ABSTRACT: Data democratization is the buzzword to describe empowering people with data. What’s getting in the way of achieving data democratization?

For decades we’ve tried to empower enterprise stakeholders with data to spot problems and opportunities and make better decisions about how to respond. Data democratization is the latest buzzword to describe this elusive goal. While there have been advances in data management, governance, and analytics, something keeps getting in the way of achieving data democratization. 

The solutions that data industry vendors and analysts often propose are about technical components and approaches, such as data platforms, architectures, formats, programming languages, and now generative AI. This makes sense because we need new technical approaches to address the massive scale and complexity of modern data. But technical solutions, while necessary, are not sufficient. 

The Human Factor 

One constant barrier to data democratization receives far less attention, the human factor. Thomas Jefferson wrote about the human factor in fostering political democracy:

“Whenever the people are well-informed, they can be trusted with their own government.”

Jefferson said that for democracy to work, the citizenry must have a basic level of education and be well-informed on the issues of the day. The same is true of a data democracy. For data to empower people, people must understand how to use it. They must know the conclusions they can draw from it, the suppositions it does not support, and most importantly, how to care for data to protect its quality and secure it from theft and misuse. 

Data Ownership

But getting people to accept responsibility for data is an ongoing struggle. In 2023, we’re still talking about who owns data—the same conversation we were having in 2013, 2003, and 1993. We can thank data mesh for the current focus on this question. Its core principle of domain ownership of data calls for the business units that generate operational data and the technology teams that support them to take responsibility for their data’s quality, availability, security, and documentation. 

In my experience, business stakeholders and software teams resist owning their data because they don’t know how. Many of them are not well-informed about using or caring for data. People in these roles at companies large and small, cloud-native and legacy-bound, have told me that data is not their job. It’s someone else’s problem. A data democracy cannot thrive in such an environment regardless of how much technology we throw at the problem.

Many people have told me that data is not their job. It’s someone else’s problem.

If business domains can’t or won’t own their data, then who does? That responsibility most often falls to the information technology (IT) department, not because they want it, but because no one else will do it. Funneling data ownership responsibilities and tasks to one team generates a never-ending backlog. This creates the canard that IT is the bottleneck to data. If so, it’s only because others have forfeited their responsibilities.

If people think IT is the problem, then they also believe that technology is the solution. And so we find ourselves in an unrelenting cycle of implementing new data technologies, architectures, and tools while trying to keep these changes from impacting the people who need data to run the business. 

Cultural Leadership

The data age that we’re learning to live in represents a societal change that impacts everyone. From the C-suite of global corporations to my 92-year-old mother who’s regularly targeted by identity thieves, we all must assimilate some basic knowledge about data and take responsibility for being well-informed data citizens. 

For most organizations, and society in general, this amounts to a big cultural change. Cultural change is hard and takes time. Thomas Jefferson faced a similar challenge with his democracy startup. In the early 19th century American society didn’t require workers who could read and write and do simple arithmetic. Jefferson foresaw both the economic and political need for citizens to receive a basic education. He said “An enlightened citizenry is indispensable for the proper functioning of a republic. Self-government is not possible unless the citizens are educated sufficiently to enable them to exercise oversight”.

Jefferson’s example illustrates a truth we now hold to be self-evident, that culture change starts at the top. Leaders must express clear values as to data’s critical importance to the organization. They must ensure that employees understand what living by those values every day looks like. They must make adhering to these data values a key part of performance expectations and they must model the expected behaviors themselves.

Living by data values must be a key part of performance expectations, and leaders must model new behaviors themselves.

Leaders must also provide the education, time, and opportunity for their people to assimilate new knowledge, skills, and responsibilities. Data literacy programs are an essential part of managing the data age’s cultural change. If you want to find out more about data literacy, check out my colleague Dave Wells’s ebook Building a Data Literacy Program: What, Why, and How. However, data literacy by itself is not enough. Without a change of mindset driven by senior leadership, the knowledge a literacy program imparts won’t take root.  

Let’s face it. The goal posts have moved. What it means to be a competent adult has changed. It happens with every societal transition, as it did going from the agrarian age to the industrial age. There are some new must-have skills we all need to acquire, each to our own ability, to survive and thrive in the data age. If we want data democratization, then we have to accept the responsibilities of data citizenship.