Detail. Again.

It’s only in starting to write this (and therefore filing it my perfectly constructed and maintained filing system) that I realised I’ve blogged about detail pretty recently. People will start to think that I’m obsessed.

But this time I wanted to talk about the dilemma that I come across often. I’ve just reported on a survey, and in that I had a hundred and fifty odd responses, from various grades in various locations, with both quant/rating and qual/free text questions. That’s a lot of data points. But my summary and recommendations ran to precisely 899 words. If it didn’t put quite so much spacing in it, that’d barely run to two pages.

Is that enough? Is that value for the time I’ve spent and charged on it?

I think so. (I hope so, I’ve not had feedback yet…) And it’s the approach I’ve followed for a long time, with some success. Indeed I remember a distinct stage of my career when the reports/proposals that I wrote changed from being judged on how long/comprehensive/detailed they were to how short/concise/to-the-point that they were. And a sadistic-yet-helpful boss that used to get me to summarise, strictly on one page. And then to do it again, but this time double-spaced.

So, taking this report as an example, I’ve got those many, many data points (about 2,104 since I’m doing precision today) down to two main themes. And in doing so, I can then make 10 recommendations to specifically tackle those two themes.

Now, there’s also another 50 odd pages of charts where I report on and summarise all of that data. At the appropriate time, that’s available to delve into. But if I reported on all of that, in real detail, upfront it’s going to obscure: “what’s happening?” and “what should I do?” And I think that the real value is in summarising and summarising again, until I – and by extension my client – is confident that we’ve hit the nub of the matter.

Data's just numbers, right?

I’ve written about most of the types of research that I’ve done before. In, what some people have described as, exhaustive detail. If you look that up in a dictionary, it’s a compliment. But I’m not 100% sure that they’re using it in that sense…

I’ve talked about enjoying the challenge of qualitative research. Bringing together multiple, divergent, abstract and often contradictory ideas. I like piecing that together into the story that best makes sense of it; that connects most of the ideas, most often. And within that there’s some perception, some inference, some creative license.

Data is different. Data is hard. Data is absolute. And that – tragically – excites me too. You’ve got all the pieces of the jigsaw, and they’re only ever going to fit together one way. You can’t obfuscate, you can’t flim-flam, and you can’t use your intuition. (And sometimes it’s nice to turn off and just chunk through data. Especially, say, if there’s a test match on.)

BUT, there’s still a story to be told. It’s rarely any use just taking data and pumping out some graphs. (Quite apart from anything else, your choice and layout of graphs will determine how easily people can make much sense of them. But that’s another blog….) You need to start to link themes together. What might the low-rating here mean next to the high rating there? What could cause that apparent contradiction? Why are these people scoring higher than these?

Sometimes the outcome is that you need to do further, research to understand fully. But it’ll be precise and targeted – and hence a lot cheaper than it might have been. Other times, you’ll get the answers, and context, that you needed. Data tells a story. And it’s a story I love finding.