Maggie Cosgrove

Senior Partner, Cosgrove & Associates

Maggie Cosgrove is a senior partner with Cosgrove & Associates. Ms. Cosgrove has deep experience in policy analysis, grant management, and community college research and evaluation. Her experience includes evaluating Department of Labor, National Science Foundation, and urban redevelopment grants. Ms. Cosgrove has a proven track record of providing excellent training and customer service to college partners. Specific areas of expertise include developmental and utilization-focused evaluation, developmental education redesign, development of career pathways, return on investment analysis, and employer and community stakeholder engagement. Ms. Cosgrove is committed to social justice and efforts to enhance equity in student outcomes for all students.


Blog: Utilization-focused Evaluation

Posted on December 11, 2019 by , in Blog
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
John Cosgrove
Senior Partner, Cosgrove & Associates
Maggie Cosgrove
Senior Partner, Cosgrove & Associates

 

As seasoned evaluators committed to utilization-focused evaluation, we partner with clients to create questions and data analysis connected to continuous improvement. We stress developmental evaluation[1] to help link implementation and outcome evaluation. Sounds good, right? Well, not so fast.

Confession time. At times a client’s attention to data wanes as a project progresses, and efforts to actively engage clients to use data for continuous improvement do not generate the desired enthusiasm. Although interest in data re-emerges as the project concludes, that enthusiasm seems more related to answering “How did we do?” rather than exploring “What did we learn?” This phenomenon, depicted in the U-shaped curve in Figure 1, suggests that when data may have great potential to impact continuous improvement (“the Messy Middle”), clients may be less curious about their data.           

To address this issue, we revisit Stufflebeam’s guiding principle: the purpose of evaluation is to improve, not prove.[2] Generally, clients have good intentions to use data for improvement and are interested in such endeavors. However, as Bryk points out in his work with networked improvement communities (NIC),[3] sometimes practitioners need help learning to improve. Borrowing from NIC concepts,[4] we developed the Thought Partner Group (TPG) and incorporated it into our evaluation. This group’s purpose is to assist with data interpretation, sharing, and usage. To achieve these goals, we invite practitioners or stakeholders who are working across the project and who have a passion for the project, an interest in learning, and an eagerness to explore data. We ask this group to go beyond passive data conversations and address questions such as:

  • What issues are getting in the way of progress and what can be done to address them?
  • What data and actions are needed to support sustaining or scaling?
  • What gaps exist in the evaluation?

The TPG’s focus on improvement and data analysis breathes life into the evaluation and improvement processes. Group members are carefully selected for their deep understanding of local context and a willingness to support the transfer of knowledge gained during the evaluation. Evaluation data has a story to tell, and the TPG helps clients give a voice to their data.

Although not a silver bullet, the TPG has helped improve our clients’ use of evaluation data and has helped them get better at getting better. The TPG model supports the evaluation process and mirrors Englebart’s C-level activity[5] by helping shed light on the evaluator’s and the client’s understanding of the Messy Middle.

 

 


[1] Patton, M. Q. (2010). Developmental evaluation: Applying complexity concepts to enhance innovation and use. New York: Guilford Press.
[2] Stufflebeam, D. L. (1971). The relevance of the CIPP evaluation model for educational accountability. Journal of Research and Development in Education.
[3] Bryk, A., Gomez, L. M., Grunow, A., & LeMahieu, P. G. (2015). Learning to improve: How America’s schools can get better at getting better. Cambridge, MA: Harvard Education Publishing.
[4] Bryk A. S., Gomez, L. M., & Grunow A. (2010). Getting ideas into action: Building networked improvement communities in education. Stanford, CA: Carnegie Foundation for the Advancement of Teaching. Also see McKay, S. (2017, February 23). Quality improvement approaches: The networked improvement model. [blog].
[5] Englebart, D. C. (2003, September). Improving our ability to improve: A call for investment in a new future. IBM Co-Evolution Symposium.

Blog: Partnering with Clients to Avoid Drive-by Evaluation

Posted on November 14, 2017 by , in Blog ()
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
   
 John Cosgrove

Senior Partner, Cosgrove & Associates

 Maggie Cosgrove

Senior Partner, Cosgrove & Associates

If a prospective client says, “We need an evaluation, and we will send you the dataset for evaluation,” our advice is that this type of “drive-by evaluation” may not be in their best interest.

As calls for program accountability and data-driven decision making increase, so does demand for evaluation. Given this context, evaluation services are being offered in a variety of modes. Before choosing an evaluator, we recommend the client pause to consider what they would like to learn about their efforts and how evaluation can add value to such learning. This perspective requires one to move beyond data analysis and reporting of required performance measures to examining what is occurring inside the program.

By engaging our clients in conversations related to what they would like to learn, we are able to begin a collaborative and discovery-oriented evaluation. Our goal is to partner with our clients to identify and understand strengths, challenges, and emerging opportunities related to program/project implementation and outcomes. This process will help clients not only understand which strategies worked, but why they worked and lays the foundation for sustainability and scaling.

These initial conversations can be a bit of a dance, as clients often focus on funder-required accountability and performance measures. This is when it is critically important to elucidate the differences between evaluation and auditing or inspecting. Ann-Murray Brown examines this question and provides guidance as to why evaluation is more than just keeping score in Evaluation, Inspection, Audit: Is There a Difference? As we often remind clients, “we are not the evaluation police.”

During our work with clients to clarify logic models, we encourage them to think of their logic model in terms of storytelling. We pose commonsense questions such as: When you implement a certain strategy, what changes to you expect to occur? Why do you think those changes will take place? What do you need to learn to support current and future strategy development?

Once our client has clearly outlined their “story,” we move quickly to connect data collection to client-identified questions and, as soon as possible, we engage stakeholders in interpreting and using their data. We incorporate Veena Pankaj and Ann Emery’s (2016) data placemat process to engage clients in data interpretation.  By working with clients to fully understand their key project questions, focus on what they want to learn, and engage in meaningful data interpretation, we steer clear of the potholes associated with drive-by evaluations.

Pankaj, V. & Emery, A. (2016). Data placemats: A facilitative technique designed to enhance stakeholder understanding of data. In R. S. Fierro, A. Schwartz, & D. H. Smart (Eds.), Evaluation and Facilitation. New Directions for Evaluation, 149, 81-93.