The U.S. Department of Health and Human Services (HHS) needed to increase data literacy across the organization so that employees at all levels of decision-making could harness the power of data to identify new insights, automate workflows, and increase the efficiency of the organization. In partnership with Data Society, the HHS launched an eight-week-long data science training program called the HHS CoLab.
The tailored data science boot camp included in-person, live-streaming, and on-demand training to help HHS students maximize learning at their own pace and in the format that works best for them. The CoLab brought HHS employees together to learn new data science techniques, collaborate with each other, and develop a capstone project that had a demonstrable impact on the Department.
The U.S. Department of Health and Human Services (HHS) needed to increase data literacy across the organization so that employees at all levels of decision-making could harness the power of data to identify new insights, automate workflows and increase the efficiency of the organization.
HHS wanted its staff to have more autonomy and independence to use data science to advance the institution.
HHS identified a few key issues that challenged the organization:
The first run of the program took 25 HHS employees from different areas of the agency, such as the National Institutes of Health and its Office of the Secretary. The students selected had a wide range of experience with data science – some were experienced coders while others were beginners.
To ensure a relevant curriculum, Data Society custom-designed a program focused on the exact skills and technologies that the HHS needed. Students were able to access a comprehensive suite of courses for staff ranging from entry-level analysts and non-technical managers to advanced data scientists.
Signature to most Data Society training, students were asked to complete capstone projects that had direct applications to their work.
Several capstone projects individually saved money for the U.S. Department of Health and Human Services, resulting in a savings of over $500,000 per year in expenses and incredible real-life applications that deliver recognized impact for constituents.
The shared understanding of the principles of data-driven decision-making and data science algorithms allowed staff from different parts of HHS (e.g., the CDC, the NIH, etc.) to communicate effectively and build cross-departmental tools and capabilities.