An evolutionary complex systems decision-support tool for the management of operations

J.S. Baldwin, P.M. Allen, K. Ridgway

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Abstract

This research aimed to add both to the development of complex systems thinking in the subject area of Operations and Production Management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision-support tools for operations and production managers. A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems model resulting in a series of simulations. The findings included both reassuring and some unexpected results. The simulation based on the CEO's opinions led the most cohesive and synergistic collection of practices describing the firm, closely followed by the Marketing and R&D Managers. The Manufacturing Manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised. By drawing directly from the opinions and views of managers rather than from logical 'if-then' rules and averaged mathematical representations of agents that characterise agent-based and other self-organisational models, this work builds on previous applications by capturing a micro-level description of diversity and a learning effect that has been problematical not only in terms of theory but also in application. This approach can be used as a decision-support tool for operations and other managers providing a forum with which to explore a) the strengths, weaknesses and consequences of different decision-making capacities within the firm; b) the introduction of new manufacturing technologies, practices and policies; and, c) the different evolutionary trajectories that a firm can take.
Original languageEnglish
Number of pages14
JournalIOP Conference Series: Materials Science and Engineering
Volume26
Issue number1
DOIs
Publication statusPublished - 2011
EventTrends in Aerospace Manufacturing Conference, TRAM09 - Rotherham , United Kingdom
Duration: 9 Sep 200910 Sep 2009

Keywords

  • agent based
  • company performance
  • computational model
  • decision support tools
  • learning effects
  • manufacturing technologies
  • mathematical representations
  • methodological approach
  • operations and production management
  • production manager
  • senior managers
  • simulation-based
  • computer simulation
  • decision making
  • decision support systems
  • industrial management
  • industry
  • managers
  • manufacture
  • research and development management
  • human resource management

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