English
Stout completed a statewide efficiency and effectiveness analysis of Michigan’s intake and referral systems/processes for residents with low incomes who had civil legal needs. The project involved a system-wide analysis and process mapping to understand how efficiently and effectively Michigan residents were receiving the assistance they were seeking or were referred to an organization that could assist them. Stout worked closely with the Michigan Justice for All Commission and its Triage and Referral Working Group to interview leadership and staff at Michigan Legal Help (MLH), Lakeshore Legal Aid’s Counsel and Advocacy Law Line (CALL), and the State Bar of Michigan’s Lawyer Referral Service (LRS). Stout also conducted independent research and deployed mystery calling. MLH, CALL, and LRS provided quantitative data that Stout used to develop a set of data visualizations and maps to better understand geographic concentrations of Michigan residents seeking assistance, interactions with MLH, and types of assistance sought, among other key data points.
Stout’s independent research included comparing MLH’s website to those of other states to identify best practices and opportunities for Michigan’s intake and referral systems/process to be enhanced. The final component of Stout’s work was to leverage its independent call center to conduct mystery calling. The purpose of the mystery calling was to:
- Experience the intake and referral ecosystem firsthand
- Identify strengths, weaknesses, and opportunities for improvement at the moments of direct interaction with Michigan residents seeking legal help
- Inform the development of key performance indicators, data collection recommendations, and iterative evaluation recommendations
The project culminated in a comprehensive report with a process map and recommendations for a more efficient and effective intake/referral system and improved user experience. As of late 2024 / early 2025, the Michigan Justice for All Commission began working to implement several of Stout’s recommendations.
