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5. A reflective researcher with skills in:
(b) Conducting research

5b3 Process for identifying Key Performance Indicators for Data Warehousing

Development Plan Portfolio Documentation
Determine the measurable factors that would be most useful to administrators and managers for both tactical and strategic decision support, for implementation using data warehousing technologies. Describe the role of the Data Warehouse Steering Committee and the techniques used to determine key measurable factors for inclusion in a data warehouse.

I began with a series of preliminary meetings, then on November 11, 1998, I set up the Data Warehouse Steering Committee. The following links show minutes of those meetings, and reports that were prepared for the committee.

The Role of the Data Warehouse Steering Committee

In the preliminary meetings, key staff from Information Technology Services (ITS) and Institutional Research met in training sessions on data warehousing, and we begin listing important decision criteria for chosing a data warehouse engine and we had some initial discussions about some of the data elements that would be needed in the data warehouse.

After several meetings, it became clear that we needed to broaden the scope of attendees considerably, because there was an attempt to focus to early on implementation details. On November 11, 1998, we had the inaugural meeting of the Data Warehouse Steering Committee (see minutes). In this meeting, the members introduced themselves, then were taken through two handouts on What is Data Warehousing? and Data Warehouse Elements to Evaluate. The Gary Dickerson conducted a Business Readiness Assessment using a survey instrument, and discussed a framework for data warehousing using an outline from The Data Warehouse Institute (TDWI).

At the next meeting of the Steering Committee (see minutes), we reviewed a dictionary of data warehousing terms, then Gary Dickerson reported the results of the Business Readiness Assessment. Following a demonstration of a an end-user data analysis tool (PowerPlay from COGNOS), the group brainstormed on important subject areas to be included in the data warehouse. Here are the items that were identified in that meeting (listed alphabetically):

    1. Applications, Acceptances, Registrations
    2. Class Sizes
    3. Costs and sources of funds for different mixes of students
    4. Deans Statistics
    5. Donor Tracking/Analysis (Census Report)
    6. Faculty Load Analysis
    7. Faculty Productivity
    8. Market Segment Analysis
    9. Program cost tracking, multiple sources of income/revenue per student
    10. Registration Analysis
    11. Research cost tracking for various kinds of research
    12. Retention Analysis
    13. Student Achievement/Outcomes
    14. Student Aid Tracking/Analysis
    15. Viable Majors

The intention was to circulate the list as use it as a basis for further comment and discussion. However, attempts to gain additional funding to staff the project were not successful, and since Gary's team of software developers were already occupied Y2K remediation and web registration, very little was done after this meeting until the middle of the year 2000.

I sent out a memo on June 15, 2000 calling the Steering Committee together again. We reviewed what we had done so far and revisited our objectives. The committee met on June 20 (agenda, minutes). At this meeting, the Dean's Statistics Subject Area was chosen as a starting point. A Data Warehousing Development Committee was set up to be responsible for this pilot project

Resources problems continued to plague ITS, but with the help of student labor, a datamart was built using Microsoft SQL Server, and a Dean's Statistics datacube was developed that supported OLAP data analysis via Microsoft Excel.


The Data Warehouse Steering Committee played a crucial role in pulling together a wide spectrum of users, decision makers, and administrators, but it has not been used to full effectiveness to date because of a shortage of development resources. Nevertheless, our list of Key Performance Indicators continues to be developed and refined owing to the increased importance with which this decision support capability is being regarded. The completion of the University's Strategic Plan and the process that led up to it highlighted several indicators not in this list.

Some additional items that have been identified include:

    1. Alumni Satisfaction
    2. Demographics, external comparisons
    3. Grade Distributions
    4. Report To NAD (Dallas Kindopp's comparative statistics)
    5. Student Demand By Course/Section
    6. Student Satisfaction

These items came to light during the development of the Strategic Plan, in the Noel-Levitz Student Satisfaction Survey, in focus group meetings, and in meetings to develop a Knowledge Management Strategy (January 2002). While progress on the development of a data warehouse has been disappointingly slow, interest in the decision support improvements that it promises is not waning, but rather is gathering momentum.

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Created: Wednesday, January 30, 2002 9:15 PM
Last Modified: Saturday, June 1, 2002 9:48 PM