There is always a buzz topic in the world of data analytics and in the last few years ‘data literacy’ has been thrust into the spotlight. Specifically, “raising data literacy”.
‘What do we mean by data literacy and how do we raise it’ is tough to answer, as people will interpret this in different ways. A rather rudimental definition of ‘raising data literacy’ would probably suggest it’s the responsibility of ‘the analyst’ to build understanding of data and data outputs in everyone else.
In truth this probably isn’t an effective solution – and ‘raising data literacy’ doesn’t fall solely at the feet of those within data analytics teams. It is mutually beneficial all round for analysts and their service customers to have a shared understanding of data, and analytics, AND the priorities of the service.
So rather than a ‘teaching’ exercise one party does TO the other, we see ‘raising data literacy’ as something we all come together to realise. Whilst there is a role for analysts to play translating some complex concepts, it is also the analysts duty to understand services' needs, processes, and priorities. And from our service colleagues we expect a willingness to share their domain expertise, and an enthusiasm for finding out a bit more as to how data and analytics could help them achieve their business priorities.
What is Data Literacy?
It might clarify further if I break this down into 3 components that we are working through at Essex County Council and partners:
Data Literacy: What is data (see the four v’s of data), what data does the organisation hold, what other data is available, what is the quality of the data, where does it ‘live’ (note, data is very much ‘living’ in that it changes), how can I get it when I need it, what can ‘I’ do myself
Analytics Literacy: How do I interpret the data, what can I do with it (what is the art of the possible), what do statistical tests tell me, what is analytics, what is data science (and associated terms), how do I present data, how do I know my outputs are reliable
Organisational Literacy: What are the service priorities, what are we trying to change/do differently, what have we tried before, what are we currently doing, who are our customers and what do they want, what data/analysis are we currently using, what are the big issues that keep us up at night
*Its worth noting that data and analytics is only part of the evidence parcel. Research, commissioning expertise, lived experiences, subject matter expertise, all triangulate to inform service actions.
All of these 'literacy themes' are overlapping and the process is quite cyclical - but the shared ambition (of both the analyst and the decision makers) is to make ‘things’ better. This cause is helped and accelerated if there is senior buy-in, with the accompanying understanding of the value data and analytics can bring.
Why is it important we have this understanding?
Research from MIT suggests if just one board member is data literate it increased productivity / efficiency 11% and increased as more people are data literate.
88% of organisations with organisation-wide data literacy programmes exceed business goals (Deloitte, 2022)
There are many other facts and figures that illustrate how ‘greater data literacy’ results in better outcomes.
However, despite this clear indication of the importance, only 5% of organisations classify themselves as data literate (Data Camp, 2022), and 74% of employees (outside of data teams) feel overwhelmed or unhappy when working with data related tasks.
The title of this blog is deliberately provocative, as for a while it felt like everyone talked about the importance of data literacy at a very surface level without really doing anything about it.
Unfortunately it’s not something that is going to organically develop. Data and analytics can be quite daunting and complicated to wrap heads around, and the whole profession continues to move forward at an extremely rapid pace that makes it even trickier to keep up with.
So what have we done in Essex?
We have taken a couple of approaches, working both bottom-up and top-down.
Within the data analytics team we are spending more time ensuring we are involving our customers in the design of our work, and the entirety of our data project life cycle. We have also worked on communicating effectively with data and analytical outputs.
We’ve taken it upon ourselves to learn the service’s business priorities, strategies, and forward plans, but also the systems they use (such as case management systems from a front-end user perspective).
This is starting to reap the rewards. Investing a bit more time ensuring there is a shared understanding of what final outputs ‘should’ look like, massively increase the likelihood that customers have the confidence to take action from them.
From the top-down we have run various local sessions attempting to normalise analytical approaches and how they can support business priorities (you can read about many of them across our previous blogs) emphasizing the ‘value added’. We have attempted to plain English-afy abstract terms like ‘machine learning’, and ‘data lake’, and regularly strived to myth bust (such as “artificial intelligence doesn’t mean algorithms making decisions”)
The team have become well-versed on the data literacy theme – and were key note speakers at the government Data Science Festival earlier this year (with a ‘Freaky Friday’ body swap twist on the topic – how can the data analyst and commissioning lead see things from the others perspective).
And finally last week saw the launch of the Data Masterclass across Essex Public Services. The Data Masterclass is a six-week online programme designed by the Data Science Campus at the ONS, adapted for colleagues across Essex public sector organisations in collaboration with the Essex Centre for Data Analytics.
This is the first time that ONS has made the course content available to local government and wider public sector partners like Police, Fire and health organisations – and in our first iteration we have 40 senior leaders (data enthusiasts) participating. They’ll be hearing from industry experts such as the UKs national statistician Sir Professor Ian Diamond, Mathematician Professor Hannah Fry, and economist Sir Andrew Dilnot. All of whom discuss data and analytics in engaging and accessible ways. (Plus some Essex specific content and case studies from ourselves and partners)
This is incredibly exciting – I personally made sure I got myself involved in this programme. It’s looking increasingly unlikely that I will ever be in Take That, or play for Tottenham Hotspur, but I can say I was on the same billing as some of the UKs best analytical minds (albeit through unashamedly gate-crashing their data party!)