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Army turns to data analytics and machine learning for skill identification, talent recruitment and development

The National Defense Strategy and the Army Strategy both point out that the global security environment is increasingly complex and shaped by several emergent trends. In the past, the Army has enjoyed a competitive advantage over any potential adversary in capital, technology, and people. More recently, however, near-peer, revisionist great powers such as China and Russia have improved their large-scale ground combat capabilities by increasing their capital expenditures and reducing the technology gap, leaving people as our enduring
strategic advantage.


The strategic environment poses challenges that necessitate organizational change within the Army. The most reliable insurance against an uncertain future is a sustained investment in the human dimension of combat power. The Army Vision states: Improving our agility begins with changing how we recruit, develop, manage, and train personnel. We will need a whole-of-Army recruitment and retention strategy and must commit to personnel policies that better develop and manage Soldiers and Army Civilians in order to optimize individual performance.


Recent conflicts have reinforced the need to balance the technological focus of Army modernization with an emphasis on the human, cultural, and political continuities of armed conflict. Therefore, the Army will require enhanced capabilities in the cognitive, physical, and
social (CPS) components of the human dimension and must optimize the performance of each Soldier, Civilian, and team. These capabilities are necessary for the future Army to maintain overmatch against its adversaries and win.


The Multi-Domain Task Force is a model of how the Army envisions joint-warfighting on future battlefields against near-peer competitors, like Russia and China. Before the Army activates additional formations, though, Murray said it will first need the right talent to fill the ranks.  Talent is the unique intersection of skills, knowledge, and behaviors in every person. Talent management involves integrating various activities to generate a positive, synergistic effect on organizational outcomes and harness individual aptitudes for the mutual benefit of the individual and the organization. Talent management is a required capability that impacts readiness. Future Army organizations require the capability to manage individual talent throughout the lifecycle through an integrated approach leveraging accessions, retention, professional development, and assignment strategies to ensure optimal employment of all members of the Army Profession.


They  require the capability to use cognitive, physical, and social assessments that measure abilities and accurately predict future success of members of the Army Profession to implement enhanced talent management so the right person receives the right career assignment (to include training and education) at the right time.


They  require the capability to integrate and synchronize human dimension initiatives (training and education, science and technology, medical, and personnel policies, programs, and initiatives) to ensure they are effective and efficient in providing adaptable, trained, and resilient forces that meet the Army’s challenges in the future operational environment.


AI and Machine learning Talent sourcing and recruitment

Talent sourcing and recruitment are at the center of developing and maintaining the U.S. labor force. The U.S. Bureau of Labor Statistics (BLS) projects that  Employment is projected to grow from 162.8 million to 168.8 million over the 2019-29 decade, an increase of 6.0 million jobs. Successful talent acquisition is a demanding task requiring the capacity to discover and evaluate the skills and experiences of both active and passive candidates.

AI is participating in a new tech-driven era of recruiting and hiring by increasing capacity and saving employers time. Today, machine learning is emerging as a strategy to help employers more efficiently conduct talent sourcing and recruitment. Companies are training machine learning algorithms to help employers automate repetitive aspects of the recruitment process such as resume and application review. Companies are using machine learning to help identify top candidates from large candidate pools. Companies are developing AI assistants to pre-screen candidates and to respond to inquiries regarding positions using natural language processing.


Army’s  personnel management system automation

The Army has been tweaking its personnel management systems as part of its People Strategy, released in October, which outlines how the service plans to acquire, train and keep its talent. And better data is key to finding the best talent, especially when it comes to tech.


Creating a robust pipeline of new talent into the Total Army is our main effort through 2028 because it will ensure that we have the breadth
and depth of talent needed for the MDO-capable force of 2035 envisioned by the Army Strategy. The Army must place a greater emphasis on acquiring the right people through better screening and assessments allowing us save and reinvest valuable resources by reducing attrition.


“We know who the cyber officers are because they’re already in the cyber branch. What we don’t know is the infantry officer who also has some sort of certification as some sort of coder — he’s got some unique data analytics skills that aren’t captured in his traditional educational background,” said Maj. Gen. Joseph Calloway, Army Human Resources Command’s commanding general. Calloway said the command is working to capture and harness that information and develop ways of better tailoring officers’ assignments, including tapping into data pertaining to outside knowledge, skills, and other desired traits — such as where soldiers travel or may have lived in their youth — that wouldn’t necessarily show up on their record brief, which encapsulates formal education and career highlights. The Army recently assigned about 15,000 officers using an automated program as part of the Army Talent Alignment Program (ATAP), which seeks to better match unit needs with officers’ skills, Army officials told reporters during a briefing.


The Army  plan to use a range of technologies, incentives, programs, and policies to identify the talents of its people and the talent demands of its organizations in timely, accurate, and granular detail. It applies data-driven analytical tools to its talent employment and development efforts. This data drives a dynamic and accurate long-term workforce planning system which reduces talent gaps and increases overall Army readiness. It also enables the Army to rapidly build appropriately talented special mission teams – cohesive teams that are trained, disciplined, and fit to win. Leverage technology and comprehensive assessments to assess individual knowledge, skills, and behaviors to maximize human potential and output.


Army wants a data analytics tool or software for  talent recruitment, skill identification,

The U.S. Army plans to release an opportunity for small businesses to propose platforms that could help identify, develop and deploy “emerging technology leaders” across the service using machine learning and data science, Nextgov reported in Nov 2020. The service describes ETLs as uniformed experts who can connect military operators to engineers, scientists and technologists. The Army wants a data analytics tool or software that can be used in talent recruitment, skill identification, talent selection, development and distribution efforts.


The initiative has three phases and the first phase will provide $256K in funds over four months to support the development of operational concepts or constructs for theory or algorithms that could be used to identify and recruit ETLs. Phase II will focus on the demonstration of software prototype, while Phase III will deal with the integration of machine learning algorithms and software analytics to help reduce the workload of staffing personnel.


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