Students: New! | Length: Stay Tuned
Big or small, every nonprofit program requires coveted dollars and endless hours of staff and volunteer investment. But how can you make sure your programs work? And how can you demonstrate your impact to current and potential funders, peers, and partners?
This upcoming course, Maximizing your Impact: Program Evaluation for Nonprofits, will show you how to structure and manage your programs, program evaluations, and funding applications to measure and demonstrate your value. The course will be taught by Dr. Dan Treglia, resident Research and Data Whaler and a professor at the University of Pennsylvania with 15 years experience in nonprofit and government evaluation.
This course will focus on two strategies critical to maximizing and proving your impact:
- Real-time performance management to track progress and anticipate challenges, and
- Robust program evaluation that can prove your value to stakeholders, including funders and government partners
We’ll walk step-by-step through implementing these strategies in a fast-moving nonprofit environment.
Topics covered will include:
- Choosing the most important outcomes to measure and how to measure them,
- Leveraging existing data and collecting new data without overburdening clients and program staff,
- Creating systems to track and review real-time performance to anticipate challenges and make adjustments,
- Managing program stakeholders to review and make the most of your data, and
- Structuring a program’s implementation so it can be easily and convincingly evaluated
Finally, you’ll learn how to present this work to external stakeholders. We’ll cover how to present your performance management and evaluation plans in a funding application, packaging your completed evaluation into a final report, and how to parlay those findings and lessons learned into the next round of funding.
About Dr. Treglia
Dan Treglia is a PostDoctoral Fellow at the University of Pennsylvania’s School of Social Policy and
Practice who uses quantitative methods to address a range of social policy issues – most notably
homelessness – with a clear focus on policy and programmatic implications.
Dan’s recent work focuses on the use of large administrative data sets to address multi-sector,
seemingly intractable problems. Recent examples include an evaluation of the Supportive Services for
Veteran Families program, a homelessness prevention and rapid re-housing program run by the VA; a
randomized controlled trial of a homelessness prevention program in New York City; the integration of
machine learning algorithms into a VA homelessness screening tool to improve resource targeting; and
forecasting healthcare and nursing home needs and costs among older homeless adults.