Bethan Blakeley: Tearing down barriers

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Yet again, I find myself sitting here, staring at an empty page on Word, trying to work out how best to talk about the latest thing that’s annoyed me about our industry. Don’t get me wrong, I love working in research and analytics, but sometimes…

The source of my ranting this time is the colossal gap that is too often found between analytics and research, or even analytics and the rest of the world. A gap that, realistically, just shouldn’t exist; that makes my job, and many others’ jobs, much harder on a day-to-day basis. Yep – that one.
I was attending a talk by a respected analyst on a fascinating subject – and when she got to talking about the nitty-gritty of what she was doing and how she was doing it, there was an awkward pause. Her eyes shifted around the room, and then to the floor. She started her explanation with, “Well, I have to admit…”

Her confession? She was using Microsoft Excel for some of her analysis. That’s it.

She felt the need to admit she was using Excel – like it was some sort of big, dirty secret. Something people shouldn’t do. You see the same tool snobbery time and time again, and it’s safe to say it drives me mad.

There are hundreds, if not thousands, of tools out there you can use to help with your analytics. From R, Python and SPSS to (dare I say it) Excel – and there isn’t one tool that is better or worse than the others. I definitely have my favourite tools for certain tasks. Horses for courses, if you will. But pretending that we’re somehow above using a tool that is arguably a bit more mainstream does us much more harm than it does good. It doesn’t make us look even cleverer; it just builds barriers. Barriers between us and the people who need to understand the recommendations we’re giving after the data analysis stages. Huge walls between us and the next generation of data wranglers.

I’ve said it before and I’ll say it again – people, generally, struggle with numbers. Many see an analyst’s work as intimidating, confusing, full of jargon, and beyond their reach because “I was never any good at maths anyway”.

It’s our job to tear down those barriers. We need to be making our work more accessible to the wider population, not the opposite. We need to be able to explain our findings, and how we got there, in a jargon-free and accessible way. We need to inspire people to want to play with numbers, to find it interesting enough to want to give it a go – not keep up this crazy façade that what we do is complicated and technical, and only the very few gifted individuals among us will be able to understand.

If we’re able to do a piece of solid analysis in an accessible tool such as Excel, we should be shouting about it, not hiding it with shifty eyes and hushed voices. The more we can get people to engage with what we’re doing, and how, the more we will engage them in our insights and our recommendations – and the more clout our work will have in the wider world.

It’s as simple as that. It’s high time, as an industry, we stamped out this behaviour for good. Stop using complicated techniques when simple ones will give the same output. Stop using confusing words when it distracts from what is actually important. Stop pretending we don’t all use Excel for the odd pieces of analysis.

It’s high time we got over ourselves.

Bethan Blakeley is analytics director at Boxclever. She writes a regular column for Impact magazine and contributes to Research Live. This article was first published in the January 2023 issue of Impact.