Executive Overview


The University of Michigan is committed to enhancing its position among the world's premier teaching and research universities. Over the last several years, the University has undertaken a number of initiatives aimed at improving the quality of its administrative services that support the teaching, learning, research, and public service missions. While some progress has been made, Michigan needed to address the question of how to integrate its various initiatives into a comprehensive strategy for administrative cost reduction, organizational restructuring, process innovation, and quality improvement that will enable the University to make the necessary investment in targeted areas, both academic and administrative. Strategic Data Planning (SDP) provides a road map for integrating these initiatives into a comprehensive strategy.

In October 1993 the Executive Computing Committee charged the Strategic Data Planning project team to create an information systems plan for the University of Michigan. The project team was to establish a long term direction for the effective use of information resources to support the goals of the institution.

The primary objectives of the SDP effort at the University of Michigan are to:

The ultimate goal of SDP is to provide a "road map" to maximize the effectiveness and efficiency of our administrative processes through the sharing of data. Process innovation and quality improvement opportunities will be pursued prior to systems development efforts. This approach will provide a greater opportunity to improve the quality of services and reduce administrative costs than would be achieved by simply applying technology to automate current policies, processes and procedures. This direction will enable the University to present a cohesive and coherent image to those we serve while also increasing our administrative efficiency.


The core administrative processes of the University were the focus of the initial Strategic Data Planning effort and include the areas described in the table below. The Administrative Information Technology Coordinating Committee (AITCC), which was charged by the Executive Computing Committee (ECC) to recommend administrative projects, oversees the Strategic Data Planning Project. Project sponsors and project managers are responsible for specific areas of the project:

SDP Sub ProjectProject SponsorProject Manager
Managed Financial ResourcesRobert MoenartCharles Hawkins
Managing the Student RelationshipRobert HolbrookLaura Patterson
Managing the Development RelationshipRoy MuirJuliana Brown
Managing the Employment Relationship Jackie McClainThomas Palmer

All four sub projects are staffed by a team from the Information Technology Division to ensure a consistent approach. The research and the employment area will be completed and integrated into the plan later in 1995.

The scope of this report focused on the following thirty-three administrative functions within the three completed sub projects:

	Academic Record
Accounting and Financial Reporting
Career Development
Co-Curricular Activities
Cost Reimbursement
Curriculum Development
Gift/Pledge Management
Graduate Admissions
Information Management for Development
Physical Plant
Plant Extension
Prospect Management
Registration and Scheduling
Safety and Security
Strategic Program Planning for Development
Student Financial Support and Payment
Financial Aid
Student Accounting
Student Orientation
Teaching Administration
Undergraduate Admissions


The SDP methodology attempts to answer the following questions:

The term "strategic data planning" is something of a misnomer. While such planning identifies data requirements, it gives equal attention to defining the processes necessary to meet an organization's goals. By combining the resulting process and data models, and factoring in the current environment, SDP can identify projects (quality improvement, systems development, and process innovation approaches) and potential organizational and policy changes necessary to support the overall vision. These models and priorities are defined through the following set of activities:

The Strategic Data Planning project team gathered information from over 500 administrators from central administrative units and schools and colleges to identify institutional goals, define process and data models, integrate and analyze the models to understand relationships between the various components, and inventory and evaluate current systems that support the future-oriented models.

This information was analyzed by the SDP project team resulting in the Findings, Recommendations, and Next Steps that are outlined in the plan.


In addition to a project plan, the SDP interview process identified significant findings in several areas. Each is defined in detail in the report.

Demands and Opportunities

A demand or opportunity is an external factor that impacts the University of Michigan by forcing it to respond or by providing an opportunity to further its mission. These demands or opportunities are the driving force behind the goals. UM is subject to many current and future demands and opportunities; those highlighted in the interview process are:


A goal is a long term general statement of direction. A goal is approachable, not necessarily attainable, and far reaching. Projects that are defined in the SDP can be prioritized, in part, based on their support for these goals which were identified in the interview process:


During the information gathering steps, several issues, or themes, were consistently cited by participants. Participants and the SDP project team feel that the resolution of these issues will increase the potential for successful implementation of the SDP results. While efforts are underway to resolve some of these issues, the Executive Computing Committee should ensure that action is initiated on each of these items.

Guiding Principles

The following principles were gathered from participants and other sources during the course of the project. They are intended to guide implementation of the Strategic Data Plan throughout the University:

Current Systems Support

The Current Systems Support assessment establishes a baseline understanding of the systems that support administrative process and information needs. Approximately, 228 mechanisms and 207 data collections were identified by over 70 technical and user participants.

With few exceptions, most central systems provide inadequate support for current and future process and information needs. The University of Michigan should embark on a systematic migration from today's current systems to replacement systems that can provide the levels of support necessary to meet current and future information needs. The recommendations are based on this conclusion and provide a road map for this systematic migration.

Major issues identified in this assessment:


Over 70 projects were identified by the SDP Project Team within the current scope of the project. The projects fall into several different project types:

Data Infrastructure Projects

The Data Infrastructure projects identify repositories of data that are used in a majority of processes throughout the University. These repositories should be shared across the University and these data should be thought of as core, or institutional, data of the University. The resulting databases should be considered separate from the systems that create, update, and retrieve the information stored within them. This separation provides the basis for true integration which will reduce or eliminate redundant data storage and the negative implications of redundancy. In addition, Data Infrastructure Projects should be the primary focus of any Data Access Project initiatives as these projects represent the majority of data needed across the University community.

Technology Infrastructure Projects

During the SDP project, several technologies were consistently identified by staff as key enablers for the implementation of future process and data requirements. These technologies should be pursued as Technical Infrastructure Projects. They should be funded centrally since they would allow for innovations and improvements in multiple projects.

Process Innovation Projects (PI)

Process Innovation Projects imply a radical redesign (or design since many of these processes have evolved over time) to dramatically improve operating effectiveness, increase quality, change provider-supplier relationships, and enhance services. These projects assume that policy, process, and organizational changes are necessary. These projects focus on satisfying the customer of the process. These projects assume subsequent Systems Development and Data Access initiatives and that they will evolve into a Quality Improvement Project once implemented. Most of these projects will require a compelling case for change to be successful and should be reviewed by an external consultant before initiation, given the high cost of this type of project.

Quality Improvement Projects (QI)

Quality Improvement Projects imply an M-Quality (i.e., quality improvement) approach to incrementally improve operating effectiveness, increase quality, change provider-supplier relationships, and enhance services. These projects assume improvements are available across organizational boundaries in processes and procedures. The projects focus on satisfying the customer of the process. These projects assume subsequent systems development and data access initiatives and may be a precursor to process innovation after some short term fixes are addressed.

Systems Development Projects (SD)

Systems Development Projects imply that a systems development effort will be required to automate the processes to improve operating effectiveness, increase quality, eliminate mundane tasks, change provider-supplier relationships, and enable the enhancement of services. These projects assume major incremental changes to the policy, process, and organization have already been accomplished or that minor changes can be made as part of the project. These projects assume a subsequent Data Access initiative and may be a precursor to a Process Innovation or Quality Improvement Project as systems development may be necessary to provide short term relief.

Data Access Projects (DA)

Data Access Projects provide data in a reporting environment separate from the operational environment. These projects are necessary given current technology. Information should be replicated from operational systems in a timely manner.

Common Process Areas

Most of the projects except the Data Infrastructure Projects and the Technology Infrastructure Projects fall into one of 12 Common Process Areas. Common Process Areas are clusters of processes that create or update common data. These Common Process Areas should be assigned a Process Owner/Manager to manage the processes as they cross organizational boundaries. The 12 Common Process areas are:

Academic ServicesPhysical Resources
Curriculum DevelopmentProcurement
DevelopmentSafety, Security, and Environment
Enrollment ManagementStudent Enrollment
Financial ResourcesStudent Finance
Payroll and BenefitsStudent Life

Common Process Profiles and Project Definitions are available in the report. In addition, more information is available for each project from the SDP Project Team. Sequences for implementation are also recommended in the plan. This "ideal" sequence provides the road map for systematic migration from our current environment to the environment envisioned for the future. Since reality will dictate a less than ideal approach at times, the Strategic Data Plan should be used to understand tradeoffs and other implications prior to any project initiation.

Key Points

The results of SDP are based on five key points:

Project List

The following is a list of the projects identified as a result of the SDP. Project types are indicated with a two character code in parenthesis that corresponds to the project types defined earlier in this section. In addition to project types, the projects on the list are also organized by levels indicating a general sequence or order of implementation. Projects that create data that are used by other projects are given a higher level than projects that update or retrieve data created by these projects. Projects at lower levels will benefit from the completion of projects at a higher level. Project dependencies are not explicitly defined in this overview. A more specific dependency chart is available in the report.

Project List by Level
General Implementation Sequence Order Overview
Based on Data Creation and Dependencies

Data Infrastructure Projects
Economic Event
Good or Service
Rule, Reg., Policy, Procedure
Technology Infrastructure Projects
Analytical and Forecasting Tools
Electronic Documents
Electronic Calendaring
Electronic Timekeeping
Multi-media and Hypertext
Interactive Voice Response
Alternative Input Devices
Remote/Local Printing
Level 1
Co-Curricular Pgm Mgt (SD)
Curriculum Database (SD)
Financial Reporting (QI)
Investment (QI)
Person/Org Mgt (SD)
Process Economic Event (PI)
Space Management (SD)
Level 2
Academic Record (PI)
Billing and Rec Mgt (PI)
Budgeting (QI)
Counseling Mgt (SD)
Course Approval (QI)
Credentials/Training (QI)
Endowment/Gifts (QI)
Events Planning, Marketing, and Administration (QI)
Flexible Benefits (PI)
Gift Processing (PI)
Gift/Grant (QI)
Incidents Tracking (SD)
Security (SD)
Small Payments (QI)
Student Activity (QI)
Student Enrollment (PI)
Graduate Enrollment
Professional Enrollment
Undergraduate Enrollment
Level 3
Career Development and Placement (QI)
Electronic Application (SD)
Electronic Viewbook (SD)
Housing Mgt (SD)
Procurement (QI)
Transfer Credit (QI)
Level 4
Degree Audit (SD)
Food Service Mgt (SD)
Risk Mgt (QI)
Receiving (QI)
Transcript and Certification Delivery (SD)
Level 5
Academic Advising (PI)
Enrollment Mgt (PI)
Claims Management (QI)
Course and Classroom Scheduling (PI)
Inventory Mgt (PI)
Payment Mgt (PI)
Level 6
Asset Mgt (QI)
Benefits Administration and Enrollment (SD)
Construction Projects (SD)
Cost Reimbursement (DA)
Maintenance Mgt (QI)
Registration (PI)
Teaching Administration (QI)
Tuition and Fees (QI)
Level 7
Parking Mgt (SD)
Student Finance (PI)
Transportation Mgt (SD
Notes: Projects are in alphabetic sequence within each level. No other sequence is intended

Suggested Technical Migration Approach

While this project was difficult to complete, we believe that planning is the easy part and implementation will be more difficult. To assist in the migration from where our systems are currently to where we want them to be, we offer the following recommendation. There are other approaches that should be considered and certainly this approach needs to be reviewed and refined by the Information Technology Division and other key technology providers.

  1. Complete Data Infrastructure projects as soon as possible to provide direction and vision.

  2. Implement new data stores using new technology.

  3. Provide bi-directional feeds to/from resulting databases from/to operational systems.

  4. Build new systems based on new data stores.

  5. Replicate data in new data stores into a Data Access environment.

Next Steps

In order to fully implement the results of the Strategic Data Plan, some key next steps are outlined: