April 2020
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TD Magazine

Multiple Federal Initiatives Encompass Future of Work Efforts

Wednesday, April 1, 2020

The US Department of Defense is one of the government agencies focusing on the 21st century workforce.

The US government is the largest single employer in the country, with nearly 3 million civilian employees, including more than 1 million in the Department of Defense (DoD). Each department, agency, bureau, and office has a different mission and culture. Disparate systems and authorities govern personnel actions, and in some cases, a literal act of Congress is required to update personnel policies. Despite those complexities, the federal government faces the same future of work headwinds as all employers, and it needs to modernize its talent management approach accordingly.


Current federal initiatives

In the federal government, the 2018 President's Management Agenda, along with several related initiatives, provides a long-term road map for developing a workforce for the 21st century. These federal-wide initiatives and policies seek to ensure that the future federal workforce is well trained, is managed by

evidence-based requirements, and has the necessary supporting data to make well-informed decisions. Here are a few examples.

President's Management Agenda. In April 2018, the Donald Trump administration released this overarching strategy for modernizing government operations to improve their quality and cost-efficiency. The strategy starts with three foundational drivers:

  • IT modernization—adopting modern technology to improve customer service, user experience, and data security
  • data, accountability, and transparency—improving how the government uses the data it has, ensures its protection, and drives public value
  • people—preparing for the 21st century workforce.

Each of those is considered a cross-agency priority, and the strategy includes 11 other cross-agency priorities, such as improving customer service and sharing quality services, which cut across those three foundational goals. The third priority—people—has the most obvious implications for the future of work. That priority outlines a thoughtful strategy that includes efforts that would look familiar to any large employer, such as improving employee performance incentives, investing in continuous learning, and using data-driven processes for people analytics.

Foundations for Evidence-Based Policymaking Act of 2018. The Evidence Act, signed in January 2019, encourages the use of data to inform policy decisions. It also establishes processes for modernizing federal data management practices and improving secure data access. Although this act does not direct any specific talent management applications, it reinforces the President's Management Agenda priority of data-driven workforce management.

Federal data strategy. Similar to the Evidence Act, the federal data strategy guides the federal government's management and use of data, with a focus on three principal areas: practicing ethical governance, conscious design (which emphasizes the high-quality collection and use of data), and learning culture. Most relevant to this discussion, the learning culture component includes three sub-elements: investing in learning, developing data leaders, and practicing accountability. The strategy also details practices for agencies, such as building a culture that values data and promotes public use.

In the waning days of 2019, the president's administration released the federal data strategy's 2020 action plan, which identifies actions for establishing processes, building capacity, and aligning existing efforts to better leverage data as a strategic asset. It also details relevant pilot projects already underway across the government. This year's actions intended to drive talent development include conducting baseline assessments of staff literacy and capacity; identifying opportunities to increase staff data skills; furnishing tools, frameworks, and skills catalogs; and establishing bodies for standards and information sharing.

The National Council for the American Worker. In July 2018, Trump issued an executive order that directs development of a national strategy to ensure the US workforce has access to affordable, relevant, and innovative education and job training that prepares them to compete in the global economy. This project extends beyond the federal workforce but has applicability there as well.

The executive order created an American Workforce Policy Advisory Board, which has been working with the private sector and education institutions to help address the US workforce skills crisis both in and out of government. A sampling of recent materials and guidance the advisory board produced includes recommendations for developing interoperable learning records, suggestions for modernizing candidate recruitment and training practices, and ways to measure and encourage employer-led training investments.

DoD case study: Implementing talent development reform

While excellent initial progress has been made on those initiatives, the government is not yet finished. So, how long will it take to implement this vision of a contemporary, well-trained workforce, and how can the government build it?

DoD has been examining talent development reform for years. In 2015, the Navy, for example, launched its Sailor 2025 program, and the Air Force released its Strategy Master Plan Human Capital Annex the same year. Similarly, then-Secretary of Defense Ash Carter announced the Force of the Future initiative in 2015, a Pentagon-wide effort to reform talent management across the department. Those efforts (and many others like them) generally focus on outcomes, such as a career-long continuum of learning, blending distributed and face-to-face learning, making training available at the point of need, and leveraging a data-driven system to better personalize L&D to individuals.

In this article, however, the following case study focuses more narrowly—not on all DoD talent management initiatives but on the DoD intelligence organizations' efforts. The DoD Intelligence and Security enterprise began reforming its talent development operation more than a decade ago. Although technology has advanced since then, the case study still offers useful insights for the modern, federal-wide initiatives.

The Intelligence Reform and Terrorism Prevention Act of 2004, which involves preparing personnel for duty assignments in other government or intelligence organizations, triggered the DoD Intelligence and Security workforce reforms. Then-Secretary of Defense Donald Rumsfeld created the Under Secretary for Intelligence and Security, which brought together 10 disparate intelligence components under a single organizational umbrella. (This is akin to the different executive departments in the federal government, each with its different culture and mission.)

In time, the intelligence components were instructed to focus on talent development efforts and to develop a shared vision for a common technical infrastructure. To begin that work, the Office of the Under Secretary of Defense for Intelligence chartered a learning enterprise architecture working group in 2015. It spanned across the 10 different components and supported the development of a responsive, interoperable, automated, multidomain enterprise learning architecture that would include the necessary infrastructure and supporting technologies.

The group's goal was to improve the visibility of, and access to, learning and performance support products for a diverse, globally dispersed intelligence and security workforce.

One of the working group's first tasks was to baseline the current state of learning systems across the participating components. It accomplished that by updating and revalidating an existing learning technology inventory. The process reaffirmed the original report's findings, which concluded that the components' architectures were, for the most part, not interoperable. That meant components were unable to support interorganizational learning discovery, were less likely to collaborate in the development and delivery of learning solutions, and could not use data to inform strategic decisions about talent development outcomes or investments.

The working group simultaneously began to design a framework for the envisioned system, which was tentatively called the talent development toolkit. It used the term talent development to convey a broad scope, including conventional training and education as well as nontraditional, informal, immersive, and social learning. The toolkit also considered performance support and professional development certificates and credentials.

Working closely with the DoD's Advanced Distributed Learning (ADL) Initiative and the Office of Personnel Management's USALearning program, the working group focused on identifying the requirements for implementing an end-to-end solution that integrates across discovery, development, delivery, evaluation, assessment, and reporting functions.

In 2017, DoD Intelligence and Security commissioned USALearning to conduct a learning enterprise functional analysis, which examined the state of its learning enterprise systems from the perspective of the talent development toolkit requirements. The study validated the learning technology inventory's findings, and it outlined recommendations for closing gaps between the status quo and the desired enterprise toolkit ecosystem. Chief among the recommendations were:

  • Implement enterprise-wide data collection, analysis, and sharing.
  • Establish a learner-centric environment.
  • Reduce and eliminate the duplication of effort wherever possible.
  • Provide transparent governance to achieve the shared vision.

In 2018 and 2019, DoD Intelligence and Security worked with the ADL Initiative to translate its Total Learning Architecture technical specifications to the talent development toolkit. In other words, the ADL Initiative was already developing a solution to address the recommendations identified by the USALearning functional analysis, but the ADL Initiative's work was research-centric and not system specific. In 2019, the ADL Initiative delivered the Talent Development Toolkit Requirements and Architecture Study, which translated the generic Total Learning Architecture principles into the specific DoD Intelligence and Security technology systems. Also that year, the ADL Initiative released its Modernizing Learning book via the Government Publishing Office. The book outlines a comprehensive strategic vision for achieving enterprise learning systems such as the talent development toolkit.

Now in active development, the toolkit design will enable stakeholders to access a structured, end-to-end technology-enabled ecosystem to help employees, supervisors, managers, and organizations to:

  • discover, deliver, document, and display all relevant talent development materials and events from a single portal
  • exchange data (for example, completions) with the wider enterprise talent management system
  • access data-driven decision aids
  • incorporate granular data, such as competencies and certifications
  • discover and access L&D opportunities across the enterprise
  • record and get credit for completed learning activities
  • access evaluation and assessment resources
  • enjoy business operations improvements, such as cost efficiencies, improved handling of secure and privacy-sensitive data across federated system boundaries, and time savings by making individuals' credentials portable across organizations.

Lessons learned for the federal enterprise

The government is building many of the appropriate systems and processes that should enable forward movement over the next decade on many of the objectives of the President's Management Agenda, Evidence Act, federal data strategy, and other federal modernization initiatives. These systems and processes emphasize federating data across stovepipes, creating governance boards and policy structures, and developing common infrastructure components (for example, shared course catalogs and learner record repositories).

The elements that are less sure, and therefore jeopardize achievement of enterprise talent development capabilities across the federal government, include the lack of a secure universal identifier and proven mechanisms for maintaining trust among stakeholders, frequent changes to and shifts in focus by political leadership, and—most importantly—investment and consistent prioritization toward culture change for competency-based talent management.

In 2020, for example, the Office of Personnel Management abandoned efforts previously underway to establish an employee digital record. That project was intended to be a single, comprehensive view of an employee's federal career. Absent a government-wide standard, employee data remains trapped in disparate agency HR IT systems to the detriment of employee mobility, employer talent management capabilities, and the goals of the federal initiatives previously summarized.

On a more positive note, forums and mechanisms already exist across the government to convene on issues surrounding talent management. Each major functional category (including HR, IT, finance, acquisition, performance, learning, and data) has a government-wide council, such as the Chief Learning Officer Council or Chief Information Officer Council. There are also multiple lines of business for functional areas, including the HR line of business that the Office of Personnel Management manages. And, as part of the President's Management Agenda, shared services have been established across the government.

However, a lack of coordination across bodies remains, which limits their effectiveness. A shared vision of the federal learning ecosystem would better allow the development of standards, which the chartered councils could govern and the federal departments (along with industry and academia) could implement. Based on lessons learned from the talent development toolkit case study, the federal-wide vision should address the following integration touchpoints, which would help best prepare the future federal workforce:

  • universal unique identification—protecting learners' privacy
  • national certification and credential registry—one source for national certifications
  • national common course catalog—visibility into learning events
  • national learning record store—data home to follow learners
  • national chancellor for government learning—one person responsible for action
  • national learning directory—a better use of classrooms and capability
  • national learning data standards—to allow data, content, and events to be shared
  • national learning requirements process—ensuring the rigor of developing content
  • national development center—a home for these national programs
  • national learning lexicon—to better understand the language of learning
  • national competency directory—a firm foundation from which to build learning.

Finally, even if all stakeholders coordinate and develop common standards, each organization's culture and the quality of its change management will ultimately determine the success (or failure) of future federal-wide workforce efforts. Successes must initially be won at the bureau and department levels before attempting to connect them across the federal enterprise.

Congress and the president's administration must play a role, moving aside outdated policies that reinforce the status-quo bureaucracy and hinder modern talent management actions. Likewise, they can inspire progress by continuing to emphasize and invest in the modernization, professionalism, and capability of the future US federal workforce.

About the Author

Jason Briefel is executive director of the Senior Executives Association, overseeing its day-to-day operations and leading execution of the priorities and policies of the board of directors. He leads strategic engagement efforts with members of SEA’s Corporate Advisory Council and other organizations. Briefel served as SEA interim president from February to September 2016. Additionally, he serves as SEA’s legislative director, representing the association on Capitol Hill and with the administration.

Briefel also is the director of government affairs at Shaw Bransford & Roth. He joined the firm’s government affairs practice in 2012. He provides legislative and organizational representation to clients of the firm’s government affairs practice, as well as conducting nonlegal research for law firm clients as necessary.

About the Author

Reese Madsen is the founder and owner of MEMY&I, LLC. He is a senior learning executive that consults on program design, development, and improvement for the federal government sector. Using his 40 years of federal service and the last 15 as a chief learning officer at the Department of Defense to support national and federal learning programs. His experience included leading a learning enterprise of 52 schoolhouses and programs for the U.S.’s largest government department - including overseeing a $2 billion budget supporting 2.5 million professionals. He developed policies, plans, programs, and training for civilian, military, government, academic, and industry workforces. This included maintaining a Learning Enterprise comprising of 5,000+ courses, the first nationally accredited government certifications, and providing more than 21 million hours of instruction per year.

About the Author

Sae Schatz works at the intersection of human cognition and learning, technology, and data. From 2015 to 2022, she was the director of the Advanced Distributed Learning (ADL) Initiative, a government program for research, development, and policy stewardship. Before joining the civil service, Schatz worked as an applied human–systems scientist in both business and academia, and she formerly held an assistant professorship with the University of Central Florida’s Institute for Simulation and Training. Schatz is a prolific writer and professional presenter as well as a graphic designer who often uses those skills to enhance books, presentations, and infographics.

1 Comment
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Thank you to the authors! This is a wonderful articulation of the need for a federal learning ecosystem. I also appreciate your identification of integration touchpoints.
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