We’ve all heard the maxim that data is king. Since the early 2000s, the power of data has ballooned unchecked as our economies hurtled towards digitization. Brands and corporations that recognized the opportunity have amassed untold wealth, while legislators are still scrambling to retrofit rules to govern its use.
Yet although the tussles between governments and Big Tech dominate the headlines, we’re overlooking a wider societal shift in which data is playing the starring role. As some market players deepen their understanding and increase their power, those who don’t have a handle on their own data fall further behind. As “traditional” businesses disintegrate and digital tightens its grip, we’re at risk of creating a new hierarchy of power: where the data literates reign over the data illiterates.
Being data illiterate doesn’t mean you don’t have access to data. Few companies these days operate in a data free zone (the mass panic over GDPR is testament to that). Rather, data illiteracy results from a lack of the skills, time or resources needed to properly understand and utilize insights. As data illiterates fall further behind, their economic potential diminishes. For those desperate to catch up, many end up outsourcing their data needs — thereby funneling more power to the already powerful and pushing comprehension of their own data further out of reach.
This cycle is picking up speed. The widening of the gap between those capitalizing on data and those unable to is widening. This divide transcends individuals, companies, and geographies, leaving some at permanent risk of marginalization. And, as is often the way, it’s public sector organizations that are among those most at risk.
Take Britain’s National Health Service (NHS). Responsible for the health of nearly every one of the UK’s 66 million citizens, the organisation has access to unparalleled amounts of data. But they’re not great at using it. This is causing a litany of problems and consequently boosting prospects for corporate giants.
Firstly, underutilization of data prevents the health service from being able to identify problems and innovate effectively to solve them. Silos remain, staffing issues fail to be addressed, patients have disjointed experiences. With each unaddressed issue, the whole institution lags further and further behind the curve.
To cure systemic ills, NHS managers seek outside help. And this can often work out well. Data literates can come in, find and process the data in a way the NHS can’t, and fix things. Companies like IBM, Microsoft, and AWS see healthcare institutions as a massive growth opportunity for this reason. But when public institutions outsource data literacy, not all the third parties getting involved are in it for the right reasons. In many cases, it puts power into the hands of those who understand how to leverage it but have no interest in empowering their clients alongside them. Instead of the involvement of data literates creating an opportunity for the data illiterates to better understand their own insights, reliance on non-collaborative outsourcing grows and the motivation to achieve a level playing field diminishes.
This is also a piecemeal approach. Without an internally-driven push to digitize, customer experience — in this case that of patients and staff — can vary wildly. Despite the NHS offering incredible care, free at the point of use, it can be a frustrating, anachronistic system to navigate. As users lose patience, user-friendly, tech-first services like Babylon, Livi, or Doctorly come along and fill the gap. Data literates offering faster, more accessible services are so far ahead of the game — iterating, investing, expanding — that public sector institutions can’t compete.
We’re currently on the cusp of a new phase of data supremacy and it could go one of two ways: Either data literate challengers will disrupt and overwhelm traditional offerings, or they will become partners to help organizations and individuals better manage, understand, and leverage their own data. If everyone is to benefit from the era of big data, we must push to make the latter a reality.
Driving up data fluency requires investment and education. This upskilling needs to encompass an understanding of what data is, how it’s collected, and how the insights it provides can be leveraged. Embedding this at all levels — from the classroom all the way through to organizations’ training strategies — should become a priority for all businesses and policy makers. Perhaps bank startup loans could be conditional on the completion of a course in data analytics. Students could be offered a short-course Data Literacy certificate. The government could offer free data training to those receiving job-seeker benefits.
To translate this education into a level playing field, we then need to champion tech companies who want to partner with public sector institutions, traditional companies, and individuals to help them take control of their own data. We should fund initiatives that bring them together, enabling expertise to be pooled and showcase how, with a little help, data illiterate organizations can develop their own fluency; combining in-house control and external expertise to create the most favorable outcome for citizens.
Because this isn’t just a public sector issue. Scores of small, independent businesses are being squeezed by competitors with superior data capabilities. Retail behemoths like ASOS and BooHoo built their strategies around data. They use it to find, track, understand, and upsell their market. Every click, eyeball, and abandoned basket is scrutinized, the learnings fed back into a well-oiled digital machine. Independent retailers, with far fewer resources, are too busy keeping their heads above water to get a handle on the myriad of data points they should be leveraging.
The old argument goes that of course these forward-thinking companies are outstripping laggard rivals. That’s capitalism, right? But if we accept this line of reasoning, we risk sleep-walking towards a monopolistic economy — one in which Amazon’s stranglehold sucks oxygen from local businesses the world over, where BooHoo strips the market down to a skeleton, or where Google controls everything from how we learn to what we cook. We need to arm smaller, slower, or less well financed organizations with the tools they need to stay competitive.
We cannot write off data illiteracy as a choice. It’s an economics issue. The poorer farmer doesn’t grow less delicious tomatoes, but she’ll grow fewer of them than her neighbor who had the capital to invest in data tools and made micro-adjustments to her farming practices as a result, improving her yield. From healthcare to agriculture, we need to lay stronger foundations when it comes to data literacy if we are to achieve parity of opportunity. Not all companies will use data as smartly, or benefit from it as much, but they should have access to the same tools. Likewise, the data literates should find new ways to partner with less literate organizations — ways that don’t require the less literate organization to cede all control, and where mutual gain rather than dominance is the objective.
Improving data literacy across society will create stronger, more empowered communities that can compete in our digitized world. Unless we invest in making this happen, we risk handing over the keys to the kingdom to a very small number of very big companies.