There’s real value in undertaking data democratisation, but it’s dependent on output. Raw, surface-level data can only reveal so much – no matter what pair of hands it’s placed in. Data needs to be aggregated, explored and manipulated to yield practical insights. We call this process analytics democratisation and, when done right, it can be transformative for businesses across a range of industries.
However, even when businesses are on board with data democratisation and understand its necessity, they can struggle to take it a step further with analytics democratisation. Let’s explore some common reasons why and what can be done.
Taking a progressive view of data governance
IT and data teams have traditionally been the central gatekeepers of company data, acting as approvers or blockers of any use of this data. Management teams can declare this model of governance as outdated in an embrace of democratisation – but they need to walk the walk. They must make a serious commitment to analytics democratisation, and this starts with designating a data leader internally to ensure governance is modernised and moving in the right direction.
There’s a common and easily understood view that data democratisation and governance stand at odds with each other. Greater use of data, so the logic goes, means greater risk of data misuse. However, this overlooks what effective governance can do. It can serve as the bigger picture to scale access to data responsibly without additional risk. It does so by granting the appropriate permissions so that all business users can work with the data they need to while keeping safe, and places an emphasis on data quality and regulatory standing.
A designated leader for analytics democratisation (ideally a Chief Data and Analytics Officer (CDAO) should be empowered to drive this meaningful change. It could be through establishing frameworks for internal data ownership or centralising data and analytics with function to break down siloes and maintain data as a shared resource. They’re the steps that will accelerate the time to scale analytics in an enterprise and achieve a ROI from data democratisation. This is exactly what data governance should be doing in 2024 – serving the purpose of enablement and unlocking value through the effective governing of new technologies.
To facilitate this shift, technology is key. Data and IT teams require a platform view of what users are doing with data with clear data lineage. This view needs to scale so that as many business users as required can work with data in a governed, controlled environment without facing blockers.
Kissing goodbye to the bandwidth trade-off
Analytics has always been characterised by bandwidth trade-offs. IT and analytics teams have a finite amount of bandwidth to help other teams with data insights and building analytics. On top of this, data and IT practitioners won’t typically be the specialists in the business domains they’re pulling data or a dashboard for, such as procurement, supply chain management or finance.
A simple push for data democratisation doesn’t necessarily remedy this. It needs to be followed up with analytics democratisation – specifically, self-service analytics. These intuitive, code-free, and code-friendly tools are designed to give everyday business users the ability to dig into their data and derive insights without specialist technical knowledge.
There are various self-serve analytics tools out there, and businesses must seek out a solution that reflects their internal capabilities. Ease of use is a must but it’s also important to factor in the tool’s compatibility with existing data infrastructure and applications, as well as support for future analytics needs. For many, that will be increased integration of non-structured data using technologies such as generative AI.
So, we have the right tool to facilitate analytics democratisation and governance is no longer holding that process back. There’s still one more potential blocker to analytics democratisation – a lack of data literacy.
The learning process
While self-serve analytics tools are easy to use, they don’t render analytics totally self-explanatory. Training that drives home the best ways to analyse and communicate with data will lead to better outputs. It’s going to result in business users using self-service analytics tools as intended – acting on data within a business context to optimise business outcomes. This is a boon for overall business performance. According to The Data Literacy Project, improving data literacy leads to an increase in enterprise value of $320 to $534 million over organizations with lower data literacy.
It’s not just a matter of rolling out training – it’s also about getting delivery right. Many companies will offer employees two hours of training covering how to build graphs and charts using a new analytics tool. What would be better is an hour of training and an hour of education that explains core concepts of creating best-in-class visualizations. Otherwise you will likely have trained people and they will build numerous dashboards that are awful.
And then, post-training, a continual commitment to upskilling can be carried out. It could be hosting regular hackathon competitions, giving employees access to interactive on-demand learning resources or standing up a centre of excellence to continually drive improvements and optimised analytics across departments. Whatever the measure, the important thing is that technology is always supplemented with training and education so there is a systemic approach to fostering employees’ analytics journey.
The added benefit of providing education to go with training is that it will provide the foundation of data literacy so that organisations don’t have a rose-tinted view of new technologies like genAI. They’ll recognise that it’s not a silver bullet, instead seeing what it’s good at and bad at, just like any other technology in the analytics toolbox.
Becoming a world-class data-led company
Proponents and evangelists speak of the huge benefits that are there for the taking from data democratisation. In truth, it’s seeing things through to analytics democratisation that’s going to unlock these benefits and drive real ROI from data democratisation principles. Progressive governance and self-service tools on a bedrock of data literacy amount to a winning ticket to becoming a world-class data-led company that leaves the competition in the dust.
Alan Jacobson
Alan Jacobson is Chief Data and Analytics Officer at Alteryx.
