What is data literacy and why is it so important?
Almost everyone agrees that data is a very important part of business, but it can be hard to see how to realise the goal of actually changing an organisation into the sort of data-driven utopia everyone is dreaming of. Even when everybody is enthusiastic about making effective use of data and there is management buy-in to divert resources to data projects, the results are sometimes disappointing. Perhaps you have lots of data, but somehow it seems so hard to actually do anything useful with it.
This symptom is usually caused by a lack of data literacy: the general understanding, pervasive through an organisation, of what data is and how it works. This isn’t a matter of technical skills. By analogy, almost everybody needs a basic financial literacy to understand concepts such as budgets and cashflow to do their jobs effectively, even when an organisation might have a CFO and a Finance department. Similarly, although your organisation might need technical data specialists and a Chief Data Officer, the organisation as a whole needs basic data literacy.
Everyone needs to have some data literacy
As an example, consider an organisation with several departments and a central office supplies purchaser. It would seem sensible for the departments to have a place they can keep track of what supplies they’re running out of, so when the purchaser puts an order in then can go and look at what’s needed.
Perhaps the departments all come up with their own solutions - the developers have a busy internal Wiki, so a page on that is the obvious choice for them. The finance department go for a spreadsheet on a shared drive, and so on. For the purchaser, they now have a tedious list of different platforms they need to learn, have credentials to access, and to combine shopping lists in a plethora of formats (one department might ask for “post-its”, another for “stickies” - and that’s forgetting the unwritten rule that the developers want a selection of all the colours and sizes for their complicated agile rituals, while the support folks just want the square yellow ones, so even what “post-it” means depends on the team).
Perhaps the purchaser pre-empts this problem and sets up a central ordering system based around their needs, and then everyone else has the problem - familiar to anyone who’s worked for a large enough organisation - of having to log into the dreaded Internal System and navigate its horrible interface to try and find the correct item codes and cost centre codes and try to fill the form in correctly.
The solution to avoiding these problems isn’t any particular technical skill. It’s not SQL or R or Python. Instead, it’s about understanding some simple, basic, concepts, like “Having codes for things only works if everyone knows (and agrees on) what the codes they use mean”, or “Just because it’s in a computer doesn’t mean it’s usable data” - and, most importantly, “Data is only useful if the producers can produce it in a form the consumers can consume”, with the vital corollary “To make a data-driven process work, the producers and consumers need to talk to each other about their needs”.
Data literacy avoids wasted effort
In a data-literate organisation, anyone working with data in any respect is aware of these things, and more: that data is subject to regulations like GDPR and where to look up the details if you need them, that conversion between data formats can be hard so it’s a good idea to plan to avoid it, what sort of data is held where in the organisation, and who to ask to get access to it or to find out if some data you’re considering collecting is already being collected.
Data-literate organisations have conversations about important choices, because people are aware that they’re necessary - and because they are aware of the data landscape within the organisation, so know who to involve. People within them are aware of how data can be useful - so they don’t waste time on data without value, and ensure data is collected and handled in ways that let its value be realised. They know that producing a dashboard full of pretty charts is only useful if those charts actually mean something, and that the viewers understand that meaning, and that meaning is actually something useful to the viewers.
Spread data literacy by iteratively improving
These things can be learnt the hard way, through making mistakes and then clearing up after them. They are rarely taught in any courses (although we hope to impart some in our upcoming blog posts on data literacy!) But generally, most people learn them through absorbing them as part of a data-literate organisation’s culture: once they’ve seen how a data-literate organisation works and picked up the principles themselves, they carry that on through their career. The best way to spread data literacy in your organisation is through setting good examples - and making sure they get seen!
Data literacy is one key component to building data maturity. Explore our Building data maturity services for more options on how to maximise the value of your data in your organisation. Also see 6 Major barriers to data literacy for further reading on data literacy.
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