TR177: Framework for Measuring Rationale Clarity of AEC Design Decisions

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Abstract/Contents

Abstract: Current Architecture, Engineering, and Construction (AEC) design processes rely on precedent to resolve complex decisions. However, changing stakeholder concerns, design methods, and building products negate much of this precedent knowledge. Project teams need to clearly communicate their decision rationale in order to develop consensus about design decisions. The AEC industry requires a new framework to evaluate decision making. This paper builds on a broad range of theory including Decision-Based Design, Decision Analysis, Decision Theory, linguistics, logic, organization theory, and social welfare. First, this paper describes rationale as a set of assertions regarding distinct components (i.e. managers, stakeholders, designers, gatekeepers, objectives, constraints, options, and analysis) that support design decisions. Second, this paper describes conditions of clarity (i.e. coherent, concrete, connected, consistent, convincing, certain, and correct). These are used to measure the clarity of assertions, components, and the rationale as a whole. Taken together, this Rationale Clarity Framework (RCF) enables an objective evaluation of existing decision support methods. RCF provides a broad yet structured view for assessing process, organization, and product performance and for assessing AEC industry dynamics.

Type of resource	text
Date created	November 2008

Author	Chachere, John
Author	Haymaker, John

Subject	CIFE
Subject	Center for Integrated Facility Engineering
Subject	Stanford University
Subject	Clarity
Subject	Decision
Subject	Decision-Making
Subject	Design
Subject	Management
Subject	Organization Models
Subject	Process Modeling
Subject	Process Models
Subject	Project Management
Subject	Rationale
Subject	Rationale Clarity Framework
Subject	Validation
Genre	Technical report

Location	https://purl.stanford.edu/fm497vr4971

Use and reproduction: User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.

Preferred Citation: Chachere, John and Haymaker, John. (2008). TR177: Framework for Measuring Rationale Clarity of AEC Design Decisions. Stanford Digital Repository. Available at: http://purl.stanford.edu/fm497vr4971

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