Closed FOA-ETA-21-05 CFDA 17.261 Discretionary

Workforce Data Quality Initiative – WDQI Round 8

Posted by Employment and Training Administration

Opportunity snapshot. This Grants.gov announcement — Workforce Data Quality Initiative – WDQI Round 8 — is cataloged under number FOA-ETA-21-05 and tied to CFDA assistance listing 17.261, posted by Employment and Training Administration. Grants.gov currently shows the opportunity as closed, first posted on March 22, 2021. The funding category is Discretionary, delivered as a grant.

Award economics. The award range on file is Up to $2,900,000. The agency has projected $11.6 million in total estimated funding for this announcement. It expects to issue 7 awards. If the agency funds the expected 7 awards from the $11.6 million estimated pool, the average award works out to roughly $1.7 million. Cost sharing is not required, so applicants do not need to commit matching funds to be competitive on this opportunity. Federal award ranges are often upper bounds; actual allocations reflect program appropriations, the strength of the applicant pool, and the evaluation committee's scoring.

Deadline and action path. This opportunity closed on April 26, 2021. Future funding cycles may be published under the same CFDA number, so monitoring the parent program page is the most reliable way to catch re-announcements. Every Grants.gov submission requires an active SAM.gov registration and a Unique Entity ID. Review the Eligibility section below carefully — federal eligibility categories (nonprofit, state or local government, tribal, individual, educational institution, small business) have distinct registration and reporting requirements. Pre-application outreach to the listed agency contact is permitted and often welcomed — it helps clarify scope and scoring priorities.

Award Range

Up to $2,900,000

Close Date

April 26, 2021

The closing date for receipt of applications under this announcement is April 26, 2021. Applications must be received no later than 4:00:00 p.m. Eastern Time.

Posted

March 22, 2021

Est. Total Funding

$11,600,000

Expected Awards

7

Instrument

Grant

Description

The purpose of this program is to support the development or expansion of state workforce longitudinal administrative databases. Collecting and analyzing longitudinal data can provide a comprehensive picture of whether education programs lead to employment in related fields, whether jobseekers are obtaining training-related employment, and the impact of training on workers’ earnings throughout their careers. Through such deep dive analyses, states can identify service delivery strategies that improve employment opportunities, as well as demonstrate the benefits of education and workforce programs on employment outcomes. Data linkages can help state and local leaders identify effective pathways through education and training services that lead to success in the workforce and can provide individuals with information that helps them make informed choices about their education and career(s). WDQI grants provide funding to eligible SWAs to accomplish all, or a combination, of the following objectives: Develop or improve the State Workforce Longitudinal Administrative Database. SWAs can use this funding to develop a new state workforce longitudinal administrative database, to incorporate new data sources, or to expand/strengthen existing data sources into their existing database so individual-level records can be matched across workforce training programs and over time.Connect workforce data with education data contained in the Statewide Longitudinal Data System (SLDS). WDQI requires that workforce data be matched with education data, consistent with all relevant federal and state privacy and confidentiality laws, to ultimately create a state longitudinal administrative database with individual-level information from pre-kindergarten through post-secondary and training into the workforce system. The connection of workforce and education data enables the analysis of individuals’ receipt of both education and training services to help determine ways to maximize the outcomes of these services and improve the effectiveness of the programs.Improve the quality and breadth of the data in workforce longitudinal administrative databases. It is important that data in the workforce longitudinal administrative databases are complete, accurate, and relevant to understand the impact of state workforce development programs on job seekers and employers. Data collection processes should be streamlined and standardized to ensure that the data are valid.Use longitudinal data to evaluate the performance of federally and state- supported education and job training programs. Evidence-based decision making is the foundation for effective program management and strategic planning. Longitudinal administrative databases provide business intelligence for policymakers and stakeholders to make programmatic adjustments in an effort to improve education and workforce programs.Provide user-friendly information to help customers select the education and training programs that best suit their skills. These state-customized scorecards contain data to help job seekers make informed decisions about programs that offer skills training needed to pursue in-demand jobs. Publicly-searchable-by-training provider and program-of-study scorecards allow anyone, including policymakers, students, and researchers, to search labor market information and available training and subsequent outcomes, such as program completion, employment, and wage information of participants in these training programs.Integrate performance, fiscal, and/or case-management systems with the longitudinal administrative database. Integration across multiple components of state data systems is a vital step towards improved program management and enhanced state data analytics capabilities. WDQI grants become even more vital as states move towards developing and building a more integrated data system structure, as envisioned under WIOA. ETA believes that these system enhancements will facilitate SWA’s development of comprehensive information sharing tools (e.g., mobile applications, dashboards, or interactive scorecards) enabling access to longitudinal administrative data system for different program needs including case managers, fiscal staff, or performance staff, to name a few. Linking information from longitudinal data systems, state-based wage-data-matching systems, and cross-program/departmental systems has the potential to improve workforce data quality.

Eligibility

25

Official Listing on Grants.gov

View full details, application forms, and submission instructions.

View on Grants.gov

Agency Contact

Anu Mathew <br/>Grants Management Specialist <br/>Mathew.Anu@dol.gov

Key Dates

Posted March 22, 2021
Close Date April 26, 2021
Archive Date May 26, 2021
Last Updated March 22, 2021

Frequently Asked Questions

What is this grant opportunity?
This is a federal funding opportunity titled "Workforce Data Quality Initiative – WDQI Round 8", offered by Employment and Training Administration. It is associated with CFDA program 17.261. The purpose of this program is to support the development or expansion of state workforce longitudinal administrative databases. Collecting and analyzing longitudinal data can provide a comprehensive ...
Is this opportunity still open?
No, this opportunity is closed. It closed on April 26, 2021. Check the parent program page for future funding cycles.
How much funding is available?
The award range for this opportunity is Up to $2,900,000. Total estimated funding: $11,600,000. Expected number of awards: 7.
How do I apply?
Applications for federal grant opportunities are typically submitted through Grants.gov. Visit the official listing at grants.gov for application instructions, required documents, and submission deadlines.

Disclaimer: This information is sourced from Grants.gov and SAM.gov and is for informational purposes only. Opportunity details, deadlines, and eligibility requirements change frequently. Always verify current information directly on Grants.gov before applying. PlainGrants is not affiliated with any federal agency.

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Data sourced from official U.S. government datasets. See our methodology for details. Retrieved and formatted by PlainGrants Editorial