Day:
Tuesday, November 5, 2019
Time:
10:30 AM - 12:00 PM
Location:
Manchester, Mezzanine Level
First Learning Outcome: The context in which data is presented is critical to directing beneficial organizational change.
Second Learning Outcome: The methods of collecting, contextualizing, and presenting data can affect organizational buy-in and collaboration.
Third Learning Outcome: Effective organizational change can be led by more data but can also be led by less data and more conversation.
Core Competencies: Collaborative Decision-Making and Consensus-Building, Interpretation and Application of Institutional and External Data
Proficiencies: Enrollment Management: SEM Assessment, Enrollment Management: SEM Leadership
Intended Audience: Some experience in the profession, Significant experience in the profession
Contextual Data and Implementation Strategies to Influence Organizational Change
Category
Session
Description
The institutions of today are data-driven, or at least data-informed, in their decision-making. The data elements that are sought and/or used to make these decisions, however, are complicated and nuanced at best and have their interpretation marred in bias at worst. This presentation will address the variety of questions that keepers of large datasets inevitably get and how these requests can be used to start or continue productive conversations that lead to beneficial organizational change. Examples will be offered of how missing or incomplete context may stifle prudent action and how appropriate context to data elements can be developed. Means of collecting data will be discussed as well as the influence that these methods might have on developing organization buy-in and collaboration. Mini-case studies from multiple institutions will be shared along with lessons learned. Experiences and questions from session attendees will be discussed as time allows.
Examples of questions that will be addressed:
What are potential problems with providing too much data?
Is it ever not beneficial to collect or analyze data?
Are decisions based on more data better?
What are the best approaches to presenting and explaining nuances in trends?
What are the risks in providing data without context or with incomplete context?
How do we discover what data elements or context we are missing?
Submission ID:
6607
Presenter(s):
Alexis Pope Appalachian State University
Susan Davies Augusta University
Winner Status
- Session