Prescriptive Analytics: A Survey of Approaches and Methods

  • Katerina LepeniotiEmail author
  • Alexandros Bousdekis
  • Dimitris Apostolou
  • Gregoris Mentzas
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 339)


Data analytics has gathered a lot of attention during the last years. Although descriptive and predictive analytics have become well-established areas, prescriptive analytics has just started to emerge in an increasing rate. In this paper, we present a literature review on prescriptive analytics, we frame the prescriptive analytics lifecycle and we identify the existing research challenges on this topic. To the best of our knowledge, this is the first literature review on prescriptive analytics. Until now, prescriptive analytics applications are usually developed in an ad-hoc way with limited capabilities of adaptation to the dynamic and complex nature of today’s enterprises. Moreover, there is a loose integration with predictive analytics, something which does not enable the exploitation of the full potential of big data.


Prescriptive analytics Business analytics Data analytics Big data Literature review 



This work is partly funded by the European Commission project H2020 UPTIME “Unified Predictive Maintenance System” (768634).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Katerina Lepenioti
    • 1
    Email author
  • Alexandros Bousdekis
    • 1
  • Dimitris Apostolou
    • 1
    • 2
  • Gregoris Mentzas
    • 1
  1. 1.Information Management Unit (IMU), Institute of Communication and Computer Systems (ICCS)National Technical University of Athens (NTUA)Zografou, AthensGreece
  2. 2.Department of InformaticsUniversity of PiraeusPiraeusGreece

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