Innovation, Risk, Agility, and Learning, Viewed as Optimal Control and Estimation

ABSTRACT This paper summarizes how a well‐understood problem—optimal control and estimation in “noisy” environments—provides a framework to advance understanding of a well‐known but less well‐mastered problem—system innovation life cycles and management of decision risks and learning. The ISO15288 process framework and its exposition in the IN COSE Systems Engineering Handbook (2015) describe system development and other life cycle processes. Concerns about improving the performance of processes in dynamic, uncertain, and changing environments are partly addressed by “agile” systems engineering approaches. Both are typically described in the procedural language of business processes, so it is not always clear whether the different approaches are fundamentally at odds, or just different sides of the same coin. Describing the target system, its environment, and the life cycle management processes using models of dynamical systems allows us to apply earlier technical tools, such as the theory of optimal control in noisy environments, to emerging innovation methods.

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Publication Details

Journal
Insight
Published
2024-08-01
DOI
https://doi.org/10.1002/inst.12500
Primary Topic
Complex Systems and Decision Making
Type
article
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article

Innovation, Risk, Agility, and Learning, Viewed as Optimal Control and Estimation

William D. Schindel
Insight
Complex Systems and Decision Making
article

Innovation, Risk, Agility, and Learning, Viewed as Optimal Control and Estimation

William D. Schindel
article en

Abstract

ABSTRACT This paper summarizes how a well‐understood problem—optimal control and estimation in “noisy” environments—provides a framework to advance understanding of a well‐known but less well‐mastered problem—system innovation life cycles and management of decision risks and learning. The ISO15288 process framework and its exposition in the IN COSE Systems Engineering Handbook (2015) describe system development and other life cycle processes. Concerns about improving the performance of processes in dynamic, uncertain, and changing environments are partly addressed by “agile” systems engineering approaches. Both are typically described in the procedural language of business processes, so it is not always clear whether the different approaches are fundamentally at odds, or just different sides of the same coin. Describing the target system, its environment, and the life cycle management processes using models of dynamical systems allows us to apply earlier technical tools, such as the theory of optimal control in noisy environments, to emerging innovation methods.

InsightVol. 27(4)
Responsible consumption and production
Openalex Percentile: Top 84%
Complex Systems and Decision Making
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Innovation, Risk, Agility, and Learning, Viewed as Optimal Control and Estimation — William D. Schindel · Insight (2024) | TGRS Research Map | TGRS