An agile approach for academic analytics: a case study
In: Journal of enterprise information management: an international journal, Band 30, Heft 5, S. 701-722
ISSN: 1758-7409
Purpose
The purpose of this paper is to describe an agile approach to academic analytics that is currently being applied on one of the campuses of a leading higher educational institution in the Caribbean. This agile approach enables the rapid development of a strategic analytics roadmap and proof-of-concept analytics applications for the institution.
Design/methodology/approach
The approach was developed using Design Science which involves the development and rigorous evaluation of an artifact. The agile approach is the artifact and the design evaluation was done using the observational method of primary cases studies where the artifact is studied in depth in a business environment, in this case this was a leading higher educational institution in the Caribbean.
Findings
The final output, the roadmap, highlights the importance of a balanced portfolio of analytics initiatives, relevant and tailored to the institution's specific context that includes technology and applications projects, as well as capacity building, organizational structures and policy initiatives.
Research limitations/implications
The approach that was used and the specific techniques proposed can be extended by other researchers and in so doing will increase the body of research as it relates to agile analytics.
Practical implications
The approach will be beneficial to educational institutions that are considering how best to harness the strategic value of its data. The analytics roadmap will allow the institution to be clear about the path they should take to maximize their investments in analytics initiatives.
Originality/value
A number of existing well-accepted research techniques have been synthesized in the development and application of this agile approach. The approach and final roadmap consider the institution's readiness for and understanding of what is involved in analytics before investing significant resources in its adoption.