Date of Submission

8-11-2021

Document Type

DiP

Degree

Doctor of Education

Department

Education

Keywords

adaptive leadership, cross-functional collaboration, data-driven decision-making, distributed leadership, strategic enrolment management

Abstract

The institutional pressures placed on the Ontario college system, exercised through funding model reform, brought forward organizational challenges difficult for even the most fiscally savvy to navigate. The enrollment corridor mechanism and the expansion of the proportions of the differentiation envelope to create a performance-based grant, implemented via the 2020-25 Strategic Mandate Agreement (SMA3), demonstrate the Provincial Government’s calls for efficiencies and accountability and the alignment of institutional and provincial priorities. Remaining financially sustainable while moving from performance reporting to performance funding and weathering the impacts of the Covid-19 pandemic requires a solid understanding of not only enrollment challenges and opportunities but also data and information used to inform decisions. Institutional Research (IR) units are responsible for providing leaders with data and information for this work. However, access to data and information does not imply their effective use (Marsh et al., 2006), pointing to a gap in data literacy skills amongst higher education leaders (Mathies, 2018). The problem of practice that will be examined is the role of IR in supporting effective data-driven decision-making related to achievement of the College X enrollment and SMA3 priorities. This Organizational Improvement Plan proposes that an existing Strategic Enrollment Management governance structure be leveraged for development and implementation of a group-level capacity building strategy. The planned change is used to inform enhancements to existing data tools and resources responsive to stakeholder needs and mindful of organizational context. The Change Path Model (Cawsey et al., 2016) provides the framework to implement this solution using distributed and adaptive leadership approaches.

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