Making Data Work
for

HEALTH AND HUMAN SERVICES
Industry: Government & Healthcare | Headquarters: Washington, D.C. | Size: 80,000 employees

Organization Bio

The United States Department of Health & Human Services (HHS), also known as the Health Department, is a cabinet-level department of the U.S. federal government with the goal of protecting the health of all Americans and providing essential human services. Its motto is “Improving the health, safety, and well-being of America”.

“We have plenty of people who are subject-matter experts and eminent in their fields ofstudy, but it is not sustainable for us to rely on outsourced data science knowledge and skillsets. More importantly, it is hard for us to see the concrete opportunities (and the realities of addressing them) if we do not have a basic handle on data science, data architecture, and the state of the art.”

— Will Yang Director, HHS

The Challenge

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. They did not have cohesive communities around data sharing and problem solving. Emploees had an overwhelming amount of data to sortthrough and analyze. Employees were spending a lot of valuable time sorting through text data and proposals.

$500,000

Annual Costs Saved

16,000%

ROI

4

FTE's Freed Up

The Solution

In partnership with Data Society, the HH looked to launch an eight-week-long data science training program called CoLab. The goal was to build a community of practice around learning data science. The CoLab is a way to bring HHS employees together as skilled data scientists who continuously learned from each other and from their peers, while unlocking the full potential of the data they received.

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 experiences coders while others’ were beginners. Data Society implemented a customized data science bootcamp that 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. 

To ensure a relevant curriculum, Data Society customdesigned 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.

In addition to the trainings, Data Society’s teaching assistants and instructors provided additional support to help students successfully execute capstone projects that had direct applications to their work. Several capstone projects individually saved HHS over $500,000 per year in expenses.

The Results

The shared understanding of the principles of data-driven decision-making and data science algorithms allowed staff from different parts of HHS (i.e. the CDC, the NIH, etc.) to communicate effectively and built cross-departmental tools and capabilities.

  • The Python programming skills that staff learned increased efficiency and facilitated the development of new tools and solutions.
  • Students reported that the program advanced their skills, helped them identify new ways of analyzing data, and automate laborious processes.
  • The program resulted in millions of dollars in annual cost savings to HHS.
  • Subsequent installments of the program had over 450 applications for 30 spots

 

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