Data literacy: the drive to educate the public sector workforce
Connecting state and local government leaders
As data-based decision-making becomes ever more important, data academies begin to blossom in local government.
There are certain positions in state and local government that everyone recognizes as essential to the successful use of data. They’re the obvious ones: data analysts, data scientists and experts in privacy and ethics. Those roles are hard to fill, but even when they are, there’s still a missing link. Michelle Littlefield, the chief data officer for the city and county of San Francisco, refers to this link as “upskilling the workforce.”
Increasingly, the idea of data training for all workers is beginning to take hold. “Data is everyone’s job.,” says Melissa Schigoda, director of the Bloomberg Philanthropies City Data Alliance at the Bloomberg Center for Government Excellence. “It can’t be an isolated centralized team that’s doing the data and no one else. It really takes the whole organization.”
Understanding the power of data is not just with your data analytics people. “Everybody has to understand, at some level, the importance of data,” says Rita Reynolds, chief information officer for the National Association of Counties.
Leaders in San Francisco have understood this reality for a while. The city runs a Data Academy that is available to all its staff. The initiative was temporarily put on hold during the pandemic when resources were diverted, but this year it was relaunched with 11 courses.
The most in demand courses include Intro to Power BI, a tool that guides users in data visualization; Leveraging the City’s Open Data; and courses about geographic information systems and coding for data analysis. Most of the coursework is offered live virtually, with office hours so that staff can follow up on what they don’t understand.
“My long-term goal is to identify coursework and platforms that can help us push forward and become more data fluent as an organization,” Littlefield says. “The bottom-line priority for me and for San Francisco is that we learn how to leverage the data that we have in the best way possible to make the best decisions.”
The Baltimore Data Academy
Across the country on the other coast, Baltimore this year launched its own data academy. The idea grew out of its mayor’s work with the City Data Alliance.
Since early 2022, the alliance has worked with more than 40 U.S and Latin American cities whose mayors are committed to building data capacity with a focus on governance, use, transparency and increased staff data literacy.
One of those leaders is Baltimore Mayor Brandon Scott, who took office in December 2020 with a commitment to building the city’s data capacity. With its long-standing and well-known CityStat system, Baltimore has often been cited as a leader in the use of data. But like all governments, it has struggled with data quality problems and a lack of staff buy-in.
Rudy de Leon Dinglas, now director of planning and operations at the Bloomberg Center for Government Excellence, recalls his own experience as the outcomes and evaluation manager at the Baltimore Fire Department between 2015 and 2019. The toughest part of the job, he says, was winning the trust of firefighters and paramedics who were out in the early morning hours responding to emergencies, with often limited understanding of why it was important for them to carefully record their activities.
“They were running calls left and right and they didn’t realize that the data they had to enter at 3 a.m. could lead to changes that would lighten their load and improve services to Baltimore residents,” he says. “But if they didn’t put good information in, I wasn’t going to get good information out.”
Fast forward to early 2023 and the establishment of the Baltimore Data Academy, which the city put together with the Baltimore-based center at Johns Hopkins University. In a July episode of the podcast “Data Points,” Baltimore’s Chief Data Officer Justin Elszasz explained that the academy was designed to reach employees at all levels. The goal has been to help employees see how data plays a role in their day-to-day work lives and “understand why data quality is important, why we track certain things the way we track them,” he said.
The academy has plans to build on its initial offering, the Foundations of Data Literacy course. It has added a course targeted at individuals who work with spreadsheets to help them better understand how to tease out insights and use the information before them to drive decisions. And future courses will be geared to managers and supervisors. The online, learn-at-your-own-pace curriculum was developed based on listening to employees to evaluate and hear what they needed to better work with data and understand where gaps in data knowledge occur.
As other cities begin to consider how to communicate data information through the workforce, a key component is an assessment of where employees are with regard to data and what kinds of instructions are most needed. It’s important, says Schigoda, to think about “how you’re assessing your data workforce, so you know where to focus your trainings. By constantly assessing how you’re doing, you can really target your limited resources.”
Barriers and Solutions
For all governments, one of the top challenges to developing greater data literacy is having the time and resources to focus employee and employer attention, especially when organizations are short-staffed and training time must compete with service delivery.
One challenge to pushing data training across an organization is communicating to individuals why the training is needed in the first place. This is particularly problematic if they are leery of an expansion of job responsibilities and dubious about their own technological ability. “We who understand data have to bring it down to a lower level,” says Reynolds.
Employees must see that this training pays off for them personally, which may not be immediately obvious. In Baltimore, Elszasz emphasizes the importance of making the Data Academy courses part of the city’s learning management system, with employees who successfully complete a course getting credit for that in their personnel files—helping to signal to their supervisors or managers that they may be ready for a promotion or a raise.
Reynolds notes that data literacy training should be included when employees are onboarded. “New employees are coming in that never worked in government and have no idea,” says Reynolds. “You need to be literate on the regulations you have to follow.” The key, she says, “is emphasizing education about the importance of consistent and shareable data, data protection and knowing what data is needed.”
Also, while there are many training materials available, there are fewer targeted to frontline employees. “I think that’s where [the Center for Government Excellence] has a really unique role to play in translating data skills and making them applicable to what people are experiencing every day,” says Schigoda.
Perhaps most important of all is getting buy-in from a community’s leaders. When there isn’t support from the top, the resources necessary are unlikely to be available.
The Emergence of Generative AI
Reynolds believes that generative AI will likely introduce a whole set of new reasons to emphasize data training for all government employees.
Pilot projects are creating private generative AI chatbots that can sweep up and deliver information to staffers in a closed setting, whether it’s for a single agency or a larger organization or government, such as a county. That idea would potentially deliver a wide array of information to staffers, creating “a drastic change in who can have access to data,” says Reynolds.
And that, in turn, means that generative AI will increase the need for employees at all levels to know how to protect their own data, to fully understand privacy rules and to be able to distinguish credible information from misinformation. While this tool will greatly increase the ability for staffers to understand policies and pull out answers to research questions, they would also need to know how to question the answers they get, and how to spot bias embedded in generative AI algorithms.
It's clear that generative AI is just one more solid reason why data literacy is so important. As data becomes the language of government, “being technologically literate is just as important as being able to read and write,” Schigoda says.
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