As Alex Roberts, Editor, DataIQ, has noted, “Data culture often sits hand in hand with data literacy as the two have a symbiotic relationship”. Many organisations are at the maturity stage when they must think beyond this, too: how can these definitions help to measure the two separately and strategically?
What are data literacy and data culture?
David Reed, Chief Knowledge Officer and Evangelist, DataIQ, states in his book Becoming Data Literate: “Data literacy is a mindset that makes sense of the organisation, its market and customers through the use of data, combined with behaviours that share data definitions, assets, language and ways of working.”
Zoom out further, and you begin to understand how literacy acts as a key component of culture.
Data culture refers to the extent to which an organisation has a thriving, collaborative data community and a data-first mindset across the business that impacts key business decisions.
Consequently, literacy and fluency levels belong to the person and is impacted by individual skills, experience and confidence and bleeds into personal mindset. Culture belongs to an entire organisation, capturing a collective and collaborative whole and speaking to the synergy between individuals.
Put simply, literacy is the individual mindset; culture is the organisation mindset.
Which comes first?
To create organisational change, one must approach the problem on an individual level first to consider what is going on in the mind of the individual within an organisation. This understanding manifests in language.
It is only logical to begin with the language piece; how can you understand and address levels of collaboration, innovation and trust if the practitioner or team do not understand what is on the table nor what is being discussed?
Understanding literacy and the pitfalls in certain areas can lead to some quick-wins and change-implementation that will help steer the focus onto a cultural ways-of-working piece. If this is done in the reverse, it is likely literacy will be the only focus area, and other key pain-points (for example, data transparency and a data-first mindset) will become overshadowed in talks of fluency, shared definitions and training academies.
For the full-bodied nuances of data culture to get the airtime they deserve, DataIQ suggest that literacy comes first, and once the individual mindset is driven by the right messages, the overall organisational community can be approached.
What is the evidence?
In recent DataIQ research, it was found that of all organisations who self-identified as having a “thriving community of data practitioners,” only one third believed they had suitable data literacy levels. These organisations would benefit from tailoring content and communication first and then recognising the impact this would have on the organisation’s commitment to data-first thinking.
Let us position it this way: how can a business leverage data-first thinking if it does not use a commonly understood language to drive decisions?
Outside of DataIQ, other research speaks to the impact of literacy and culture issues separately on organisational change and the role of the data leader.
The AWS CDO Agenda 2024 report, stated that “difficulty in changing organisational behaviours and attitudes” was the most frequently mentioned challenge for CDOs (70%).
This was followed by the “absence of data-driven culture or data-driven decision-making” (59%) and a “lack of data literacy or understanding” (50%) of respondents.
How do you measure literacy and culture?
At DataIQ, we offer two assessments for organisations to measure their data literacy levels and data culture levels.
In the Literacy for Teams assessment, DataIQ posit statements written from a pseudo-personal standpoint, such as “I trust our internal data sources” and “I know how to access the data I need.” Through investigating whether individuals in the organisation have good understanding of their own data capabilities, one can begin to surface the extent to which this understanding extends into the wider business.
In the Culture for Teams assessment, DataIQ use the ten dimensions as outlined in the DataIQ report The Ten Pain-Points of Culture. These questions are positioned from an organisational viewpoint: respondents are asked to rate their level of agreement with statements such as “the organisation regards data guidelines and regulations as foundational knowledge,” and “data informs our KPIs, objectives and key results.” This is in effort to move the respondent away from a siloed individual perspective and towards thinking as part of a whole business unit.
This is put into practice with our senior leaders, too. On our Advisory Board, there is a pillar devoted to the synergy between the two topics, so as not to miss how they work together. The Culture and Skills board sees our data experts discuss best-practice for movement towards evidence-based decision-making, while ensuring data is part of the vision and is valued as a strategic asset.
