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

Purpose – The purpose of this is 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. Design/methodology/approach – 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 (ECS) model resulting in a series of simulations. Findings – The findings highlighted the effects of the diversity in management decision making on the firm's evolutionary trajectory. The CEO appeared to have the most balanced view of the firm, closely followed by the marketing and research and development 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. Research limitations/implications – 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 that has been problematical both in theory and application. Practical implications – This approach can be used as a decision‐support tool for operations and other managers providing a forum with which to explore: the strengths, weaknesses and consequences of different decision‐making capacities within the firm; the introduction of new manufacturing technologies, practices and policies; and the different evolutionary trajectories that a firm can take. Originality/value – With the inclusion of “micro‐diversity”, ECS modelling moves beyond the self‐organisational models that populate the literature but has not as yet produced a great many practical simulation results. This work is a step in that direction.