Case Study: Florida Health’s Journey to Data Modernization

The Data Modernization Challenge

Florida’s Department of Health (Florida Health) exemplifies this modernization challenge. The agency manages 14,000 employees across Florida and its 67 counties, coordinating “all strategic planning, accreditation efforts, any health improvement planning, data monitoring, analysis, and performance management,” said Elmore.

From outbreak to vital record management, Florida Health serves as the cornerstone of public health protection for Floridians. As a data-rich organization, Florida Health wanted to modernize its effort, including constructing a new data lakehouse.

This technological upgrade would consolidate all organizational data into a unified view. However, to use these new analytics capabilities, Florida Health needed to prepare its workforce. The agency partnered with North Highland to “create a replicable framework for assessing the staff’s training needs and then deploying that training program,” explained Elmore.

Building a Data Culture Assessment Framework

Developing a comprehensive data culture assessment framework presents significant hurdles. To simplify the work, Elmore and her team used “existing methodologies at Florida Health, some industry standards, and expertise that North Highland created over time.” North Highland needed to synthesize this information to meet the “themes applicable to Florida Health,” said Elmore.

That meant juggling multiple components, such as personas, functions, and use cases. Elmore started with Florida Health’s definition of data literacy: the ability to effectively collect, understand, interpret, and communicate data to drive meaningful actions and decisions.

From this shared definition, Elmore developed an inventory of skills and competencies. She and her team conducted 10 interviews, created 22 focus groups, and completed a survey-based assessment of 5,000 people to understand data literacy requirements, use cases, and expectations.

North Highland’s work culminated in two reports: a skills assessment analysis and a gap analysis. With the help of Claude, a generative AI model, North Highland rapidly processed and interpreted large volumes of text, gaining valuable insights that would have taken longer to manually process.

Creating a Skills Inventory

Understanding the data literacy gaps at Florida Health required defining competencies, skills, and behaviors. Elmore mentioned that North Highland’s approach mirrored an earlier DGIQ + EDW presentation given by Julian Kirby, senior analyst at Canada’s Department of Fisheries and Oceans.

Through her analysis, Elmore identified six core competencies:

• Data management
• Data interpretation and visualization
• Security, privacy, and ethical data use
• Public health informatics
• Research methods and evaluation
• Advanced analytics

From there, North Highland constructed proficiency levels based on behaviors, skills, and technologies. Not everyone needed to be the most technical or strategic with their data operations. For example, executives do not necessarily need to know SQL to retrieve data, but they should understand how to set the foundation and direction. Given the diverse workforce, Elmore needed to find out what workers knew and what Florida Health expected them to know.

Understanding Expectations

Defining the workforce through personas – based on training needs, characteristics, and different behaviors – became central to North Highland’s approach. Elmore highlighted three personas:

• Data consumers: Analysts, data entry staff, and others who use data to find insights and make decisions
• Staff development functions: People who equip others with data skills
• Data providers: Backend infrastructure and database management

Once Elmore’s team developed the workforce personas, they dug into each of the layers. This process led to a massive spreadsheet that covered six competencies, three personas, 45 functions, and three departmental levels, a proficiency expectations matrix. This comprehensive mapping tool, combined with focus group insights, revealed significant findings. “Data was really important to people, and they were looking for guidance,” Elmore explained.

Elmore dug in further with survey questions, including a combination of self-assessments and knowledge-based questions that increased in complexity. The results painted a picture of executives’ strategic knowledge and whether they met expectations.

The Findings

The key findings revealed strengths and gaps, providing areas to target training. They concluded that Florida Health has a strong foundation, including:

• Executive buy-in and support
• Strategic capability that met expectations
• Highly engaged staff in data governance and training
• Minimal gaps in security, privacy, and ethics

Responses from interviews and focus groups identified “training and knowledge on existing data systems and practices” as a top priority. Staff and management strongly desired “more centralized systems and data” and experienced pain points from human error and manual processes. They were more comfortable with popular technologies like Excel, PowerPoint, and SurveyMonkey but less comfortable with advanced technologies.

Elmore’s team documented these insights in comprehensive assessment and gap analysis reports. These insights informed North Highland’s recommendations for Florida Health to successfully adopt its data lakehouse and advance data modernization efforts.

The Next Steps

After completing the assessment and gap report, Elmore recommended a three-pronged approach.

• A Training Roadmap:A targeted roadmap that closes the gaps mentioned in the report and provides guidance for departments to maintain their data literacy skills
• A foundational data literacy course:A course focusing on the baseline knowledge that each Florida Health worker needs to succeed in additional training and comply with data best practices
• An HR Toolkit: For a narrow set of data-driven positions, acollection of resources to use when recruiting, selecting, hiring, and managing Florida Health workers

North Highland developed these deliverables in parallel with Florida Health’s data lakehouse implementation.

By addressing both workforce culture and technology simultaneously, Florida Health positioned itself to maximize its data capabilities, enhancing its ability to protect Florida residents’ health and safety. Klann noted that the agency wanted to get the most value from its data modernization initiative. With its strong foundation, Florida Health was ready from day one.

The methodology developed by Elmore and Klann offered a replicable framework for DGIQ + EDW participants to take back to their organizations. Through their strategic approach – enhanced by AI tools like Claude for qualitative analysis – North Highland created a practical blueprint, enabling organizations to successfully modernize data technologies with their workforce.