When bad things happen to good processes: a theory of entropy for process science

Abstract

Purpose

This research fills a gap in process science by defining and explaining entropy and the increase of entropy in processes.

Design/methodology/approach

This is a theoretical treatment that begins with a conceptual understanding of entropy in thermodynamics and information theory and extends it to the study of degradation and improvement in a transformation process.

Findings

A transformation process with three inputs: demand volume, throughput and product design, utilizes a system composed of processors, stores, configuration, human actors, stored data and controllers to provide a product. Elements of the system are aligned with the inputs and each other with a purpose to raise standard of living. Lack of alignment is entropy. Primary causes of increased entropy are changes in inputs and disordering of the system components. Secondary causes result from changes made to cope with the primary causes. Improvement and innovation reduce entropy by providing better alignments and new ways of aligning resources.

Originality/value

This is the first detailed theoretical treatment of entropy in a process science context.

Citation

Meyer, B.C., Bumblauskas, D., Keegan, R. and Zhang, D. (2024), "When bad things happen to good processes: a theory of entropy for process science", International Journal of Productivity and Performance Management, Vol. 73 No. 5, pp. 1387-1404. https://doi.org/10.1108/IJPPM-01-2022-0056