In a conference as big and diverse as NEXT Berlin it’s inevitable that not every theme will chime with every attendee. For example, I’ve never really got into the idea of the quantified self – the concept of measuring things about yourself, and capturing that data for self-improvement. It always struck me as a little self-obsessed and a little too demanding of my time for the results it offers. There have been great and inspiration speakers on the topic at NEXT – like Tim Ferris – but they just never seemed relevant to my life.

I’ve sat in presentations thinking that it all sounds very cool, but it’s really just for the sports enthusiast who is data minded, not the likes of me. When the most strenuous regular exercise you do is regular inspirational strolls along the beach, running data, or heavily tracked calorie patterns just doen’t see very relevant.

In short, the quantified self seemed irrelevant to me, as my body is not exactly what you’d call a performance tool.

That was the case, at least, until my wife suggested I got a silent alarm to wake me on days when I need to be up and out before our baby daughter – who is still sleeping in the same room as us – awakes. I settled on using Sleep Cycle for the iPhone, because it does a great job of setting a silent alarm, and in choosing the best time to wake you by monitoring your sleep cycle.

How does it do that? It uses the motion sensors in the phone – the accelerometer and the gyroscope – to sense how much you’re moving. When you’re in the light sleep phase nearest your wake-up time, it triggers the alarm. Simply put, my phone starts vibrating on the corner of my bed when I’m pretty close to awake anyway, easing my way into a new day, and leaving my (sleep-deprived) wife and baby daughter still safely asleep.

So far, so good. But what dawned on me over time is that it’s actually gathering a lot of data on your sleep. The app is not just measuring my sleeping patterns, it’s storing and graphing that data for me. I can see exactly how well I slept as soon as I awake.

This is an example of the data it has on one night’s sleep:

Can you guess at what times my daughter woke up? This has proved pretty useful when we’re trying to figure out what Hazel’s sleeping patterns have been in recent weeks – because we’re both so disorientated by patchy sleep that we’re not sure by the time morning hits…

More than that, though, it’s giving me a pattern of how well I’m sleeping, which can give me early warning of a problem building up. The three month graph (at the top of the page) gives me very clear signs that my sleep quality is plummeting in recent weeks. That’s something I can think about and start planning to correct.

Sometimes the acquisition of data is an exciting thought, but I think we’re past that phase now. After all, it was 2011’s conference theme… To move the quantified self out of the realm of the data enthusiast and into the mainstream, we need more compelling examples of how it can make a powerful difference in people’s life.