Correlation and causation : a potential pitfall for efficient asset management

Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
South African Institute for Industrial Engineering
Abstract
ENGLISH ABSTRACT: The successful coordination of activities and practices within a system rely on the organisation’s ability to make informed decisions. Decisions must be made quickly and effectively, while ensuring efficient Physical Asset Management (PAM). Access to processed data, in the form of reliable information, on how sub systems interact greatly simplifies decision-making. Many organisations mistake correlation for causation when analysing this data. Such a mistake carries great consequences for organisations, since important decisions might unknowingly be based on self-invented problems, while the true problem is left unresolved. It is crucial to understand the difference between correlation and causation when practising root cause analysis within a PAM environment. Although root cause analysisis presumed a highly specialised field, organisations can equip themselves to better understand how different events within a PAM system are interconnected. If done correctly this might simplify the process of detecting problems, which might exist within a system.This paper highlights the differences between correlation and causation. Potential pitfalls on how correlation can be mistaken for causation within a PAM environment are identify and explained. Recommendations are made on how to avoid these pitfalls.
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Description
CITATION: Heyns, J. H. & Vlok, P. J. Correlation and causation : a potential pitfall for efficient asset management. In SAIIE26 Proceedings, 14–16 July 2014, Muldersdrift, South Africa.
The original publication is available at http://conferences.sun.ac.za/index.php/saiie
Keywords
Asset management, Causation, Decision making
Citation
Heyns, J. H. & Vlok, P. J. Correlation and causation : a potential pitfall for efficient asset management. In SAIIE26 Proceedings, 14–16 July 2014, Muldersdrift, South Africa