Appendix H



Analytics and Business Intelligence Strategy at Penn State


Introduction and Background                                                  

This informational report describes the strategy that Penn State’s Information Technology (IT) department is currently implementing on a University-wide level to build a modern, state-of-the-art analytics and business intelligence (BI) initiative at Penn State. In February 2018, Penn State hired Jon Crutchfield, Senior Director, Business Intelligence to engage with students, faculty, and staff members to develop and implement strategies to enhance the University’s use of data. The goal is to work with University stakeholders to develop and implement a successful, comprehensive analytics and BI initiate

Today, Penn State generates an enormous amount of data, but is unable to efficiently transform much of that data into actionable information. Too much data is currently stored in formats that do not promote analysis, in isolated systems inaccessible to many people who need it, and disconnected from other related data. At the same time, too much data is being copied, distributed, and modified with very little transparency or control. These conditions increase risk of data exposure and prevent the University from developing necessary insights needed to support strategic initiatives and institutional goals.

Below is the high-level plan to change how Penn State governs data and makes data available for analysis. The plan addresses developing data governance policies and procedures aligned with University strategic priorities and goals; setting standards for data definitions, dictionaries and reporting conventions; setting priorities for improving data infrastructure; coordination collaboration and reporting across functional areas; and enabling more sophisticated analyses.


To successfully leverage data as a strategic asset, the University must begin with the core principle that data is an asset owned by the institution and move away from siloed “data ownership.” Developing a data-driven culture requires governance by a representative body of stakeholders and is enabled by a collection of supported tools.

Building a governed, integrated, validated, accessible, effective, and secure data ecosystem is key to maintaining and enhancing Penn State’s position as a leader in higher education. A successful analytics and BI strategy must be focused on informing and supporting the University’s mission and strategic plan. A successful decision support framework will insure decision makers at all levels and in all areas have access to the right data in the right format at the right time to make the right decision.

Short Term Strategy

Assess the current state and create analytics and BI strategic plan by engaging key stakeholders to better understand data governance, data management, business processes, and challenges and opportunities. Assessment efforts will inform the creation of a strategic plan for improving analytics and BI throughout the University.

Learn from and partner with internal and external groups to create an analytics community, including faculty, students, staff, and administrators. Host a second Data Summit in December 2018. Share and scale the good work happening in multiple areas of the University. Leverage existing groups like the Institutional Research Interest Group and create new groups to share best practices and learn from each other.

Implement data governance at the institutional level, establishing groups, roles, and responsibilities for governing data. Data governance promotes trust and transparency by clearly articulating stakeholders’ responsibilities, and providing data access in a consistent, well documented, and interconnected way. The governance groups will be responsible for establishing specific data management requirements and access rules, in alignment with the principles of data governance established by the Analytics & Business Intelligence Steering Committee, including the prioritization of communication, education, training, support, and stakeholder community building. The Analytics & Business Intelligence Steering Committee approved a data governance framework and has created and charged the Data Governance Working Group to work through data governance implementation issues, and the creation of an official data dictionary.

Improve existing systems and tools, including LionPATH, WorkLion, and iTwo to ensure we gain maximum benefit from existing investments while planning and building future environments.

Long Term Strategy

Create technical and organizational environments that empower people to use their analytical skills, which have been underutilized. Grow skills in data warehousing, analysis, and visualization. Recruit additional talent aligned with the strategic plan.

Use systems and analytical insights to make processes more efficient, effective, and user friendly. Develop a comprehensive awareness, education, training, and support plan help get full value from existing and new tools. Embed data governance policies in business processes and systems.

Create technical architecture that enables documented and authoritative sources of data, accessible from supported analytical and visualization tools, while providing flexibility to meet emerging needs. Build systems with improved data integration, better support for

business processes, enhanced user interface and user experience, and computing power to support artificial intelligence and machine learning.


Below is a tentative high-level timeline summarizing major new efforts for each activity. This timeline does not represent significant work done prior to 2018. Additional work will also continue for each activity beyond the end of the bars show, but at lower levels of effort. The data governance framework and the analytics and BI strategy will include periodic reviews to ensure efforts are sustainable over time.September 18, 2018 Senate Agenda, Appendix H, Image 1Access Current State: January 2018 to December 2019
Develop Data Governance: January 2018 to Approximately September 2018
Implement Data Governance: Approximately May 2018 to December 2019
Develop Analytics and BI Strategy: January 2018 to Approximately May 2019
Implement Analytics and BI Strategy: Approximately September 2018 to December 2020


  • Fred Aebli
  • Robert Bridges
  • Mary Beth Clark
  • Barbara Dewey
  • Roger Egolf, Chair
  • Joseph Enama
  • Mathew Krott
  • Michal Kubit
  • Anna Mazzucato
  • John Messner
  • Terry O’Heron
  • Barry Pawlowski
  • Jacqueline Reid-Walsh
  • Jennifer Sparrow
  • Eric Walker, Vice Chair


  • Fred Aebli, Vice chair
  • Mary Beth Clark
  • Barbara Dewey
  • Roger Egolf, Chair
  • David Han
  • Michal Kubit
  • John Messner
  • Jacqueline Reid-Walsh
  • Francesca Ruggiero
  • Shuan Shen
  • Harold Smith
  • Jennifer Sparrow
  • Christine Truica