Title: Exploring the relationships between continuous improvement and predictive analytics

Authors: Brian J. Galli; Lanndon A. Ocampo

Addresses: School of Computer Science, Innovation, and Management Engineering, Long Island University, Brookville, NY 11548, USA ' Department of Industrial Engineering, Cebu Technological University, Corner M.J. Cuenco Ave. & R. Palma St., Cebu City, 6000, Philippines

Abstract: This study aimed to examine the elements and applications of predictive analytics (PA) models within the field of continuous improvement (CI). While the roles of data science, PA, and big data have been explored in the current literature (e.g., supply chain management), fragmented insights scarcely exist concerning the role of PA on CI initiatives. Articles concerning the role of PA and BI in CI projects were utilised in a systematic literature review. Furthermore, the paper stresses the vital role that big data analytics plays in both CI and PA during decision-making. The paper studies other important CI and PA aspects that pertain to continuous improvement projects, which are aspects that are often overlooked in the existing literature. The findings from this study emphasise the critical role that PA tools and concepts can and should have in CI initiatives. Critical organisational and operational structures also need to be implemented to establish and maintain the use of PA tools and concepts in CI initiatives. Overall, this paper serves to fill the gap that overlooks the relationship between these two variables.

Keywords: data; continuous improvement; CI; business intelligence; BI; big data; predictive analytics; PA.

DOI: 10.1504/IJAOM.2019.10021911

International Journal of Advanced Operations Management, 2019 Vol.11 No.3, pp.189 - 210

Received: 29 Jan 2018
Accepted: 11 Oct 2018

Published online: 07 Jul 2019 *

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