Two Men, One Song

In my last post (eons ago now, I know…) I introduced the Data Human Index, a framework for measuring how human-centred a digital experience really is.

Before I show you how it works in practice, I want to tell you where this thinking actually started. Not in a boardroom or a consultancy, but in a PhD survey with fewer than 70 respondents and a song called Yesterday Once More.

In 2010, I ran a small music memory survey as the first cycle of my PhD research. I wanted to know whether other people experienced music the way I did, whether songs carried specific memories vivid and emotional enough to be worth building something around.

Most findings confirmed what I expected. People remembered songs attached to specific moments: a road trip, a first relationship, a loss. Music wasn’t just something people listened to, it was something they lived inside.

But buried in the data was something I wasn’t expecting.

Two respondents had submitted the same song: Yesterday Once More by The Carpenters. On the surface, they had almost nothing in common.

Respondent No. 1 · a young Taiwanese man, born in the late 1980s

It is one of my dad’s favourite songs and it reminds me of the time I spent with my family in Taiwan.

Respondent No. 15 · a British man, considerably older, on a memory from 1973

My father had recently died, and I had taken my mother out for the day. This particular song was on the radio, and it always brings back memories of that day.

Different countries. Different ethnicities. Different generations. No connection to each other whatsoever. One man grieving a father he had just lost while another, a boy, simply happy to be near his.

The same song. The same emotional core.

I still get goosebumps thinking about it.

Now think about what a data system would have done with those two people. It would have placed them in completely different segments and by every measurable signal, they were very different people. And yet at the level of human meaning, they were saying the same thing.

That’s the gap that sits at the centre of everything I’ve been working on since. Data systems are extraordinarily good at measuring what people do, but they are much less good at understanding what those behaviours mean. That’s the difference between a system that measures people and one that understands them.

The Data Human started from that gap. Not from a theory or a framework, but from two men on opposite sides of the world, quietly holding the same memory of a father and a song.

Behind every data point is a person. And behind every person is something data alone will never fully capture.

That’s what this work is about, and it’s why the Index matters to me in a way that goes beyond frameworks and scoring.

More on that soon.