• Media type: E-Article
  • Title: A Methodology for Constructing Collective Causal Maps*
  • Contributor: Scavarda, Annibal José; Bouzdine‐Chameeva, Tatiana; Goldstein, Susan Meyer; Hays, Julie M.; Hill, Arthur V.
  • imprint: Wiley, 2006
  • Published in: Decision Sciences
  • Language: English
  • DOI: 10.1111/j.1540-5915.2006.00124.x
  • ISSN: 0011-7315; 1540-5915
  • Keywords: Management of Technology and Innovation ; Information Systems and Management ; Strategy and Management ; General Business, Management and Accounting
  • Origination:
  • Footnote:
  • Description: <jats:title>ABSTRACT</jats:title><jats:p>This article develops a new approach for constructing causal maps called the Collective Causal Mapping Methodology (CCMM). This methodology collects information asynchronously from a group of dispersed and diverse subject‐matter experts via Web technologies. Through three rounds of data collection, analysis, mapping, and interpretation, CCMM constructs a parsimonious collective causal map. The article illustrates the CCMM by constructing a causal map as a teaching tool for the field of operations management. Causal maps are an essential tool for managers who seek to improve complex systems in the areas of quality, strategy, and information systems. These causal maps are known by many names, including Ishikawa (fishbone) diagrams, cause‐and‐effect diagrams, impact wheels, issue trees, strategy maps, and risk‐assessment mapping tools. Causal maps can be used by managers to focus attention on the root causes of a problem, find critical control points, guide risk management and risk mitigation efforts, formulate and communicate strategy, and teach the fundamental causal relationships in a complex system. Only two basic methods for creating causal maps are available to managers today—brainstorming and interviews. However, these methods are limited, particularly when the subject‐matter experts cannot easily meet in the same place at the same time. Managers working with complex systems across large, geographically dispersed organizations can employ the CCMM presented here to efficiently and effectively construct causal maps to facilitate improving their systems.</jats:p>