You are given two reports by the government agency.  

Report 1:
The Secret Service plays a critical role in protecting the President, Vice President, their immediate families, and national leaders, among others. In addition, the component is responsible for safeguarding the nation’s currency and financial payment systems. To accomplish its mission, Secret Service officials reported that, as of June 2018, the component had approximately 7,100 employees (including the Uniformed Division, special agents, and administrative, professional, and technical staff). These employees were assigned to the component’s headquarters in Washington, D.C., and 133 field offices located throughout the world (including 115 domestic offices and 18 international offices). The Secret Service’s employees are heavily dependent on the component’s IT infrastructure and communications systems to perform their daily duties. According to data reported on the Office of Management and Budget’s IT Dashboard, the component planned to spend approximately $104.8 million in fiscal year 2018 to modernize and maintain its IT environment. To manage this IT environment, the Secret Service hired a full-time CIO in November 2015. In addition, in an effort to improve its management structure, the component consolidated all IT staff and assets under this new CIO in March 2017. OCIO officials stated that these staff include the government employees who provide direct and indirect support of the day-to-day operations of the Secret Service’s enterprise systems and services. According to Secret Service officials, the component’s IT workforce included 190 staff, as of July 2018. These officials stated that 166 of these employees were located in the component’s headquarters in Washington, D.C., and 24 were located in domestic field offices. The officials also reported that these July 2018 staffing levels were below their current approved staffing level of 220 staff (which included 44 positions in domestic field offices). Secret Service IT staff also deploy to other locations, as necessary, to provide support for certain security activities. For example, the Secret Service reported that, in 2017, OCIO deployed over 79 staff to New York, N.Y., to provide communications support during the United Nations General Assembly. As a component of DHS, the Secret Service must follow the department’s policies and processes for managing acquisitions, including IT acquisitions. DHS categorizes its acquisition programs according to three levels that are determined by the life cycle costs of the programs. These levels then determine the extent of required program and project management and the acquisition decision authority (the individual responsible for management and oversight of the acquisition). The department also categorizes its acquisition programs as major or non- major based on expected cost. Table 1 describes the levels of DHS’s acquisition programs and their associated acquisition decision authorities. DHS’s policies and processes for managing major acquisition programs are primarily set forth in its Acquisition Management Directive 102-01 and Acquisition Management Instruction 102-01-001. In particular, these policies establish that a major acquisition program’s decision authority is to review the program at a series of predetermined acquisition decision events to assess whether the program is ready to proceed through the acquisition life cycle phases. Figure 1 depicts the acquisition life cycle established in DHS acquisition management policy. DHS’s Acquisition Management Directive and Instruction do not establish an acquisition life cycle framework for the department’s non-major acquisition programs. Instead, according to the Instruction, Component Acquisition Executives (i.e., the senior acquisition official within a component that is responsible for implementation, management, and oversight of the component’s acquisition process) are required to establish component-specific non-major acquisition policies and guidance that support the “spirit and intent” of the department’s acquisition policies. To that end, the Secret Service developed a policy that establishes an acquisition life cycle framework for its non-major acquisition programs. This acquisition framework for the component’s non-major acquisition programs is consistent with the acquisition framework that DHS established for its major acquisition programs. In particular, the Secret Service’s framework includes the same phases and decision events as DHS’s framework (e.g., acquisition decision event 2A, the point at which the acquisition decision authority determines whether a program may proceed into the obtain phase). In addition, DHS’s Systems Engineering Life Cycle Instruction and Guidebook outline a framework of major systems engineering activities and technical reviews that are to be conducted by all DHS programs and projects, both major and non-major. This framework is intended to ensure that appropriate systems engineering activities are planned and implemented, and that a program’s development effort is meeting the business need. In particular, the systems engineering life cycle framework consists of nine major activities (e.g., requirements definition, integration, and testing) and a set of related technical reviews (e.g., preliminary design review) and artifacts (e.g., requirements documents). DHS policy allows programs to tailor these activities, technical reviews, and artifacts based on the unique characteristics of the program (e.g., scope, complexity, and risk). For example, a program may combine systems engineering technical reviews and artifacts, or add additional reviews. This tailored approach must be documented in a program’s systems engineering life cycle tailoring plan. The systems engineering technical reviews are intended to provide DHS the opportunity to determine how well a program has completed the necessary systems engineering activities. Each technical review includes a minimum set of exit criteria that must be satisfied before a program may move on to the next systems engineering activity. At the end of the technical review, the program manager must develop a technical review completion letter that documents the outcome of the review, including stakeholder concurrence that the exit criteria were satisfied. Moreover, DHS’s agile instruction, which was first issued in April 2016 and updated in April 2018, identifies agile as the preferred development approach for the department’s IT programs and projects. Agile is a type of incremental (i.e., modular) development, which calls for the rapid delivery of software in small, short increments rather than in the typically long, sequential phases of a traditional waterfall approach. DHS’s agile instruction also states that component CIOs are to set modular (i.e., incremental) outcomes and target measures to monitor progress in achieving agile implementation for IT programs and projects. To that end, the department identified core metrics that its agile IT programs are to use to monitor progress, including the number of story points completed per release and the number of releases per quarter. Further, DHS policy and guidance have established an acquisition (i.e., contract) review process that is intended to enable the DHS CIO to review and effectively guide the department’s IT expenditures. According to the department’s IT acquisition review guidance, DHS components with a CIO (which includes the Secret Service) are to submit to DHS OCIO for review, IT acquisitions that (1) have total estimated procurement values of $2.5 million or more; and (2) are funded by a level 1, 2, or 3 program with a life cycle cost estimate of at least $50 million (i.e., a major investment, as defined by DHS’s capital planning and investment control guidance). DHS policies and guidance also establish numerous responsibilities for the department’s component-level CIOs that are aimed at ensuring proper oversight and management of the components’ IT investments. Among other things, these component-level CIO responsibilities relate to topics such as IT budgeting, portfolio management, and oversight of programs’ systems engineering life cycles. Table 2 identifies 14 selected IT oversight responsibilities for DHS’s component CIOs. The Secret Service acquires IT infrastructure and services that are intended to improve its ability to execute its investigation and protection missions. According to data reported on the Office of Management and Budget’s IT Dashboard, the Secret Service planned to spend about $104.8 million on IT in fiscal year 2018, which included approximately $34.6 million for the development and modernization of its IT infrastructure and services, and about $70.2 million for the operations and maintenance of this infrastructure (including 21 existing IT systems). Also according to data reported on the IT Dashboard, as of April 2018, the Secret Service had one major IT investment (called the Information Integration and Technology Transformation and discussed in more detail later in this report), seven non-major IT investments, and one non- standard infrastructure investment. Figure 2 depicts the Secret Service’s planned IT spending for fiscal year 2018. The Secret Service has faced long-standing challenges in managing its IT infrastructure. For example, A National Security Agency audit of the Secret Service’s IT environment in 2008 identified network and system vulnerabilities that needed immediate remediation to protect the component’s systems and electronic information. The Secret Service determined in 2010 that it had IT capability gaps associated with three key areas: network security, information sharing and situational awareness, and operational communications. The component reported that it required a significant IT modernization effort with sustained investment of resources to replace dated and restrictive network and communications capabilities. The Secret Service also reported in 2010 that it had 42 mission- support applications that were operating on a 1980’s mainframe that lacked multi-level security (i.e., the ability to view classified information from two security levels, such as secret and top secret, at the same time), was beyond its equipment life cycle, and was at risk of failing. Further, in 2011, DHS’s Office of Inspector General reported that the Secret Service’s existing infrastructure did not meet current operational requirements. According to the Secret Service, this dated infrastructure was unable to support newer technologies (e.g., Internet protocol), share common DHS enterprise services, or migrate to the department’s consolidated data centers. To address challenges with its IT environment, in 2009, the Secret Service initiated the IITT investment, which is intended to modernize and enhance the component’s infrastructure, communications systems, applications, and processes. In particular, IITT is a portfolio of programs and projects that are meant to, among other things, improve systems availability in support of the Secret Service’s business operations, increase interoperability with other government systems and networks, enhance the component’s system and network security, and enable scalability to support growth. From 2010 to July 2018, according to OCIO officials, the Secret Service spent approximately $392 million on IITT. In fiscal year 2018, the component had planned to spend approximately $42.7 million on IITT (i.e., about 40 percent of its total planned IT spending for the fiscal year), according to data reported on the Office of Management and Budget’s IT Dashboard. In total, the planned life cycle cost estimate for IITT is at least $811 million. As of June 2018, IITT was a major investment comprised of two programs (one of which included three projects) and one standalone project (i.e., it was not part of another program) that had capabilities that were in planning or development and modernization. These programs and project were the Enabling Capabilities program, Enterprise Resource Management System program (which included three projects that were each being implemented using an agile methodology: Uniformed Division Resource Management System, Events Management, and Enterprise-wide Scheduling), and the Multi-Level Security project. Table 3 describes the IITT programs and projects that had capabilities that were in planning or development and modernization, as of June 2018. The table also includes the associated level, acquisition decision authority, estimated life cycle costs, and planned or actual dates of operational capability for each of the programs and projects. (Appendix II also provides additional information on these programs and projects.) The Enabling Capabilities program within IITT is designated as a major acquisition program. As such, its acquisition decision authority is the DHS Under Secretary for Management, and both DHS and the Secret Service provide oversight to this program. IITT’s other program and project—the Enterprise Resource Management System program (which includes three projects, as discussed earlier) and Multi-Level Security project—are designated non-major acquisition programs. In June 2011, DHS’s Under Secretary for Management delegated acquisition decision authority for this non-major program and project to the Secret Service Component Acquisition Executive. As such, oversight of the Enterprise Resource Management System program (including its three projects) and the Multi- Level Security project is conducted primarily at the component level. The Secret Service also implemented other capabilities that are now in operations and maintenance (i.e., the capabilities have been fielded and are operational) as part of the IITT investment, such as a capability to move data between systems in separate classification levels (e.g., top secret and secret) and communications interoperability. Table 4 describes IITT capabilities that are in operations and maintenance. DHS, including the Secret Service, has faced long-standing challenges in effectively managing its workforce. In January 2003, we designated the implementation and transformation of DHS as high risk, including its management of human capital, because it had to transform 22 agencies—several with major management challenges—into one department. This represented an enormous and complex undertaking that would require time to achieve in an effective and efficient manner. Since that time, the department has made important progress in strengthening and integrating its management functions. Nevertheless, we have continued to report that significant work remains for DHS to improve these management functions. Among other things, we previously reported that the department had lower average employee morale than the average for the rest of the federal government. We also reported that, in 2011, based on employee responses to the Office of Personnel Management’s Federal Employee Viewpoint Survey—a tool that measures employees’ perceptions of whether and to what extent conditions characterizing successful organizations are present in their agency—DHS was ranked 31st out of 33 large agencies on the Partnership for Public Service’s Best Places to Work in the Federal Government rankings. The most recent results of these surveys in 2017 showed that DHS continues to maintain its low rankings. DHS’s Office of Inspector General has reported on challenges that the Secret Service has faced in managing its IT workforce. Specifically, in October 2016, the Inspector General reported that the Secret Service CIO did not have oversight of, or authority over, all IT resources, including the workforce; in particular, almost all of the component’s IT employees were located in a division outside of OCIO; and the Secret Service had vacancies in key positions responsible for managing IT, including not having a full-time CIO from December 2014 through November 2015. As previously discussed, the Secret Service has taken actions to address these two issues with the management of its IT workforce. These actions included hiring its full-time CIO in November 2015 and consolidating the workforce and all IT assets under this CIO in March 2017. Of the 14 selected responsibilities established for component-level CIOs in DHS’s IT management policies, the Secret Service CIO had fully implemented 11 responsibilities and had partially implemented 3 responsibilities. Table 5 summarizes the extent to which the Secret Service CIO had implemented each of the 14 responsibilities. The Secret Service CIO fully implemented 11 of the 14 selected component-level CIO responsibilities. Examples of the responsibilities that the CIO fully implemented are as follows: Develop, implement, and maintain a detailed IT strategic plan. Consistent with DHS’s IT Integration and Management directive, in January 2017, the Secret Service CIO developed an IT strategic plan that outlined the CIO’s strategic IT goals and objectives, as well as tasks intended to meet the goals and objectives. The CIO maintained this strategic plan, to include updating it in January 2018. The CIO also took steps to implement the tasks identified within the strategic plan, such as working to develop an IT training program. In particular, as part of this effort to develop an IT training program, OCIO identified recommended training for the office’s various IT workforce groups (discussed in more detail later in this report). Concur with each program’s and/or project’s systems engineering life cycle tailoring plan. In accordance with DHS’s Systems Engineering Life Cycle instruction, the Secret Service CIO concurred with the systems engineering life cycle tailoring plan for one program and three projects included in the Secret Service’s IITT investment. Specifically, the CIO documented his approval via his signature on the tailoring plans for IITT’s Enabling Capabilities program, and Multi-Level Security, Uniformed Division Resource Management System, and Events Management projects. Participate on DHS’s CIO Council, Enterprise Architecture Board, or other councils/boards as appropriate, and appoint employees to serve when necessary. As required by DHS’s IT Integration and Management directive, the Secret Service CIO participated on two required DHS-level councils/boards, and appointed a delegate to serve in his place, when necessary. Specifically, the Secret Service CIO or the CIO’s delegate—the Deputy CIO—attended bi-monthly meetings of the DHS CIO Council. In addition, another Secret Service CIO appointee—the component’s Chief Architect—attended an ad hoc meeting of the Enterprise Architecture Board in June 2017. In addition, the Secret Service CIO had partially implemented three component-level CIO responsibilities, as follows. Manage the component IT investment portfolio, including establishing a component-level IT acquisition review process that enables component and DHS review of component acquisitions (i.e., contracts) that contain IT. As directed in DHS’s Capital Planning and Investment Control directive and guidebook, the Secret Service CIO took steps to manage the component’s IT investment portfolio, including reviewing certain contracts containing IT. For example, among our random sample of 33 IT contracts that the Secret Service awarded between October 1, 2016, and June 30, 2017, we found that the CIO or the CIO’s delegate had reviewed 31 of these contracts. However, the CIO had not established and documented a defined process for reviewing contracts containing IT, which may have contributed to why the CIO or the CIO’s delegate did not review 2 of the 33 contracts in our sample. OCIO officials were unable to explain why neither of these officials reviewed the 2 contracts, which had a combined planned total procurement value of approximately $1.75 million. In particular, one of the contracts, with a planned total procurement value of about $1,122,934, was to provide credentialing services for the 2017 Presidential Inauguration. The other contract, with a planned total procurement value of about $629,337, was to provide maintenance support for a logistics system. The OCIO officials acknowledged that both contracts should have been approved by one of these officials. Without establishing and documenting an IT acquisition review process that ensures that the CIO or the CIO’s delegate reviews all contracts containing IT, as appropriate, the CIO’s ability to analyze the contracts to ensure that they are a cost-effective use of resources and are aligned with the component’s missions and goals is limited. Ensure all component IT policies are in compliance and alignment with DHS IT directives and instructions. As required by DHS’s IT Integration and Management directive, the Secret Service CIO had ensured that certain component IT policies were in compliance and alignment with DHS IT directives and instructions. For example, in alignment with the department’s IT Integration and Management directive, the Secret Service’s Investment Governance for IT policy specifies that the component CIO (in conjunction with each Secret Service Office) is responsible for developing the component IT spend plan, as well as developing and maintaining an IT strategic plan. However, the Secret Service’s enterprise governance policy was not in compliance with DHS’s IT Integration and Management directive. Specifically, while the department’s policy states that the Secret Service CIO is responsible for developing and reviewing the component’s IT budget formulation and execution, the Secret Service’s enterprise governance policy does not specify this as the CIO’s responsibility. According to OCIO officials, the Secret Service CIO participates in the development and review of the IT budget formulation and execution as a member of the Executive Resources Board (the Secret Service’s highest-level governing body, which has the final decision authority and responsibility for enterprise governance), and the Secret Service Deputy CIO is a voting member of the Enterprise Governance Council (the Secret Service’s second-level governance body and advisory council to the Executive Resources Board). However, the Secret Service’s enterprise governance policy has not been updated to reflect these roles. The Secret Service did not update its enterprise governance policy to properly reflect the CIO’s and Deputy CIO’s roles on the Executive Resources Board or Enterprise Governance Council because OCIO officials were not aware that these roles were not properly documented in the component’s policy until we identified this issue during our review. Further compounding the issue of the Secret Service’s enterprise governance policy not properly reflecting the CIO’s and Deputy CIO’s roles and responsibilities on the component’s governance boards is that the Secret Service has not developed a charter for its Executive Resources Board. We have previously reported that a best practice for effective investment management is to define and document the board’s membership, roles, and responsibilities. One such way to do so is via a charter. According to Secret Service officials, the component does not have a charter for the board because, while the Secret Service has established the board pursuant to law, there is little statutory guidance on how the board must be formalized, including whether a charter is required. The officials acknowledged that development of a board charter is a best practice. They stated that, in response to our review, the component has begun efforts to develop a charter for the Executive Resources Board, but they did not know when it would be completed. Until the Secret Service updates its enterprise governance policy to specify (1) the CIO’s current role and responsibilities on the Executive Resources Board, to include developing and reviewing the IT budget formulation and execution, and (2) the Deputy CIO’s role and responsibilities on the Enterprise Governance Council, the CIO’s ability to develop and review the component’s IT budget may be limited. Further, until the Secret Service develops a charter for its Executive Resources Board that specifies the roles and responsibilities of all board members, including the CIO, the Secret Service will not be effectively positioned to ensure that all members understand their roles and responsibilities on the board and will perform them as expected. Set modular outcomes and target measures to monitor the progress in achieving agile implementation for IT programs and/or projects within their component. Consistent with DHS policy, the Secret Service CIO has set modular outcomes and target measures to monitor the progress of two IITT projects that the component is implementing using an agile methodology—Uniformed Division Resource Management System and Events Management. For example, the modular outcomes set for these projects included measuring planned and actual burndown (i.e., the number of user stories completed). In addition, the projects were to measure their velocity (i.e., the rate of work completed) for each sprint (i.e., a set period of time during which the development team is expected to complete tasks related to developing a piece of working software). However, the modular outcomes and target measures did not include product quality or post-deployment user satisfaction, although such measures are leading practices for managing agile projects. According to Secret Service OCIO officials, the component does not mandate the specific metrics that its agile projects are to use; instead, each project is to determine the metrics based on stakeholder requirements and unique project characteristics. The officials further stated that these metrics are to be documented in an acquisition program baseline and program management plan; this baseline and program management plan are then to be approved by the CIO. To its credit, the component’s one agile project that, as of May 2018, had deployed its system to users—the Uniformed Division Resource Management System—did measure product quality. OCIO officials also stated that they regularly receive verbal, undocumented feedback from users on the system and they plan to conduct a documented user satisfaction survey on this system by September 2018. Nevertheless, without ensuring that product quality and post- deployment user satisfaction metrics are included in the modular outcomes and target measures that the CIO sets for monitoring agile projects, the Secret Service lacks assurance that the Events Management project or other future agile projects will measure product quality or post-deployment user satisfaction. Without guidance specifying that agile projects track these metrics, the projects may not do so and the CIO may be limited in his knowledge of the progress being made on these projects. Workforce planning and management is essential for ensuring that federal agencies have the talent, skill, and experience mix they need to execute their missions and program goals. To help agencies effectively conduct workforce planning and management, the Office of Personnel Management, the Chief Human Capital Officers Council, DHS, the Secret Service, and we have identified numerous leading practices related to five workforce areas: strategic planning, recruitment and hiring, training and development, employee morale, and performance management. Table 6 identifies the five workforce areas and 15 selected leading practices associated with these areas (3 practices within each area). Of the five selected workforce planning and management areas, the Secret Service had substantially implemented two of the areas and minimally implemented three of the areas for its IT workforce. In addition, of the 15 selected leading practices associated with these workforce planning and management areas, the Secret Service had fully implemented 3 practices, partly implemented 8 practices, and did not implement any aspects of 4 practices. Table 7 summarizes the extent to which the Secret Service had implemented for its IT workforce the five selected workforce planning and management areas and 15 selected leading practices associated with those areas, as of June 2018. Strategic workforce planning is an essential activity that an agency needs to conduct to ensure that its human capital program aligns with its current and emerging mission and programmatic goals, and that the agency is able to meet its future needs. We previously identified numerous leading practices related to IT strategic workforce planning, including that an organization should (1) establish and maintain a strategic workforce planning process, including developing all competency and staffing needs; (2) regularly assess competency and staffing needs, and analyze the IT workforce to identify gaps in those areas; and (3) develop strategies and plans to address gaps in competencies and staffing. The Secret Service minimally implemented the three selected leading practices associated with the IT strategic workforce planning area. Specifically, the component partly implemented two of the practices and did not implement one practice. Table 8 lists these selected leading practices and provides our assessment of the Secret Service’s implementation of the practices. Establish and maintain a strategic workforce planning process, including developing all competency and staffing needs—partly implemented. The Secret Service took steps to establish a strategic workforce planning process for its IT workforce. For example, the Secret Service CIO developed and maintained a plan that identified strategic workforce planning tasks, to include analyzing the staffing requirements of the IT workforce. In addition, the Secret Service defined general core competencies (e.g., communication and customer service) for its workforce, including IT staff. However, OCIO did not identify all required knowledge and skills needed to support this office’s functions. In particular, while OCIO identified certain technical competencies that its IT workforce needs, such as cybersecurity, the office did not identify and document all of the technical competencies that it needs. OCIO officials stated that they did not identify and document the technical competencies that the office needs because the Secret Service was focused on reorganizing the IT workforce under a single, centralized reporting chain within the CIO’s office. Consequently, the officials stated that they had not completed the work to identify all required IT knowledge and skills necessary to support the office. Yet, the Secret Service completed the IT workforce reorganization effort over a year ago, in March 2017 and, since then, OCIO has not identified all of the required IT knowledge and skills that the office needs. OCIO officials told us that they plan to identify all of the technical competency needs for the IT workforce, but they were unable to specify a time frame for when these needs would be fully identified. Until OCIO identifies all of the required knowledge and skills for the IT workforce, the office will be limited in its ability to identify and address any competency gaps associated with this workforce. In addition, the Secret Service did not reliably determine the number of IT staff that it needs in order to support OCIO’s functions. Specifically, in January 2017, an independent review of the staffing model that the component used to identify its IT workforce staffing needs found that the model was not based on any verifiable underlying data. In late August 2018, Office of Human Resources officials reported that they had hired a contractor in early August 2018 to update the staffing model to improve the quality of the data. These officials expected the contractor to finish updating the model by August 2019. The officials plan to use the updated model to identify the Secret Service’s IT workforce staffing needs for fiscal year 2021. Updating the staffing model to incorporate verifiable workload data should increase the likelihood that the Secret Service is able to appropriately identify its staffing needs for its IT workforce. Regularly assess competency and staffing needs, and analyze the IT workforce to identify gaps in those areas—not implemented. The Secret Service regularly assessed the competency and staffing needs for 1 of the occupational series within its IT workforce (i.e., the 2210 IT Specialist series). However, it did not regularly assess the competency and staffing needs for the remaining 11 occupational series that are associated with the component’s IT workforce, nor identify any gaps that it had in those areas. OCIO officials stated that they had not assessed these needs or identified competency or staffing gaps because, among other things, the Secret Service was focused on reorganizing the IT workforce under a single, centralized reporting chain within the CIO’s office. However, as previously mentioned, the component completed this effort in March 2017, but OCIO did not subsequently assess its competency and staffing needs, nor identify gaps in those areas. OCIO officials reported that they plan to assess the competencies of the IT workforce to identify any gaps that may exist; however, they were unable to identify a specific date by which they expect to have the capacity to complete this assessment. Until OCIO regularly analyzes the IT workforce to identify its competency needs and any gaps it may have, OCIO will be limited in its ability to determine whether its IT workforce has the necessary knowledge and skills to meet its mission and goals. Further, Office of Human Resources officials reported that they plan to update the staffing model that they use to identify their IT staffing needs to include more reliable workload data. However, as discussed earlier, the Secret Service had not yet developed that updated model to determine its IT staffing needs. Office of Human Resources officials reported that once they update the staffing model they plan to re- evaluate the Secret Service’s IT staffing needs. The officials also stated that, going forward, they plan to reassess these needs each year as part of the annual budget cycle. Regular assessments of the IT workforce’s staffing needs should increase the likelihood that the Secret Service is able to appropriately identify the number of IT staff it needs to meet its mission and programmatic goals. Develop strategies and plans to address gaps in competencies and staffing—partly implemented. The Secret Service developed recruiting and hiring strategies to address certain competency and staffing needs (e.g., cybersecurity) for its IT workforce. These strategies included, among other things, participating in DHS-wide recruiting events and using special hiring authorities. However, because OCIO did not identify all of its IT competency and staffing needs, and lacked a current analysis of its entire IT workforce, the Secret Service could not provide assurance that the recruiting and hiring strategies it developed were specifically targeted towards addressing current OCIO competency and staffing gaps. For example, without an analysis of the IT workforce’s skills, OCIO did not know the extent to which it had gaps in areas such as device management and cloud computing. As a result, the Secret Service’s recruiting strategies may not have been targeted to address any gaps in those areas. Until the Secret Service updates its recruiting and hiring strategies and plans to address all IT competency and staffing gaps identified (after OCIO completes its analysis of the entire IT workforce, as discussed earlier), the Secret Service will be limited in its ability to effectively recruit and hire staff to fill those gaps. According to the Office of Personnel Management, the Chief Human Capital Officers Council, and our prior work, once an agency has determined the critical skills and competencies that it needs to achieve programmatic goals, and identifies any competency or staffing gaps in its current workforce, the agency should be positioned to build effective recruiting and hiring programs. It is important that an agency has these programs in place to ensure that it can effectively recruit and hire employees with the appropriate skills to meet its various mission requirements. The Office of Personnel Management, the Chief Human Capital Officers Council, and we have also identified numerous leading practices associated with effective recruitment and hiring programs. Among these practices, an agency should (1) implement recruiting and hiring activities to address skill and staffing gaps by using the strategies and plans developed during the strategic workforce planning process; (2) establish and track metrics to monitor the effectiveness of the recruitment program and hiring process, including their effectiveness at addressing skill and staffing gaps, and report to agency leadership on progress addressing those gaps; and (3) adjust recruitment plans and hiring activities based on recruitment and hiring effectiveness metrics. The Secret Service minimally implemented the selected three leading practices associated with the recruitment and hiring workforce area. Specifically, the component partly implemented one of the three practices and did not implement the other two practices. Table 9 lists these selected practices and provides our assessment of the Secret Service’s implementation of the practices. Implement recruiting and hiring activities to address skill and staffing gaps by using the strategies and plans developed during the strategic workforce planning process—partly implemented. OCIO officials implemented the activities identified in the Secret Service’s recruiting and hiring plans. For example, as identified in its recruiting plan, OCIO participated in a February 2017 career fair to recruit job applicants at a technology conference. In addition, in August 2017, OCIO participated in a DHS-wide recruiting event. Secret Service officials reported that, during this event, they conducted four interviews for positions in OCIO. However, as previously discussed, OCIO did not identify all of its IT competency and staffing needs, and lacked a current analysis of its entire IT workforce. Without complete knowledge of its current IT competency and staffing gaps, the Secret Service could not provide assurance that the recruiting and hiring strategies that it had implemented fully addressed these gaps. Establish and track metrics to monitor the effectiveness of the recruitment program and hiring process, including their effectiveness at addressing skill and staffing gaps, and report to agency leadership on progress addressing those gaps—not implemented. The Secret Service had not established and tracked metrics for monitoring the effectiveness of its recruitment and hiring activities for the IT workforce. Officials in the Office of Human Resources attributed this to staffing constraints and said their priority was to address existing staffing gaps associated with the Secret Service’s law enforcement groups. In June 2018, Office of Human Resources officials stated that they plan to implement metrics to monitor the effectiveness of the hiring process for the IT workforce by October 2018. The officials also stated that they were in the process of determining (1) the metrics that are to be used to monitor the effectiveness of their workforce recruiting efforts and (2) whether they need to acquire new technology to support this effort. However, the officials did not know when they would implement the metrics for assessing the effectiveness of the recruitment activities and whether they would report the results to leadership. Until the Office of Human Resources (1) develops and tracks metrics to monitor the effectiveness of the Secret Service’s recruitment activities for the IT workforce, including their effectiveness at addressing skill and staffing gaps; and (2) reports to component leadership on those metrics, the Secret Service and the Office of Human Resources will be limited in their ability to analyze the recruitment program to determine whether the program is effectively addressing IT skill and staffing gaps. Further, Secret Service leadership will lack the information necessary to make effective recruitment decisions. Adjust recruitment plans and hiring activities based on recruitment and hiring effectiveness metrics—not implemented. While the Secret Service CIO stated in June 2018 that he planned to adjust the office’s recruiting and hiring strategies to focus on entry- level staff rather than mid-career employees, this planned adjustment was not based on metrics that the Secret Service was tracking. Instead, the CIO stated that he planned to make this change because his office determined that previous mid-career applicants were often unwilling or unable to wait for the Secret Service’s lengthy, required background investigation process to be completed. However, as previously mentioned, the Secret Service did not develop and implement any metrics for assessing the effectiveness of the recruitment and hiring activities for the IT workforce. As a result, the Office of Human Resources and OCIO were not able to use such metrics to inform adjustments to their recruiting and hiring plan and activities, thus, reducing their ability to target potential candidates for hiring. Until the Office of Human Resources and OCIO adjust their recruitment and hiring plans and activities as necessary, after establishing and tracking metrics for assessing the effectiveness of these activities for the IT workforce, the Secret Service will be limited in its ability to ensure that its recruiting plans and activities are appropriately targeted to potential candidates. In addition, the component will lack assurance that these plans and activities will effectively address skill and staffing gaps within its IT workforce. An organization should invest in training and developing its employees to help ensure that its workforce has the information, skills, and competencies that it needs to work effectively. In addition, training and development programs are an integral part of a learning environment that can enhance an organization’s ability to attract and retain employees with the skills and competencies needed to achieve cost-effective and timely results. DHS, the Secret Service, and we have previously identified numerous leading training and development-related practices. Among those practices, an organization should (1) establish a training and development program to assist the agency in achieving its mission and goals; (2) use tracking and other control mechanisms to ensure that employees receive appropriate training and meet certification requirements, when applicable; and (3) collect and assess performance data (including qualitative or quantitative measures, as appropriate) to determine how the training program contributes to improved performance and results. The Secret Service minimally implemented the selected three leading practices associated with the training and development workforce area. Specifically, the component partly implemented two of the three practices and did not implement one practice. Table 10 lists these selected leading practices and provides our assessment of the Secret Service’s implementation of the practices. Establish a training and development program to assist the agency in achieving its mission and goals—partly implemented. OCIO was in the process of developing a training program for its IT workforce. For example, OCIO developed a draft training plan that identified recommended training for the office’s various IT workforce groups (e.g., voice communications employees). However, the office had not defined the required training for each IT workforce group. In addition, OCIO officials had not yet determined which activities they would implement as part of the training program (e.g., soliciting employee feedback after training is completed and evaluating the effectiveness of specific training courses), nor did they implement those activities. OCIO officials stated that they had not yet fully implemented a training program because their annual training budget for fiscal year 2018 was not sufficient to implement such a program. However, resource constrained programs especially benefit from identifying and prioritizing training activities to inform training budget decisions. Until OCIO (1) defines the required training for each IT workforce group, (2) determines the activities that it will include in its IT workforce training and development program based on its available training budget, and (3) implements those activities, the office may be limited in its ability to ensure that the IT workforce has the necessary knowledge and skills for their respective positions. Use tracking and other control mechanisms to ensure that employees receive appropriate training and meet certification requirements, when applicable—partly implemented. OCIO used a training system to track that the managers for IITT’s programs had met certain certification requirements for their respective positions. In addition, OCIO manually tracked the technical training that certain IT staff took. However, as discussed earlier, OCIO did not define the required training for each IT workforce group. As such, the office was unable to ensure that IT staff received the appropriate training relevant to their respective positions. Until it ensures that IT staff complete training specific to their positions (after defining the training required for each workforce group), OCIO will have limited assurance that the workforce has the necessary knowledge and skills. Collect and assess performance data (including qualitative or quantitative measures, as appropriate) to determine how the training program contributes to improved performance and results—not implemented. As previously discussed, OCIO did not fully implement a training program for the IT workforce; as such, the office was unable to collect and assess performance data related to such a program. OCIO officials stated that, once they fully implement a training program, they intend to collect and assess data on how this program contributes to improved performance. However, the officials were unable to specify a time frame for when they would do so. Until OCIO collects and assesses performance data (including qualitative or quantitative measures, as appropriate) to determine how the IT training program contributes to improved performance and results (once the training program is implemented), the office may be limited in its knowledge of whether the training program is contributing to improved performance and results. Employee morale is important to organizational performance and an organization’s ability to retain talent to perform its mission. We have previously identified numerous leading practices for improving employee morale. Among other things, we have found that an organization should (1) determine root causes of employee morale problems by analyzing employee survey results using techniques such as comparing demographic groups, benchmarking against similar organizations, and linking root cause findings to action plans; and develop and implement action plans to improve employee morale; (2) establish and track metrics of success for improving employee morale, and report to agency leadership on progress improving morale; and (3) maintain leadership support and commitment to ensure continued progress in improving employee morale, and demonstrate sustained improvement in morale. With regard to its IT workforce, the Secret Service substantially implemented the selected three practices associated with the employee morale workforce area. Specifically, the component fully implemented two of the selected practices and partly implemented one practice. Table 11 lists these selected practices and provides our assessment of the Secret Service’s implementation of the practices. Determine root causes of employee morale problems by analyzing employee survey results using techniques such as comparing demographic groups, benchmarking against similar organizations, and linking root cause findings to action plans. Develop and implement action plans to improve employee morale—fully implemented. The Secret Service used survey analysis techniques to determine the root causes of its low employee morale, on which we have previously reported. For example, the component conducted a benchmarking exercise where it compared the morale of the Secret Service’s employees, including IT staff, to data on the morale of employees at other agencies, including the U.S. Capitol Police, U.S. Coast Guard, and the Drug Enforcement Administration. As part of this exercise, the Secret Service also compared its employee work-life offerings (e.g., on-site childcare and telework program) to those available at other agencies. In addition, the Secret Service developed and implemented action plans for improving employee morale. Among these action plans, for example, the component implemented a student loan repayment program and expanded its tuition assistance program’s eligibility requirements. Establish and track metrics of success for improving employee morale, and report to agency leadership on progress improving morale—fully implemented. The Secret Service tracked metrics for improving employee morale and reported the results to leadership. For example, the component tracked metrics on the percentage of the workforce, including IT staff, that participated in the student loan repayment and tuition assistance programs. In addition, the Chief Strategy Officer reported to the Chief Operating Officer the results related to meeting those metrics. Maintain leadership support and commitment to ensure continued progress in improving employee morale, and demonstrate sustained improvement in morale—partly implemented. Secret Service leadership developed and implemented initiatives that demonstrated their commitment to improving the morale of the Secret Service’s workforce. For example, since 2014, the Secret Service had worked with a contractor to identify ways to improve the morale of its entire workforce, including IT staff. However, as of June 2018, the Secret Service was unable to demonstrate that it had sustained improvement in the morale of the component’s IT staff. In particular, the component was only able to provide IT workforce-specific results from one employee morale assessment that was conducted subsequent to the consolidation of this workforce into OCIO in March 2017. These results were from an assessment conducted by the component’s Inspection Division in December 2017 (the assessment found that the majority of the Secret Service’s IT employees rated their morale as “very good” or “excellent.”) While the component also provided certain employee morale results from the Office of Personnel Management’s Federal Employee Viewpoint Survey in 2017, these results were not specific to the IT workforce. Instead, this workforce’s results were combined with those from staff in another Secret Service division. According to OCIO officials, the results were combined because, at the time of the survey, the IT workforce was administratively identified as being part of that other division. OCIO officials stated that, going forward, they plan to continue to assess the morale of the IT workforce on an annual basis as part of the Federal Employee Viewpoint Survey. In addition, the officials stated that OCIO-specific results may be available as part of the 2018 survey results, which the officials expect to receive by September 2018. By measuring employee satisfaction on an annual basis, the Secret Service should have increased knowledge of whether its initiatives that are aimed at improving employee morale are in fact increasing employee satisfaction. Agencies can use performance management systems as a tool to foster a results-oriented organizational culture that links individual performance to organizational goals. We have previously identified numerous leading practices related to performance management that are intended to enhance performance and ensure individual accountability. Among the performance management practices, agencies should (1) establish a performance management system that differentiates levels of staff performance and defines competencies in order to provide a fuller assessment of performance, (2) explicitly align individual performance expectations with organizational goals to help individuals see the connection between their daily activities and organizational goals, and (3) periodically provide individuals with regular performance feedback. The Secret Service substantially implemented the selected three leading practices associated with the performance management workforce area. Specifically, the component fully implemented one of the three practices and partly implemented the other two practices. Table 12 lists these selected leading practices and provides our assessment of the Secret Service’s implementation of the practices. Establish a performance management system that differentiates levels of staff performance and defines competencies in order to provide a fuller assessment of performance—partly implemented. The Secret Service’s performance management process requires leadership to make meaningful distinctions between levels of staff performance. In particular, the component’s performance plans for IT staff, which are developed by the Office of Human Resources and tailored by OCIO, as necessary, specify the criteria that leadership use to determine if an individual has met or exceeded the expectations associated with each competency identified in their respective performance plan. The performance plans include pre-established, department-wide competencies that are set by DHS, as well as occupational series-specific goals that may be updated by the Secret Service. However, because OCIO did not fully define and document all of its technical competency needs for the IT workforce, as discussed earlier, the Secret Service’s performance plans for IT staff did not include performance expectations related to the full set of technical competencies required for their respective positions. In addition, because OCIO officials were unable to specify a time frame for when they will identify all of the technical competency needs for the IT workforce (as previously discussed), the officials were also unable to specify a time frame for when they would update the IT workforce’s performance plans to include those relevant technical competencies. Until OCIO updates the performance plans for each occupational series within the IT workforce to include the relevant technical competencies, once identified, against which IT staff performance should be assessed, the office will be limited in its ability to provide IT staff with a complete assessment of their performance. In addition, Secret Service management will have limited knowledge of the extent to which IT staff are meeting all relevant technical competencies. Explicitly align individual performance expectations with organizational goals to help individuals see the connection between their daily activities and organizational goals—partly implemented. The Secret Service’s performance plans for IT staff identified certain goals that appeared to be related to organizational goals and objectives. For example, the performance plan for the Telecommunications Specialist occupational series (which is one of the series included in OCIO’s IT workforce) identified a goal for staff to support the voice, wireless, radio, satellite, and video systems serving the Secret Service’s protective and investigative mission. This performance plan goal appeared to be related to the component’s strategic goal on Advanced Technology, which included an objective to create the infrastructure needed to fulfill mission responsibilities. However, the Secret Service was unable to provide documentation that explicitly showed how individual employee performance links to organizational goals, such as a mapping of the goals identified in employee performance plans to organizational goals. Specifically, while Office of Human Resources officials stated that each Secret Service directorate is responsible for ensuring that employee goals map to high-level organizational goals, OCIO officials stated that they did not complete this mapping. The officials were unable to explain why they did not align the goals in their employees’ performance plans to the component’s high-level goals. According to the officials, the Secret Service is in the process of implementing a new automated tool that will require each office to explicitly align individual performance expectations to organizational goals. The officials stated that OCIO plans to use this tool to create employees’ fiscal year 2019 performance plans. By explicitly demonstrating how individual performance expectations align with organizational goals, the Secret Service’s IT staff should have a better understanding of how their daily activities contribute towards achieving the Secret Service’s goals. Periodically provide individuals with regular performance feedback—fully implemented. Secret Service leadership periodically provided their IT staff with performance feedback. Specifically, on an annual basis, OCIO staff received feedback during a mid-year and end-of-year performance feedback assessment. In our prior work, we have stressed that candid and constructive feedback can help individuals maximize their contribution and potential for understanding and realizing the goals and objectives of an organization. Further, this feedback is one of the strongest drivers of employee engagement. According to leading practices of the Software Engineering Institute, effective program oversight includes monitoring program performance and conducting reviews at predetermined checkpoints or milestones. This is done by, among other things, comparing actual cost, schedule, and performance data with estimates in the program plan and identifying significant deviations from established targets or thresholds for acceptable performance levels. In addition, the Software Engineering Institute previously identified leading practices for effectively monitoring the performance of agile projects. According to the Institute, agile development methods focus on delivering usable, working software frequently; as such, it is important to measure the value delivered during each iteration of these projects. To that end, the Institute reported that agile projects should be measured on velocity (i.e., number of story points completed per sprint or release), development progression (e.g., the number of user stories planned and accepted), product quality (e.g., number of defects), and post-deployment user satisfaction. DHS and the Secret Service had fully implemented the selected leading practice for monitoring the performance of one program and three projects within the IITT investment, and conducting reviews of this program and these projects at predetermined checkpoints. In addition, with regard to the selected leading practice for monitoring agile projects, the Secret Service had fully implemented this practice for one of its two projects being implemented using agile and had partially implemented this practice for the other project. Table 13 provides a summary of DHS’s and the Secret Service’s implementation of these leading practices, as relevant for one program and three projects within IITT. Monitor program performance and conduct reviews at predetermined checkpoints or milestones. Consistent with leading practices, DHS and the Secret Service monitored the performance of IITT’s program and projects by comparing actual cost, schedule, and performance information against planned targets and conducting reviews at predetermined checkpoints. For example, within the Secret Service: The Enabling Capabilities program and Multi-Level Security project monitored their contractors’ costs spent to-date on a monthly basis and compared them to the total contract amounts. OCIO used integrated master schedules to monitor the schedule performance of the Enabling Capabilities program and Multi-Level Security project. OCIO also monitored the cost, schedule, and performance of the Uniformed Division Resource Management System and Events Management projects during monthly status reviews. In addition, DHS and the Secret Service conducted acquisition decision event reviews and systems engineering life cycle technical reviews of IITT’s program and projects at predetermined checkpoints and, when applicable, identified deviations from established cost, schedule, and performance targets. For example: Secret Service OCIO met with DHS’s Office of Program Accountability and Risk Management in February 2017, and with DHS’s Acting Under Secretary for Management in June 2017, to discuss a schedule breach for the Enabling Capabilities program. In particular, the Enabling Capabilities program informed DHS that the program needed to change the planned date for acquisition decision event 3 (the point at which a decision is made to fully deploy the system) in order to conduct tests in an operational environment prior to that decision event. This delay was due to the Secret Service misunderstanding the tests that it was required to conduct prior to that decision event. Specifically, the Enabling Capabilities program had conducted tests on “production representative” systems, but these tests were not sufficient to meet the requirements for acquisition decision event 3. The project team for Multi-Level Security identified that certain technical issues they had experienced would delay system deployment and full operational capability (the point at which an investment becomes fully operational). As such, in October 2017, the project notified the Secret Service Component Acquisition Executive of these expected delays. In particular, the web browser that was intended to provide users on “Sensitive But Unclassified” workstations the ability to view information from different security levels, experienced technical delays in meeting personal identity verification requirements. The project team also described for the executive how the schedule delay would affect the project’s performance metrics and funding, and subsequently updated the project plan accordingly. Measure and monitor agile projects on, among other things, velocity (i.e., number of story points completed per sprint or release), development progression (e.g., the number of features and user stories planned and accepted), product quality (e.g., number of defects), and post-deployment user satisfaction. Secret Service OCIO measured its two agile projects—Uniformed Division Resource Management System and Events Management— using certain agile metrics. In particular, OCIO officials measured the Uniformed Division Resource Management System and Events Management projects using key metrics related to velocity and development progression. For example, the officials measured development progression for both projects on a daily basis. In addition, OCIO officials monitored each project’s progress against these metrics during bi-weekly reviews that they conducted with each project team. The OCIO officials also tracked product quality metrics for the Uniformed Division Resource Management System. For example, on a monthly basis, the officials tracked the number of helpdesk tickets that had been resolved related to the system. In addition, on a quarterly basis, they tracked the number of Uniformed Division Resource Management System defects that (1) had been fixed and (2) were in the backlog. However, while OCIO officials received certain post-deployment user satisfaction information from end-users of the Uniformed Division Resource Management System by, among other things, tracking the number of helpdesk tickets related to the system and via daily verbal, undocumented feedback from certain Uniformed Division officers, OCIO officials had not fully measured and documented post- deployment user satisfaction with the system, such as via a survey of employees who use the system. The officials stated that they had not conducted and documented a survey because they were focused on (1) addressing software performance issues that occurred after they deployed the system to a limited number of users, and (2) continuing system deployment to the remaining users after they addressed the performance issues. OCIO officials stated that they plan to conduct such a documented survey by the end of September 2018. The results of the user satisfaction survey should provide OCIO with important information on whether the Uniformed Division Resource Management System is meeting users’ needs. The Secret Service’s full implementation of 11 of 14 component-level CIO responsibilities constitutes a significant effort to establish CIO oversight for the component’s IT portfolio. Additional efforts to fully implement the remaining 3 responsibilities, including ensuring that all IT contracts are reviewed, as appropriate; ensuring that the Secret Service’s enterprise governance policy appropriately specifies the CIO’s role in developing and reviewing the component’s IT budget formulation and execution; and ensuring agile projects measure product quality and post-deployment user satisfaction, will further position the CIO to effectively manage the Secret Service’s IT portfolio. When effectively implemented, IT workforce planning and management activities can facilitate the successful accomplishment of an agency’s mission. However, the Secret Service had not fully implemented all of the 15 selected practices for its IT workforce for any of the five areas— strategic planning, recruitment and hiring, training and development, employee morale, and performance management. The Secret Service’s lack of (1) a strategic workforce planning process, including the identification of all required knowledge and skills, assessment of competency gaps, and targeted strategies to address specific gaps in competencies and staffing; (2) targeted recruiting activities, including metrics to monitor the effectiveness of the recruitment program and adjustment of the recruitment program and hiring efforts based on metrics; (3) a training program, including the identification of required training for IT staff, ensuring that staff take required training, and assessment of performance data regarding the training program; and (4) a performance management system that includes all relevant technical competencies, greatly limits its ability to ensure the timely and effective acquisition and maintenance of the Secret Service’s IT infrastructure and services. On the other hand, by monitoring program performance and conducting reviews at predetermined checkpoints for one program and three projects associated with the IITT investment, in accordance with leading practices, the Secret Service and DHS provided important oversight needed to guide that program and those projects. Measuring projects on leading agile metrics also provided the Secret Service CIO with important information on project performance. We are making the following 13 recommendations to the Director of the Secret Service: The Director should ensure that the CIO establishes and documents an IT acquisition review process that ensures the CIO or the CIO’s delegate reviews all contracts containing IT, as appropriate. (Recommendation 1) The Director should update the enterprise governance policy to specify (1) the CIO’s current role and responsibilities on the Executive Resources Board, to include developing and reviewing the IT budget formulation and execution; and (2) the Deputy CIO’s role and responsibilities on the Enterprise Governance Council. (Recommendation 2) The Director should ensure that the Secret Service develops a charter for its Executive Resources Board that specifies the roles and responsibilities of all board members, including the CIO. (Recommendation 3) The Director should ensure that the CIO includes product quality and post-deployment user satisfaction metrics in the modular outcomes and target measures that the CIO sets for monitoring agile projects. (Recommendation 4) The Director should ensure that the CIO identifies all of the required knowledge and skills for the IT workforce. (Recommendation 5) The Director should ensure that the CIO regularly analyzes the IT workforce to identify its competency needs and any gaps it may have. (Recommendation 6) The Director should ensure that, after OCIO completes an analysis of the IT workforce to identify any competency and staffing gaps it may have, the Secret Service updates its recruiting and hiring strategies and plans to address those gaps, as necessary. (Recommendation 7) The Director should ensure that the Office of Human Resources (1) develops and tracks metrics to monitor the effectiveness of the Secret Service’s recruitment activities for the IT workforce, including their effectiveness at addressing skill and staffing gaps; and (2) reports to component leadership on those metrics. (Recommendation 8) The Director should ensure that the Office of Human Resources and OCIO adjust their recruitment and hiring plans and activities, as necessary, after establishing and tracking metrics for assessing the effectiveness of these activities for the IT workforce. (Recommendation 9) The Director should ensure that the CIO (1) defines the required training for each IT workforce group, (2) determines the activities that OCIO will include in its IT workforce training and development program based on its available training budget, and (3) implements those activities. (Recommendation 10) The Director should ensure that the CIO ensures that the IT workforce completes training specific to their positions (after defining the training required for each workforce group). (Recommendation 11) The Director should ensure that the CIO collects and assesses performance data (including qualitative or quantitative measures, as appropriate) to determine how the IT training program contributes to improved performance and results (once the training program is implemented). (Recommendation 12) The Director should ensure that the CIO updates the performance plans for each occupational series within the IT workforce to include the relevant technical competencies, once identified, against which IT staff performance should be assessed. (Recommendation 13) DHS provided written comments on a draft of this report, which are reprinted in appendix III. In its comments, the department concurred with all 13 of our recommendations and provided estimated completion dates for implementing each of them. For example, with regard to recommendation 2, the department stated that the Secret Service would update its enterprise governance policy and related policies to outline the roles and responsibilities of the CIO and Deputy CIO, among others, by March 31, 2019. In addition, for recommendation 13, the department stated that the Secret Service OCIO will include relevant technical competencies in performance plans, as appropriate, in the next performance cycle that starts in July 2019. If implemented effectively, these actions should address the weaknesses we identified. The department also identified a number of other actions that it said had been taken to address our recommendations. For example, in response to recommendation 8, which calls for the Office of Human Resources to (1) develop and track metrics to monitor the effectiveness of the Secret Service’s recruitment activities for the IT workforce and (2) report to component leadership on those metrics, DHS stated that the Secret Service’s Office of Human Resources’ Outreach Branch provides to the department metrics on recruitment efforts toward designated priority mission-critical occupations. However, for fiscal year 2017, only 1 of the 12 occupational series associated with the Secret Service’s IT workforce was designated as a mission-critical occupation for the component (i.e., the 2210 IT Specialist series). The 11 other occupational series were not designated as mission- critical occupations. In addition, for fiscal year 2018, none of these 12 occupational series were designated as mission-critical occupations. As such, metrics on recruiting for these IT series may not have been reported to DHS leadership. Moreover, while we requested documentation of the recruiting metrics for the Secret Service’s IT workforce and, during the course of our review, had multiple subsequent discussions with the Secret Service regarding such metrics, the component did not provide documentation that demonstrated it had established recruiting metrics for its IT workforce. Tracking such metrics and reporting the results to Secret Service leadership, as we recommended, would provide management with important information necessary to make effective recruitment decisions. Further, in response to recommendation 10, which among other things, calls for the CIO to define the required training for each IT workforce group, the department stated that the Secret Service OCIO recently developed training requirements for each workforce group, which were issued during our audit. However, while during our audit OCIO provided a list of recommended training courses, the office did not identify them as being required courses. Defining training that is required for each IT workforce group, as we recommended, would inform OCIO of the necessary training for each position and enable the office to prioritize this training, to ensure that its staff have the needed knowledge and skills. In addition to the aforementioned comments, we received technical comments from DHS and Secret Service officials, which we incorporated, as appropriate. We are sending copies of this report to the appropriate congressional committees, the Secretary of Homeland Security, the Director of the Secret Service, and other interested parties. In addition, this report is available at no charge on the GAO website at http://www.gao.gov. Should you or your staffs have any questions on information discussed in this report, please contact me at (202) 512-4456 or HarrisCC@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made major contributions to this report are listed in appendix IV. Our objectives were to evaluate the extent to which: (1) the U.S. Secret Service (Secret Service) Chief Information Officer (CIO) has implemented selected information technology (IT) oversight responsibilities, (2) the Secret Service has implemented leading workforce planning and management practices for its IT workforce, and (3) the Secret Service and the Department of Homeland Security (DHS) have implemented selected performance and progress monitoring practices for the Information Integration and Technology Transformation (IITT) investment. To address the first objective, we analyzed DHS’s policies and guidance on IT management to identify the responsibilities that were to be implemented by the component-level CIO related to overseeing the Secret Service’s IT portfolio, including existing systems, acquisitions, and investments. From the list of 33 responsibilities that we identified, we then excluded the responsibility that was associated with information security, which is expected to be addressed as part of a separate, subsequent GAO review. We also excluded those responsibilities that were significantly large in scope (e.g., implement an enterprise architecture) or that, in our professional judgment, lacked specificity (e.g., provide timely delivery of mission IT services). As a result, we excluded from consideration for this review a total of 10 CIO responsibilities. For the 23 that remained, we then combined certain responsibilities that overlapped with other related responsibilities. For example, we combined related responsibilities on the component CIO’s review of IT contracts. As a result, we identified 14 responsibilities for review. We validated with the acting DHS CIO that these responsibilities were key responsibilities for the department’s component-level CIOs. We then included all 14 of the responsibilities in our review. The 14 selected component-level CIO responsibilities were: 1. Develop and review the component IT budget formulation and execution. 2. Manage the component IT investment portfolio, including establishing an IT acquisition review process that enables component and DHS review of component acquisitions (i.e., contracts) that contain IT. 3. Develop, implement, and maintain a detailed IT strategic plan. 4. Ensure all component IT policies are in compliance and alignment with DHS IT directives and instructions. 5. Concur with each program’s and/or project’s systems engineering life cycle tailoring plan. 6. Support the Component Acquisition Executive to ensure processes are established that enable systems engineering life cycle technical reviews and that they are adhered to by programs and/or projects. 7. Ensure that all systems engineering life cycle technical review exit criteria are satisfied for each of the component’s IT programs and/or projects. 8. Ensure the necessary systems engineering life cycle activities have been satisfactorily completed as planned for each of the component’s IT programs and/or projects. 9. Concur with the systems engineering life cycle technical review completion letter for each of the component’s IT programs and/or projects. 10. Maintain oversight of their component’s agile development approach for IT by appointing the responsible personnel, identifying investments for adoption, and reviewing artifacts. 11. With Component Acquisition Executives, evaluate and approve the application of agile development for IT programs consistent with the component’s agile development approach. 12. Set modular outcomes and target measures to monitor the progress in achieving agile implementation for IT programs and/or projects within their component. 13. Participate on DHS’s CIO Council, Enterprise Architecture Board, or other councils/boards as appropriate, and appoint employees to serve when necessary. 14. Meet the IT competency requirements established by the DHS CIO, as required in the component CIO’s performance plan. To determine the extent to which the Secret Service CIO has implemented these responsibilities, we obtained and assessed relevant component documentation and compared it to the responsibilities. Specifically, we obtained and analyzed documentation including evidence of the CIO’s participation on the Secret Service governance board that has final decision authority and responsibility for enterprise governance, including the IT budget; monthly program management reports showing the CIO’s oversight of IT programs, projects, and systems; monthly status reports on program spending; the Secret Service’s IT strategic plan; the Secret Service’s enterprise governance policy; meeting minutes from the DHS board and council on which the CIO participated (i.e., the CIO Council and Enterprise Architecture Board); and documentation demonstrating whether the CIO met the IT competency requirements. In addition, we obtained and analyzed relevant documentation related to the CIO’s oversight of the major IT investments on which the Secret Service was spending development, modernization, and enhancement funds during fiscal year 2017. As of July 2017, the component had one investment—IITT—that met this criterion. IITT is a portfolio investment that, as of July 2017, included two programs (one of which included three projects) and one standalone project (i.e., it was not part of another program) that had capabilities that were in planning or development and modernization: the Enabling Capabilities program, Enterprise Resource Management System program (which included three projects, called Uniformed Division Resource Management System, Events Management, and Enterprise-wide Scheduling), and Multi-Level Security project. In particular, we obtained and analyzed documentation related to the CIO’s oversight of the systems engineering life cycles for IITT’s Enabling Capabilities program and the Uniformed Division Resource Management System, Events Management, and Multi-Level Security projects. This documentation included acquisition program baselines, systems engineering life cycle tailoring plans, and systems engineering life cycle technical review briefings and completion letters. We then compared the documentation against the five selected systems engineering life cycle oversight responsibilities (responsibilities 5, 6, 7, 8, and 9). We also obtained and analyzed documentation related to the CIO’s oversight of two projects that the Secret Service was implementing using an agile methodology—Uniformed Division Resource Management System and Events Management. Specifically, we obtained and assessed documentation of (1) the CIO’s approval for these projects to be implemented using an agile methodology and (2) the agile development metrics that the CIO established for each of these projects. We then compared this documentation to the three agile development-related component-level CIO responsibilities (responsibilities 10, 11, and 12). Further, to determine the extent to which the Secret Service CIO had established an IT acquisition (i.e., contract) review process that enabled component and DHS review of component contracts that contain IT (which is part of responsibility 2), we first asked Secret Service officials to provide us with a list of all new, unclassified IT contracts that the component awarded between October 1, 2016, and June 30, 2017. The Secret Service officials provided a list of 54 contracts. We validated that these were contracts for IT or IT services by: (1) searching for them in the Federal Procurement Data System – Next Generation; (2) identifying their associated product or service codes, as reported in that system; and (3) determining whether those codes were included in the universe of 79 IT product or service codes identified by the Category Management Leadership Council. In validating the list of 54 contracts provided by the Secret Service, we determined that 5 of the contracts were not associated with an IT product or service code. As such, we removed those contracts from the list. In addition, we found that three other items identified by the component were not in the Federal Procurement Data System – Next Generation. Secret Service officials subsequently confirmed that these three items were not contracts. We therefore removed these three items from the list. As such, the final list of validated contracts identified by the Secret Service included 46 IT contracts. In addition, to identify any IT contracts that were not included in the list provided by the Secret Service, we conducted a search of the Federal Procurement Data System – Next Generation to identify all unclassified contracts that (1) the component awarded between October 1, 2016, and June 30, 2017; (2) were not a modification of a contract; and (3) were associated with 1 of the 79 IT product or service codes identified by the Category Management Leadership Council. Based on these criteria, we identified 144 Secret Service IT contracts in the Federal Procurement Data System – Next Generation (these 144 contracts included the 46 contracts previously identified by Secret Service officials). We then asked Secret Service officials to validate the accuracy, completeness, and reliability of these data, which they did. From each of these two lists of IT contracts (i.e., the list of 46 IT contracts identified by the Secret Service and the list of 144 IT contracts that we identified from the Federal Procurement Data System – Next Generation), we then selected random, non-generalizable samples of contracts, as described below. First, from the list of 46 IT contracts identified by Secret Service officials, we removed 4 contracts that had total values of less than $10,000. To ensure that we selected across all contract sizes, we randomly selected 12 contracts from the remaining list of 42 contracts, using the following cost ranges: $10,000 to $50,000 (4 contracts), more than $50,000 to less than $250,000 (4 contracts), and more than $250,000 (4 contracts). Second, from our list of 144 IT contracts that we identified from the Federal Procurement Data System – Next Generation, we removed the 46 contracts identified by Secret Service officials. We also removed 12 contracts that had total values of less than $10,000. To ensure that we selected across all contract sizes, we randomly selected 21 contracts from the remaining list of 86 contracts, using the following cost ranges: $10,000 to $50,000 (7 contracts), more than $50,000 to less than $250,000 (7 contracts), and more than $250,000 (7 contracts). In total, we selected 33 IT contracts for review. We separated the contracts into the three cost ranges identified above in order to ensure that contracts of different value levels had been selected. This enabled us to determine the extent to which the CIO appropriately reviewed contracts of all values. To determine the extent to which the CIO had established an IT contract approval process that enabled the Secret Service and DHS, as appropriate, to review IT contracts, we first asked Secret Service Office of the CIO (OCIO) officials for documentation of their IT contract approval process. These officials were unable to provide such documentation. Instead, the officials stated that the Secret Service CIO or the CIO’s delegate approves all IT contracts prior to award. The officials also provided documentation that identified four staff to whom the CIO had delegated his approval authority. Further, the officials stated that, in accordance with DHS’s October 2016 IT acquisition review guidance, they submitted to DHS OCIO for approval any IT contracts that met DHS’s thresholds for review, including those that (1) had total estimated procurement values of $2.5 million or more, and (2) were associated with a major investment. Based on the IT acquisition review process that Secret Service OCIO officials described, we then obtained and analyzed each of the 33 selected IT contracts and associated approval documentation to determine whether or not the Secret Service CIO or the CIO’s delegate had approved each of the contracts. In particular, we (1) reviewed the name of the contract approver on the approval documentation, and (2) compared the signature dates that were on the contracts to the signature dates that were identified on the associated approval documentation. In addition, to determine whether or not the Secret Service CIO submitted to DHS OCIO for approval the IT contracts that (1) had total estimated procurement values of $2.5 million or more, and (2) were associated with major investments, we first analyzed the 144 Secret Service IT contracts that we had previously pulled from the Federal Procurement Data System – Next Generation to determine which contracts met the $2.5 million threshold. We identified 4 contracts that met this threshold. We then requested that OCIO identify the levels (i.e., major or non-major) of the investments associated with these contracts. According to OCIO officials, 3 of the 4 contracts were associated with non-major investments and 1 was not associated with an investment. As such, based on DHS’s October 2016 IT acquisition review guidance, none of these contracts needed to be submitted to DHS OCIO for review. We also interviewed Secret Service officials, including the CIO and Deputy CIO, regarding the CIO’s implementation of the 14 selected component-level responsibilities. We assessed the evidence against the selected responsibilities to determine the extent to which the CIO had implemented them. To address the second objective—determining the extent to which the Secret Service had implemented leading workforce planning and management practices for its IT workforce—we first identified seven topic areas associated with human capital management based on the following sources: The Office of Personnel Management’s Human Capital Framework. Office of Personnel Management and the Chief Human Capital Officers Council Subcommittee for Hiring and Succession Planning, End-to-End Hiring Initiative. GAO, High-Risk Series: Progress on Many High-Risk Areas, While Substantial Efforts Needed on Others. GAO, IT Workforce: Key Practices Help Ensure Strong Integrated Program Teams; Selected Departments Need to Assess Skill Gaps. GAO, Department of Homeland Security: Taking Further Action to Better Determine Causes of Morale Problems Would Assist in Targeting Action Plans. GAO, Human Capital: A Guide for Assessing Strategic Training and Development Efforts in the Federal Government. GAO, Results-Oriented Cultures: Creating a Clear Linkage between Individual Performance and Organizational Success. DHS acquisition guidance. Secret Service acquisition guidance. Among these topic areas, we then selected five areas that, in our professional judgment, were of particular importance to successful workforce planning and management. They were also previously identified as part of our high-risk and key issues work on human capital management. These areas include: (1) strategic planning, (2) recruitment and hiring, (3) training and development, (4) employee morale, and (5) performance management. We also reviewed these same sources and identified numerous leading practices associated with the five topic areas. Among these leading practices, we then selected three leading practices within each of the five areas (for a total of 15 selected practices). The selected practices were foundational practices that, in our professional judgment, were of particular importance to successful workforce planning and management. Table 14 identifies the five selected workforce areas and 15 selected associated practices. To determine the extent to which the Secret Service had implemented the selected leading workforce planning and management practices for its IT workforce, we obtained and assessed documentation and compared it against the 15 selected practices. In particular, we analyzed the Secret Service’s human capital strategic plan, human capital staffing plan, IT strategic plan, documentation of the component’s staffing model that it used to determine the number of IT staff needed, an independent verification and validation report on the component’s staffing models, documentation of the current number of IT staff, the Secret Service’s recruitment and outreach plans, documentation of DHS’s hiring authorities (which are applicable to the Secret Service), the Secret Service’s training strategic plan, IT workforce training plan, action plans for improving employee morale, and templates used for measuring and reporting employee performance. We also interviewed Secret Service officials—including the CIO, Deputy CIO, and workforce planning staff—about the component’s workforce- related policies and documentation. Further, we discussed with the officials the Secret Service’s efforts to implement the selected workforce practices for its IT workforce. Regarding our assessments of the Secret Service’s implementation of the 15 selected workforce planning and management practices, we assessed a practice as being fully implemented if component officials provided supporting documentation that demonstrated all aspects of the practice. We assessed a practice as not implemented if the officials did not provide any supporting documentation for that practice, or if the documentation provided did not demonstrate any aspect of the practice. We assessed a practice as being partly implemented if the officials provided supporting documentation that demonstrated some, but not all, aspects of the selected practice. In addition, related to our assessments of the Secret Service’s implementation of the five selected overall workforce areas, we assessed each area as follows, based on the implementation of the three selected practices within each area: Fully implemented: The Secret Service provided evidence that it had fully implemented all three of the selected practices within the workforce area; Substantially implemented: The Secret Service provided evidence that it had either fully implemented two selected practices and partly implemented the remaining one selected practice within the workforce area, or fully implemented one selected practice and partly implemented the remaining two selected practices within the workforce area; Partially implemented: The Secret Service provided evidence that it had partly implemented each of the three selected practices within the workforce area; Minimally implemented: The Secret Service provided evidence that it partly implemented two selected practices and not implemented the remaining one selected practice within the workforce area, or partly implemented one selected practice and not implemented the remaining two selected practices within the workforce area; or Not implemented: The Secret Service did not provide evidence that it had implemented any of the three selected practices within the workforce area. To address the third objective—determining the extent to which the Secret Service and DHS have implemented selected performance and progress monitoring practices for IITT—we reviewed leading project monitoring practices and guidance from the Software Engineering Institute. First, we reviewed the practices within the Project Monitoring and Control process area of the Institute’s Capability Maturity Model Integration® for Acquisition. Based on our review, we identified four practices associated with monitoring program performance and progress. In our professional judgment, all four of these practices were of significance to managing the IITT investment given the phase of the life cycle that the investment was in. As such, we elected to include all four of these practices in our review, and combined them into one practice, as follows: Monitor program performance and conduct reviews at predetermined checkpoints or milestones by, among other things, comparing actual cost, schedule, and performance data with estimates in the program plan and identifying significant deviations from established targets or thresholds for acceptable performance levels. Next, given the agile development methodology that the Secret Service was using for certain projects within IITT, we reviewed the Software Engineering Institute’s technical note on the progress monitoring of agile contractors. Based on our review, and in consultation with an internal expert, we selected four agile metrics that the Institute identified as important for successful agile implementations and that, in our professional judgment, were of most significance to monitoring the performance of IITT’s agile projects. We then combined these four metrics into one practice, as follows: Measure and monitor agile projects on velocity (i.e., number of story points completed per sprint or release), development progression (e.g., the number of features and user stories planned and accepted), product quality (e.g., number of defects), and post-deployment user satisfaction. To determine the extent to which DHS and the Secret Service had implemented the first selected practice, we analyzed relevant program management and governance documentation for IITT’s Enabling Capabilities program, and Multi-Level Security, Uniformed Division Resource Management System, and Events Management projects. In particular, we analyzed acquisition program baselines, DHS acquisition decision event memorandums, artifacts from DHS and Secret Service program oversight reviews, cost monitoring reports, program integrated master schedules, and program status briefings, and compared this documentation to the selected practice. We also interviewed Secret Service OCIO officials regarding the Secret Service’s and DHS’s efforts to monitor the IITT investment’s performance and progress. To determine the extent to which the Secret Service had implemented the second selected practice related to measuring and monitoring agile projects on agile metrics (i.e., velocity, development progression, product quality, and post-deployment user satisfaction), we obtained and analyzed agile-related documentation for the two projects that the Secret Service was implementing using an agile methodology—Uniformed Division Resource Management System and Events Management. Specifically, to determine the extent to which the Secret Service was measuring and monitoring these two projects on metrics for velocity and development progression, we obtained and analyzed documentation, such as sprint burndown charts and monthly program status reports, and compared it to the selected practice. In addition, the agile metrics for product quality and post-deployment user satisfaction were only applicable to projects that had been deployed to users. As such, these metrics were applicable to the Uniformed Division Resource Management System (which the Secret Service had deployed to users) and were not applicable to Events Management (which the Secret Service had not yet deployed to users, as of early May 2018). We therefore obtained and analyzed documentation demonstrating that Secret Service OCIO measured product defects for the Uniformed Division Resource Management System. We also requested documentation demonstrating that OCIO had measured and monitored post-deployment user satisfaction for this project, including via a survey. OCIO officials stated that they had not conducted such a survey and were unable to provide documentation demonstrating they had measured post- deployment user satisfaction for the Uniformed Division Resource Management System. To assess the reliability of the cost, schedule, and agile-related data that were in DHS and the Secret Service’s program management and governance documentation for the IITT investment, we (1) analyzed related documentation and assessed the data against existing agency records to identify consistency in the information, and (2) examined the data for obvious outliers, incomplete, or unusual entries. We determined that the data in these documents were sufficiently reliable for our purpose, which was to evaluate the extent to which DHS and the Secret Service had implemented processes for monitoring the IITT investment’s performance and progress. We conducted this performance audit from May 2017 to November 2018 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives. As of June 2018, the Secret Service’s Information Integration and Technology Transformation (IITT) investment included two programs (one of which included three projects) and one project that had capabilities that were in planning or development and modernization, as described below: Enabling Capabilities. This program is intended to, among other things, (1) modernize and enhance the Secret Service’s information technology (IT) network infrastructure, including increasing bandwidth and improving the speed and reliability of the Secret Service’s IT system performance; (2) enhance cybersecurity to protect against potential intrusions and viruses; and (3) provide counterintelligence and data mining capabilities to improve officials’ ability to perform the Secret Service’s investigative mission. Enterprise Resource Management System. This program comprises three projects that are intended to provide: a system that will enable the Secret Service’s Uniformed Division to efficiently and effectively plan, provision, and schedule missions (this project is referred to as Uniformed Division Resource Management System), a system that will unify the logistical actions (e.g., assigning personnel) surrounding special events that Secret Service agents need to protect, such as the United Nations General Assembly (this project is referred to as Events Management), and a capability for creating schedules for Secret Service agents and administrative, professional, and technical staff, as well as the ability to generate reports on information such as monthly hours worked (this project is referred to as Enterprise-wide Scheduling). Multi-Level Security. This project is intended to enable authorized Secret Service users to view two levels of classified information on a single workstation. Previously, data at various security levels were contained and used in multiple disparate systems. Multi-Level Security is intended to streamline users’ access to information at different security levels in order to enable them to more quickly and effectively perform their duties. Table 15 provides the planned life cycle cost and schedule estimates (threshold values) for each IITT program and project that had capabilities in planning or development and modernization, as of June 2018. In addition, the table describes any changes in those cost and schedule estimates, as well as the key reasons for any changes, as identified by officials from the Secret Service’s Office of the Chief Information Officer. In addition to the contact named above, the following staff made key contributions to this report: Shannin O’Neill (Assistant Director), Emily Kuhn (Analyst-in-Charge), Quintin Dorsey, Rebecca Eyler, Javier Irizarry, and Paige Teigen.

 

 Report 2:
The issue of who gets disciplined and why is complex. Studies we reviewed suggest that implicit bias—stereotypes or unconscious associations about people—on the part of teachers and staff may cause them to judge students’ behaviors differently based on the students’ race and sex. Teachers and staff sometimes have discretion to make case- by-case decisions about whether to discipline, and the form of discipline to impose in response to student behaviors, such as disobedience, defiance, and classroom disruption. Studies show that these decisions can result in certain groups of students being more harshly disciplined than others. Further, the studies found that the types of offenses that Black children were disciplined for were largely based on school officials’ interpretations of behavior. For example, one study found that Black girls were disproportionately disciplined for subjective interpretations of behaviors, such as disobedience and disruptive behavior. A separate study used eye-tracking technology to show that, among other things, teachers gazed longer at Black boys than other children when asked to look for challenging behavior based on video clips. The Department of Health and Human Services (HHS) reported that this research has highlighted implicit bias as a contributing factor in school discipline and may shed some light on the persistent disparities in expulsion and suspension practices, even though the study did not find that teacher gazes were indicative of how they would discipline students. Children’s behavior in school may be affected by health and social challenges outside the classroom that tend to be more acute for poor children, including minority children who experience higher rates of poverty. Research shows that experiencing trauma in childhood may lead to educational challenges, such as lower grades and more suspensions and expulsions; increased use of mental health services; and increased involvement with the child welfare and juvenile justice systems, according to HHS’s Substance Abuse and Mental Health Services Administration (SAMHSA). Further, a substantial share of children nationwide are estimated to have experienced at least one trauma, referred to as an adverse childhood experience (ACE), according to the National Survey of Children’s Health. Additionally, as we recently reported, there has been an increase in certain mental health issues within the school age population. For example, from 2005 to 2014, the suicide rate of youth ages 15 to 19 rose slightly, with older youth having a much higher rate of suicide than younger youth, and since 2007, the percentage of youth ages 12-17 experiencing a major depressive episode increased. About 50 million students were enrolled in K-12 public schools during the 2013-14 school year, according to the CRDC. About 90 percent of students attended traditional public schools; the remainder were enrolled at public charters, magnets, and other types of schools (see table 1). About half of all public school students were White and the other half fell into one of several minority groups, with Hispanic and Black students being the largest minority groups (see fig. 1). The number of boys and girls in public schools was almost evenly split. A larger percentage of boys were students with disabilities. Nearly half of all public school students went to schools where 50 percent or more of the students were low-income, and about a quarter went to schools where 75 percent or more of the students were low-income (see table 2). Discipline of students dropped between 2011-12 and 2013-14 over the six broad categories of discipline reported in Education’s CRDC, which were (1) out-of-school suspensions, (2) in-school suspensions, (3) referrals to law enforcement, (4) expulsions, (5) corporal punishment, and (6) school- related arrests. For example, in school year 2011-12 about 3.4 million (or 6.9 percent) of K-12 public school students were suspended out-of-school at least once, and in school year 2013-14 these suspensions fell to about 2.8 million (or 5.7 percent). Other disciplinary actions affected a much smaller portion of the student body—specifically, less than 0.5 percent of all K-12 public school students were expelled, referred to law enforcement, had a school-related arrest, or experienced corporal punishment in 2013-14, according to Education’s reported data. Education’s Office for Civil Rights and Justice’s Civil Rights Division are responsible for enforcing a number of civil rights laws, which protect students from discrimination on the basis of certain characteristics (see table 3). As part of their enforcement responsibilities, both agencies conduct investigations in response to complaints or reports of possible discrimination. Education also carries out agency-initiated investigations, which are called compliance reviews and which target problems that Education has determined are particularly acute. Education may also withhold federal funds if a recipient is determined to be in violation of the civil rights laws and the agency is unable to reach agreement with the parties involved. In addition, Justice has the authority to file suit in federal court to enforce the civil rights of students in public education. Education and Justice have also issued guidance to assist public schools in meeting their obligations under federal law to administer school discipline without unlawfully discriminating against students on the basis of race, color, or national origin. According to the guidance, public schools are prohibited by federal law from discriminating in the administration of student discipline based on protected characteristics. Further, Education and Justice have noted in their guidance that disciplinary policies and practices can result in unlawful discrimination based on race, for example, in two ways: first, if students are intentionally subject to different treatment on account of their race; and second, if a policy is neutral on its face but has a disproportionate and unjustified effect on students of a particular race, referred to as disparate impact. According to Education and Justice guidance, significant and unexplained racial disparities in student discipline give rise to concerns that schools may be engaging in racial discrimination that violates federal civil rights laws; however, data showing such disparities, taken alone, do not establish whether unlawful discrimination has occurred. Two significant, recently enacted laws include provisions related to school discipline: the Every Student Succeeds Act (ESSA) and the Child Care and Development Block Grant Act of 2014 (CCDBG Act of 2014). ESSA, enacted in December 2015, amended Title I program requirements to allow states’ accountability systems to use multiple indicators of success, which can include measures of school climate and safety. As we previously reported in 2017, some states were considering measures related to suspension rates or school attendance. Additionally, ESSA amended the Elementary and Secondary Education Act of 1965 to authorize the Student Support and Academic Enrichment Program, under which school districts may use grant funding to, among other things, design and implement a locally-tailored plan to reduce exclusionary discipline practices in elementary and secondary schools. These grants also allow the use of funding to expand access to school- based mental health services, including counseling. In addition, the CCDBG Act of 2014 allows states to use certain funds to support the training and professional development of child care workers through activities such as behavior management strategies and training that promote positive social and emotional development and reduce challenging behaviors, including reducing expulsions of young children for those behaviors. Black students, boys, and students with disabilities were disproportionately disciplined in K-12 public schools, according to our analysis of Education’s most recent CRDC data. This pattern of disproportionate discipline persisted regardless of the type of disciplinary action, level of school poverty, or type of public school these students attended. Across each disciplinary action, Black students, boys, and students with disabilities experienced disproportionate levels of discipline. Black students were particularly overrepresented among students who were suspended from school, received corporal punishment, or had a school- related arrest (see fig. 2). For example, Black students represented 15.5 percent of all public school students and accounted for 39 percent of students suspended from school, an overrepresentation of about 23 percentage points. Differences in discipline were particularly large between Black and White students. Although there were approximately 17.4 million more White students than Black students attending K-12 public schools in 2013-14, nearly 176,000 more Black students than White students were suspended from school that school year. See appendix IV, table 12 for additional data on the disciplinary experiences of different racial or ethnic groups. For example, American Indian and Alaska Native students had higher than average rates of receiving each of the six disciplinary actions. This pattern of disproportionate discipline affected both Black boys and Black girls—the only racial group for which both sexes were disproportionately disciplined across all six actions. For example, Black girls were suspended from school at higher rates than boys of multiple racial groups and every other racial group of girls (see fig. 3). Further, boys as a group were overrepresented, while girls were underrepresented among students disciplined across each action. Specifically, boys accounted for just over half of all public school students, but were at least two-thirds of students disciplined across each of the six actions, according to our analysis of Education’s school year 2013-14 data. Boys were particularly overrepresented among students who received corporal punishment, by about 27 percentage points (see fig. 4). These kinds of disparities presented as early as pre-school (see sidebar). Additional information about discipline for pre-school students is in appendix IV, table 17. Regardless of the level of school poverty, Black students, boys, and students with disabilities were suspended from school at disproportionately higher rates than their peers (see fig. 6). This was particularly acute for Black students in high-poverty schools, where they were overrepresented by nearly 25 percentage points in suspensions from school. This pattern persisted across all six disciplinary actions, as well. A similar pattern emerged for boys and students with disabilities. However, unlike Black students, boys and students with disabilities were particularly overrepresented among students suspended from low-poverty public schools (poverty less than 25 percent). Effect of School Poverty on Discipline GAO used a regression model to examine the independent effect of school poverty on discipline in school year 2013-14. The model showed that increases in the percentage of low-income students in a school were generally associated with significantly higher rates for each of the six disciplinary actions GAO reviewed (in-school and out-of-school suspensions, referrals to law enforcement, expulsions, corporal punishment, and school- related arrests). In these schools, boys and students with disabilities were overrepresented by approximately 24 and 20 percentage points, respectively. See appendix IV, table 14 for more information on discipline by the poverty level of the school. In addition, see sidebar for regression results that were relevant to poverty and school discipline. Full results from our regression model are in appendix I, table 10. Regardless of the type of public school a student attended—traditional, magnet, charter, alternative, or special education—Black students, boys, and students with disabilities were disciplined at disproportionately higher rates than their peers, with few exceptions (see fig. 7). For example, Black students were disproportionately suspended from all types of public schools, and this was particularly acute in charter schools. That is, although they represented about 29 percent of all students in charter schools, Black students accounted for more than 60 percent of the students suspended from charter schools (about 32 percentage points higher than their representation in those schools). Boys and students with disabilities were particularly overrepresented among students suspended from traditional public schools (roughly 19 and 14 percentage points, respectively, above their representation in traditional public schools). Effect of School Type on Discipline GAO used a regression model to examine the independent effect of attending different types of public schools on disciplinary outcomes. The model showed several significant associations between school type and the likelihood of receiving discipline. For example, attending an alternative school was associated with a significantly higher likelihood of being suspended (in-school or out-of-school), expelled, referred to law enforcement, or arrested for a school-related incident, compared to attending a traditional public school. The model also showed that students were significantly less likely to be suspended (in-school or out-of-school) if they attended a magnet, charter, or special education school as compared to a traditional public school. We found a few exceptions to the general pattern of Black students, boys, and students with disabilities receiving disproportionately high rates of discipline by school type. For example, Black students attending special education schools did not receive corporal punishment at disproportionate levels. See appendix IV, table 15 for additional information on discipline by the type of public school. In addition, see sidebar for regression results that were relevant to school type and school discipline. Full results from our regression model are in appendix I, table 10. We also found a regional component to discipline in public schools. For example, corporal punishment generally occurred in southern states. See appendix II for maps showing the rates of disciplinary actions by public school district. We spoke with school officials at five school districts about how they are addressing discipline, including challenges they face in responding to student conduct given the complex issues influencing student behavior. Several school officials noted a range of issues, including complex issues such as the effects of poverty, mental health issues, and family dysfunction, that they said contributed to behavior that leads to discipline (see fig. 8). For example, officials at a high-poverty Georgia high school said that their students have additional responsibilities, such as raising or watching siblings or working to support their family, which may cause students to be late to, or skip, class. This observation is consistent with our recent report on child well-being, which cited research showing that children in poverty are more likely to face academic and social challenges than their peers, and with our analysis of CRDC data, which showed that rates of chronic absenteeism (being absent 15 or more days in a school year), were higher in high-poverty schools. See appendix IV, table 19 for detailed data on chronic absenteeism. At one high school in Georgia, officials said that attendance issues were the reason for a majority of disciplinary actions at their school. They said that if students were repeatedly late to school or did not get to their next class within the set amount of time, students could amass enough infractions to warrant suspension from school. In contrast, an official at an elementary school in Georgia said that they usually do not discipline their students for being late to school, as they have found that it was often due to circumstances beyond the child’s control. According to several school officials, some groups such as homeless youth, American Indian, or Lesbian, Gay, Bisexual, Transgender, or Questioning (LGBTQ) students have had greater attendance problems than others. For example, education officials in California said that homeless and foster youth frequently miss school because of all the transitions and instability in their lives. In a school in Texas, officials also reported attendance issues with students who are homeless or in foster care because they lack transportation and clothing. Similarly, we previously reported that American Indian students face school attendance challenges, including access to reliable transportation. In addition, American Indian and Alaska Native students had the highest rates of chronic absenteeism in school year 2013-14, compared to students of other races, according to our analysis of CRDC data (see appendix IV). LGBTQ students are at a high risk of suicide and other emotional issues during adolescence, and often feel disconnected from their peers and families, according to county education officials in California. According to these officials, this can contribute to attendance problems. Officials in our five selected school districts also described what they perceived as a growing trend of behavioral challenges or provided examples related to mental health and trauma, such as increased anxieties, thoughts of and attempts at suicide, and depression among students. For example, state education officials in Georgia said they viewed a growing number of their students as being “trauma complex.” Officials at one school in Massachusetts said that they involve the mental health clinicians or social worker for additional support when students are dealing with traumatic experiences, depression, or are struggling to self- regulate. Further, officials at another school in Massachusetts said that many of their students have experienced trauma and this may lead to more aggressive behaviors at the elementary school level, and to more self-destructive behaviors at the middle school level. Specifically, these officials said that children who have experienced trauma may kick, bite, and punch others when they are younger and cut themselves or become suicidal when older. Similarly, officials at a school in Texas said that they have seen a growth in suicidal ideation and self-harm among the students. Some school officials also said that they felt ill-equipped or that schools lacked resources to deal with the increase in students with mental health issues and the associated behaviors. School officials in all five of the selected states also said that social media results in conflicts or related behavioral incidents among students, such as related bullying and arguments. Officials at a school in Georgia said that social media arguments can cause students who were not part of the original situation to be pulled in, creating classroom disruptions that end in discipline for a larger group. Moreover, officials in a North Dakota middle school said that disagreements on social media last for longer periods of time. They said that social media has also been used to facilitate the purchase of illegal drugs, which can result in students being arrested in school and expelled. Use of Corporal Punishment in School for Five Selected States California, Massachusetts, and North Dakota: Corporal punishment in schools is prohibited. Texas: If a school district adopts a policy to permit corporal punishment, school staff may use corporal punishment unless the student’s parent has provided a written, signed statement prohibiting it. None of the schools GAO visited used corporal punishment, according to officials. Georgia: Boards of education are authorized to determine policies related to corporal punishment, including allowing school staff, at their discretion, to administer corporal punishment in order to maintain discipline. However, none of the schools GAO visited used corporal punishment, according to officials. School district officials from three of the five selected districts we visited stated that officials at individual schools generally have a lot of discretion in determining what discipline a student receives. In several schools, officials said they often try other avenues first to address behavior, such as detention, alerting or having a discussion with the parent, or taking away certain privileges such as making the student eat lunch with the teacher instead of with their friends. However, for certain offenses, officials in most districts said that discipline was automatically more severe. Gun possession, for example, prompts an automatic expulsion at most of the school districts we visited. In another example, school district officials in Texas said drug-related incidents, physical assault of a teacher or student, or extreme sexual behaviors can result in a student being placed in an alternative school. School officials at one alternative school we visited stated that 80 to 90 percent of their students are there due to drug-related incidents. Officials in several of the school districts said their districts had School Resource Officers who only become involved in school disciplinary issues when requested by school administrators. In a Texas high school with over 3,800 students, a school official said School Resource Officers patrol school grounds, monitor gang activity, and may become involved when there are illegal drug issues. Officials also said that School Resource Officers sometimes provide trainings for students, parents, or school staff on subjects such as safety, good decision making, substance abuse, and peer pressure. Further, although corporal punishment was legal in two of the five states we visited (see sidebar), the school district officials with whom we spoke in those states said it was not used anymore in their districts. Our analysis of schools nationwide using school year 2013-14 data showed that corporal punishment tended to be most prevalent in southern states (see maps in appendix II). While there is no one-size-fits-all solution to addressing challenging student behavior, or to the evident disparities in discipline for certain student groups, officials in two school districts we visited told us they recognize the importance of finding alternatives to discipline that unnecessarily removes children from the learning environment. Some school officials said they have begun to specifically address disparities for certain student groups. Officials in all selected school districts reported they are implementing efforts to better address student behavior or reduce the use of exclusionary discipline. For example, officials in all school districts said that they are implementing alternative discipline models that emphasize preventing challenging student behavior and focus on supporting individuals and the school community, such as positive behavioral interventions and supports (PBIS), restorative justice practices, and social emotional learning (SEL) (see sidebar). For example, officials at a selected school district in Texas said they have implemented a classroom management model that uses positive behavior techniques. Texas state law allows schools to develop and implement positive behavior programs as disciplinary alternatives for very young students. This was also true in California, where state law specifically lists suggested alternatives to suspension, including restorative justice, a positive behavior support approach with tiered interventions, and enrollment in programs that teach positive social behavior or anger management. Examples of Alternatives to Discipline that Removes Students from the Classroom Positive Behavioral Interventions and Supports (PBIS): A school-wide framework that focuses on positive behavioral expectations. By teaching students what to do instead of what not to do, the school can focus on the preferred behaviors. All of the selected school districts used some form of positive behavioral intervention and supports. One school official told us that PBIS has significantly reduced their discipline referral numbers and provided teachers more tools to get behavior situations under control. Restorative Justice Practices: This approach focuses on repairing harm done to relationships and people. The aim is to teach students empathy and problem-solving skills that can help prevent inappropriate behavior in the future. For example, according to officials we interviewed at one school, their restorative practices help students take ownership of their actions and work collaboratively to restore relationships that may have been strained. Officials at another school said schools use mediation techniques as alternatives to suspensions. Social and Emotional Learning (SEL): SEL enhances students’ abilities to deal effectively and ethically with daily tasks and challenges. SEL integrates the following five core competencies: self-awareness, self- management, social awareness, relationship skills, and responsible decision making. At a school implementing this model, officials said that they are strengthening their SEL program to improve the whole child instead of treating discipline and mental and behavioral health separately. With regard to directly addressing disparities in school discipline, officials at one school district in California said they created a new leadership team for equity, culture, and support services, and developed a district- wide equity plan that includes mandatory training on implicit bias for principals. Officials from that district also said they had recently changed a policy to increase the consistency of discipline actions across the district’s schools. Similarly, officials at a school district in Massachusetts reported they were working to build awareness among school leadership to address racial bias and the achievement gap through multiyear trainings. Officials we spoke with at a school within that district said they conduct trainings for staff on implicit bias and other related issues to reduce school discipline disparities. As some of the schools and districts we visited have begun implementing alternative discipline models and efforts to reduce the use of exclusionary discipline in recent years, we heard from officials in two districts that there has been difficulty with implementation due to limited resources, staffing turnover, and resistance on the part of some parents. During our visits to schools, we observed classroom spaces that school officials used to manage student behavior, including through various alternative approaches to discipline (see fig. 9). Officials in two school districts said they are moving away from exclusionary discipline because it decreases the amount of academic instruction. Officials at one school district in Georgia said that the district had a history of overusing exclusionary discipline and they understood that schools cannot “suspend their way out of behavioral and discipline issues.” Officials at that district said they are currently rolling out PBIS to their schools, although progress has been slow. While they said discipline rates have decreased and they have received fewer parent and staff complaints, change is difficult because of limited resources, staff turnover, and some resistance to alternative discipline versus punitive discipline on the part of both some school staff and parents. State education officials in all five states said that changes to state law were made or considered related to school discipline in the past several years. For example, California officials said that state law now prohibits suspensions and expulsions for children in grades K-3 for willful defiance. For all ages suspensions may only be used when other means of correction fail to bring about proper conduct. Similarly, Massachusetts law requires that during a student meeting or a hearing to decide disciplinary consequences for a student, school administrators consider ways to re-engage students in the learning process and that expulsion only be used after other remedies and consequences have failed. Massachusetts also revised its state law effective July 2014 to require that schools provide educational services for expelled students. Georgia state law includes a preference for reassignment of disruptive students to alternative educational settings in lieu of suspending or expelling such students. In addition, most of the selected states plan to include school discipline or absenteeism as measures of school quality in their state ESSA Title I plans (see sidebar). According to administrative data from Education, the Office for Civil Rights (OCR) resolved over 2,500 K-12 school discipline cases between 2011 and summer 2017 through several means, including voluntary resolution (leading to agreed-upon actions and subsequent monitoring), dismissal, or closure due to insufficient evidence. These cases stemmed both from external complaints and reviews self-initiated by Education. When we analyzed a non-generalizable sample of resolved cases, we found that most of them focused on alleged racial discrimination or disability status. In the four cases we selected for more in-depth review, the school districts agreed to address discipline issues by, for example, designating a discipline supervisor, training staff, revising district policies, holding student listening sessions, and regularly reviewing data to identify disparities (see case descriptions below). Some of these remedies are designed to reduce exclusionary discipline or improve overall school climate, and others are more directly focused on addressing disparities in school discipline. For example, having school leadership regularly review data, particularly when disaggregated by race and other student characteristics, would increase awareness of disparities. Education Case 1: Race and Exclusionary Discipline in a Mississippi School District. OCR’s 2014 investigation of the Tupelo Public School District found that Black students were disproportionately disciplined in nearly all categories of offenses. These commonly included subjective behaviors like disruption, defiance, disobedience, and “other misbehavior as determined by the administration.” The consequences for “other misbehavior” in high school could be severe, ranging from detention to referral to an alternative school. Once at the alternative school, students were searched thoroughly each day upon entry, escorted by security officers when changing classes, and not allowed to carry purses or book bags. OCR concluded that the district’s discipline codes afforded administrators broad discretion, and found different treatment of Black students when looking at specific disciplinary records. For example, among several students who were disciplined for the first offense of using profanity, Black students were the only ones who were suspended from school, while White students received warnings and detention for substantially similar behavior. To address these issues, the district entered into a voluntary resolution agreement whereby it committed to taking specific actions to ensure that all students have an equal opportunity to learn in school. It agreed, among other things, to revise its student discipline policies, practices, and procedures to include clear and objective definitions of misconduct, eliminate vague and subjective offense categories, and describe criteria for selection within the range of possible penalties when imposing sanctions. The district also agreed to require that alternatives to suspension and other forms of exclusionary discipline be considered in all cases except where immediate safety of students or staff is threatened, and where the behavior in question is such that the disruption to the educational environment can only be remedied by removal, or where the student’s removal is a result of the district’s progressive discipline policy. Education Case 2: Disability and Restraint & Seclusion in a Non- Public California School. This 2016 OCR investigation focused on restraint and seclusion of a student with disabilities who was placed at the non-public school with which Oakland Unified School District contracted to provide the student with certain services, including developing and implementing behavior intervention plans. OCR found the use of prone restraint on this student to be severe, persistent, and pervasive: staff held the student face-down 92 times over a period of 11 months, with the longest duration of a single face-down restraint being 93 minutes. Examples of behaviors that led to the use of restraint included disruptive behavior, not following directions, pushing desks, and ripping up assignments. Staff said that the student wanted to be disciplined and understood prone restraint to be disciplinary. OCR determined that the district allowed the student to be treated differently for non-dangerous behavior on the basis of disability. The district entered into a resolution agreement, committing to resolve these issues by offering individual relief to the student—arranging for an evaluation of the student for adverse effects of the restraint and seclusion, with recommendations for addressing areas of harm—and implementing district-wide policy changes related to restraint and seclusion. The latter included establishing a protocol for responding to any contracted non-public schools’ reports of restraining or secluding district students, and providing training on positive interventions. Excerpt from Christian County, KY Case An African American 10th grader was assigned 1-day out-of-school suspension for skipping school. In comparison, a white 12th grader was assigned a conference with the principal for skipping school. The African American student had 19 previous disciplinary referrals, while the white student had 28 previous disciplinary referrals. Education reported that it would be difficult for the district to demonstrate how excluding a student from attending school in response to the student’s efforts to avoid school meets an important educational goal. Education Case 3: Race and Exclusionary Discipline in a Kentucky School District. In this 2014 case, OCR found that Christian County School District disciplined Black students more frequently or harshly than similarly situated White students. Specifically, Black students were more than 10 times more likely than White students to receive out-of-school suspension for disorderly conduct, and Black students were more likely to be assigned to an “Isolated Classroom Environment” when discipline was for a violation that afforded discretion. OCR also found that the district’s discipline code did not define 61 types of violations, including ones that involve interpretation, such as disorderly conduct, failure to follow directions, deliberate classroom disruption, and profanity. OCR found that administrators had wide discretion in determining the consequences for such actions, and noted that the discipline code allowed for virtually every type of sanction, including expulsion, for each type of violation. OCR also found inconsistencies in treatment of students in different racial groups when looking at individual records (see sidebar). Although district officials said they were aware of the higher rates of discipline for Black students, OCR found that there were no safeguards to ensure that discretion would be exercised in a nondiscriminatory manner. To resolve these issues, the district agreed to ensure as much as possible that misbehavior is addressed in a way that avoids exclusionary discipline, collaborate with experts on research-based strategies to prevent discrimination in discipline, and provide support services to decrease behavioral difficulties, among other things. Education Case 4: Race and Informal Removals in a California Charter School. In this 2015 case, OCR investigated whether Black students were disproportionately disciplined at a charter school which emphasizes Hmong culture and language. The complaint noted that the student’s parents had been asked to take him home on a few occasions because he was disruptive in class. School administrators confirmed the practice of “early dismissal” in response to misbehavior, but said they did not consider the dismissal to be disciplinary. Because the school did not maintain records of these removals, OCR was unable to determine if the student was subjected to discriminatory discipline. However, OCR noted that the practice of removing students from school for disciplinary reasons without appropriate recordkeeping and due process makes it almost impossible for the school to assess whether it is fully meeting its duty of ensuring nondiscrimination with respect to discipline. To resolve these issues, the school agreed, among other things, to revise its discipline policies, provide due process and alternatives to exclusionary discipline, and clearly prohibit the kinds of informal suspensions that OCR observed. Justice also investigates discrimination in school discipline based on complaints filed under federal civil rights statutes and as part of monitoring desegregation orders. Three recently-resolved cases investigated exclusionary discipline or restraint and seclusion for students of color and those with disabilities (see case descriptions below). Justice Case 1: Race and Exclusionary Discipline in an Arkansas School District. This Justice case, originally stemming from a desegregation order, focused on whether the Watson Chapel School District was discriminating against Black students in its administration of school discipline. Justice found that the district suspended and expelled Black students at significantly higher rates than White students, and that district policies and procedures were responsible for this difference. The parties signed a Consent Order in 2016, under which the school district agreed to implement positive interventions and supports, transition away from exclusionary discipline, revise the code of conduct to list specific levels of disciplinary infractions and consequences, prohibit corporal punishment, establish a memorandum of agreement with any law enforcement agency that supplies school resource officers, and provide training to staff. In addition, the district agreed to provide due process before students receive out-of-school suspensions, expulsions, or referrals to the alternative education program because of disruptive behavior. Justice Case 2: Race and Disability in a Maryland School District. Justice investigated complaints that discipline policies in the Wicomico County Public School District resulted in the discriminatory suspension of Black and Latino students and students with disabilities. After the investigation, Justice and the district negotiated and entered into a voluntary out-of-court settlement agreement in January 2017. The district agreed to hire a consultant to implement positive behavioral interventions and supports and restorative practices, revise the code of conduct to include objective definitions of behavioral infractions and incorporate alternatives to exclusionary discipline, establish clear guidelines for when law enforcement intervention is appropriate, and provide appropriate due process procedures. Justice Case 3: Race and Restraint & Seclusion in a Kentucky School District. This 2017 Justice case investigated whether Covington Independent Schools’ disciplinary practices, including the use of exclusionary discipline, restraint, and seclusion, discriminated on the basis of race, national origin, or disability. The parties agreed to negotiate a settlement agreement under which the district agreed to develop a process to regularly identify students who disproportionately had disciplinary referrals, with a focus on offenses that may be the result of unaddressed behavioral needs such as disruptive behavior or aggression, defiance, and being “beyond control.” The district also agreed to discontinue the use of “calm rooms” (where students are isolated during an episode of misbehavior) and prohibit the use of physical restraint except in the case of imminent danger that could not be addressed through de-escalation techniques. The district agreed to adopt an intervention procedure to meet the needs of students with disabilities who may need support beyond the standard discipline policies. In addition, if parents of students with disabilities were asked to come to the school to become involved in an ongoing instance of misbehavior, the district could no longer require the parent to take the student home unless the student had been assigned an out-of-school suspension or expulsion. Education and Justice collaborated on a “Rethink Discipline” campaign in 2014 to address what they viewed as widespread overuse of suspensions and expulsions. This awareness campaign included comprehensive guidance to help states and schools implement alternatives to exclusionary discipline, reduce discrimination, and identify root causes of disparities (see sidebar). The agencies have also collaborated to provide guidance encouraging school districts that use school resource officers to formalize partnerships with local law enforcement agencies and clarify that school resource officers should not administer discipline in schools. Education has also issued special guidance related to the discipline of students with disabilities, including an explanation of the requirement to provide appropriate strategies to address behavior in students’ individualized education programs (IEPs). This guidance stated that when a student with a disability is regularly sent home early from school for behavior reasons, it is likely that the child’s opportunity to make progress in the general education curriculum is significantly impeded (see sidebar). The guidance states that being sent home regularly in this way constitutes a disciplinary removal, which comes with statutory reporting obligations and other considerations. For further information on available federal guidance related to discipline in public schools, see appendix III. available could result in an inappropriately restrictive placement. demonstrates that disciplinary measures such as short-term removals from the current placement (e.g., suspension), or other exclusionary disciplinary measures that significantly impede the implementation of the individualized education program (IEP), generally do not help to reduce or eliminate reoccurrence of the misbehavior. Education and other federal entities have also awarded grants and established special initiatives related to student behavior and school discipline, many of which started around the same time as the federal Rethink Discipline campaign and were designed to be complementary. For example, Education awarded about $130 million from 2014-2016 to states and school districts through the School Climate Transformation Grant, which was established in 2014 to support districts taking steps to improve behavioral outcomes. According to Education, nearly 3,000 schools have worked to implement these behavioral support systems through the grant, and preliminary outcomes data have shown increased student attendance and fewer disciplinary referrals. In addition, Education awarded about $68 million for fiscal years 2015-2019 to over 20 school districts under Project Prevent—a grant to promote conflict resolution skills in students, particularly when they have been exposed to pervasive violence. According to the districts’ grant summary documents, these districts have experienced nearly 10,000 fewer violent behavioral incidents and have provided access to mental health services for over 5,000 students. Justice’s research arm, the National Institute of Justice, also started the Comprehensive School Safety Initiative in 2014 and has since provided about $84 million to fund nearly 40 research projects and interventions that address school discipline and safety, such as implementing restorative practices and studying the root causes of the school-to-prison pipeline. More recently, Education collaborated with HHS to fund the Pyramid Equity Project for early learning programs, which is designed to address implicit bias in school discipline, implement culturally responsive practices in addressing student behavior, and use data systems to understand equity issues. For ongoing technical assistance related to student behavior and school discipline, Education sponsors centers on supportive learning environments, improving student engagement and attendance, and implementing positive behavioral interventions and supports (PBIS). For example, the National Center on Safe Supportive Learning Environments provides information and resources on addressing school discipline, mental health, substance abuse, physical safety, student engagement, and other related issues. Justice funds a technical assistance center on school-justice partnerships that works to enhance collaboration among schools, mental and behavioral health specialists, and law enforcement officials. This center recently published a bulletin on the intersection of exclusionary school discipline and the juvenile justice system, which offers tips for judges who handle school-related cases and information on successful efforts to reduce the number of school-based referrals to law enforcement. For a list of other technical assistance centers related to student behavior or discipline, see appendix III. Lastly, to help identify discipline disparities among the nation’s schools, Education collects comprehensive data on school discipline every other year through the CRDC. The agency publicly releases highlights from these data through their “First Look” documents and in annual reports, which typically focus on a limited number of disciplinary actions (primarily suspensions) and student demographics (usually race and disability status). Education’s public analyses of school discipline data have not included school characteristics like poverty level or type of school. Education encourages districts and schools to disaggregate their data by various student demographics and examine it for disparities. In addition, Education’s Office of Special Education and Rehabilitative Services recently examined racial and ethnic disparities for students with disabilities using data collected under IDEA, Part B. This IDEA report provides the public with information on whether districts had significant disproportionality on the basis of race or ethnicity in the discipline of students with disabilities. We provided a draft of this report to the Departments of Education and Justice for review and comment. These agencies provided technical comments, which we incorporated as appropriate. We also provided selected draft excerpts relevant to officials we interviewed in state agencies, school districts, and school officials. We received technical comments from those officials in four of our five selected states, which we incorporated as appropriate. As agreed with your offices, unless you publicly announce the contents of this report earlier, we plan no further distribution until 30 days from the report date. At that time, we will send copies to the appropriate congressional committees, the Secretary of Education, the Secretary of Health and Human Services, the Attorney General, and other interested parties. In addition, the report will be available at no charge on the GAO website at http://www.gao.gov. If you or your staff have any questions about this report, please contact me at (617) 788-0580 or nowickij@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made key contributions to this report are listed in appendix V. The objectives of this report were to examine (1) the patterns in disciplinary actions among public schools, (2) the challenges selected school districts reported with student behavior and how they are approaching school discipline, and (3) the actions the Department of Education (Education) and the Department of Justice (Justice) have taken to identify and address any disparities or discrimination in school discipline. To conduct this work we (1) analyzed federal discipline data by student demographics and school characteristics; (2) visited five school districts to provide illustrative examples of approaches to school discipline; and (3) interviewed federal agency officials and reviewed agency documentation, federal laws, regulations and policies, selected state laws, and a selection of resolved school discipline cases. To inform all aspects of our work, we interviewed representatives from several nonfederal civil rights organizations and advocacy organizations that represent parents and families, individuals with disabilities, and people from specific racial or ethnic backgrounds, such as Hispanic, African-American, and American Indian communities. We also met with academic subject matter experts to discuss issues related to school discipline, including disparities in school discipline and initiatives intended to reduce exclusionary discipline. In addition, we reviewed two dozen articles containing research that had been published since 2010 to further understand the context of school discipline issues and programs. We evaluated the methods used in the research and eliminated the research if we felt the methods were not appropriate or rigorous. The following sections contain detailed information about the scope and methodology for this report. To determine the patterns in disciplinary actions among public schools, we used Education’s Civil Rights Data Collection (CRDC) to analyze discipline data from all public schools by student demographics (e.g., race, sex, disability) and school characteristics (e.g., school type, such as charter or magnet school). Our analyses of this data, taken alone, do not establish whether unlawful discrimination has occurred. The CRDC is a biennial survey that is mandatory for every public school and district in the United States. Conducted by Education’s Office for Civil Rights, the survey collects data on the nation’s public schools (pre-K through 12th grade), including disciplinary actions as well as student characteristics and enrollment, educational and course offerings, and school environment, such as incidents of bullying. CRDC data are self-reported by districts and schools, and consequently there is potential for misreporting of information. In school years 2011-12 and 2013-14, the CRDC collected data from nearly every public school in the nation (approximately 17,000 school districts, 96,000 schools, and 50 million students in school year 2013-14). Using the public-use data file of the CRDC, we focused our analysis primarily on data for school year 2013- 14, the most recent data available at the time of our analysis. We also compared disciplinary data from school years 2011-12 and 2013-14 to analyze how discipline may have changed over that period. The 2013-14 CRDC collected data on six broad types of disciplinary actions: (1) out-of-school suspensions, (2) in-school suspensions, (3) referrals to law enforcement, (4) expulsions, (5) corporal punishment, and (6) school-related arrests. The CRDC did not collect data on less severe forms of discipline, such as detentions, Saturday school, or removing privileges to engage in extracurricular activities, such as athletic teams or field trips. As shown in table 4, we combined related variables for out-of- school suspension and expulsion; we also provide a crosswalk of discipline variables used in this report and those captured in the CRDC. For each of the six disciplinary actions in our review, we examined discipline counts and rates both overall and disaggregated by student demographic characteristics. Specifically, we examined counts and rates for each disciplinary action by student sex (boy or girl), race or ethnicity (see table 5), disability status (students with or without disabilities), and English Language Learners. Using the CRDC, we also examined race and sex intersectionally, for example, disciplinary rates for Black boys or White girls. In order to analyze discipline counts and rates by the poverty level of the school, we pulled in data on free or reduced-price lunch eligibility from the 2013-14 Common Core of Data (CCD), and matched it to schools in the 2013-14 CRDC, which did not collect eligibility data. The CCD is administered by Education’s National Center for Education Statistics, and annually collects nonfiscal data about all public schools in the nation. A student is generally eligible for free or reduced-price lunch based on federal income eligibility guidelines that are tied to the federal poverty level and the size of the family. State education agencies supply these data for their schools and school districts. We then sorted schools into quartiles based on the percentage of students eligible for free or reduced-price lunch as follows: 0 to 25 percent, 25.1 to 49.9 percent, 50 to 74.9 percent, and 75 to 100 percent (see table 6). The poverty thresholds and measure of poverty discussed here and throughout this report were commonly used in the literature and also aligned with how Education analyzed its data. To analyze discipline counts and rates by the type of public school a student attended, we sorted schools into mutually exclusive categories and reviewed disciplinary data by student demographic information. The 2013-14 CRDC allowed schools to self-identify as special education, magnet, charter, and alternative schools (see table 7). The categories of public schools in the CRDC were not mutually exclusive; that is, schools could select multiple school types to describe their school, such as a charter school that was also an alternative school. To create mutually exclusive categories for analytical purposes, we applied the following criteria: Alternative school: all schools that selected “alternative” as the school type in the CRDC, even if they selected other types as well. Special education school: schools that selected “special education” as the school type in the CRDC, except those schools that also selected the alternative school type. Charter school: schools that selected “charter” as the school type in the CRDC, except those schools that also selected the alternative school type and/or the special education school type. Magnet school: schools that selected “magnet” as the school type in the CRDC, except those schools that also selected the alternative school type, the special education school type, and/or the charter school type. Traditional school: schools that did not select any other school type in the CRDC. Table 8 provides the breakdown of students and schools captured in the 2013-14 CRDC after applying these criteria. For each of our school discipline analyses, we also examined disparities in disciplinary rates by student demographics. Specifically, we compared each student groups’ representation among students disciplined to their representation in the overall student population. For example, if boys accounted for 50 percent of all K-12 public school students, but represented 75 percent of students that received a given disciplinary action, then boys would be overrepresented among students that received that type of discipline by 25 percentage points. We also compared disciplinary rates across student groups and similarly examined disparities based on school poverty level and school type for all students. We also analyzed CRDC data on discipline of pre-school students. The disciplinary data for pre-school students that was collected in the CRDC for school year 2013-14 was different than disciplinary data collected for K-12 students. Specifically, data on pre-school discipline was limited to out-of-school suspensions and expulsions. Findings from our analysis of pre-school discipline data are included where applicable in the report and additional data are provided in appendix IV, table 17. In addition to analyzing data on school discipline, we also analyzed data on chronic absenteeism, which was defined as students who were absent 15 or more days during the school year for any reason, which could include for suspensions and expulsions. The CRDC also collected data on instances in which students were restrained—both physically and mechanically—or secluded at school. Education has provided a resource document with principles to school districts that indicates restraint and seclusion should only be used in instances where a student’s “behavior poses imminent danger of serious physical harm to self or others,” and should never be used as punishment or discipline. However, multiple sources, including civil rights complaints filed with Education, news stories, and other reports have alleged that these practices have been used in response to student misbehavior, in particular for students with disabilities. We included data on chronic absenteeism and restraint and seclusion in our analyses, and present related findings in appendix IV, tables 18 and 19. We determined that the data we used from the CRDC and CCD were sufficiently reliable for the purposes of this report by reviewing technical documentation, conducting electronic testing, and interviewing officials from Education’s Office for Civil Rights and National Center for Education Statistics. For our analysis of the 2013-14 CRDC, we used the final data file that was publicly available as of June 2017 because it corrected errors in the original data previously submitted by several school districts. We conducted a generalized linear regression using the 2013-14 CRDC and CCD data to explore whether and to what extent certain school-level characteristics were associated with higher rates of each disciplinary action. Such a model allowed us to test the association between a given school characteristic and the percentage of students receiving a given disciplinary action, while holding other school characteristics constant. We selected different school characteristics (our independent variables) for the regression based on factors that Education’s Office for Civil Rights and other researchers have identified as potential drivers of school discipline rates (our dependent, or outcome variables). Table 9 lists the variables we included in our regression model. We conducted a separate regression for each of the six disciplinary actions listed as an outcome variable. We excluded some schools from our regression model. Specifically, we excluded schools that met one or more of the following criteria: Data were not available in both the CRDC and CCD data sets, and therefore we were unable to determine the percentage of students eligible for free or reduced-price lunch in these schools or whether these schools were located in rural, suburban, or urban areas. School was listed as “ungraded” in the CRDC because we could not determine if these schools offered grade 6 or above. School only offered pre-school because pre-school disciplinary data were reported separately and differently than K-12 disciplinary data in the CRDC. School identified as a juvenile justice facility in the CRDC. In the 2013-14 CRDC, schools could identify as a juvenile justice facility, and select one of the other school types in our analysis (i.e., traditional, magnet, charter, alternative, and special education schools). Due to this overlap, and because it is reasonable to expect discipline within a juvenile justice facility could function differently than discipline in other schools, we excluded these schools from our regression model. School had less than 10 students enrolled because in smaller schools minor fluctuations in the numbers of students receiving a given disciplinary action could have a large effect on disciplinary rates. In the 2013-14 data, these exclusions reduced the total number of public schools in our regression model from a universe of 95,507 public schools to 86,769 public schools. All regression models are subject to limitations and for this model the limitations included: Data we analyzed were by school rather than student. Consequently, we were not able to describe the association between our independent variables and a student’s rate of different disciplinary actions, while controlling for characteristics of an individual student, such as sex, race or ethnicity, disability status, or grade level. Instead, the school-level nature of the CRDC data limited our description of the associations between school characteristics and disciplinary rates to whether there was an increase, decrease, or no effect on disciplinary rates for schools with a given characteristic, controlling for other characteristics of the entire school’s population, such as percent of students who are boys or are Black. Some variables that may be related to student behavior and discipline are not available in the data. For example, in this context, it could be that parent education or household type (single- versus multiple- headed household) could be related to student behaviors, such as those that lead to receiving the six disciplinary actions we analyzed. Results of our analyses are associational and do not imply a causal relationship because, for example, CRDC data were not gathered by a randomized controlled trial, where students would be randomized to attend schools with certain characteristics. Typically, a generalized linear regression model provides an estimated incidence rate ratio, where a value greater than one indicates a higher or positive association, in this case, between the disciplinary outcome and the independent variable of interest, such as being a charter school or having a higher percentage of Black students. An estimated incidence rate ratio less than one indicates a lower incidence of a given disciplinary action when a factor is present. Given the limitations of our model as described above, we present the results of our regression model in table 10 by describing the direction of the associations, rather than an estimated rate (incidence) of disciplinary outcomes. For categorical variables in table 10, we provided the comparison school characteristic in brackets and italics. For example, the results in this table should be interpreted as students attending alternative schools were significantly more likely than students attending traditional schools to be suspended out of school. For continuous variables (i.e., those starting with “Percent”), the results in this table should be interpreted as the likelihood of receiving a given disciplinary action as the percentage of students in the school with a given characteristic increased. For example, as the percentage of students eligible for free or reduced- price lunch increased, we found that the likelihood of receiving each of the six disciplinary actions also increased. It should be noted that interactions (i.e., where we combine both race and sex variables) should be interpreted differently than other variables in table 10. Though an interaction may be “negative,” it does not necessarily imply that the group presented in the interaction was significantly less likely to receive the given disciplinary action because interactions are interpreted relative to the main effect of each variable in the interaction. For example, as shown in table 10, the interaction for percentage of Black boys was negative for out-of-school suspensions; however, the estimated incidence of out-of-school suspensions for a school with a higher than average percentage of Black students and a higher than average percentage of boys was positive. Since the contribution for an interaction coefficient is relative, in this example the contribution of the main effects outweighed that of the interaction, resulting in a positive effect altogether, despite the negative interaction. To obtain information on how selected school districts are addressing discipline issues, including any challenges they face in doing so, we selected five school districts to serve as illustrative examples. To select school districts, we used CRDC data to sort school districts into categories based on district size; the presence of disparities in out-of- school suspension rates for boys, Black students, or students with disabilities; and whether the out-of-school suspension rate was increasing or decreasing between the two most recent CRDC collections. With regard to size, we collapsed several categories that Education has previously used into three groupings, each with roughly one-third of all students attending public schools in school year 2013-14: Large School District: 25,000 or more students (34.7% of all students in 2013-14) Medium School District: 5,000 to 24,999 students (33.2% of all students in 2013-14) Small School District: Less than 5,000 students (32.1% of all students in 2013-14) Further, we focused on out-of-school suspensions for selection purposes because this disciplinary action was one of the most frequently reported disciplinary actions employed by schools in Education’s two most recent data collection efforts on the issue (2011-12 and 2013-14 CRDC). Moreover, out-of-school suspensions are an exclusionary disciplinary action; that is, they remove or exclude students from the usual instructional or learning environment. Selecting districts with a range of out-of-school suspension rate was intended to generate a mix of districts that commonly use exclusionary discipline, as well as those that may employ alternatives. For site selection, we used out-of-school suspension data in two ways. First, we excluded districts that did not have a disparity in out-of-school suspension rates for Black students, boys, or students with disabilities. Prior GAO work and Education’s data showed that these groups were particularly vulnerable to discipline disparities, and the purpose of this research objective was to understand district efforts to identify and address such disparities. Second, we grouped school districts by whether their out-of-school suspension rate increased or decreased between 2011-12 and 2013-14. Exploring school districts that changed in different ways over time was intended to help us identify successful efforts to reduce suspensions as well as challenges districts face in addressing disparate discipline. Using the above criteria, we grouped school districts into the following categories: Category 1 and 2: Large school district and out-of-school suspension rate that increased (or decreased) from 2011-12 to 2013-14 Category 3 and 4: Medium school district and out-of-school suspension rate that increased (or decreased) from 2011-12 to 2013- 14 Category 5 and 6: Small school district and out-of-school suspension rate that increased (or decreased) from 2011-12 to 2013-14. After sorting school districts into the above categories, we randomized the list within each category to improve the methodological rigor of selecting school districts. In addition, we applied a series of post-checks to our list of districts in each grouping to ensure we had appropriate variety to consider other key factors in school discipline. Specifically, we checked for variety in: types of public schools in the district, geographic diversity both in terms of region of the country and use of corporal punishment in the district, and use of restraint or seclusion in the district. To select specific districts, we started with the district in each category that was at the top of the randomized list and then applied the above post-checks. We then conducted outreach to district superintendents or their designees via telephone and email to obtain their agreement to participate in this review. When school districts were unresponsive to our outreach or unwilling to participate, we contacted additional districts that had similar characteristics in order to achieve variety in our final selections. This resulted in the selection of five schools districts, one each in California, Georgia, Massachusetts, North Dakota, and Texas (see table 11). We visited each district and interviewed district-level officials involved in school discipline and school climate initiatives. These officials included superintendents, assistant superintendents, program managers, and directors of applicable district departments (e.g., student support services and special education). We also reviewed district-level discipline data, school district discipline policies, and relevant state laws related to school discipline to better understand the local context in each selected district. In the five districts we visited, we also interviewed officials at a total of 19 schools. At each school, we typically met with principals and/or assistant principals, and in some instances, spoke with other personnel at the school, such as counselors, attendance coordinators, school resource officers (i.e., law enforcement officers), and teachers. In each district, we selected a variety of schools to visit based on grade level, school type, and disciplinary data. For each selected district, we also interviewed officials from the state educational agency that oversees that district to better understand the statewide context around discipline, such as state laws that may affect district disciplinary policies, statewide initiatives related to discipline, and state-level monitoring of district-level disciplinary actions. In California, we also met with the county office of education that oversees the district we selected because, in that state, counties have a primary role in the local school district accountability structure. Because we selected these school districts judgmentally, we cannot generalize the findings about these districts’ approaches to discipline, and the challenges they face, to all school districts and schools nationwide. To determine the extent to which, and in what ways, Education and Justice are identifying and addressing discipline disparities and discrimination, we interviewed agency officials at headquarters and regional offices, reviewed agency documentation and administrative data, reviewed federal laws and regulations, and reviewed a non-generalizable sample of seven recently resolved school discipline investigations undertaken by Education and Justice (which we refer to as cases). With both agencies, we interviewed officials about each agency’s responsibilities with respect to federal civil rights laws and regulations, as well as the actions the agencies took to enforce them. We also discussed each agency’s guidance, support to school districts on these issues (e.g., grants and technical assistance), and data collection activities. In addition, we collected and reviewed relevant agency procedures and guidance documents. We also requested and reviewed Education’s data on the number of civil rights complaints received and cases related to school discipline investigated from 2011 to August 2017 to better understand the scope of the agency’s efforts. Education provided these data from their internal database, where investigators categorized cases as being related to school discipline. We assessed the reliability of this source through discussion with knowledgeable officials and reviewing key documents and determined the data to be reliable for our purposes. To select resolved school discipline cases to review, we searched Education’s and Justice’s respective online repositories of resolved investigations and compliance reviews, as well as Education’s annual reports, to create a list of resolved cases related to school discipline. We then narrowed the list to cases resolved in approximately the past 3 years (from 2014 to May 2017) and excluded long-standing cases that were opened several decades ago to help ensure the information in the cases reflected recent policies and practices in each agency. We also excluded cases regarding institutions of higher education because they were outside the scope of this review. This resulted in a list of 12 relevant resolved cases—9 for Education and 3 for Justice. From this list, we selected 7 cases to review in depth to better understand Education’s and Justice’s investigatory processes and resolutions with regard to school discipline cases in pre-K through 12th grade, and to provide illustrative examples in our report. We selected 4 cases from Education that provided a mix of the type of alleged discrimination (e.g., race or disability) and type of discipline (e.g., suspension, expulsion, arrest, etc.). We selected all 3 relevant cases from Justice. For each case, we reviewed the type of investigation (complaint investigation or compliance review); the reason for the investigation; any applicable findings or recommendations; and the ultimate resolution of the investigation, such as a voluntary agreement with the school district or remedies to address findings. In all instances, we are presenting Education’s and Justice’s findings and do not reach any independent conclusions regarding the cases. We conducted this performance audit from November 2016 to March 2018 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives. This appendix contains maps showing rates of disciplinary actions by school district for each of the six disciplinary actions captured in the Department of Education’s Civil Rights Data Collection for school year 2013-14. Funded by Department of Education (Education): National Center on Safe Supportive Learning Environments: offers information and technical assistance focused on improving student supports and academic enrichment. This includes resources on using positive approaches to discipline, as well as promoting mental health for students and ensuring the safety and effectiveness of physical learning environments. https://safesupportivelearning.ed.gov/. National Student Attendance, Engagement, and Success Center: a center that disseminates evidence-based practices and facilitates communities of practice to help students attend school every day, be engaged in school, and succeed academically, so that they graduate high school prepared for college, career, and civic life. It offers webinars on identifying the root causes of chronic absence, linking school climate and exclusionary discipline to absenteeism, and improving attendance for vulnerable students. http://new.every1graduates.org/nsaesc/ National Technical Assistance Center for the Education of Neglected or Delinquent Children and Youth: provides technical assistance to state agencies with Title I, Part D programs and works to improve education services for children and youth who are neglected, delinquent, or at risk. This includes running the Supportive School Discipline Communities of Practice, which brings together education and justice leaders for knowledge-sharing events and offers webinars on discipline initiatives such as restorative practices. https://www.neglected-delinquent.org/ Positive Behavioral Interventions and Supports Technical Assistance Center: funded by Education’s Office of Special Education Programs, this center supports implementation of a multi- tiered approach to social, emotional and behavior support. In addition, it offers resources on cultural responsiveness, addressing discipline disproportionality, and interconnecting mental health with behavior support systems, among other issues. https://www.pbis.org/. Funded by Department of Health and Human Services (HHS): Center of Excellence for Infant and Early Childhood Mental Health Consultation: supports states, tribes, and communities in promoting mental health and school readiness. It provides training to leaders in early childhood education around mental health and school readiness issues. https://www.samhsa.gov/iecmhc Center for School Mental Health: works to strengthen policies and programs in school mental health to improve learning and promote success for youth. This center is supported in full by HHS’s Maternal and Child Health Bureau, Division of Child, Adolescent and Family Health Adolescent Health Branch in the Health Resources and Service Administration. http://csmh.umaryland.edu/ National Center for Trauma-Informed Care and Alternatives to Seclusion and Restraint: works to develop approaches to eliminate the use of seclusion, restraints, and other coercive practices and to further advance the knowledge base related to implementation of trauma-informed approaches. https://www.samhsa.gov/nctic National Child Traumatic Stress Network: works to improve access to care, treatment, and services for children and adolescents exposed to traumatic events. The group provides a comprehensive focus on childhood trauma by collaborating with the health, mental health, education, law enforcement, child welfare, juvenile justice, and military family service systems. http://nctsn.org/ National Resource Center for Mental Health Promotion and Youth Violence Prevention: offers resources and technical assistance to states, tribes, territories, and local communities to promote overall child wellness and prevent youth violence. http://www.healthysafechildren.org/ Now Is the Time Technical Assistance Center: provides national training and technical assistance to recipients of the Healthy Transitions (youth access to mental health) and Project Advancing Wellness and Resilience Education (AWARE) grants. https://www.samhsa.gov/nitt-ta/about-us Funded by Department of Justice (Justice): School-Justice Partnership National Resource Center: provides trainings and webinars, and partners with stakeholders in the law enforcement, juvenile justice, mental health, and public education arenas. The National Council of Juvenile and Family Court Judges operates this center. https://schooljusticepartnership.org/ Office of Juvenile Justice and Delinquency Prevention (OJJDP) This appendix contains several tables that show the underlying data used throughout this report, as well as additional analyses we conducted using the Department of Education’s Civil Rights Data Collection (CRDC) and Common Core of Data (CCD) for school year 2013-14. Our analyses of Education’s data, as reflected in these tables, taken alone, do not establish whether unlawful discrimination has occurred. The following tables and information are included in this appendix: Table 12: students who received disciplinary actions captured in the CRDC, disaggregated by student sex, race or ethnicity, and English Language Learner status. Table 13: students with or without disabilities who received disciplinary actions captured in the CRDC, disaggregated by student sex and race or ethnicity. Table 14: students who received disciplinary actions captured in the CRDC, disaggregated by the poverty level of the school and other student characteristics. Table 15: students who received disciplinary actions captured in the CRDC, disaggregated by the type of public school and other student characteristics. Table 16: students who received disciplinary actions captured in the CRDC, disaggregated by the grades offered in the school and other student characteristics. Table 17: pre-school students who were suspended from school, disaggregated by student sex and race or ethnicity, as well as the poverty level of school and the type of public school. Table 18: students who were restrained—mechanically or physically—or secluded, disaggregated by student sex, race or ethnicity, and disability status as well as the poverty level of school and the type of public school. Table 19: students who were chronically absent, disaggregated by student sex, race or ethnicity, and disability status, as well as the poverty level of school and the type of public school. Table 20: schools that reported having access to a school counselor or sworn law enforcement officer, disaggregated by the poverty level of school and the type of public school. Table 21: students disciplined for harassment or bullying, disaggregated by student sex, race or ethnicity, and disability status. In addition to the contact named above, Sherri Doughty (Assistant Director), Amy Moran Lowe (Analyst-in-Charge), James Bennett, Holly Dye, Aaron Karty, Jean McSween, John Mingus, James Rebbe, Sonya Vartivarian, and David Watsula made key contributions to this report. Also contributing were Johana Ayers, Deborah Bland, Irina Carnevale, Caitlin Croake, Vijay D’Souza, Gretta Goodwin, Gloria Hernandez-Saunders, Reginald Jones, DuEwa Kamara, John Karikari, Ted Leslie, Sheila R. McCoy, Brittni Milam, Cady Panetta, Moon Parks, Caroline Prado, Steven Putansu, Maria Santos, Margie K. Shields, Ruth Solomon, Alexandra Squitieri, and Barbara Steel-Lowney.

Question: Write a one-page summary of the report 1.

Answer: Commonly known for protecting the President, the Secret Service also plays a leading role in investigating and preventing financial and electronic crimes. To accomplish its mission, the Secret Service relies heavily on the use of IT infrastructure and systems. In 2009, the component initiated the IITT investment—a portfolio of programs and projects that are intended to, among other things, improve systems availability and security in support of the component's business operations. GAO was asked to review the Secret Service's oversight of its IT portfolio and workforce. This report discusses the extent to which the (1) CIO implemented selected IT oversight responsibilities, (2) Secret Service implemented leading IT workforce planning and management practices, and (3) Secret Service and DHS implemented selected performance monitoring practices for IITT. GAO assessed agency documentation against 14 selected component CIO responsibilities established in DHS policy; 15 selected leading workforce planning and management practices within 5 topic areas; and two selected leading industry project monitoring practices that, among other things, were, in GAO's professional judgment, of most significance to managing IITT. The U.S. Secret Service (Secret Service) Chief Information Officer (CIO) fully implemented 11 of 14 selected information technology (IT) oversight responsibilities, and partially implemented the remaining 3. The CIO partially implemented the responsibilities to establish a process that ensures the Secret Service reviews IT contracts; ensure that the component's IT policies align with the Department of Homeland Security's (DHS) policies; and set incremental targets to monitor program progress. Additional efforts to fully implement these 3 responsibilities will further position the CIO to effectively manage the IT portfolio. Of the 15 selected practices within the 5 workforce planning and management areas, the Secret Service fully implemented 3 practices, partly implemented 8, and did not implement 4 (see table). Within the strategic planning area, the component partly implemented the practice to, among other things, develop IT competency needs. While the Secret Service had defined general core competencies for its workforce, the Office of the CIO (OCIO) did not identify all of the technical competencies needed to support its functions. As a result, the office was limited in its ability to address any IT competency gaps that may exist. Also, while work remains to improve morale across the component, the Secret Service substantially implemented the employee morale practices for its IT staff. Secret Service officials said the gaps in implementing the workforce practices were due to, among other things, their focus on reorganizing the IT workforce within OCIO. Until the Secret Service fully implements these practices for its IT workforce, it may be limited in its ability to ensure the timely and effective acquisition and maintenance of the component's IT infrastructure and services. Of the two selected IT project monitoring practices, DHS and the Secret Service fully implemented the first practice to monitor the performance of the Information Integration and Technology Transformation (IITT) investment. In addition, for the second practice—to monitor projects on incremental development metrics—the Secret Service fully implemented the practice on one of IITT's projects and partially implemented it on another. In particular, OCIO did not fully measure post-deployment user satisfaction with the system on one project. OCIO plans to conduct a user satisfaction survey of the system by September 2018, which should inform the office on whether the system is meeting users' needs. GAO is making 13 recommendations, including that the Secret Service establish a process that ensures the CIO reviews all IT contracts, as appropriate; and identify the skills needed for its IT workforce. DHS concurred with all recommendations and provided estimated dates for implementing each of them.