Data Literacy and Culture
“As the volume of data at our fingertips increases, so too does the value that can be derived from that data and the importance of the insights that can be generated. While many organisations are using technologies that can help to make the most of this data, they’re often held back by the data literacy of the organisation and the culture landscape regarding data.
What I’m going to do in this blog today is talk about some of the common barriers that are holding organisations back from becoming more data literate and how some of these challenges can be approached to help you work more efficiently and effectively. While this blog itself is going to be a high-level discussion around each of the topics, future posts will address each of the challenges in more depth, and look at various ways to overcome them.
Before I do so, it’s important to stress why data literacy is important. Ultimately in my view you can put the right solutions in place to present data, but unless people actively engage with that data and understand what it means (or the outcomes it can drive), it’s unlikely to unlock the true potential of your data.
The importance of a company’s culture
One of the key areas is company culture. Do you have a culture that is designed to support data literacy? Do you have executive buy-in to help drive greater data literacy? Is there a desire to empower individuals to make their own decisions?
The development of a culture that embraces data literacy often starts at the top – getting senior exec buy-in to help drive this culture within the wider organisation. But why is it important to get senior leadership buy in?
Its importance comes down to how decisions are often made within an organisation. If there’s a highly centralised decision making culture, then no matter how much the employees understand the data and how insightful their decisions are, the benefits from this data are vastly reduced if they don’t have the authority to use the data and make informed decisions leveraging their expertise.
I’m not advocating allowing people to make every decision without oversight. However, what I do advocate is freeing up the exec to make more strategic decisions, while also leveraging the expertise of the relevant teams to make decisions based upon data. This can be combined with their own local knowledge to help drive really effective outcomes
Understanding and improving your technology journey to unlock value
Another element is technology. While culture may inhibit the effectiveness of the technology implemented, it is also important to consider how you bring data together. How do you make sure the data is accurately modelled? Following on from that, how do you visualise it in a way which is intuitive for end users or stakeholders to interrogate?
To do this it’s important to understand where the important data currently sits. Is it in single data repository? Does it sit across numerous LOB systems, or is it potentially even managed within excel spreadsheets? There’s no wrong answer to this question, but it helps you understand what the next step or stage in your technology journey is.
Is it visualising the data better via the likes of Power BI? Is it consolidating a few key data sources using platforms such as Azure? Is it bringing in some more advanced modelling or data cleansing?
It’s all part of the journey, and in general what I would say is no matter which element you’re considering, do so in a phased approach. Work with the key stakeholders to define the data sources or challenges that will unlock the greatest value quickest.
Once the value of the solution has been proved, look to broaden it out in a number of sprints incorporating the next most valuable aspect. This way you can ensure that value is unlocked throughout the project, rather than waiting 12 / 18 months for a whole centralised enterprise data warehouse with accurate modelling and numerous reports to go live at the same time. This both unlocks value quicker, but also allows flexibility in how the process evolves and what areas are incorporated next.
Growing your organisation’s data skills
The third and final more common blocker is data skills and expertise, and how organisations can help upskill current members of staff with new and potentially unfamiliar technologies.
The great thing about this is that while it does present a challenge, it also presents an opportunity. You can not only help improve the effectiveness of your organisation, but also increase the capabilities and skills of your in house teams – be that in data science, data engineering, data visualisation, or even cloud platform management.
It’s also not as costly as you may think. I’d always recommend leveraging the free resources which are available to you – whether that’s via Microsoft Learn, blogs or videos i.e. our Unlock the Potential of Your Data with Microsoft Power BI webinar series. Take advantage of these as much as possible or potentially (if you’re eligible for the Azure Migrate Programme) leverage the Enterprise Skills Initiative to benefit from the free instructor-led training that it provides.
However, if you do want more tailored training, you could also reach out to an experienced data partner to help deliver some bespoke in person training to help empower your staff. Even better, if you are getting a partner to support your deployment, you can ensure that knowledge transfer and enablement is built into the deliverables. This will ensure that the project is as successful as possible in the long term.
Whilst I’ve touched on a lot of these concepts and areas at a high level, I will follow up with more in depth blogs on each of these in the future. However if you can’t wait until then and would like to learn more about how to improve data literacy and create a more data driven culture, please feel free to reach out to [email protected] or call 01904 562200.”
A blog by Ben Gannon – Data and Ai Specialist, Phoenix Software