The Data Directive: Why Public Sector Organizations Are Adopting a ‘Data Culture’

Data has become something of a buzzword in the public sector. That’s no surprise — with the advent of artificial intelligence and other emerging technologies, government agencies have more data at their disposal than ever before. As a result, they are looking for ways to use it effectively in order to manage their mission, make effective decisions, scale data-driven decision-making capabilities and bring about lasting change. 

Ultimately, better data management will require a culture shift across the public sector, and agency leaders today are beginning to embrace what’s become known as a “data culture.” 

According to a Tableau-sponsored report produced by IDC, a data culture is one that “encompasses values, behaviors, and attitudes of executives and employees that promote and enable use of relevant data as the driving force of decision making.”

Moreover, a data culture is less about the data itself and more about how agencies are effectively interpreting it. This type of data analysis helps organizations make smart, timely decisions that positively impact their employees and constituents. The adoption and implementation of effective data culture won’t happen overnight, but with the right resources, tools and policies, agencies will be well-positioned for future success.

Evaluating Data Maturity Agencywide 

Before any organization can drive an effective data strategy, they must evaluate their current successes and recognize areas for improvement. 

“To start, agencies might consider asking themselves, is data siloed?” said Rob Bohn, regional vice president  of public sector Strategic Business Development at Tableau. “Is it hard to see and understand data, is the data guarded by certain people within the organization or data access boarder?” 

Once they diagnose their data maturity, agencies can begin to embed it into their culture. 

Public Sector Leaps Toward Data Innovation 

The good news is the federal government has already taken steps to build more data-driven practices. In 2018, the Trump administration identified a new cross-agency priority to leverage data as a strategic asset. That initiative birthed what has now become the Federal Data Strategy, a call to action for agencies to leverage the full value of data to serve the public good, through “ethical governance, conscious design and a learning culture.” Other initiatives like the Open Data Policy encourage agencies to make data more transparent and accessible. 

“The amount of time and attention put toward data and data culture right now is really fantastic,” Bohn said. “The government is really focusing on collecting the data, protecting the data and organizing the data.” 

However, there are certainly opportunities for improvement. Some agencies haven’t yet cracked the code on how to successfully use, share or democratize that data. Bohn says agencies can overcome these challenges with modern data visualization tools. 

“That's when you'll start to see the outliers, the holes and/or the other data sets that you need to connect and use the data to drive the mission outcome, whether it's detecting fraud, waste and abuse, or increasing diversity and inclusion within an agency,” he explained. “These missions have specific data needs that you're not going to understand until you actually start to visualize and analyze the data.”  

Bohn has witnessed agencies spend somewhere between 80% and 90% of their time budgeted for data on collecting and governing that data — but only 10% of it actually analyzing and using the data. 

“I’d love to see that equation flipped,” he said. Effective decisions, Bohn explained, aren’t made with datasets alone; insights only become actionable once they have been thoroughly analyzed and understood in a broader context. 

Consider, for example, an Excel spreadsheet that lists the number of COVID-19 cases in the United States. These rows of data don’t tell much of a story on their own. But once that data is structured, understood and visualized, it becomes a useful tool for government leaders to make important and impactful decisions about everything from testing sites to reopening plans. 

Recipe for Successful Data Culture 

According to Srinivas Kosaraju, senior director of public sector solution engineering at Tableau, data culture can also be hard to define. 

“Everybody has a data culture,” he said. “The question is, what is that and how can you make it better?”

Tableau has created a framework to help organizations do just that. Having spent several years working with customers to improve their data strategy, the company identified five elements of a successful data culture: 

• Trust: Leaders trust their people and people trust the data.
• Commitment: People treat data as a strategic asset, and they fully commit to realizing the value of their data assets. 
• Talent: To effectively analyze data and use it to make better decisions, agencies must invest in their employees: a data culture, after all, is ultimately composed of ‘data people.’ 
• Sharing: Data requires collaboration: Most problems can’t be solved by one individual or team. They rely on collaborative teams to share ideas and insights with one another.
• Mindset: People prioritize data over intuition, anecdotes or rank. A shared, data-first mindset creates an environment where ideas lead to innovation and impact. 

Indeed, implementing this data culture may seem like an arduous feat. But more often than not, adopting a data culture doesn’t mean ditching the way things have always been done. Instead, agencies can build on progress already made. 

“Agencies should add data to whatever process they’re currently using to make decisions,” Kosaraju said. “The integration of data into current operations has the power to drive stronger and more effective business outcomes without requiring an entire process overhaul.” 

And, like any culture, data culture must start at the top. It’s up to agency leaders to take the first steps toward developing and implementing a data culture. 

“We’re seeing the role of the chief data officer change and evolve into not just a data officer, but a data and analytics officer: the CDAO. The CDAO is not only responsible for policy, but they're also in charge of centralizing tools, platforms and processes to maximize scale and reach. Ultimately this role is better positioned to support growth and engagement,” Kosaraju said. 

This new role increases emphasis on leveraging data for impact. It places the onus on organizations to prove they can use their data to make decisions. 

“Data stewardship is the foundation that allows all employees to access data, empowering them to explore and ask questions of the data so they can make better decisions,” Bohn said. “To get there, organizations need a clear and strong data strategy, backed and exemplified by leadership.” 

Be sure to check out other topics covered in this series:

• Thanks to Data Visualization, Federal Agencies Can Now Track and Mitigate the Spread of COVID-19
• Behind the Numbers: Amid Financial Uncertainty, Data Visualization Spurs Economic Recovery

Click here to find out how Tableau can help you implement a data culture at your agency.