Spring 2013 - 62645 - PA680PB - Policy Research Project
Measuring and Modeling Performance for Debt Management Services, US Department of Treasury
|Instructor(s):|| Matwiczak, Kenneth
|Day & Time:||Th 2:00 pm -5:00 pm|
|Waitlist Information:||For LBJ Students: UT Waitlist Information|
In recent years, governments have come under increasing pressure to improve the quality and cost effectiveness of service delivery. Governments must plan to do more with less, delivering more and greater outcomes in a more efficient manner.
Debt Management Services (“DMS”) at the U.S. Department of the Treasury (“Treasury”) is currently undergoing significant internal re-evaluation of mission and goals, reorganization and consolidation of functions and offices, and planning for implementation of these efforts. DMS currently does not have metrics that can used to indicate progress toward established program and department goals in a cohesive, coherent form.
This project proposes to work in conjunction with the DMS leadership and staff in the Austin regional office to (1) define relevant and appropriate measures of performance, and (2) using agreed to measures, develop a spreadsheet model that can be used to communicate DMS progress toward established goals and to identify strengths and weaknesses in their efforts. The basic research question would be: Is there a useful, relevant, reliable, and unified way to measure, summarize, and report performance and progress at DMS, from the department to program level?
Students in this project will draw on problem-framing, policy analysis, interaction with DMS and Treasury “experts”, and quantitative methodology skills to develop a spreadsheet-based “performance” model (“Model”) for Treasury and DMS. When implemented, the model will provide a baseline for performance comparison, over time, for DMS and Treasury. The resulting performance model will also give DMS leadership a framework to use in making resource allocation decisions that will balance outcomes against cost-effectiveness.
The project could involve travel to locations at which DMS policy is developed and debt collection functions and operations are performed, depending on funding availability, timing, on-going project definition, etc. The project will also produce a publishable report for Director of Debt Management Services, U.S. Department of the Treasury. Students will be provided the opportunity to meet and interact with relevant staff in DMS and at Treasury, as well as present, in person, project results to DMS, designated Treasury personnel, and other distinguished guests, at various points in the project. This will be a “student-led” project, with guidance and expectations provided by the principal investigator (Instructor) and the Director of DMS, (i.e., the Client).
To accomplish this, the Policy Research Project will perform the following tasks:
- Develop an understanding of performance measurement in government organizations through review of the relevant literature, class lectures, and practical exercises.
- Learn the Multi-Attribute Utility (MAU) performance modeling philosophy and methodology, (i.e., model input requirements, data needs, model outputs, analysis tools, etc.)
- Review and document current and recent Department of Treasury and Client (DMS) debt collection policies, programs and procedures.
- In conjunction with DMS and Treasury, through surveys, interviews, brainstorming sessions, meetings, and other collaborative means, develop outcomes and outcome-based metrics for use in the MAU Model.
- Identify and collect the relevant data, as identified by the outcomes and other metrics.
- Using the MAU Model, and other tools, perform an analysis of the data to identify performance and cost indicators.
- Demonstrate sensitivity analysis and comparative results of the MAU Model.
- Develop a formal report for Treasury and DMS that would include all background work and data developed by the project, (e.g. annotated bibliography, summary results of surveys and interviews, literature reviews, etc.), an annotated database of any data collected for the Model, the Model itself, (with appropriate definitions and instructions), and any resulting conclusions, suggestions, and recommendations