We attempt to use general systems theory (GST) to understand why the resources of Texaco's corporate information technology function consistently did not match its task during its 40-year lifetime. Our interpretation uses mechanistic, organic, and colonial systems metaphors, each with three components. The first is an analysis of a management action system made up of organizational indicators such as Texaco's revenues, profits, employee numbers, IT budgets, and IT personnel numbers. The second is a narrative of performance versus resource needs, which shows a gap between the resources and expanding responsibilities of Texaco's IT function. The third is a management perception system, which offers reasons why top management continually misinterpreted IT's performance as inferior. Our results show that the mechanistic, organic, and colonial interpretations converge. In addition, our GST-based interpretations show how top management might have remedied the situation.
Colonial systems are presented as an alternative to the mechanistic and organic systems paradigms. They are based upon the inclusion of an evolutionary social history (Ernst Mayr), species-level evolution (Eldredge and Gould), and local context (Martin Heidegger) as central premises in the definition of human systems. The colonial viewpoint of systems is differentiated from the mechanistic and organic models by ten different axioms that define how systems operate during both homeostasis (stability) and radical change. From the axiomatic descriptions of colonial systems, the method of punctuated prototyping is derived to clarify how local colonies survive and prosper by creating and adopting isolated prototypes. This change mechanism (1) requires the self-awareness to recognize the necessity for change, and (2) describes the empowerment necessary for the colonists to build and adopt successful prototypes. The colonial systems model can be applied to explanations about how information systems, organizations, and social institutions change. Further, colonies can be used as a metaphor to design new human systems that capture a greater degree of humanness than do the models of machines and organisms.