The technology industry, perhaps more than any other, overflows with hype and jargon. In our own area of data analytics, terms like data lakes, data mining or cluster computing are ubiquitous. Many of our customers say the overuse of these buzzwords creates so much confusion among senior leadership that it can derail important conversations about new technology or data strategy.
Simply ignoring the jargon is not an option. It means missing out on some the most exciting new technologies and strategies for managing a modern business. Instead, it’s essential we help people separate the signal from the noise and understand the terms that really matter, the kind that can shape an organisation’s approach for decades.
This is a perfect example of a buzzword, but it’s an approach that’s long been close to our hearts at Tableau. Perhaps the best definition of data democratisation I’ve seen comes from Bernard Marr, author of “Big data in practice”. He describes it as the creation of an environment where anybody can use data, at any time, to make decisions free from barriers to access or understanding.
We have been at the forefront of this concept for years. Data democratisation is an incredibly effective framework to describe a process which knits technology and procedure together, and ultimately delivers tangible benefits for a business and every one of its employees.
How organisations advance data democratisation depends largely on their choice of technology, but also who they let use it. In the past, insights could only be gleaned by data experts with advanced coding skills. Today, technology has unlocked access and eased understanding for everyone, irrespective of their specialist training or programming language skills.
Making technology more accessible and empowering to a wide range of people has been our focus for nearly two decades. We are constantly working to make visual analytics more intuitive and easier to use. Functionalities like drag-and-drop and the ability to go deeper into data with a simple click allow people to build confidence as they work with their data, organising and reorganising it into whatever shape grants them clarity, without the need for expert help.
Of course, accessibility is about far more than interface. Integrating machine learning and AI capabilities into data analytics solutions means systems are learning the intent of the user and the data they are trying to access. The technology behind inferring human meaning is hugely complex, but essential to help people who approach a problem from a unique viewpoint. We are seeing (and hearing) these intuitive leaps improve daily in consumer offerings like Siri and Alexa. This trend is beginning to permeate the corporate world.
A lot of this advancement has emerged as natural language processing (NLP) has been integrated more fully into designing solutions for how people interact with data. NLP, a sub-field of linguistics, data science and AI, has been around since the 1950s, but is today being deployed on ever larger scales to improve self-service data analytics.
These are just a few examples of how technology is giving people a voice, making it easier for them to interrogate data on their own. Grasping the power of new technology, however, is only half the battle for data democratisation.
No matter how intelligent, powerful or intuitive, technology alone cannot deliver the transformation most businesses want. Data democratisation acknowledges that lasting change means addressing the human factor. In a 2018 study, IDC analysts found organisations investing trillions of dollars in modernising their businesses. Nearly three quarters (70%) of these initiatives were failing due to prioritising technology investment without equivalent efforts towards building the culture necessary for success.
This isn’t to say the technology is the easy part to get right. It just emphasises the importance of a similar level of focus on culture.
Most businesses that have developed a sizeable data library have rational concerns about opening access across the business. When data can be influenced by inexperienced hands, it’s more vulnerable to corruption. Historically, the simplest solution was to lock all but the most expert users out. We might call this the time of data disenfranchisement.
Simon Beaumont, director for the global business intelligence centre of excellence at real estate services firm Jones Lang LaSalle (JLL), argues passionately against this approach. In a recent presentation about creating a data culture at JLL, he made it clear that businesses that fail to enable a data literate workforce end up with nothing but wasted potential and barely-seen data providing absolutely no value.
Companies that are getting value from their data - and Tableau customer JLL is just one example - are often those that have taken the time to build a culture of responsibility and respect for that data.
Several customers I’ve spoken to have found that the best place to start developing their own data culture is by establishing a benchmark. This means a thorough audit of all processes regarding data, identifying its custodians and gatekeepers, and a survey of the general level of data literacy among staff. This process is critical for identifying where education or hands-on experience is most lacking, and where attention and support would be of greatest help.
The next step is allowing your workforce the chance to explore data, with a safety net of continuous support and feedback. A common strategy among our most successful customers is creating an active and helpful internal community connecting novices and experts alike.
In these communities, data culture champions are crucial. These are the people who can articulate their enthusiasm, thinking process and approach to their peers. They are also the first to provide answers and guidance for more novice users experimenting with their dashboards.
When these champions come from a wide range of roles within the organisation, staff benefit from relatable examples and evidence of the power data fluency unleashes. Once employees can share and celebrate each other’s data insights, knowledge grows alongside an inventory of case studies which live on as ideal entry points for newcomers.
Nurturing a data culture across large and complex organisations is challenging, but offers tangible rewards. JLL reports that creating a data literate workforce has generated $50 million worth of documented benefits to the business over the last five years.
Another customer of ours, from the world of financial services, is on a multi-year journey of outreach and engagement with its staff, establishing a centre of excellence, and even created a new data community manager role. The result has been that thousands of digital workers are now able to self-service data analytics whenever they need it to make smarter business decisions.
This is data democratisation in action: the interplay of more accessible technology with a culture that values and celebrates best data practice, with no-one left out or left behind.
Organisations like ours will continue working to improve technology which makes data more accessible. We will also continue our efforts to encourage the culture that ensures technology provides real results.
James Eiloart is SVP EMEA at Tableau