Purpose - University timetabling is one of the most difficult problems faced in higher education. This is not only due to its computational complexity but also because of multiple stakeholder involvement, and constraints on classroom/lecturer/equipment sharing while trying to maximize satisfaction of all parties involved. Although established software solutions have existed in the higher education sector for several decades, they are often used as a calendar tool for bookkeeping manually generated timetables and have lack of involvement of the most important stakeholders: the students. In this paper, we present our study of students perspectives and experiences with the academic timetable in Munster Technological University Bishopstown campus, and discuss our development of a student-centric timetabling tool. Design/methodology/approach – Our approach starts with a Characteristics of the Process (CTP) study for picturing the current state, benefits and inefficiencies of the conventional practice with data analytic methods. Then, we discuss our findings from our engagement with students to get Critical Customer Requirements (CCR) through interviews and surveys. We next present our proposed analytical solution that will address the Key Process Output Variables (KPOV). Findings – Our research revealed that schedule compactness is the priority for most students. Their preferences can be incorporated in an intelligent way to current timetabling practice. Research limitations/implications – In its current form, this study has lack of reaching other campuses and departments of the institute to get different preferences and include specific requirements such as music school and apprenticeship programs. Practical implications – As a simulation tool, our solution will enable decision-makers to improve institute’s sustainability metrics by assessing the impact of different infrastructure expansion/renovation options as well as different room/lecturer assignments. By maximizing the shared resource efficiencies several other KPOVs are planned to improve in the short term, such as minimizing students traveling distance between different classes distributed in campus and reducing energy consumption through tailored timetabling and zonal heating. Originality/value – Our solution will bring a mid to long-term value to the institute in terms of (1) improving student and staff experience, and (2) engagement with courses. Developing an artificial intelligence (AI) based solution to the problem that incorporates requirements of all stakeholders involved will lead to a more holistic timetabling solution. Therefore, conducting the student survey which results in refining CCRs through detailed data analysis and formulating an analytical method to address KPOVs are the main originalities of the paper that we believe add significant value to the literature.