Why data literacy is the key to future-proofing your career

Jobs come and go, but data is here to stay

Some years ago, I read a book that’s had a profound effect on how I look at careers and advise the people I mentor. That book is The 100-Year Life: Living and Working in an Age of Longevity by Scott and Gratton. In it, the authors talk about how the arc of a career history is so much more extended now than it was in our parents’ generation and our grandparents’ generation. They point out that a child born in the early years of this millennium has a 50% chance of living to 100.

I’ll say that again: a 50% chance of living to 100.

A lifetime of learning and resilience

That means a working career is now arguably approaching 70 years long. But I don’t think we’ve really woken up to that yet. We haven’t updated our world view. We’re not used to the idea of having a career that stretches out for close to three quarters of a century. And many of us (myself definitely included) are not good at doing the same thing over and over again for six or seven decades.

What does that mean? It means we’re all going to have to get really good at reinventing ourselves as we go, and re-skilling in a significant way 2–3 times over our lifetimes. At least! So we’ll need to be resilient and we’ll need to become lifetime learners.

Now me, I work in tech. I have done since I left academia after eleven super enjoyable years of tertiary education and post docs. I love what I do and I believe that companies in various flavours of the ‘tech industry’ offer a wealth of career options for many people. No matter what role you have in the tech industry — engineer, product designer, agile facilitator, architect, business analyst — the work you do will be impacted by the rise of data, machine learning and artificial intelligence (AI) in your working lifetime.

So how do you begin to understand this fascinating area and future-proof yourself and your skillset? It begins with data literacy.

Data literacy needs to be in everyone’s job description

At Xero, we want our people to do the best work of their lives. And in 2020, that means helping them improve their ability to source, use and understand the massive amounts of information that flows into and around our company. You might think data literacy is only important for financial analysts and data scientists. But we don’t think that’s right at all.

Data literacy for our executive team might include their ability to look at a data visualisation and distinguish between situational and systemic movements. Data literacy for an engineer in one of our product pods could be all about knowing how to structure a database schema to support future-looking analytical queries, as well as current-day operational needs.

To improve our data literacy, we’re developing a playbook for product teams to help them spot and triage opportunities where they can use machine learning techniques to build even more #beautiful customer experiences. The playbook helps them level up from ‘I’ve heard about AI and I think it’s cool’ to actually being able to apply some of the foundational techniques in a meaningful way — and knowing when the extra complexity is worth the extra effort.

The exponential growth in the amount of data in the world isn’t slowing down anytime soon. And as these digital breadcrumbs generated by day-to-day activity become ubiquitous in our everyday experience, data and the conclusions we draw from it is also becoming easier and easier for bad actors to manipulate. Along with teaching numeracy and the ability to read, we believe it’s important for people to be taught how to think critically about data and statistics, and spot places where they are used badly, so they don’t get taken for a ride.

These are lifelong skills and important ones. We hope our folk will stay with us for years, but even if they move on from Xero, they’ll take those new abilities with them. The ability to look at the world in a more quantitative way, and a logical framework to be able to question the things they see.

Avoiding a dystopian data future

There’s also a fair bit of talk — some of it rather daunting — about dystopian futures driven by this explosion of data. Some of the algorithms being developed and deployed really do have the potential to change our criminal justice and legal systems. We face a real risk of accidentally ‘freezing’ ourselves in the 2020s and enshrining the social and societal norms of today, because that’s ‘when’ we collected the data that pours into these massive, under-specified algorithms.

That’s why it’s extremely important to make sure that the people involved in the conversations about these algorithms come from a diverse background and can bring a broad spectrum of views. I’m not suggesting that companies or governments deliberately set out to write things that are biased or lock in some particular status quo. But it’s really easy to do it unconsciously.

Building strong data literacy skills across a workforce will therefore pay dividends for a company and for society, as it ensures we have a wide range of voices at the ‘algorithm decision-making table’. This reduces the likelihood of accidentally building something that turns out to be detrimental; to the company and to the world in general.

Unlocking new career opportunities

The rapid pace of this industry means that in many cases, the people we need to help us drive the savvy and thoughtful development of ‘augmented intelligence’ products aren’t in the conversation yet. Often it’s because the roles don’t exist yet and there aren’t many experienced and skilled people to lead the way.

For example, we’re currently looking for data evangelists to help drive data literacy at scale across the organisation. It’s a role that doesn’t really exist in the mainstream right now, so finding them is tricky. These folk need to have a passion for making sure that diverse voices are being heard, and some of them will need a background in organisational development, or be able to teach adults new skills effectively (it’s very different from teaching children!).

We work really hard to make sure that our data is clean and coherent and ordered, so we can build great insights and better support our customers. But everyone has a role to play in building great data and data products. High levels of data literacy empower everyone in the company to spot opportunities to use data well — helping to ensure we create products that consider a full spectrum of possible futures and reduce the unconscious bias that stems from too few people contributing ideas.

Most importantly for the individual, lifting data literacy opens doors to new roles, even roles we have yet to imagine.