{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T16:23:19Z","timestamp":1779121399682,"version":"3.51.4"},"reference-count":48,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2017,9,11]],"date-time":"2017-09-11T00:00:00Z","timestamp":1505088000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JEIM"],"published-print":{"date-parts":[[2017,9,11]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The final output, the roadmap, highlights the importance of a balanced portfolio of analytics initiatives, relevant and tailored to the institution\u2019s specific context that includes technology and applications projects, as well as capacity building, organizational structures and policy initiatives.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>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\u2019s readiness for and understanding of what is involved in analytics before investing significant resources in its adoption.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/jeim-06-2016-0121","type":"journal-article","created":{"date-parts":[[2017,7,31]],"date-time":"2017-07-31T07:13:29Z","timestamp":1501485209000},"page":"701-722","source":"Crossref","is-referenced-by-count":8,"title":["An agile approach for academic analytics: a case study"],"prefix":"10.1108","volume":"30","author":[{"given":"Maurice","family":"McNaughton","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lila","family":"Rao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gunjan","family":"Mansingh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020120523534079500_ref001","article-title":"Agile BI: complementing traditional BI to address the shrinking decision Window","author":"Aberdeen-Group","year":"2011"},{"issue":"4","key":"key2020120523534079500_ref002","first-page":"163","article-title":"Continental airlines flies high with real-time business intelligence","volume":"3","year":"2004","journal-title":"MIS Quarterly Executive"},{"issue":"8","key":"key2020120523534079500_ref003","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1145\/545151.545178","article-title":"Business applications of data mining","volume":"45","year":"2002","journal-title":"Communications of the ACM"},{"issue":"1","key":"key2020120523534079500_ref004","first-page":"1","article-title":"Signals: applying academic analytics","volume":"33","year":"2010","journal-title":"Educause Quarterly"},{"key":"key2020120523534079500_ref005","doi-asserted-by":"crossref","unstructured":"Arnold, K.E. and Pistilli, M.D. (2012), \u201cCourse signals at Purdue: using learning analytics to increase student success\u201d, paper presented at the 2nd International Conference on Learning Analytics and Knowledge, Vancouver, BC, April 29-March 2.","DOI":"10.1145\/2330601.2330666"},{"issue":"2","key":"key2020120523534079500_ref006","first-page":"1","article-title":"Academic analytics and data mining in higher education","volume":"4","year":"2010","journal-title":"International Journal for the Scholarship of Teaching and Learning"},{"key":"key2020120523534079500_ref007","first-page":"61","volume-title":"Educational Data Mining and Learning Analytics Learning Analytics","year":"2014"},{"issue":"3","key":"key2020120523534079500_ref008","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/s12599-009-0044-5","article-title":"Developing maturity models for IT management","volume":"1","year":"2009","journal-title":"Business & Information Systems Engineering"},{"issue":"4","key":"key2020120523534079500_ref009","first-page":"40","article-title":"Academic analytics","volume":"42","year":"2007","journal-title":"EDUCAUSE Review"},{"key":"key2020120523534079500_ref010","year":"2000"},{"issue":"4","key":"key2020120523534079500_ref011","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.2307\/41703503","article-title":"Business intelligence and analytics: from big data to big impact","volume":"36","year":"2012","journal-title":"MIS Quarterly"},{"issue":"4","key":"key2020120523534079500_ref012","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1109\/51.853478","article-title":"Diagnosing myocardial perfusion from PECT Bull\u2019s-eye maps-a knowledge discovery approach","volume":"19","year":"2000","journal-title":"IEEE Engineering in Medicine and Biology Magazine"},{"issue":"4","key":"key2020120523534079500_ref013","doi-asserted-by":"crossref","first-page":"547","DOI":"10.2307\/3250947","article-title":"Data warehousing supports corporate strategy at First American Corporation","volume":"24","year":"2000","journal-title":"MIS Quarterly"},{"key":"key2020120523534079500_ref014","volume-title":"Competing on Analytics: The New Science of Winning","year":"2007"},{"key":"key2020120523534079500_ref015","unstructured":"De Bruin, T., Freeze, R., Kaulkarni, U. and Rosemann, M. 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