Abstract
Prescriptive analytics has emerged as a technological driver in data-intensive enterprise environ- ments, as it tries to transform valuable insights into actionable recommendations and act upon them in order to meet business objectives. The basic idea is to go beyond the findings of descriptive data anal- ysis and predictive modeling to answer the questions “What should be done?” and “Why should it be done?”. However, there is often an inconsistent understanding about constituent elements of prescrip- tive analytics, which may hinder the development of adequate information systems. For this reason, the paper deals with a conceptualization by conducting a systematic literature review. The research goal is to extract fundamental aspects and facets from different perspectives and consolidate them into a coherent view towards a common understanding of a prescriptive analytics system.
Recommended Citation
Stefani, Karolin and Zschech, Patrick, "Constituent Elements for Prescriptive Analytics Systems" (2018). Research Papers. 39.
https://aisel.aisnet.org/ecis2018_rp/39