What is a data democracy, and how can your company build one?

What you’ll learn: 

Companies that have a data democracy — an organizational state in which employees have access to reusable data assets, the skills and motivation to use them, and strategic guidance — generate significantly higher returns from data monetization. New research reveals the specific connecting structures leaders need to build this environment and maximize the value of their data investments. 

Inaccessible or unused data does nothing for your organization. Yet, on average, only 28% of employees draw on reusable data assets, according to new research by Nick van der Meulen, Ida Someh, Barbara Wixom, and Cynthia Beath from the MIT Center for Information Systems Research. 

This is a costly failure: In companies where one-third or more of employees use data assets, data monetization accounts for 15% of total revenues. In organizations with less use, revenue from data monetization falls to under 5%.

The new research looks at the barriers to data reuse and methods for establishing a “data democracy.” 

What is a data democracy? 

A data democracy is an organizational state in which employees regularly and universally have access to data assets, along with the skills to exploit them, the motivation to engage with them, and guidance to use them strategically. 

Barriers to establishing a data democracy 

Understanding the potential barriers to creating a data democracy is the first step toward establishing one. In a research briefing, the researchers highlight four frictions that could be limiting data use: 

• Employees don’t always have easy access to data; without it, data assets “are merely sunk costs,” the researchers write.
• Employees don’t always have the skills, or data literacy, to exploit data in useful ways.
• Employees may not have the motivation to use data because there are no clear incentives or avenues for doing so.
• Employees sometimes lack strategic guidance about how data use can complement broader organizational strategies and help a company achieve its goals.

4 steps to overcoming challenges in establishing a data democracy 

1. Establish a baseline of data asset use. Before investing in new initiatives, leaders must understand how and in what ways data is currently being used. They should seek answers to questions like “What percentage of data is available to employees as reusable data assets?” and “What percentage of employees typically makes use of these assets?” 

2. Identify data asset use gaps. With a baseline of data usage established, leaders should diagnose the root cause of gaps, drawing on the four barriers described above. Can employees easily find and use data assets — that is, do they have access to data? If they have access, do they have the skills needed to solve problems with data? Do they have clear incentives to use data, and are employees above them in the organization leading by example? And is there explicit guidance around the strategic priorities of data use? Identifying which of these areas are inhibiting data use allows companies to focus resources on addressing the most significant barriers.

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3. Deploy connections as solutions. Once specific gaps have been identified, leaders should create internal connecting structures to help bridge those gaps. If data access is a challenge for employees, there are two structures that are particularly helpful: enterprise services, which give employees centrally managed access to data assets, and social networks, which facilitate peer-to-peer knowledge sharing that helps employees understand available data assets and how to use them. If a lack of skills is the primary barrier, large-scale data literacy training is a good start, but it should be complemented with cross-functional teams. This would allow business domain experts to learn contemporary data techniques while data experts gained a deeper understanding of a given business context.

If motivation is low, embedding experts within business units can give employees access to hands-on support and build their confidence; additionally, they should be offered clear incentives, and leadership should set an example of effective data use. Finally, the research points to centers of excellence as the critical connector for providing strategic guidance. A CoE coordinates strategy and provides clarity on how data fits into larger strategic plans — for instance, clearly tracing the benefits of data use to income statement line items. It’s worth noting that organizations that provide clear strategic guidance generate more than four times the share of revenue from data monetization — 17% versus 4% — than those that do not.

4. Measure and iterate. Track the impact of these interventions on the percentage of employees actively using data assets, as well as the financial return from data monetization initiatives. Use these insights to refine your approach and guide next actions.

These four steps are a start, the researchers note, and by taking them, leaders can close the costly gap between data asset availability and use. 

“The systematic design of a data democracy fosters an agile workforce of enabled and empowered experts — the engine that translates data assets into financial returns,” the researchers write. 

Read the research briefing: Mobilize Your Data Democracy 

Nick van der Meulen is a research scientist at the MIT Sloan Center for Information Systems Research. He conducts academic research that targets the challenges of senior-level executives, with a specific interest in how companies need to organize themselves differently in the face of continuous technological change. He teaches the MIT Sloan Executive Education course Digital Strategies for Transforming Your Business. 

Ida Someh is a research affiliate at MIT CISR and a senior lecturer in business information systems at the University of Queensland, Australia. Her research focuses on the organizational and societal impact of data, analytics, and artificial intelligence. 

Barbara Wixom is a principal research scientist at MIT CISR. Since 1994, her research has explored how organizations generate business value from data assets. Her methods include large-scale surveys, meta-analyses, lab experiments, and in-depth case studies. She teaches the MIT Sloan Executive Education course Data Monetization Strategy: Creating Value Through Data.

Cynthia Beath is an academic research fellow at MIT CISR and professor emerita at the University of Texas. Her research interests include organization redesign for the digital era, the management of data assets, and the organizational impacts of AI.