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Data Governance Classification of Instructional Programs (CIP) Code Task Force Charge Letter

(Original on Academic and Student Affairs letterhead)

April 20, 2020

Data Governance Classification of Instructional Programs (CIP) Code Task Force
Kima Cargill, Associate Dean for Academic Affairs and Planning, Graduate School, Co-Chair
Helen Garrett, University Registrar, Enrollment Management, Co-Chair
Rick Fenger, Assistant Director, Decision Support Services, ORIS
Stephanie Harris, Institutional Analyst, Institutional Data & Analysis
Jodi McKeeman, Business Systems Analyst, UW-IT
Ann Nagel, Associate Vice Provost, Office of Privacy, Academic and Student Affairs and Chair of Data Governance Operational Committee
Matt Saxton, Associate Dean, Information School
Matt Winslow, Senior Associate Registrar, Policy and Procedure

Dear Colleagues:

Thank you for your willingness to serve on the Classification of Instructional Programs (CIP) Code Task Force charged with addressing the gaps in the current CIP Code assignment, change, and maintenance processes. This group will begin its work in June 2020 and report findings and recommendations to the Data Governance Steering Committee in August 2020.

As you are aware, the CIP code system facilitates the organization, classification, and reporting of student enrollment and program completion by a field of study. CIP Codes are used to classify programs as ‘high-demand’ or ‘STEM’ for funding and grants, they impact international student visa status, are required for state and federal mandated reporting, and are used in national institutional rankings.

We know of three possible times when a program may need to engage in this process to develop, change, or update their CIP Code:

  1. When the Federal government releases new and updated CIP Codes, and we must update affected programs in our data systems. An update is currently under way for 2020.
  2. When a program finds that they more closely align with a different CIP Code than the current one assigned.
  3. When a new program is approved and must determine which CIP Code they should use.

Data Governance uses a maturity model for major initiatives to identify current and desired end-state maturity levels for each major project. Given competing priorities and resources, not all projects will aim for full maturity. The goal for this task force is to take the UW’s process for assigning, changing and maintaining CIP Codes from a data governance maturity level of 2, repeatable, to an end-state of 3, defined (see Appendix for the complete maturity model).

To this end, this Task Force is charged with addressing the following:

  1. Determine the current state of each of these business and technical processes.
  2. Given the desired end-state maturity level:
    • Research and suggest process improvements.
    • Recommend implementation strategies to reach the future state.

This discovery should include a holistic review of the CIP Code assignment/alignment process, including, but not limited to, approval processes, implementation processes, communication, and potential downstream impacts. Actual implementation will be phase two and, as such, is beyond the scope of this Task Force.

To help answer questions and provide guidance, as needed, your co-chairs will meet briefly and regularly with Marisa Nickle, Ann Nagel and me in our Data Governance roles.

A report with findings and recommendations should be provided to the Data Governance Steering committee no later than August 2020. Thank you again for your willingness to help with this critical work.


Phil Reid
Vice Provost, Academic and Student Affairs
Professor of Chemistry


Maturity Model for Major Data Governance Initiatives
The maturity model is used to help measure the value of major data governance initiatives (e.g. data map, data stewardship, country codes). For major data governance initiatives, the data governance committees evaluate the maturity level at the initial (current) state, intended future state, and progress towards the intended future state. These metrics help the establish the baseline, create clarity on where we are going, and align expectations with the steering and operational committee, related governance groups, and our colleagues across all three campuses.

The metrics along with other high-level and pertinent information about each initiative will be published on the data governance website.

Maturity Level 5 Optimized Continuous improvement on major data governance initiatives considered “optimized” help the UW leverage data and data resources to respond to opportunity and change in a consistent and cohesive manner
Maturity Level 4 Managed Major data driven initiatives pursued through the data governance committees will be considered “managed” if they are connected to the UW strategy. Policies, best practices and supporting resources help ensure there’s a common understanding of data governance and management principles across the UW
Maturity Level 3 Defined To be considered “defined,” major data driven initiatives pursued through the data governance committees will be proactive, rather than reactive, and involve relevant data stewards, but are not connected to the UW strategy and priorities
Maturity Level 2 Repeatable Data driven initiatives are considered “repeatable” if they are regularly planned, executed, and measured in silos
Maturity Level 1 Initial “Initial” data driven initiatives are ad hoc, inconsistent, undefined, and/or lead
to incongruent results
Developed by Ann Nagel for Data Governance Operational Committee based on:

  1. Various conversations at UW with the Data Governance Task Force, Data Custodians, and Data Governance Committee Members
  2. High-level review of maturity models published by EAB, Carnegie Mellon, DataVersity, Prosci, Wikipedia, AICPA, Department of Defense, Marisa Sanchez Organization Dev & Change Mgmt Consulting

Adopted by Data Governance Operational Committee at the 3/5/2020 meeting