Funding Supports
State agencies depend on a variety of different funding sources to develop and operate State Longitudinal Data Systems (SLDSs)4. An SLDS requires millions of dollars in financing to cover the upfront expenses, on-going maintenance fees, and employee wages needed to construct and sustain a data system. SLDS managers turn to several financing sources for their capital needs, including state legislative assigned budgets, federal grant awards, and contributed funding support from SLDS partners. However, these managers typically are unable to turn to other conventional forms of financing such as debt lending or private institution investment due to their state government ties. This creates capital concerns for SLDS managers that do not receive sustained funding support from state and federal sources, and may ultimately lead to the end of active management of the SLDS if no other funds can be obtained.
The most common form of SLDS funding obtained by state agencies is provided by the National Center for Education Statistics (NCES) Statewide Longitudinal Data Systems (SLDS) Grant Program5. The NCES SLDS Grant Program has provided over one billion dollars to 47 state agencies since 2005 to develop their SLDSs. This grant program was created with the purpose of standardizing education data collection and access practices across states and linking student-level data across agencies. Initial grants provided by the program were generally used by states to construct the initial infrastructure of their SLDS and set the management structure between SLDS partners. Later grants were awarded to states to further develop their SLDSs in relation to student data linkages across state agencies and analysis capabilities regarding this data. Grants range between two to twenty million dollars depending on the request of the state agency and the progress that state has made in regards to their SLDS.
States such as Utah6 and Washington7 that demonstrated successful deployment of federal funds to improve their SLDS received as much of three separate grants from the program. States that show less aptitude in the effective deployment of federal funds received only one grant from the program, such as Idaho8 or Missouri. The SLDS managers of these states are not necessarily to blame for less effective deployment of funds. In many cases, this outcome is caused by a lack of political unity in the state legislature or state education departments on the topic of SLDSs and the distribution and management of sensitive student data. Three states received no federal support from the programs, these were generally caused by the negative outlook of the state towards SLDSs and student data privacy concerns for various reasons.
Centralized and federated SLDSs use funds in different ways to sustain and develop their operations. Centralized SLDSs are maintained by an active SLDS manager, commonly a division within a larger state department of education or an independent research center that reports directly to SLDS partners. These types of managers require a distinct budget to fund their operations. These funds pay the wages of the employees that manage the SLDS as well as the expenses related with developing the architecture for a centralized data warehouse. These funds also are used to pay for any vendor services that are used to develop the data warehouse. Federated SLDSs are not maintained by an active SLDS manager. Instead, these SLDSs are maintained through the joint support of each of the SLDS partners. In this scenario, funds will be needed to develop the initial SLDS architecture that will facilitate the linkage of data records between SLDS partners in a secure manner. Once this architecture is built, funds are no longer needed to actively maintain a data system. The SLDS partners are tasked to maintain their data records in way that correctly interacts with the SLDS. This places the burden of supporting the SLDS on each of the SLDS partners. Each of these partners typically allocate portions of their total operating budgets to matters concerning the SLDS.
SLDSs built around a centralized governance structure tend to receive initial development funds directly through the NCES grantee program and then depend on their respective state legislatures for ongoing support. Those systems built around federated governance structures also receive federal level funding, but tend to be supported from their stakeholders rather than directly from their state legislatures; the stakeholders themselves may have also received NCES funds and certainly receive state funds, that are then used, in part, to pay for the development and maintenance of the federated data system.
The obtainment of sustainable funding sources is critical the health of an SLDS. SLDS managers and partners require resources in the forms of both capital and labor to successfully operate an SLDS. Without these resources, these managers and partners are hard pressed to maintain the functionality of the SLDS and incapable of performing any initiatives to improve the SLDS. Less employees can be hired and less time can be allocated by existing employees to work on the SLDS. States that managed to create sustainable funding sources, either through SLDS partnership agreements or specific budgets allocated by state legislatures, demonstrate how these funds can be deployed to continually improve an SLDS. Illinois9, Virginia, and Nebraska10 provide examples of this scenario, each which achieved sustainable funding through one of the previously mentioned sources.
| NCES SLDS Grant Funding Rounds – by state11 | |||||||
| . | |||||||
| State | 2006 | 2007 | 2009 | 2009 ARRA | 2012 | 2015 | Total |
| Alabama | – | – | – | – | – | – | – |
| America Samoa | – | – | – | – | – | 7,000,000 | 7,000,000 |
| Alaska | 3,506,757 | – | – | – | 4,000,000 | – | 7,506,757 |
| Arizona | – | 5,954,518 | – | – | 4,966,706 | – | 10,921,224 |
| Arkansas | 3,328,503 | – | 4,967,991 | 9,832,689 | – | – | 18,129,183 |
| California | 3,255,445 | – | 6,000,000 | – | – | – | 9,255,445 |
| Colorado | – | 4,244,519 | – | 17,409,117 | – | – | 21,653,636 |
| Connecticut | 1,500,714 | – | 2,937,416 | – | – | – | 4,438,130 |
| Delaware | – | – | – | – | 4,616,250 | – | 4,616,250 |
| District of Columbia | – | 5,738,500 | – | – | 4,000,000 | – | 9,738,500 |
| Florida | 1,577,602 | – | 2,450,000 | 9,975,288 | – | – | 14,002,890 |
| Georgia | – | – | 8,942,640 | – | – | – | 8,942,640 |
| Hawaii | – | – | 3,477,053 | – | 3,386,693 | 6,642,010 | 13,505,756 |
| Idaho | – | – | 5,916,520 | – | 3,101,632 | – | 9,018,152 |
| Illinois | – | – | 8,999,956 | 11,869,819 | – | 7,000,000 | 27,869,775 |
| Indiana | – | 5,188,260 | – | – | 3,965,160 | – | 9,153,420 |
| Iowa | – | – | 8,777,459 | – | 3,747,281 | – | 12,524,740 |
| Kansas | – | 3,834,796 | 3,911,792 | 9,060,442 | – | – | 16,807,030 |
| Kentucky | 5,780,275 | – | 2,878,373 | – | 3,633,928 | 6,634,741 | 18,927,317 |
| Louisiana | – | – | 4,056,510 | – | – | – | 4,056,510 |
| Maine | – | 3,227,231 | – | 7,315,000 | – | – | 10,542,231 |
| Maryland | 5,690,718 | – | 5,990,186 | – | 3,963,473 | 6,990,361 | 22,634,738 |
| Massachusetts | – | – | 5,993,464 | 12,972,730 | – | 6,999,761 | 25,965,955 |
| Michigan | 3,000,000 | – | 5,517,228 | 10,624,964 | – | – | 19,142,192 |
| Minnesota | 3,272,448 | – | – | 12,411,777 | – | 6,992,025 | 22,676,250 |
| Mississippi | – | – | 3,387,308 | 7,569,716 | – | 6,588,210 | 17,545,234 |
| Missouri | – | – | 8,967,686 | – | – | – | 8,967,686 |
| Montana | – | – | 5,798,457 | – | 3,977,861 | 3,483,163 | 13,259,481 |
| Nebraska | – | 3,468,335 | – | – | 4,361,534 | – | 7,829,869 |
| Nevada | – | 5,999,975 | – | – | 3,999,990 | – | 9,999,965 |
| New Hampshire | – | 3,176,272 | – | – | 4,989,391 | – | 8,165,663 |
| New Jersey | – | – | – | – | 3,989,175 | – | 3,989,175 |
| New Mexico | – | – | – | – | – | – | – |
| New York | – | – | 7,844,313 | 19,670,975 | – | – | 27,515,288 |
| North Carolina | – | 6,000,000 | – | – | 3,639,543 | – | 9,639,543 |
| North Dakota | – | – | 6,723,090 | – | 3,943,898 | 6,475,690 | 17,142,678 |
| Ohio | 5,670,100 | – | 2,945,000 | 5,135,883 | – | – | 13,750,983 |
| Oklahoma | – | – | – | – | 4,997,082 | – | 4,997,082 |
| Oregon | – | 4,705,977 | 3,696,615 | 10,475,997 | – | – | 18,878,589 |
| Pennsylvania | 4,008,875 | – | 6,103,000 | 14,284,020 | – | 6,999,928 | 31,395,823 |
| Puerto Rico | – | – | – | – | 4,665,708 | – | 4,665,708 |
| Rhode Island | – | – | 4,667,933 | – | 4,000,000 | – | 8,667,933 |
| South Carolina | 5,795,603 | – | – | 14,890,261 | – | – | 20,685,864 |
| South Dakota | – | – | – | – | 3,033,792 | – | 3,033,792 |
| Tennessee | 3,226,313 | – | – | – | – | 6,917,059 | 10,143,372 |
| Texas | – | – | 7,879,785 | 18,195,078 | – | 6,972,522 | 33,047,385 |
| Utah | – | 4,561,763 | – | 9,617,736 | – | 6,497,783 | 20,677,282 |
| Vermont | – | – | – | – | 4,947,261 | – | 4,947,261 |
| Virginia | – | 6,054,394 | – | 17,537,564 | – | – | 23,591,958 |
| Washington | – | – | 5,941,887 | 17,341,871 | – | 6,992,452 | 30,276,210 |
| West Virginia | – | – | – | – | 4,798,697 | – | 4,798,697 |
| Wisconsin | 3,081,000 | – | 5,552,270 | 13,809,040 | – | 5,242,866 | 27,685,176 |
| Wyoming | – | – | – | – | – | – | – |
| _________ | ________ | _________ | _________ | ________ | _________ | _________ | |
| Totals | 52,694,353 | 62,154,540 | 150,323,932 | 249,999,967 | 94,725,055 | 104,428,571 | 714,326,418 |
1 State Longitudinal Data Systems Research, Bill & Vieve Gore School of Business, Westminster College, Salt Lake City, Utah; www.slds.rhaskell.org
2 Richard Haskell, PhD, Associate Professor of Finance, Gore School of Business, Westminster College, Salt Lake City, Utah (2017); http://www.rhaskell.org/haskell
3 Peter Seppi, BS Finance & Economics, Westminster College, Salt Lake City, Utah (2017): https://www.linkedin.com/in/peter-seppi-11000091
4 State Longitudinal Data Systems (SLDS), Education Commission of the States; https://www.ecs.org/state-longitudinal-data-systems/
5 National Center for Education Statistics, State Grantee Program; https://nces.ed.gov/programs/slds/stateinfo.asp
6 Utah state profile, State Longitudinal Data Systems Research; http://slds.rhaskell.org/state-profiles/utah
7 Washington state profile, State Longitudinal Data Systems Research; http://slds.rhaskell.org/state-profiles/washington
8 Idaho state profile, State Longitudinal Data Systems Research; http://slds.rhaskell.org/state-profiles/idaho
9 Illinois state profile, State Longitudinal Data Systems Research; http://slds.rhaskell.org/state-profiles/illinois
10 Nebraska state profile, State Longitudinal Data Systems Research; http://slds.rhaskell.org/nebraska
11 Grantee States, Statewide Longitudinal Data Systems Grant Program, National Center for Education Statistics; https://nces.ed.gov/programs/slds/stateinfo.asp