Federal agencies have already begun the necessary work toward digital government transformation, challenging employees to change how the government uses technology, processes data, and serves the public. General Services Administration's (GSA) Technology Services division’s “10x” program crowdsources federal employees' ideas and selects projects to fund, develop, and ideally scale. The 250 submissions to the program demonstrate the significant desire of current federal employees to create solutions for rebuilding public trust, protecting the environment, and promoting equity, all of which are priorities for the GSA and Biden administration.
Data Society works extensively with federal agencies and commercial enterprises to do just that. Signature training programs, tailored to specific job functions, are customized to deliver desired outputs. As we manage culture change, real-time feedback loops and dashboards allow executives to measure and manage progress. Through our custom training programs, employees from across the government have been able to gain the necessary data science skills.
For example, recent Health & Human Services (HHS) Co-Lab trainees presented capstone solutions for:
Of course, transforming the federal workforce starts with building a culture of data, with consistent opportunities for professional development, but with 10 data-driven steps, the path to 10x federal workforce development is clear.
Build or buy an assessment platform that can house all the response data across government agencies; this capability will be the foundation of any initiative at scale. Ideally, the status and results would be stored in a centralized location to allow enhanced analysis and understanding of internal metrics on progress and impact, as well as leverage the data to deploy tailored learning pathways and measure progress. By setting up the infrastructure correctly, the agency is ensuring the longevity and scalability of this initiative.
Once the infrastructure is in place, we recommend an agency-wide training effort, starting with departmental leadership; doing so will garner support for the new initiative and integrate the process within and across agencies. We've seen many of our partners focus on developing a base of data literacy across their organization, which consists of skills such as collecting and consistently storing data, asking the right questions about data, and understanding foundational terms and techniques in data analytics.
To identify the current skills of its workforce, the government should start with a top-down approach to understand which skills they should focus on. Like sailing a ship, the entire crew needs to know the final destination to get there, but as agencies can have different priorities, managers and leadership must outline their objectives and visions so that they can develop skills assessments aligned with the desired outcomes.
Based on the overarching vision and the identified skills, develop an assessment for staff that identifies skills gaps to best inform the data literacy training program. With this information, the government will be able to:
The outputs of the assessments should be presented as quantitative reports that demonstrate the impact of training that has already been completed and their impact on the students themselves, their teams, and their larger organizations. The measured items tie to both the learning objectives of the training and the key performance indicators (KPIs) of the team, which ensures alignment between the two. The results will also identify the skills gaps that currently exist, as well as the current skill levels of government employees.
Our experience (and industry research) indicates that a balanced training regime is essential: Online asynchronous (self-paced) programs can be valuable, but they shouldn’t be the exclusive mode of instruction, as typical self-paced training programs cannot be tailored and, with average completion rates of 4%, fail to engage students.
If the government is thinking through organization-wide transformation and high-level skills training, any learning path should include instructor-led programs (whether in person or livestreaming). Instructor-led programs can be customized toward particular use cases; they provide a structured environment for students and command a high level of interactivity during sessions. Also, these students have an opportunity to learn from each other and collaborate on similar challenges. One of the most valuable outcomes from the programs that we've run for government agencies is the community of practice that continues beyond the classroom. By incorporating live-streaming courses and asynchronous support, you're more likely to see success in terms of completion and acquired skills.
While many strive for 100% data literacy across teams, in our experience, the impact is noticeable when at least 25% of the workforce completes data science training, and analytical techniques, steeped in data, become the default approaches.
One catalyst to help encourage employees and track progress is to create standardized certifications based on the most valuable skills across the government. While there are many certifications that the government already uses, there are no professional certifications for data science that are widely recognized. By developing certification levels within the government, you can also shape the way that industry views data science competencies and encourage high-value employees to stay in government and fulfill their learning pathways. Requirements may include a certain level of training, as well as applying professional hours toward the certification and participating in mentorship programs.
To identify future skills trends, the government should use the objectives and KPIs to map out the essential skills necessary to achieve a broader vision. They should also follow hiring trends in the private sector to understand what skills are becoming more in demand. This latter task can be done using publicly available information and even scraping web data from job hiring websites to compile the fastest-growing skills in a particular industry. By anticipating these future skills, the government will be able to:
Recruiting high-value positions, such as data scientists, while competing with private sector resources is difficult for the government; therefore, it is increasingly important to develop training paths for those demonstrating an aptitude for these skills. Employees who have already shown dedication to their agency have accumulated internal knowledge and can be incentivized with comprehensive training programs and promotion tracks to mitigate recruiting competitiveness. The federal government can also make powerful, open-source software, such as R programming and Python, freely available to employees across the government. Support for these languages at the forefront of technological change, which are monitored and continuously updated by the user community, demonstrates the government's commitment to staying ahead of advances in machine learning.
With consolidated and consistent training programs, and processes that support regular skills assessments adjusted according to new strategies, ongoing development and maintenance costs are comparatively low. With a platform to show assessment results, completed training, and growth trends of employees, their managers can track and bolster progress, in alignment with training pathways and input from employees.