This portfolio encompasses data-informed decision-making across CLAS: enrollment and scheduling analysis, strategic planning support, and data coordination with campus partners in service of the Dean's Office college-wide, rather than any single unit.

Strategic data and decision support

• Serve as the Dean's Office's primary point person for translating raw institutional data (SCH, enrollment, retention, DFW rates, faculty workload) into decision-ready analysis for hiring, budget, and program planning.
• Assist with the annual faculty line request/ranking process from a data standpoint building the structural urgency, institutional impact, and workforce-alignment framework used to evaluate competing unit requests, similar to this year's tiered hiring priorities analysis.
• Maintain a standing set of unit-level data profiles (SCH trends, major/minor enrollment, faculty-to-SCH ratios) that chairs and the Dean's Office can reference year-round rather than rebuilding from scratch each cycle.

Course scheduling and enrollment forecasting

• Analyze course-level demand and scheduling patterns to help units align offerings with actual student demand, reducing both under-enrolled sections and bottlenecks in high-demand courses.
• Build forecasting models tied to incoming enrollment trends (including transfer enrollment patterns as GVSU leans into that channel) to help units plan sections and staffing 1–2 years out rather than reactively.
• Flag structural scheduling risks early, e.g., programs with heavy reliance on a single instructor for a required sequence, or persistent gen-ed bottlenecks.

Institutional reporting and cross-campus collaboration

• Serve as CLAS's liaison to the Provost's Office and Institutional Analysis on data requests, ensuring consistent definitions and methodology are used college-wide (so units aren't reporting SCH or FTE figures inconsistently).
• Represent CLAS in university-level data governance conversations, bringing college-specific context to campus-wide reporting initiatives.
• Coordinate with accreditation-facing units to ensure data needs for self-studies and program reviews are met proactively rather than under deadline pressure.

Dashboards, tools, and reporting infrastructure

• Develop and maintain dashboards/visualization tools that give chairs and the Dean's Office self-serve access to current enrollment, SCH, and workload data.
• Build repeatable reporting templates so annual asks (hiring requests, space requests, program review) come in a consistent, comparable format across units rather than each unit's own narrative style.
• Where appropriate, develop predictive models (e.g., enrollment cliffs by program, retention risk indicators) to support longer-range planning.

Strategic initiative alignment

• Connect data analytics work to the college and university's active strategic priorities like Reach Higher Together, the Academic Affairs Strategic Framework, and CLAS's own vision and commitments to ensure metrics tracked actually map to stated institutional goals rather than data collection for its own sake.
• Support the Dean's Office in demonstrating progress (or identifying gaps) against those strategic priorities using concrete data rather than anecdote.

Advising on resource allocation

• Provide data-grounded input into space allocation, hiring, and budget decisions alongside the Dean and Associate Deans, functioning as a check on purely narrative-driven requests from units.
• Help develop consistent, defensible criteria for prioritization decisions (as opposed to ad hoc judgment calls) so decisions can be explained and defended to units that don't get funded.

Communication and stakeholder engagement

• Present complex data clearly to non-technical audiences, chairs, faculty governance bodies, the Dean's Office, translating statistical analysis into actionable recommendations.
• Approach all of the above with cultural humility and genuine cross-unit collaboration, given that data-driven prioritization inevitably surfaces uncomfortable comparisons between units.