you are.

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