Data Science: NIH Needs to Implement Key Workforce Planning Activities
Fast Facts
The National Institutes of Health—a leader in the support of biomedical research—faces a shortage of employees with data science expertise. NIH needs this expertise to handle the growing amount of increasingly complex data from advances in research.
NIH plans to enhance its data science workforce, but it hasn't examined the skills of existing staff to determine what it needs to reach its goals. Until NIH addresses this skills gap, it risks not having staff in place to administer tens of billions of dollars in annual research grants.
Our 11 recommendations address this and other issues.
Highlights
What GAO Found
While the National Institutes of Health (NIH) included a data science workforce goal in its June 2018 Strategic Plan for Data Science, the agency has not fully implemented the key workforce planning activities established by federal guidance (see table). For example, NIH developed and implemented plans to enhance its data science workforce; however, these plans were not linked to gaps in its data science workforce. Near the conclusion of GAO's review, officials said that an agency-wide Data Science Workforce Working Group had been established to address priority hiring and retention needs. However, they did not provide documentation supporting the group's activities. Fully addressing the workforce planning activities would help ensure that NIH has the data science workforce it needs to effectively meet its mission.
National Institutes of Health's Implementation of Key Activities for Data Science Workforce Planning
|
Key workforce planning practices and supporting activities |
Rating |
|---|---|
|
Set the strategic direction for workforce planning |
|
|
Establish and maintain a workforce planning process |
Partially implemented |
|
Develop competency and staffing requirements |
Partially implemented |
|
Analyze the workforce to identify skill gaps |
|
|
Reassess competency and staffing needs regularly |
Not implemented |
|
Determine gaps in competencies and staffing regularly |
Not implemented |
|
Develop and implement strategies to address skill gaps |
|
|
Develop strategies and plans to address gaps in competencies and staffing |
Partially implemented |
|
Implement activities that address gaps |
Partially implemented |
|
Monitor and report progress in addressing skill gaps |
|
|
Monitor the agency's progress in addressing competency and staffing gaps |
Not implemented |
|
Report to agency leadership on progress in addressing competency and staffing gaps |
Not implemented |
Legend: Fully implemented: NIH provided evidence that addressed the activity; partially implemented: NIH provided evidence that it had addressed some, but not all of the activity; not implemented: NIH did not provide evidence that it had addressed any of the activity.
Source: GAO analysis of NIH documentation. | GAO-23-105594
NIH's data management and sharing policy, effective January 2023, is consistent with relevant Office of Science and Technology Policy data sharing requirements. However, NIH had not finalized the guidance its staff needs to evaluate the data management and sharing plans and determine researchers' compliance with them. In addition, officials stated several times during the course of GAO's review that they had revised their time frames for doing so. The officials said they were delayed in completing the guidance because they were focused on informing the public about the new policy. They also anticipated releasing the guidance by June 2023 in time to assess the first round of plans. However, NIH did not document this new time frame. Documenting the new time frame and monitoring progress against it would ensure NIH's accountability for finalizing the guidance on time. In addition, until the agency finalizes and implements the guidance, its staff are less likely to consistently assess data sharing plans. This, in turn, would limit NIH's goal of maximizing appropriate sharing of scientific data generated from federally funded research.
Why GAO Did This Study
NIH, the federal government's leader in supporting biomedical research, faces a shortage of employees with data science expertise needed to, among other things, analyze and extract insights from increasingly large and complex sets of data. In June 2018, NIH developed a Strategic Plan for Data Science, which included an objective to enhance its data science workforce that addresses this need.
The explanatory statement accompanying the Further Consolidated Appropriations Act, 2020, contained a provision for GAO to review NIH's data science workforce planning. This report, among other things, determines the extent to which 1) NIH has conducted data science workforce strategic planning in accordance with key practices and 2) NIH's data management and sharing policy and guidance are consistent with federal guidance.
To do so, GAO assessed agency documentation against key workforce planning practices identified in prior GAO work. It also compared NIH's data management and sharing policy and plans to relevant federal requirements, and interviewed NIH officials.
Recommendations
GAO is making 11 recommendations to NIH to fully implement key workforce planning activities and finalize data management and sharing guidance. NIH concurred with nine of the recommendations and stated it had implemented the other two. However, the agency did not provide sufficient evidence of the implementation. As a result, GAO continues to believe the recommendations are appropriate.
Recommendations for Executive Action
| Agency Affected | Recommendation | Status |
|---|---|---|
| National Institutes of Health | The NIH Director should ensure that NIH establishes a comprehensive data science workforce planning process that addresses the shortfalls noted in this report. (Recommendation 1) |
In December 2023, NIH stated that its working group of senior mission support personnel and data science subject matter experts was addressing this recommendation. The agency stated it would provide a status of the group's efforts in June 2024.
|
| National Institutes of Health | The NIH Director should ensure that NIH develops staffing requirements for the data science workforce. (Recommendation 2) |
In December 2023, NIH stated that its working group of senior mission support personnel and data science subject matter experts was addressing this recommendation. The agency stated it would provide a status of the group's efforts in June 2024.
|
| National Institutes of Health | The NIH Director should ensure that NIH reassesses its data science competency and staffing needs periodically. (Recommendation 3) |
In December 2023, NIH stated that its working group of senior mission support personnel and data science subject matter experts was addressing this recommendation. The agency stated it would provide a status of the group's efforts in June 2024.
|
| National Institutes of Health | The NIH Director should ensure that NIH analyzes its workforce to identify gaps in data science competencies and staffing. (Recommendation 4) |
In December 2023, NIH stated that it had created a Data Science Workforce Working Group composed of data science experts and human resource professionals to implement its data science workforce efforts. The agency stated that a subgroup charged with addressing organizational factors had begun an analysis of the data science workforce to include metrics that would identify workforce gaps. NIH stated that the analysis would recommend strategies to identify workforce gaps in training and development, competencies, recruitment, and succession planning opportunities. NIH also stated that the subgroup was creating a change management plan to address workforce gaps including the need for an NIH-wide data science workforce strategy, defining, and communicating career path opportunities, better shared infrastructure and tools to support cross-NIH collaboration, and communicating new strategies for recruiting data scientists. We will continue to monitor NIH's efforts to address the recommendation.
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| National Institutes of Health | The NIH Director should ensure that NIH develops specific strategies and plans to address identified gaps in data science competencies and staffing. (Recommendation 5) |
In December 2023, NIH reported actions it had taken and others it was planning to take to enhance its data science workforce. For example, in July 2023, NIH released a new Hiring Paths, Recruitment, & Incentives Playbook for hiring managers and human resource liaisons. The playbook outlines the numerous hiring paths (i.e., legal authorities), recruitment strategies, and incentives available at NIH. In addition, the agency issued a new GS-1560 (i.e., data scientist) standard position description and job analysis that can be used by hiring managers and human resource liaisons. NIH also launched the use of the OPM Agency Talent Portal to hiring managers and human resource liaisons. According to NIH, the tool offers targeted recruitment services and provides the ability to find talented data science personnel and invite them to apply to vacant jobs. NIH also stated that it plans to, among other things, build a data science workforce SharePoint site that houses sample position descriptions, job analyses, recruitment/outreach strategies, workforce planning and training guides, and other related information to help meet data science workforce needs. NIH's strategies and plans, however, are not linked to gaps in competencies and staffing because the agency is still working to identify these gaps. We will continue to monitor NIH's efforts to implement the recommendation.
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| National Institutes of Health | The NIH Director should ensure that NIH implements strategies and plans to address identified gaps in data science competencies and staffing. (Recommendation 6) |
In December 2023, NIH reported actions it had taken and others it was planning to take to enhance its data science workforce. For example, in July 2023, NIH released a new Hiring Paths, Recruitment, & Incentives Playbook for hiring managers and human resource liaisons. The playbook outlines the numerous hiring paths (i.e., legal authorities), recruitment strategies, and incentives available at NIH. In addition, the agency issued a new GS-1560 (i.e., data scientist) standard position description and job analysis that can be used by hiring managers and human resource liaisons. NIH also launched the use of the OPM Agency Talent Portal to hiring managers and human resource liaisons. According to NIH, the tool offers targeted recruitment services and provides the ability to find talented data science personnel and invite them to apply to vacant jobs. NIH also stated that it plans to, among other things, build a data science workforce SharePoint site that houses sample position descriptions, job analyses, recruitment/outreach strategies, workforce planning and training guides, and other related information to help meet data science workforce needs. NIH's strategies and plans, however, are not linked to gaps in competencies and staffing because the agency is still working to identify these gaps. We will continue to monitor NIH's efforts to implement the recommendation.
|
| National Institutes of Health | The NIH Director should ensure that NIH develops and tracks metrics to monitor the agency's progress in addressing data science competency and staffing gaps. (Recommendation 7) |
In December 2023, NIH stated that its working group of senior mission support personnel and data science subject matter experts was addressing this recommendation. The agency stated it would provide a status of the group's efforts in June 2024.
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| National Institutes of Health | The NIH Director should ensure that NIH develops a process to track data science staff. (Recommendation 8) |
In December 2023, NIH told us it that it had performed a data call showing that the agency had 1,096 employees performing data science or data science related duties in over 40 different occupational series. Based on this analysis, NIH determined that the ideal solution to tracking data science staff would be to conduct yearly data calls to all institutes, centers, and offices (ICOs) on current data science employees and pending vacancies. The agency provided evidence of the Workforce Analytics Workbench dashboard it had created to help ICOs analyze and forecast for the future of their workforce. The tool is intended to assist ICOs in tracking and workforce planning for their data science staff and includes filtering capabilities, retirement projections, turnover, accessions and separation trends, and machine learning predictions of turnover risk. NIH provided screenshots showing the tool's features and several analyses of data science and related workforce staff. The agency also provided an August 2023 memo that was sent out to the ICOs for the initial request for information on the current data science workforce and projected needs as well a February 2024 email announcing a data call for the Spring of 2024. By developing a process to track its data science staff, NIH has increased its ability to determine whether it is meeting its goal to acquire the workforce it needs to effectively meet its mission.
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| National Institutes of Health | The NIH Director should ensure that NIH requires reporting to agency leadership on progress made in addressing data science competency and staffing gaps. (Recommendation 9) |
In December 2023, NIH stated that its working group of senior mission support personnel and data science subject matter experts was addressing this recommendation. The agency stated it would provide a status of the group's efforts in June 2024.
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| National Institutes of Health | The NIH Director should ensure that NIH documents new time frames to complete the guidance its staff will need to assess data management and sharing plans, and ensure that the guidance is implemented. (Recommendation 10) |
We reported that NIH had delayed its plans for issuing its guidance for staff to implement the Data Management and Sharing Policy (DMS Policy) several times since July 2021. In February 2023, NIH issued the guidance, along with an associated list of checklist questions that program and grants management officials must complete to assess compliance with the DMS Policy, and an optional decision support tool for NIH program staff. In December 2023, NIH stated that these resources were being continually revised to ensure they are timely and clearly communicate to staff their responsibilities in implementing the DMS Policy. NIH also stated it was in the process of implementing the DMS Policy in the Research Performance Progress Report, with a target completion date of May 2024. The agency noted that it would then update the associated, non-competing checklists to implement the DMS and genomic data sharing policy compliance for continuation awards. We will continue to monitor the status of NIH's actions to address this recommendation.
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| National Institutes of Health | The NIH Director should ensure that NIH documents new time frames to complete the guidance its staff will need to determine researchers' compliance with their data management and sharing plans, and ensure that the guidance is implemented. (Recommendation 11) |
We reported that NIH had delayed its plans for issuing its guidance for staff to implement the Data Management and Sharing Policy (DMS Policy) several times since July 2021. In February 2023, NIH issued the guidance, along with an associated list of checklist questions that program and grants management officials must complete to assess compliance with the DMS Policy, and an optional decision support tool for NIH program staff. In December 2023, NIH stated that these resources were being continually revised to ensure they are timely and clearly communicate to staff their responsibilities in implementing the DMS Policy. NIH also stated it was in the process of implementing the DMS Policy in the Research Performance Progress Report, with a target completion date of May 2024. The agency noted that it would then update the associated, non-competing checklists to implement the DMS and genomic data sharing policy compliance for continuation awards. We will continue to monitor the status of NIH's actions to address this recommendation.
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