Data literacy for the public sector: Lessons from early pioneers in the United States

The ever-changing data landscape

Advances in the access, collection, management, analysis, and use of data across public sector organizations substantially contributed to steady improvements in services, efficiency of operations, and effectiveness of government programs. The experience of citizens, beneficiaries, managers, and data experts is also evolving as data becomes pervasive and more seamlessly integrated within decision-making processes.

In order for agencies to effectively engage in the ever-changing data landscape, organizational data literacy capacity and program models can help ensure individuals across the workforce can read, write, and communicate with data in the context of their role. Data and analytics are no longer “just” for specialists, such as data engineers and data scientists; rather, data literacy is now increasingly recognized as a core workforce competency.

Fortunately, in the United States several pioneers have emerged in strategically advancing data literacy programs and activities at the organizational level, providing benefits to individuals in the public sector workforce. Pioneering programs are those that recognize data literacy as more than training. They view data literacy programs as a holistic set of activities to engage employees at all levels with data, develop employees with relevant skills, and enable scale of data literacy by augmenting employees’ skills with guided learning support and resources.

Agencies should begin by crafting the case for change. As is common with any emerging field, varying definitions and interpretations of “data literacy” are prevalent, which can affect program design. Being explicit in what problems are being solved for, as well as the needs and drivers to be addressed with a data literacy program or capacity, are vital to mitigate false starts. Looking across the 10 pioneers discussed in this report, key lessons emerged that are relevant for government agencies as they design data literacy capacity and programs:

• Engage senior leaders with clear roles and expectations

• Clarify target competencies and personas for actionable gap analysis

• Cultivate a common, shared language

• Improve data accessibility

• Align data governance and data literacy

• Encourage the use of data in decision-making

For organizations seeking to advance data literacy programs and build capacity, the lessons also suggest a series of actionable recommendations, including:

• Sponsorship. Agency heads should designate a chief data officer or other official to sponsor the data literacy program and allocate sufficient resources for the initiative, including to staff a program lead position, provide a program budget, support public-private partnerships, and to continually analyze staff needs as the program matures.

• Transparency. In support of the case for how data literacy supports agency goals, government executives should be more transparent and illustrative in how they use data with agency staff, and support identifying the data gaps through a learning agenda.

• Incentives. As agency data literacy programs mature, agencies should intentionally reinforce the cultural values of data- and evidence-informed decisions with incentives for the use of data in grants, regulations, and policy guidance.

The pioneers discussed in this report offer early lessons as other organizations also seek to improve capabilities for using data. Recognizing that program development is a learning process also means that no agency or organization should aspire for a perfect program at the outset; every program will change over time. What is essential is that every organization begins to build its capacity for using data and evidence—and that all starts with data literacy.