Journal of International Technology and Information Management
Document Type
Article
Abstract
Developing an effective business analytics function within a company has become a crucial component to an organization’s competitive advantage today. Predictive analytics enables an organization to make proactive, data-driven decisions. While companies are increasing their investments in data and analytics technologies, little research effort has been devoted to understanding how to best convert analytics assets into positive business performance. This issue can be best studied from the socio-technical perspective to gain a holistic understanding of the key factors relevant to implementing predictive analytics. Based upon information from structured interviews with information technology and analytics executives of 11 organizations across the US, this study identifies the socio-technical components that are key to organizations’ implementation of predictive analytics.
Recommended Citation
Chen, Leida; Nath, Ravi; and Rocco, Nevina
(2024)
"Key Issues of Predictive Analytics Implementation: A Sociotechnical Perspective,"
Journal of International Technology and Information Management: Vol. 32:
Iss.
1, Article 11.
DOI: https://doi.org/10.58729/1941-6679.1565
Available at:
https://scholarworks.lib.csusb.edu/jitim/vol32/iss1/11
Included in
Business Analytics Commons, Business Intelligence Commons, Communication Technology and New Media Commons, Computer and Systems Architecture Commons, Data Storage Systems Commons, Digital Communications and Networking Commons, E-Commerce Commons, Information Literacy Commons, Management Information Systems Commons, Management Sciences and Quantitative Methods Commons, Operational Research Commons, Science and Technology Studies Commons, Social Media Commons, Technology and Innovation Commons