program process

The UniForum program offers two opportunities for data collection that will help us understand how the university's administrative services are resourced, the effectiveness of these services and how our services compare to other post-secondary institutions within Canada and internationally.

Two Data Collection Opportunities

  1. Activity data collection –  Occurring annually in late spring and summer, it involves the creation of datasets showing professional administrative resources used in the most recently completed financial year. This includes collecting supplementary data, such as the revenue the university generates and the total number of employees.
  2. A service effectiveness survey – This will be conducted annually to give a voice to staff (both academic and non-academic) to assess their satisfaction levels with the university's administration and support services. The survey will gather feedback in an organized and consistent manner to help identify improvement opportunities. 

Post - Data Collection Steps

Step 1: Normalization

First, the data is adjusted for SFU's size to make it comparable to other post-secondary institutions.

Step 2: Analysis

Next, our normalized data is independently analyzed by Cubane Consulting. The findings will be presented in the form of:

  1. Overall services reviews - High-level findings shared with SFU leadership. 
  2. University briefings - Individual briefings that are linked to the university's strategy.
  3. Detailed studies - Deep dives into particular areas of interest within the data.

Step 3: Release of results

Cubane Consulting will present the results in the fall to SFU's senior executive leaders. Following that presentation, we will develop a plan to disseminate the information more broadly.

Two datasets will be provided to SFU:

  1. SFU's dataset - This will support and enhance decision-making by providing information on the delivery models SFU has selected, how much capacity SFU uses and what that capacity costs, and customer satisfaction levels. The data can be used at the university level or leveraged by individual departments and faculties for localized management decisions. 
  2. Normalized peer dataset - This will show what delivery models other participating post-secondary institutions have selected, what they are spending on support services capacity, and how each metric compares to SFU.