HRStat

HRStat is a strategic human capital performance evaluation process that agencies use to identify, measure, and analyze human capital data to assess the impact of an agency's human capital management on its organizational results and improve human capital outcomes. See 5 CFR 250.202. It is a quarterly review process and key component of an agency's strategic planning and alignment and evaluation systems of the Human Capital Framework. Id. When effectively used, partnerships are cultivated between stakeholders within agencies who may not have previously partnered to develop, implement and monitor human capital strategies together.

Trends

The HCRs found that all agencies understand the importance and utility of HRStat and are committed to improving their HRStat programs and processes. This includes using HRStat reviews to communicate accomplishments, planned actions, and goals for identified priorities. Additionally, some agencies are strengthening their HRStat programs and processes by expanding outreach among their components. This fostered collaboration by keeping components apprised of what is discussed in the HRStat reviews and enabling them to take action.

Most agencies hold HRStat meetings quarterly, as required. However, some agencies meet more frequently and for more in-depth monitoring and discussion of progress on metrics. Meeting attendance varies but typically includes C-Suite executives, human capital program leads, and the Performance Improvement Officer.

92 percent of agencies hold HRStat meetings at least quarterly.
20 percent of agencies hold them monthly.

The HCOP, each agency's human capital implementation document, describes how an agency will execute the human capital elements stated within Agency Strategic Plan and Annual Performance Plan (APP). Intended as a dynamic document, the HCOP includes milestones, outcomes, and performance indicators. Agencies refer to their HCOPs often during the quarterly HRStat discussions to assess progress in meeting performance targets and mission goals and objectives.

Challenges

While agencies are making great strides in HRStat, some agencies struggle with allocating resources and retaining experienced staff who possess data analysis competencies and capabilities. Additionally, there is little evidence that agencies are using the results of the HRStat reviews to update and adjust their HCOP and APP. Updating the HCOP with strategies, milestones, and targets, informed by the outcomes of HRStat reviews, would help agencies make more accurate, effective, and evidence-based decisions based on timely data. Additionally, agencies should consider implementing an annual review of their HCOP to ensure strategies are in alignment with the goals and objectives included in the APP.

Most strategies within agency HCOPs include actions, targets, and metrics. However, agencies would benefit from the addition of enhanced, quantifiable metrics that are incorporated into dashboards. Quantifying metrics is important because it provides a way to measure and evaluate performance objectively. Pairing them with dashboards adds transparency and access to real-time data. Quantifiable metrics also make it easier to track and evaluate progress made over time, as well as compare against benchmarks and targets in support of mission accomplishment.

Data Governance

Trends

Most agencies have reported a significant increase in data analysis, data-driven conversations among leadership, and the use of dashboards and data visualizations. All CFO Act agencies have named a Human Capital Data Champion, most of whom attended the FY24 HCR conversations. Champions are senior level officials within agencies who drive the human capital data analytics function within their agency. They are responsible for ensuring quality agency data feeds to OPM and for driving appropriate agency utilization of OPM’s data services.

Many agencies have stood up a data analytics community of practice (CoP), or something similar, to share visualizations and analytics work they are doing across their organizations. This intentional collaboration and knowledge sharing has contributed to agency successes.  Data literacy is being weaved into dashboards, communities of practice, and leadership meetings. Some agencies seem to be quite advanced in their production of dashboards and tools to help leaders answer common operational questions and perform basic drill-down analysis.

Challenges

Unavailable, inaccurate, and contradictory data erodes trust among leaders and impedes the ability of an organization to understand its current environment or forecast into the future with confidence. The lack of complete and available data governance policies, guidance, and strategies have hindered improvement in data governance practices. Absence of data dictionaries to identify, apply, and manage digital policies, as well as legacy platforms, contribute to many of the challenges with data governance as agencies struggle with common data languages and opposing terminology. 

Additionally, agencies must overcome cultural challenges. Reluctance to provide transparency with human capital data among agency components is one example. The challenges associated with lack of transparency and trust across large agencies and departments are longstanding.

Solutions

In cases where agencies have built communities of practice to promote sharing, collaboration, and communication, agencies report experiencing fewer challenges and are building more trust and skill around data analytics. Some agencies are starting to name chief data officers for their components as a strategy to build a culture of data fluency and collaboration where it has not existed historically. OPM encourages agencies to continue working towards a mutual understanding of data dimensions and definitions to strengthen data governance and allocate space for data practitioners to collaborate as data infrastructure is developed. OPM also manages a data analytics community of practice with over 70 agencies participating, and hosted three educational sessions in 2024. The community of practice (also discussed separately in this report) promotes a common understanding of human capital data analytics tools and products.

Data Integration and Access

Trends

Data integration is a significant concern that surfaced in most HCR conversations. Interestingly, as we summarized the information agencies shared, it became clear that while agencies report nearly twice as many successes than challenges with data governance (a ratio of 2.3 to 1), the reverse is true with data integration. Overall, agencies report nearly twice as many challenges than successes – virtually the same ratio (1.7 to 1) – when it comes to integrating their data, highlighting the work yet to be done in the areas of data integration and access.

Agencies cite a lot of manual work in collecting data to respond to OPM data calls. Most agencies rely heavily on their shared service providers to obtain and collect the data they analyze. Interior Business Center (IBC) customers use IBC’s Oracle Analytic Service (OAS), previously referred to as Data Mart. DOT uses OAS directly as its analytic platform, whereas most agencies pull the data back in-house into a data warehouse. There they combine the data with other in-house data and analyze the results. National Finance Center customers also report they regularly pull data from the NFC platform and complete their analysis in-house.

Challenges

A contributing factor to data integration challenges is the fragmentation of in-house HR information technology (IT) ecosystems. These ecosystems have evolved over time as a set of “best of breed” systems for various functions. This has left agencies in the precarious position of pulling together data from various IT systems to answer seemingly straightforward questions.

Multiple agencies cited telework/remote work as an example that illustrates the challenges with data integration. Relevant data exists across core HR, timecard, and payroll systems. However, agencies must combine data from all three systems to answer questions about their workforce. The complexities and difficulty with integration increase for agencies with multiple systems for a single function, such as HHS that uses four different timecard systems. Some agency representatives, such as DOI, were quite proud of the skills they built to combine seemingly non-interoperable data sets and to “MacGyver” solutions.

Agencies are proud of the “MacGyver” strategies they have developed out of necessity to combine non-interoperable data sets.

In general, agencies are challenged by gathering disparate data from multiple systems. However, agencies do report growth and development in their ability to govern and display data once it is gathered for all systems/sources (or for agencies that have fewer collection sources). Overall, integrating data from all sources increases accuracy and positively impacts data driven decision making.

Data Competence

There is great variability in what agencies are doing to raise data literacy and competency levels. Examples include:

• webinars or forums where internal staff teach a skill,
• creating sets of data literacy courses to teach staff how to read and use data more effectively, and
• outsourcing or buying training from companies that offer general training in this discipline.

Multiple agencies discussed the need to educate users on specific aspects of data, such as definitions and timing and transfer schedules, so they can draw the right conclusions and not misinterpret what they are seeing in the data. There is an opportunity for agencies to cross-collaborate by sharing with each other more about what they are doing in this area.