Institutional Analytics in the Singapore University of Social Sciences: Objectives, Methodology, Progress & Challenges

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The institutional analytics journey at the Singapore University of Social Sciences (SUSS) can be considered a fairly recent one. For several years, learning analytics projects in the University (e.g., Enrolment and Early Predictors of Academic Performance and An Exploratory Study of [SUSS] Associates [i.e., part-time instructors] – Establishing Baseline Knowledge) were undertaken as institutional research projects, overseen by the President’s Office. This approach was changed on 1 August 2016 when institutional analytics became an important dimension of the University’s strategic thrust with the establishment of the Institutional Research & Analytics Unit (IRAU).

In particular, IRAU was tasked to:

  1. Set up the data infrastructure (in the form of an integrated database system [data warehouse]) as well as reporting/analytics infrastructure;

  2. Build up the analytics capability in SUSS, including providing analytics training and helping the different units in the University to formulate and implement analytics projects as well as deploy the findings/models; and

  3. Undertake institutional research and analytics projects of a strategic, tactical and operational nature.

Underlying the establishment of IRAU is SUSS’s aim to generate information for decision making and planning, covering areas such as admission and enrolment, programme and curriculum, teaching and learning, student and alumni relations, finance and human resources, policy making and evaluation, among others. Over time, the University hopes to nurture a data-driven and evidence-based environment to empower decision making and planning.


The methodology (or approach) to perform the tasks assigned to IRAU and nurture a data-driven and evidence-based culture in SUSS can be summarised by the following framework:


Challenges and Conclusion

Despite good progress made in implementing the methodology, the work of IRAU is not without challenges. For example, it is not easy to build up the University’s analytics capabilities when the profiles, job scopes and motivation of different faculty and staff in different departments are very diverse, and not necessarily conducive to analytics training. Hence, a fair amount of mentoring and coaching is needed. Also, beyond standardised training, customised project-based “apprenticeship” is put in place.

In addition, to have a good integrated information system, the data integrity in the data warehouse is critical. Thus, it is imperative that data owners take responsibility for the integrity of their data. Finally, there is the question of why decision makers should consider using analytics when they have been making decisions without it in the past. Here is where IRAU will need to demonstrate the usefulness of analytics via low-hanging fruits, and the University should develop strategies (KPIs) and frameworks to implement project.

To conclude, while the institutional analytics journey in SUSS is challenging, the University is confident that institutional analytics will be very rewarding – at the very least, leading to more efficient and effective decisions for the University.