Matching effort to challenge in interdisciplinary graduate program development for data analytics - the use of business process modelling to ameliorate planning bottlenecks

Abstract

The need for business process modelling in higher education is increasing as the complexity of degree programs grows to accommodate new fields in the business market. This is evidenced in the field of data analytics, which is interdisciplinary in nature and severely lacking in professional talent. This paper explores the T-shaped skills desired by businesses seeking graduates with an analytics degree and the challenges that universities face when developing interdisciplinary programs. We apply business process modelling in a university setting by mapping out the current processes involved with starting and sustaining a new graduate degree program. Through this approach, a roadmap is developed as a tool for university domain experts, which highlights areas of inefficiency that can be further streamlined to allow improved flexibility and evaluation of all graduate programs.