Operational Excellence Consulting Services

The Vendor is required to provide operational excellence consulting engagement will assess and define enterprise operating models, with a tri-campus and technology enabled orientation and an emphasis on shared services across finance, research administration, and information technology, including opportunities to more fully leverage existing enterprise technologies, data, automation, knowledge capital and AI enabled capabilities.
- Functional requirements:
1. Conduct an enterprise-level operational assessment
• Assess current-state operational processes, organization structures, service delivery models, and governance structures across finance, research administration, and information technology, with attention to decentralization, variation, and institutional constraints.
• Approach must explicitly account for decentralized authority, funding models, and variation across units, including how adoption and standardization will be achieved in a federated environment.
• Evaluate how current and future state operations are enabled by existing enterprise systems, data, and digital tools, including opportunities to embed automation and generation AI capabilities within current platforms, rather than introducing new core technology.
• Identify and assess opportunities for shared services across finance, research, and it, including:
o Scope and service boundaries
o Operating models and organization structures
o Governance and accountability
o Impacts on costs, service quality, efficiency, and flexibility
o Assessment of institutional risk and alignment with accountability
2. Engage select stakeholders and provide support for broad engagement
• Facilitate structured engagement with senior leadership, central offices, and select distributed units to inform analysis, validate findings, and build shared understanding.
• Serve as “behind the scenes” support to the administration’s broader engagement with the community and governance structure.
• They will incorporate employee experience, organizational readiness, risk ownership, and change impacts into their approach.
3. Benchmark appropriately and deliver ROI analysis
• Provide benchmarking insights drawn from comparable institutions or organizations, with clear explanation of relevance and limitations.
• Prepare and deliver ROI analysis and target settings.
• Analysis must consider ROI beyond traditional cost-based ROI, considering metrics such as throughput improvements, risk management, and customer satisfaction.
4. Develop actionable recommendations
• Produce practical, university-appropriate recommendations that balance standardization with the needs of academic and research units.
• Recommendations should prioritize process, governance, and service delivery improvements enabled through existing technologies, including embedded automation or AI capabilities, existing knowledge capital, with key performance indicators identified, and should clearly distinguish between optimization of current platforms versus any longer term considerations that may require future investment decisions.