The U.S. Air Force (USAF) human capital management (HCM) system is not easily defined or mapped. To some degree, it affects virtually every part of the Air Force: its workforce policies, procedures, and processes impact all offices and organizations that include Airmen. Furthermore, frequent minor and less frequent major administrative reorganizations regularly alter responsibilities and relationships. Generally speaking, the USAF HCM focus is to ensure the readiness of Airmen to fulfill the mission of the Air Force. USAF HCM efforts include:
- The quantity and quality of personnel,
- Promotion and retention processes,
- Training and professional development programs,
- Job classification and job assignment policies and processes, and
- Any other human capital matter.
As the key decision-makers overseeing USAF human capital, offices within Headquarters Air Force, Major Commands, and other Total Force leadership positions are assigned primary responsibilities for management. At the most senior levels of the system, strategic approaches are developed and issued through guidance and actions of the Office of the Deputy Chief of Staff for Manpower, Personnel and Services (AF/A1) and Office of the Assistant Secretary of the Air Force for Manpower and Reserve Affairs (SAF/MR). Both offices are supported by subordinate elements that provide breadth and depth in capability and perspective to inform and implement human capital policy decisions.
As strategic guidance is received, disseminated, and implemented across the Total Force, numerous disparate and connected entities take on a variety of support roles: communicating policies to Airmen, implementing training changes, developing supporting technology (e.g., personnel systems such as Talent Marketplace or training systems such as those used by the Pilot Training Next initiative1), collecting data (e.g., surveys) and conducting analysis, providing feedback to senior leaders, and so on. Among those, major players include Air Force Recruiting Service, U.S. Air Force Academy, Air Education and Training Command, Air Force Personnel Center, Air University, and Air Force Institute of Technology. Further complicating the dynamics of an already massive and complex system, additional players who may influence, make, implement, and be impacted by policy decisions include highly specialized niche communities and areas of responsibility such as USAF Special Operations Command, clinical psychologists, or operational fighter pilots or cyber warriors. Many of the offices making up the USAF HCM system have clearly defined roles and responsibilities that establish relationships vertically and horizontally across the service. However, in other areas, complicated dynamics are at play with simultaneously mutual and competing interests, fixed budget constraints and internal budget allocations, and opportunities and redundancies reflecting shared needs for personnel data and analysis.
In conducting this study, the committee did not endeavor to map the current USAF human capital organizations, offices, and individual decision-makers, or their precise responsibilities and relationships. Rather the committee focused its study on understanding the opportunities and challenges associated with related interests and needs across the USAF HCM system as a whole, as identified primarily through the committee’s numerous site visits and additional briefings that provided valuable insight and perspective on USAF human capital elements. Organizations morph and change over time; however, the goals of the organizing strategy are critical to planning for the future.
Without an understanding of the inherent complexity of the USAF HCM system, any single point policy or funding decision—variables of the ecosystem in which the system works—has the potential for widespread ramifications that may be inadequately considered, understood, or documented at the outset. Simply put, the HCM ecosystem includes both USAF
1 For more information, see: https://www.aetc.af.mil/About-Us/Pilot-Training-Next/.
human capital elements and externalities,2 which are separated by a boundary layer (Figure 2-1 provides a simplified view of this context). The Air Force internal processes are contained within a defined boundary, which dictates control or governance capability. Inputs come from outside the system to inside the system; outputs go from inside the system to outside the system. The Air Force controls and manages the elements within its boundary, but is dependent on elements outside the boundary, over which it has little or no influence. Understanding the complexity of the system requires acknowledging the larger ecosystem in which USAF HCM operates.
To begin to understand those ecosystem dynamics in more detail, the committee developed a model of the ecosystem of modern USAF HCM (emphasizing influential variables and actions rather than specific Air Force offices or organizations), including elements both under direct control of the Air Force and externalities with influence. As such, the committee modeled the ecosystem as a causal loop model by applying a systems dynamics modeling methodology that identifies causal links between vari-
2 In its use in this report, the committee adopts a systems analysis view of an externality to be a thing that exists outside of the control of the system and which may have impact on the operations of a system.
ables in a system (see Sterman, 2000). Initial drafts of the model focused on variables with which members of the committee were most familiar from their own expertise in relevant research and Department of Defense and Air Force operations. However, early drafts of it were used throughout the study to facilitate the committee’s data-gathering efforts during site visits and other briefings. As such, the model expanded and evolved and was revised to reflect input received from subject matter experts across the Air Force. Still, to complete and validate the model, additional research is necessary. In its current form, and as will be discussed below in greater detail, this kind of model is especially helpful in illustrating how a single action might have far-reaching and unanticipated effects. It is also particularly useful for identifying feedback loops. Figure 2-2 provides the committee’s model of the USAF HCM ecosystem (including USAF human capital elements and externalities); Appendix B provides additional details regarding the modeling approach.
In a causal loop diagram, the causal links demonstrate same (+) or different (–) directional changes between variables. When multiple causal links create a loop, the change effects cascade. The diagrammed change flows represent mathematical relationships. For example, if a causal loop is marked as a same (+) relationship between two variables, then a change in one variable (positive or negative) is expressed in the connecting variable with the same directional change (e.g., a positive change in one results in a positive change in another).3 Alternatively, a different (–) relationship between two variables indicates an opposite change reaction (e.g., a positive change in one results in a negative change in the other).4 The model is also color coded to facilitate exploration—as noted in Figure 2-2, variables with major connectivity across the system (yellow highlight) have the potential to generate critical reverberations throughout the system while others are external to the Air Force (red box) (e.g., geopolitical disruption) and as such may impact the internal system but are largely beyond the control of Air Force senior leaders.
Additionally, within the context of USAF HCM, seven critical focus areas (i.e., recruiting, selection, classification, and utilization, and the combined post-accession areas of attrition, promotion, and retention) are overlaid on the ecosystem model and demonstrate rough delineations and overlap in organizational component missions and areas of responsibility as an Airman traverses a career (see Figure 2-3). In considering USAF
3 A simple real-world example is evident when the number of qualified military applicants increases (positive change), the selection criteria above basic requirements (selectivity) will also increase (positive change).
4 A simple real-world example is evident when positive change in general economic conditions results in a reduction in the number of military applicants.
HCM from a system dynamics viewpoint, the relationships between these focus areas (and their corresponding organizational elements) are critically important to fully document and understand.
In sum, the ecosystem model visually demonstrates the complexity among USAF human capital elements and also the ecosystem’s inherent vulnerability to the effect of single point changes that may occur internally or externally to the Air Force. Consequently, when human capital decisions are made in isolation with limited or no consideration of strategic needs or impacts across other elements, this has the potential to result in major consequences across the Total Force and to frustrate and disenfranchise leaders and support staff working elsewhere in the system.
Before discussing the utility of the ecosystem model, a few caveats about modeling in general are in order.5
Models represent an abstraction of reality that is, by definition, limited. They do not represent the entirety of reality; thus, the adage, “the map is not the territory.” There are as many different ways of abstracting reality in models as there are aspects of reality to study and understand. For example, organizational charts are models of how an enterprise is organized; form models are representations of how something looks and feels; and data flow diagrams are models of how information moves throughout a system. Each model brings value, but each is limited by virtue of the aspect of reality it represents. The first caveat, then, is that a model does not represent the entire reality of a system. It highlights only some characteristics.
Models apply simplifications and abstractions that may appear as omissions or errors, especially if the model is used for purposes other than originally intended. Consider, as an example, a hand-drawn map of pathways to a store. The map will almost certainly not be to scale, so distance cannot be determined and any judgments made about distance would likely be incorrect. The map may also leave off important territorial features, such as creeks and hedgerows. Using the map as a model to inform a trip to the store is very useful, so the purpose of the map is fulfilled, but the level of abstraction and estimation may have consequences if the map is later used for other purposes. The second caveat is that a model is developed for a certain purpose and may be inappropriate for other purposes.
The simplifications and abstractions that may cause errors in a model may be important or unimportant, and their impact may range from high
5 For additional background information on the design and application of models in general, see Degrace and Stahl, 1993; Griss, 1998; Maier, 1996; Martino, 1993; Rechtin and Maier, 1997; Rowe et al., 1996; Schwartz, 1996; Sterman, 2000; and Williams and Smith, 1998.
to low. Further, the consequence may be greater or lesser depending on the circumstances. The lack of annotation of a creek on the map is of low consequence during the dry season but may be of major consequence during the rainy season. The third caveat, then, is that the importance and potential impact of simplifications and abstractions in a model, including those that may result in time- or circumstance-based errors, should be documented.6
Finally, a model must be validated against reality within the context of its intended use. A model developed by one or more people based on observed data may be close to the intended abstraction, but there must be systematic validation of the model components through real data collection, hypothesis testing, and behavior analysis. A model that has not been validated in this manner should be considered with suspicion. The fourth caveat is that an unvalidated model should not be used for decision-making but rather is best viewed as an illustration of the system and useful as a conversation starter.
Accordingly, to the extent the committee has developed the USAF HCM ecosystem model for this report, it is fair to characterize it as an androgogical tool. It is used to illustrate the great complexity of the system and the sometimes subtle ways that the elements of the system can and do interact. If the model is to be used operationally by the Air Force, its utility and limitations (as discussed in this chapter and Appendix B) would need to be carefully considered against its intended use (including the level of granularity necessary to understand important outcomes across the system). To meet more detailed and exact needs, the model could be expanded to include additional variables and feedback loops informed by mathematical relationships. Although that level of detail is beyond the time and scope of this study, it is an achievable endeavor through the application of systems dynamics modeling methodology, should the Air Force wish to pursue it.
As large and diverse enterprises prepare for future workforce needs, a projection of the future is necessary to guide the planning process: how many people will need to be replaced, what types of resources will be needed, where opportunities will arise, etc. Any such forecast is based on an assessment of the current situation combined with consideration of what may happen across the ecosystem, especially effects from externalities. Combining the various vectors of possibility results in possible futures, each of which
6 Note that the committee’s model does not include this documentation because it has not been fully validated. Documenting this prior to validation is ineffective because the validation process would be expected to result in changes to the model to make it conform more closely with reality.
may be considered more or less likely to occur and large or small in effect. Understanding potential futures allows planners to identify key observables to monitor and managers to implement policies and procedures to guide the enterprise into a more desirable future. For example, since 2014, the Air Force has lost more fighter pilots annually than its annual production rate, and forecasts of the commercial airline pilot marketplace are an important variable in long-term workforce planning to develop and sustain the career field (Byrnes, 2017). The paradox is that there is only one thing that is certain in forecasting the future: that these estimates will be wrong. Sometimes the forecast is only wrong in trivial ways that are easily accommodated, but sometimes the forecast can be wildly inaccurate in critical ways. Although inaccurate estimates can be made by competent teams acting in good faith, sometimes they are caused by unforeseen disruptive events referred to here as “future shocks” (e.g., the rapid global spread of COVID-19).
The certainty of error combined with the possibility of future shocks mean that contingency planning must be included as a normal part of planning. Briefly, shocks that could impact human capital planning include the following:
- Technology disruption, such as the development of new unexpected technologies that may result in the functional obsolescence of job categories or the combination of existing technologies in novel systems that revolutionize types of processes that require Air Force Specialty Codes (AFSCs) to be changed, added, or deleted. Also, the technology might change the way human capital functions are carried out (e.g., technological advances in artificial intelligence might enable new ways of selecting, classifying, or training Airmen).
- Economic disruption, such as a severe airline industry decline that invalidates well-defined models of predicted loss of pilots to commercial sector positions.
- Demographic disruption, such as significantly reducing the number of potential recruits who meet eligibility criteria (e.g., due to obesity) resulting in recruitment goals that cannot be met in quantity or quality.
- Political disruption, such as warfare that significantly impacts propensity to serve (either positively or negatively).
- Social or cultural disruption, such as values or social expectations that alter perceptions about the legitimacy of military operations.
This is a short list of the types of future shocks that can occur, and though this list is necessarily incomplete, it provides insight into how considering future shocks can inform workforce planning.
A Future Shock Example
To illustrate how the ecosystem model could be used to understand the potential a future shock has for cascading effects across the complex USAF HCM system, this section describes a fictional example of a technology disruption and follows it through the ecosystem model’s causal loops. In doing this, each actor is provided a way of easily seeing the potential for effects outside their span of control. The fictional example described, along with its cascading effects, was created from the committee’s direct conversations with various stakeholders (including, for example, USAF human capital researchers, policy and decision-makers, trainers, and career field managers) in the course of the committee’s data-gathering plenary session meetings and site visits during this study. This scenario reflects the relationships of the human capital ecosystem based on conversations with USAF HCM system officials, the committee’s experience, and the committee’s analysis of accessions and post-accessions personnel decisions (see Chapters 4 and 5). This fictional example does not describe a particular historical or predicted future shock but was created explicitly to highlight the cascading effects of a single action through the entire ecosystem model.
Fictional Example We begin with the fictional example and then use tree diagrams to step through impacted points of the ecosystem model to demonstrate cascading effects through the causal loops.
Application of the Ecosystem Model to the Future Shock Example
Based on the fictional example above, the following sections and accompanying figures illustrate the cascading effects via the ecosystem model in a tree format.
Rate of Technology Change Effects
The impact of this situation is first shown in the variable rate of technology change. The increase in rate of technology change is shown in Figure 2-4, cascading through primary and secondary effects. There are four variables that have secondary effects (illustrating the cascading effects in the model): operations disruption, need for training changes, training relevance, and accuracy of future needs forecast (and research into future needs, which cascades directly into the accuracy of future needs forecast and therefore is not further expanded upon here). These four variables (as well as others) affected by the rate of technology change, and the variables that they in turn affect, are shown in Figure 2-4.
Taking each of the second-level effects and showing their trees as the rate at which technology change increased, the first variable, operations disruption, increased. This in turn affected the large number of variables, as shown in Figure 2-5.
As the rate at which technology change increased, the need for training changes increased. This in turn affected the variables shown in Figure 2-6.
As the rate at which technology change increased, training relevance decreased. This in turn affected the variables shown in Figure 2-7.
As the rate at which technology change increased, the accuracy of future needs forecast decreased. This in turn affected the variables shown in Figure 2-8.
As shown in Figure 2-5, the increase in operations disruption affects some of the same variables affected by the increase in the rate of technology change. The cascade is caused through mission effectiveness: as mission effectiveness decreases, the job desirability declines, which in turn adversely
affects the number of applicants who want to join the Total Force. This relationship is shown in Figure 2-9.
Effect Cascade Loops
The disruption in the model that starts with an increase in the rate of technology change causes many, many feedback loops. A feedback loop occurs when a change in one variable causes changes in other variables that eventually cause a change in the first variable again, thereby repeating the cycle. The illustrations below show feedback loops for one of the primary variables affected by the increase in the rate of technology change: mission effectiveness. Appendix B illustrates another feedback loop for the variable, accuracy of future needs forecast.
Part of the challenge of understanding the effects of a particular feedback loop is that each variable in the loop may also affect other variables and therefore be included in other loops. For this reason, the loop is described and then shown with graphics, tracing the behavior through the variables. At the end of each example, the loop is highlighted in the larger ecosystem model.
Loop Example: Mission Effectiveness
The effects on mission effectiveness cascade through 141 feedback loops. One of these is described here. This loop cascades through the following variables and back to mission effectiveness:
- Mission Effectiveness
- Job Desirability
- Person-Job Fit
- Aggregate Competency Level
- (and back to) Mission Effectiveness
Future Shock Example Summary
This fictional example of a future shock and the tree diagrams that map the cascading effects it sets up illustrate how one change can have cascading effects on the human capital ecosystem. The point is not to anticipate every externality, but to recognize the potential impact on every part of the ecosystem when change occurs internally or externally. One key takeaway for the Air Force is to have a human capital system that is more “self-aware” of connections and contingencies, that is more agile in recognizing and responding to change, and that is more aligned in addressing change. Appen-
dix B further expands this example with additional trees, and the following chapters provide more details on these attributes of a “self-aware” system.
As further context for the analysis and recommended action items contained later in this report, this section provides a brief overview of the historical, current, and future workforce that comprises the USAF Total Force (i.e., active duty, reservists, and civilian employees), including important details about highly specialized career fields (additional details on the Total Force are provided in Appendix C). Although this report focuses on active duty Airmen, the Air Force benefits from a highly capable and technical workforce across its Total Force, and its human capital practices are increasingly taking a more holistic approach (e.g., recruiting efforts that include enlistments, college scholarships, and civilian direct hiring).7
In accordance with the FY2020 National Defense Authorization Act, the Air Force is allowed an active duty end strength (including military cadets) of 332,800, of which 265,136 are enlisted Airmen (Air Force Magazine, 2019). Within the active duty of the Air Force, 20.9 percent are women and 15 percent self-report as Black or African American, 4.2 percent as Asian, and separately 15.2 percent self-report as Hispanic or Latino (AFPC, 2020).
The Air Force consistently attracts and recruits to exceed its goals both in quality and quantity. In fact, the Air Force has not missed its annual recruitment goal since fiscal year 1999, when it fell short of the 33,800 recruitment goal by a mere 1,732 recruits (USAFRS, 2019). And the last failure to hit the recruitment goal before that had been another 20 years prior. Furthermore, over the past almost 20 years (FY2000 to FY2019), high school graduates consistently made up 98–99 percent of Air Force enlisted recruits with approximately 80 percent scoring into Category-IIIA and above (scoring above 50% in the test score distribution) on the Armed Force Qualification Test (AFQT), a set of subtests of the Armed Services Vocational Aptitude Battery (ASVAB)8 (USAFRS, 2019) (see Chapter 3). In total, the Air Force is consistently successful in recruiting the best and the brightest that American society has to offer.
However, the Air Force, and all the military Services, are challenged to recruit their all-volunteer workforce from among a diminishing pool of eligible youth. Disqualifications for medical, physical, educational, and other
7 The committee learned about recent changes to “Total Force” recruitment approaches during data-gathering sessions with representatives of the Air Force Recruiting Service during a committee meeting in Washington, DC (July 30, 2019) and in conjunction with the site visit to Joint Base San Antonio-Randolph (November 5–8, 2019).
8 Potential recruits scoring in the 50–99 percentile score range on the ASVAB.
reasons leave only 29 percent of youth ages 17–24 eligible to serve. And the candidate pool is further reduced by those who may be either unaware of or uninterested in military career opportunities (see JAMRS, 2016 for more information about youth propensity to serve).
As this study concludes amidst the global pandemic of COVID-19, a new challenge to the Total Force is emerging. The potential for missing recruitment goals is an obvious consequence of restrictions on public gatherings and travel, but impacts on the enlisted Airmen training pipeline have the potential to create severe long-term consequences. Disruptions to basic military training (BMT) and other technical schools may create a long-term effect as it may be impossible to surge the number of students through school houses in order to recover the lost time. As these restrictions continue, the drastic reduction in training through-put will leave a dip in Airmen quantity and expertise that moves up through the ranks for the next 20 years. As such, the events of early 2020 created a previously unrealized premium on the successful training, utilization, and retention of Airmen within the current cohort.
In addition to general needs for high-quality Airmen, the Air Force also has needs for highly skilled individuals to fill specialized career fields that are consistently difficult to fill and retain. Of those, perhaps the most visible and highly associated career field with Air Force service is that of rated pilots.9 Since 2017, the Air Force has faced a shortfall in pilots of about 2,000, and by the end of FY2019, officials testified that “the service was short 2,100 pilots—10 percent of the 21,000 pilots it needs to execute the National Defense Strategy” (Losey, 2020). To fill this shortfall, the Air Force has sought to address the issue from two sides of the problem: (1) improve retention of pilots who are attracted by lucrative civilian careers with the commercial airline industry, and (2) increase the capacity and throughput of the pilot training pipeline (1,000 officers completed pilot training in 2015; early 2020 projections indicated 1,300 will complete training in 202010—falling short of the 1,480 goal [Losey, 2020]). To advance the second, initiatives such as “Pilot Training Next” apply virtual reality and individually-paced learning to complete previously serial and rigid training better and faster. Although effects of COVID-19 on the commercial airline industry can be expected to have a positive impact on Air Force pilot retention in the short-term, competition from commercial industry should be expected to resume in the future.
9 Non-rated career fields do not involve flying an aircraft (e.g., space operations, intelligence, maintenance, or engineer).
10 For information on the early impact of COVID-19 on pilot training, see https://www.aetc.af.mil/News/Article/2172560/acting-undersecretary-visits-vance-to-observe-covid-19-impact-onpilot-training.
The Air Force also includes several highly specialized communities that provide critical capability to the Air Force and Joint Operations. For example, the Air Force Special Operations Command (AFSOC) workforce includes 28,800 of the Total Force. They conduct “global special operations missions ranging from precision application of firepower to infiltration, ex-filtration, resupply and refueling of [special operations forces] operational elements” (AFSOC, 2017). The Air Force workforce also includes highly technical career paths such as those for Airmen who work in the cyber domain and the recently established U.S. Space Force (established in 2019 as a military service branch within the Department of the Air Force).11 Both special operations and cyber career fields include notoriously difficult selection and training processes with high attrition rates—but typically for different reasons. Special operations is an extremely physically demanding career field, and incoming recruits are increasingly ill-prepared for the physical difficulty of even the selection process.12 On the other hand, cyber career fields are highly demanding in cognitive capabilities (as well as ethical and moral standards in some specialities), and the selection and training programs are rigorous.13 These two disparate examples demonstrate that human capital challenges for the Air Force are both broad and deep.
The previous sections of this chapter described a complex USAF human capital ecosystem—supporting the Total Force—and subject to cascading effects from points internal and external to the Air Force. To navigate this complexity, USAF HCM has benefited over the past 70 years from a succession of internal research support organizations that have evolved into today’s USAF human capital research organizations. The historical success of Air Force human capital—in attracting, selecting, and retaining high-quality Airmen—was made possible by these innovative and agile human capital research organizations. Collectively, over time, the research conducted within these organizations, supplemented by contracted external research organizations, has contributed to the development of current USAF human capital policies, procedures, and tools.
The historical record, detailed as a timeline in Figure 2-11 and discussed in more detail below, shows a system that has evolved substantially
12 This information was provided during the committee site visit to Joint Base San Antonio-Randolph, where the committee met with numerous representatives who provided information and perspectives on USAF Special Warfare recruiting and training (November 6, 2019).
13 This information was provided during the committee site visit to 2nd Air Force at Keesler Air Force Base (January 9, 2020).
since its emergence following World War II. Today’s USAF human capital research program has its beginnings in a successful aviation psychology program. Out of this program, several disparate personnel research organizations were established and flourished in the 1950s and 1960s. Those organizations were unified in 1968 under the centralized oversight of the Air Force Human Resources Laboratory (AFHRL). With a mission to support manpower, personnel, and training research and development, AFHRL absorbed several existing research entities and established new ones to meet the needs of the broader Air Force. Specifically, AFHRL was responsible for:
planning and executing USAF exploratory and advanced development programs for selection, motivation, training, retention, education, utilization and career development of military personnel; also the composition of the personnel force and training equipment (AFHRL, 1972, quoted in Sims et al., 2014).
By 1972, AFHRL included 365 authorized manpower positions that included military and civilians with 13 percent holding a Ph.D. and 27 percent a Master’s degree. In short, the Air Force had a robust research program under AFHRL that was exclusively focused on manpower and personnel issues, including informing policy decisions. Starting in 1983, AFHRL underwent a series of organizational changes, first being assigned to the Aerospace Medical Division and later to the Armstrong Laboratory under the Human Systems Division. In 1997, the Armstrong Laboratory, along with other laboratories, was absorbed by the Air Force Research Laboratory (AFRL). That same year, AFRL suspended funding for manpower and personnel research, and realigned other elements of AFHRL to the Human Effectiveness Directorate. Whereas previously, personnel policy and human capital decisions benefited from a dedicated and robust strategic and comprehensive research and development operation coordinated through AFHRL, the laboratory’s absorption into AFRL and almost immediate dissolution resulted in a research vacuum. Since 1997, “there has been no single resource for [Air Force] consumers of personnel research and development, and there is no obvious organization for consumers (including, of course, those who set personnel policy) to which to turn for help and strategic guidance” (Sims et al., 2014, p. 20).
Of course, the mission did not end, and personnel and manpower issues and policy decisions continued to be important matters requiring informed scientific research. Policy for Air Force selection and classification testing remain the responsibility of the personnel staff at Air Force Headquarters (AF/A1), despite lack of a dedicated research entity to support those policy decisions. Various parts of the Air Force have picked up pieces and parts
of the mission, most often to serve the needs of their specific organizations or leadership. As needed, the Air Force also continues to benefit from expert policy analysis through external entities such as RAND’s Project Air Force. Furthermore, several Air Force organizations outside the purview of the AF/A1 staff also maintain limited capability to conduct research and development in this area to meet what are sometimes perceived to be unique organizational needs for personnel decisions (e.g., the U.S. Special Operations Forces community).
For Air Force leaders, the issue is whether this disaggregated approach provides the needed foundation for policy decisions, especially in light of the complexity of the ecosystem to which those policies affect and are effected. Furthermore, the issues that will be raised in Chapters 4 and 5 suggest it does not; as a result, the Air Force may not realize the ambitions it has for its HCM system.
As this chapter demonstrates through the USAF HCM ecosystem model, managing the human capital needs of the Total Force involves complicated and complex variables and relationships internal and external to the Air Force. Navigating current needs and future planning, including preparation for future shocks, requires an HCM system that is “self aware” and aligned to be agile in recognizing and responding to expected and unexpected change. Before presenting the committee’s analysis of opportunities to strengthen the USAF HCM system (Chapters 4–6), the following chapter discusses attributes of effective systems based on professional best practices.
Air Force Magazine. (2019). U.S. Air Force Almanac. Air Force Association. Available: https://www.airforcemag.com/magazine/almanac.
AFPC (Air Force Personnel Center). (2020). Military Demographics. Available: https://www.afpc.af.mil/Portals/70/documents/03_ABOUT/Military%20Demographics%20Jan%202020.pdf.
AFSOC (Air Force Special Operations Command). (2017). Air Force Special Operations Command. Available: https://www.afsoc.af.mil/About-Us/Fact-Sheets/Display/Article/162540/air-force-special-operations-command.
Byrnes, N. (2017). Air Force Faces Fighter Pilot Shortage. U.S. Air Force. Available: https://www.af.mil/News/Article-Display/Article/1055113/air-force-faces-fighter-pilot-shortage.
DeGrace, P., & L. Hulet Stahl. (1993). The Olduvai Imperative: CASE and the state of software engineering practice. Englewood Cliffs, NJ: Yourdon Press.
Griss, M.L. (1998). Architecting for large-scale systematic component reuse. Hewlett Packard Labs Technical Report, PL-98-132. Available: http://www.hpl.hp.com/techreports/98/HPL-98-132.html.
JAMRS (Joint Advertising, Market Research & Studies). (2016). The target population for military recruitment: Youth eligible to enlist without a waiver. Defense Manpower Data Center. Available: https://dacowits.defense.gov/Portals/48/Documents/General%20Documents/RFI%20Docs/Sept2016/JAMRS%20RFI%2014.pdf.
Losey, S. (2020). Air Force: No progress in closing pilot shortfall. Air Force Times. Available: https://www.airforcetimes.com/news/your-air-force/2020/03/04/air-force-no-progress-inclosing-pilot-shortfall.
Maier, M.W. (1996). Systems Architecting: An Emergent Discipline? IEEE Aerospace Applications Conference Proceedings. Available: https://ieeexplore.ieee.org/document/496066.
Martino, J.P. (1993). Technological forecasting for decision making (3rd ed.). New York, NY: McGraw-Hill Education.
Rechtin, E., & M.W. Maier. (1997). The art of systems architecting. New York, NY: CRC Press.
Rowe, D., J. Leaney, & D. Lowe. (1996). Development of a Systems Architecting Process for Computer Based Systems. Available: https://www.computer.org/csdl/proceedings-article/iceccs/1996/76140200/12OmNwD1pUF.
Schwartz, P. (1996). The art of the long view. New York, NY: Doubleday Dell Publishing Group.
Sims, C., C. Hardison, K. Keller, & A. Robyn. (2014). Air Force Personnel Research: Recommendations for Improved Alignment. RAND Corporation. Available: https://www.rand.org/pubs/research_reports/RR814.html.
Sterman, J.D. (2000). Business dynamics: Systems thinking and modeling for a complex world. New York, NY: McGraw-Hill Education.
USAFRS (U.S. Air Force Recruiting Service). (2019). Air Force Recruiting Service. Datasheets provided to the committee by Angelo Haygood. Available by request through the study’s public access file.
Williams, L.G., & C.U. Smith. (1998). Performance evaluation of software architectures. Proceedings of the First International Workshop on Software and Performance (pp. 164–177). New York, NY: ACM.