Data-Driven Prescriptive Analytics Applications: A Comprehensive Survey

TL;DR

This comprehensive survey analyzes 104 Data-Driven Prescriptive Analytics applications, classifying their use cases, methodologies, and future research directions, providing a structured overview of the field's evolution and key patterns.

Contribution

It introduces novel taxonomies for DPSA applications, maps method usage and workflows, and identifies five future research directions in the field.

Findings

Identified 10 application domains for DPSA.

Mapped 5 method types and their combinations.

Derived 2 generic workflow patterns.

Abstract

Prescriptive Analytics (PSA), an emerging business analytics field suggesting concrete options for solving business problems, has seen an increasing amount of interest after more than a decade of multidisciplinary research. This paper is a comprehensive survey of existing applications within PSA in terms of their use cases, methodologies, and possible future research directions. To ensure a manageable scope, we focus on PSA applications that develop data-driven, automatic workflows, i.e., Data-Driven PSA (DPSA). Following a systematic methodology, we identify and include 104 papers in our survey. As our key contributions, we derive a number of novel taxonomies of the field and use them to analyse the field's temporal development. In terms of use cases, we derive 10 application domains for DPSA, from Healthcare to Manufacturing, and subsumed problem types within each. In terms of individual method usage, we derive 5 method types and map them to a comprehensive taxonomy of method usage within DPSA applications, covering mathematical optimization, data mining and machine learning, probabilistic modelling, domain expertise, as well as simulations. As for combined method usage, we provide a statistical overview of how different method usage combinations are distributed and derive 2 generic workflow patterns along with subsumed workflow patterns, combining methods by either sequential or simultaneous relationships. Finally, we derive 5 possible research directions based on frequently recurring issues among surveyed papers, suggesting new frontiers in terms of methods, tools, and use cases.