Are Data Skills Equally Distributed? Building a Society with Data at its Heart

I wanted to pitch a session at #ukgovcamp18 recently. Previously I’ve chatted a bit about the usability and accessibility of data — that is, how can we make government data more user-friendly, and open it up to the more people? This year’s session carried on this theme, but was more focused on the skills we need to collect, process, and understand data — not just consume it. At OCSI, we collect a wide range of data about inequality, but nothing about the skills we actually employ ourselves. Isn’t it time we stepped outside of our ivory tower?

Somehow I managed not to fluff my pitch, and proposed a chat entitled ‘Are Data Skills Distributed Equally?’ It got a few raised eyebrows during the intro, which I take as a sign that people are interested in the topic. And sure enough, the (post-lunch) session went really well — discussion was lively, diverse and productive — you can see the ‘official’ session notes here.

My original aim was to talk a little about how to measure and track data skills as a nation, because that’s the kind of thing we like to do at OCSI. But the conversation rapidly turned into a more fundamental one — What do we mean by “Data Skills”? What are the blockers to learning them? And how can we unblock these?

I came away from the session with three main observations:

1. ‘Data’ is about a broad mix of skills

To be fair, I don’t think there are many people who would say that ‘doing data’ boils down to a single skill. But too often, we simmer it down to a particular job, role, or technology, often depending on the audience we’re talking to. Remember that whole thing (wow, 9 years ago) about ‘Statistician’ being the sexy job in the next ten years? The rest of the original quote was actually more important: “statisticians are part of it, but it’s just a part.”

Similarly, fascination with trends and novelty means we’ll often hone in on the latest technical movements, such as ‘Big Data’, or even ‘common APIs’. Each, in its own circle, is great. But you can’t expect to follow a trend, get one skill or API in place, and sit back to see magic happen. Efforts need to be more expansive and coherent than that. And to do it *clearly*.

So we need to keep pushing for a better, more wholesome picture of what ’Data’ actually involves. Let’s broaden this out.

Wouldn’t it be great to…

  • Get a conversation going on what combination of skills is important when working with data
  • Start giving equal value to each of these skills
  • Identify where there are gaps in skills which could be filled to make things better?

2. ‘Data’ is dependent on a bunch of other stuff

I’d also argue that there can be very real *cultural* blockers, which can prevent skills from being established and supported. It’s really important that we break down stigmas of who ‘should’ be able to do what — that we start establishing data skills as something to be proud of, no matter who does them. The public perception of the *value* of data needs re-examining — it needs to be seen as something that “we can do”, not something that “happens to us”. We need to get punk about data.

Again, this should be something we can start to elucidate, and make more transparent. If we can identify the fundamental obstacles, then we can go back and address them first, before expecting people to just jump in and get on with it.

Wouldn’t it be great to…:

  • Start highlighting the things which are blocking broader takeup of the skills above
  • Have conversations with people who are starting out with data and evidence, to see what their needs and pains are
  • Work with people to actually find ways to remove these blockages?

3. The network is everything

By deliberately placing a focus on teamwork, and by tying this into a clearer vision of the skills-mix which really push data forwards, we start to shift the debate away from smart individuals, and more towards communities that need mentoring, and groups that need support above and beyond tech skills. We start to see the *connections* between these individuals as more important than the individuals themselves.

Wouldn’t it be great to…:

  • Encourage a more diverse approach to data skills networks, bringing together a wider range of backgrounds
  • Reach out to other groups which need similar support
  • Help groups to learn from other groups

Actions

Maybe the initial starting point is these two questions:

  1. What can *I* realistically do, and how can I use my position — where I’m already within a network of data professionals — to push data skills outside of their existing “comfort” networks?
  2. Who should I be talking to as part of that effort, and how? Is that a series of personal conversations, or is there scope for some larger, ongoing “group” to move this on?

More to come soon, but if you’re interested, please do get in touch! I have a list of people from ukgovcamp, and figure we can start to build the network to build the network…

Originally published at Workweek.

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Lead tech at OCSI, making data friendly for social good. Likes words. Doesn't really own a bowler hat.

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Graham

Lead tech at OCSI, making data friendly for social good. Likes words. Doesn't really own a bowler hat.