EconSys Blog

Measuring Success in Competitive Integrated Employment Approach

May 15, 2018 | By: Drew Lessard | Category: Data Collection

Following the enactment of the Workforce Innovation and Opportunity Act (WIOA) in 2014, states have been tasked with implementing improved services for Americans with significant barriers to employment

, including individuals with disabilities, into high quality jobs and careers and help employers hire and retain skilled workers. The result is the implementation of competitive integrated employment (CIE) approach that is designed to match people with disabilities with employment in integrated settings. Unlike old programs designed to employ those with impairments or disabilities, CIE approach matches these individuals with jobs at minimum wage or higher, and comparable wages to those who do not have disabilities.


For states implementing and supporting this approach, it is important to collect ample data that enables transparent reporting to visualize success. Justification of the cost of these programs is important not only at the state budgeting level, but to meet the requirements of WIOA. Here are some best practices for ensuring accurate measurements of success for states implementing these programs.

How Success is Determined in Employment First Initiatives

For states, such as Tennessee, Alabama, or Michigan, that have Employment First initiatives (EFI) to place individuals in CIE positions, success is determined based on allocated resources and the employment goals set by that state. For example, in a recent case study, EconSys helped the State of Tennessee’s Department of Intellectual and Developmental Disabilities (DIDD) measure their performance against a goal to double CIE employment. Through a partnership, the data is collected from DIDD providers twice a year through a web-based questionnaire.  The data collection tool looks at the overall rate, hourly wage, type of industry, and hours worked weekly. 

>>> Download the case study on Tracking Employment Outcomes for Individuals  with Disabilities.

Gathering Data from Third-Party Service Providers

Each state works with several employment service providers – third party agencies that place people with disabilities into work environments. These agencies are paid by the state for providing these services, so they must report on their performance on a regular basis, usually in the form of a data dump once every month.

However, most states lack a uniform system for collecting this data from providers, leading to incomplete spreadsheets that lack the ability to deep dive and evaluate true performance. Most providers send the minimum amount of data to the state to ensure they are paid for their services, but standardized data collection tools can increase the quality of this data and increase the adherence rate of providers in uploading it.

Ensuring Ample Data for Accurate Reporting

Despite the minimum requirements, most states need more than their third-party providers send them. This information helps them to meet the minimum requirements of state and federal law, but also helps to procure funding for additional programs, and enables them to develop reports and share statistics on people with disabilities in the workforce within their state.

By capturing data at the personal level, states can generate more granular reporting that dives into the areas of the program that work and those that do not, building a better picture of how to improve or grow their efforts over time.

How Data Collection Technology Can Improve EFI Program Efficacy

EFI can be vastly improved by the implementation of standardized data collection tools designed for government use. EconSys specializes in building such solutions at both the federal and state level. You can read more about our recent efforts in our case study, Data Collection for State Agency Employment Programs. You’ll learn how we addressed these common problems and built a system configurable to the needs of specific state programs.

Download the State Agency Service Provider Case Study