Title: Changing Perspectives on Workforce System Performance
1Changing Perspectives on Workforce System
Performance
- Data Validation
- Workforce Innovations
- San Antonio
- July, 2004
2Purpose of Todays Session
- Update states and grantees on what is new in data
validation - Provide information on the findings to date from
the first round of validation - Allow states and grantees to provide feedback to
ETA on how to improve the DV process
3Role of Data Validation in ETA Performance
Assessment
- Data validation is a key component in overall
performance strategy - Program funding is being directly tied to
reliable performance outcomes (performance budget
integration) - Data validation required by OIG and now being
reviewed by GAO - Data validation is integrated into reporting
- Validation tools are evolving to meet state needs
4 Programs Included in the Data Validation Effort
- Unemployment Insurance Benefits and Tax (UI)
- Workforce Investment Act (WIA)
- Trade Adjustment Assistance (TAA and NAFTA-TAA)
- Labor Exchange
- National Farmworker Jobs Program (NFJP)
- Indian and Native American Programs (INA)
- Senior Community Service Employment (SCSEP)
- Office of Apprenticeship, Training, Employment,
and Labor Services (OATELS)
5How Does Validation Work?
- Two separate processes are required to ensure
that performance data is reliable - Report Validation
- Data Element Validation
- ETA provides software to states and grantees that
analyzes participant records
6Report Validation
- Ensures that performance calculations are
accurate - DV software creates an audit trail for the
numerator and denominator for each performance
measure - Classifying participant records into performance
outcome groups enables non-technical staff to
validate and analyze program outcomes
7Data Element Validation
- Report will not be accurate if the data being
used by the software are wrong - Requires checking data elements against source
documentation to verify compliance with federal
definitions - Handbooks contain instructions and examples of
acceptable source documents for each data element
validated - States identify state-specific source
documentation to reflect the variability of state
MIS systems and state/local documentation
standards
8Reporting of Validation Results
- Data validation software produces
- Report validation summary
- Data element validation summary and analytical
reports - WIA and LX software creates files with the annual
report validation values for upload to ETA
9Validation Efforts to Date
- Many states have shared their validation results
- First round of validation was a valuable learning
experience for all - ETA has not set standards for acceptable data
quality - Standards will be set for PY 2004 data validation
10What is New for PY 2003 Validation
- New schedule for reporting and validation
- New software
- New policies for collection and retention of
source documentation
11Schedule for Reporting of Validation Results
- WIA RV will be due October 1, 2004 when the
annual report is due - WIA and TAA data element validation will be due
February 1, 2005 - LX report validation will be due November 15,
2004 with the report.
12Data Validation for National Programs
- NFJP validation to begin in February
- Reports due in June
- Pilot of process was conducted in spring
- Software will be tested further in fall
- Training session scheduled for November
- Data validation to be added to SCSEP in late 2005
- Indian and Native American validation will be
incorporated into existing reporting software
13Revised Software
- WIA Version 3.0 to be released in mid-August
- New versions TAA (version 1.3) and LX (version
1.8) validation software - All will include automated upload of DV reports
to ETA
14WIA Software Changes
- Calculate performance for the new reporting
periods - Calculate Table O
- More complete edit checks
- Ability to filter source table and performance
outcome groups to provide greater analytical
flexibility - Accept records for participants served only by
NEGs
15Software Upgrades for WIA Data Element Validation
- Revised Data Element Validation Worksheets to
reflect reduction in elements - Improved ability to identify records that have
not been validated - Ability to identify sampled records that have are
missing, invalid, wrong SSN, or whose location is
unknown. - Ability to trace exported samples
16States Experiences with Data Validation
- States had to determine staff to be responsible
for data validation - Communication of expectations and requirements to
local areas - Mode of data element validation onsite,
centralized or both
17State and Local Roles and Responsibilities
- States had varying experiences in identifying
validation assignments - Some states had no problem
- Some states took time to sort through roles of
different units - Some states still have not clarified assignments
(particularly for TAA) - Organization of case files at local areas was
often not standardized or adequate
18Improving the Clarity of Source Documentation
Requirements
- ETA has not had clear and specific policies for
collection and retention of source documentation - States need to provide clear guidance to local
areas - ETA will clarify requirements in change 1 to TEGL
3-03 - Currently in clearance
- To be issued in August
19Streamlined Data Element Validation Requirements
- As a result of state feedback, ETA reviewed and
reduced the number of elements to be validated - All elements directly related to performance or
eligibility
20Detail for reduction in elements
21Various Methods for Data Element Validation
- Onsite validation is essential to preserve the
integrity of the process - Ideal for state staff to perform validation
onsite - Promotes communication and mutual understanding
- In some cases, onsite validation is impractical
- Distances are too great
- Small number of records
- States can therefore pursue a combination of
onsite and remote validation if necessary
22Findings for WIA Report Validation
- States had problems in two areas
- Problems with extract file imported into software
- Problems with calculations
23WIA Report Validation -- File Problems
- Extract file imported into the software is
incorrect - Data in extract file does not match data in
states data system - Inconsistent data
- File is different from the file used to calculate
the report submitted to ETA - Missing records
- Changed/Updated Data
24WIA Report Validation Calculation Problems
- States excluded older Youth in advanced
training/post-secondary school from performance,
even if the youth is employed. - Failure to distinguish pre-dislocation earnings
from pre-registration earnings for dislocated
workers - Exclusion of records for earnings calculations
due to 99,999.99.
25Data Element Validation Findings
- Significant number of errors error rates
exceeded 20 for some elements - Many errors can be explained by lack of clarity
in expectations for local source documentation - Problems with changing wage records and WRIS data
26WIA Data Element Validation Results for Adults
27WIA Data Element Validation Results for
Dislocated Workers
28WIA Data Element Validation Results for Older
Youth
29WIA Data Element Validation Results for Younger
Youth
30TAA Data Element Validation Results by the
Numbers
31Continuing Challenges
- State wage record files are always changing
- One solution is to freeze the file to avoid
changes - States should track changes in order to validate
wages - Confidentiality of WRIS data
- WRIS has rules restricting access to information
- Software allows states to suppress display of
wage values
32Future of Data Validation
- Standards for acceptable error rates to be
established - ETA is moving toward a consolidated reporting
system - Data Validation will be integrated into the new
reporting system
33For More Information
- Contact Information
- Traci Di Martini
- 202-693-3698
- Dimartini.traci_at_dol.gov
- MPR Technical Assistance
-
- William Borden 609-275-2131
- Jonathan Ladinsky 609-275-2250
- WIATA_at_mathematica-mpr.com
- TAATA_at_mathematica-mpr.com
- ESTA_at_mathematica-mpr.com
- http//www.doleta.gov/Performance/reporting/tools_
datavalidation.cfm
34We Need Your Feedback
- Tell us about your experiences with Data
Validation - What did you learn that may help others
- What improvements can be made