Introduction to Information Systems & Systems Thinking

What Are Information Systems? (video)

Reflective One Minute Paper

The primary objective here is to define information systems. To do so, one must differentiate between raw, unorganised data, to processed, organised, and structured information that is meaningful. Information is necessary to for behaviour, decisions, and outcomes and can be valued by various metrics (timeliness, appropriateness, accuracy, etc). Information has a life-cycle: Creation (internal or external capture), Existence (Store/Retrieve, Use), Termination (Archive or Destroy).

The scholarly history of Information Systems has developed initially from positivist approaches (business and economics), to include interpretative (sociological) and critical (feminist, environmentalist). The use of Information Systems as a discipline has been especially effective in software development, and in the restructuring of business processes. Pragmatic processes are concerned with capturing and understanding business processes for analysis of that process, with notational systems (e.g., Business Process Model and Notation) being employed.

Three significant questions arise from this review.

Firstly, is there a possibility of transcendence or overcoming (aufhebung) to break the information life-cycle, where iteration leads to qualitative improvement (destruction of information, conversely, would be a qualitative destruction). If this so, then information (and data) should always be at the very least archived and never destroyed.

Secondly, where is Information Systems placed in academia given the influences? This is a major issue for researchers and theorists for decades (e.g., Checkland (1988), Banville and Landry (1989), Paul (2007)), which in part reflects its history of attempting to be positivist, interpretative and critical in approaches. Perhaps overlooked in this analysis is the importance of the earlier Habermas-Luhmann debates between systems and critical approaches in social theory (Habermas, Luhmann, 1971)

Finally, the possibility is raised for the insights of critical approaches in information systems and the iterative techniques of agile project management (Highsmith, 2010) to open up formal mappings such as the Business Process Model and Notation. Applying new decision points that allow for democratic inputs and dynamically changing the model maps would allow for dynamic projects as well as established operations, whilst at the same time providing rigour to agile project management.

References

Checkland, P.B. (1988), Information Systems and Systems Thinking: Time to Unite?, International Journal of Information Management, 8 p239-248

Banville, Claude., Landry, Maurice (1989), Can the Field of MIS be Disciplined?, Communications of the ACM, Vol 32 No 1, p48-60

Habermas, Jurgen., Luhmann, Niklas (1971), Theorie der Gesellschaft oder Sozialtechnologie?, Suhrkamp

Highsmith, Jim (2010), Agile Project Management, 2nd edition, Addison-Wesley

Paul, Ray J. (2007), Challenges to information systems: time to change, European Journal of Information Systems 16, p193–195. doi:10.1057/palgrave.ejis.3000681

Systems Thinking (video)

Reflective One Minute Paper

Systems Thinking

Reflective One Minute Paper

The following provides a review of the history and approaches to the concept of "systems". Etymologically, the word derives from the Greek sustēma, from sun- 'with' and histanai 'set up' meaning uniting, putting together. The first scientific use of the word comes from Carnot, referring to steam thermodynamics in the early-mid 19th century, with systems concepts being applied in evolutionary and biological sciences (e.g., Darwin, 1850s., Tansley 1910s) with the biologist Bertalanffy (from Bogdanov) developing a "general systems theory" in the 1930s. Wiener provided the notion of cybernetics, the general study of control and communication, in the 1940s, alongside computing sciences with von Neumann, Turing, and Shannon.

'Cybernetics', is derived from the Greek word for steersman or helmsman, who provides the control system for a boat or ship. Note also applies for government, "kyber-ment'. Cybernetics can be applied to itself, and as such second-order cybernetics was developed by Beer et al in the 1960s, which included the role of the observer. Soft systems methodology developed by Checkland, Wilson et al in the 1970s allowed for normative evaluations to be applied within an interrogative systems approach. Finally, Kauffman, Botkin et al in the 1990s developed a systems approach to complexity which identifies disequilibria dynamics in self-organisation.

Overlooked in the lecture is the extremely important contribution of systems theory within sociology and social theory, deriving from the functional sociology of Weber (1900s), the structuralism of Parsons (1950s), the systems theory of Luhmann (1960s), and the neofunctionalism of Alexander (2000s). Second-order cybernetics also has relevancy with Giddens' (1987) double hermeneutic, a distinguishing difference between social and natural sciences, where the observer is observed as well as the subject.

The structure of a system is a static property and refers to the constituent elements of the system and their relationship to each other. The behaviour is a dynamic property and refers to the effect produced by a system in operation. Feedback is information about the results of a process which is used to change the process. The homeostat, the human being, and the thermostat all are said to maintain homoeostasis or equilibrium, through feedback loops, which was promoted as a theory of everything (e.g., Odum, 1959). Whilst feedback plus systems behaviour was meant to provide a self-regulating system, the observed result is disequilibrium and dynamism at least in nature (equilibrium is present in machines).

Of note was the misuse of language from the computer engineering processes to systems theory (e.g., the use of "memory" for "information storage" (primary, secondary, tertiary, dynamic, fixed). Likewise the use of "information theory" instead of "signal transmission theory". Apropos, Shannon (1948) even described "A Mathematical Theory of Communication", an exceptional paper on signal transmission and noise, but which did not touch upon the pragmatics or semantics of language.

References

Giddens, A., (1987), Social Theory and Modern Sociology, Polity Press, p20-21

Odum, Howard (1959) "The relationships between producer plants and consumer animals, between predator and prey, not to mention the numbers and kinds of organisms in a given environment, are all limited and controlled by the same basic laws which govern non-living systems, such as electric motors and automobiles.", Fundamentals of Ecology, 2nd ed p44

Shannon, C.E., (1948), A Mathematical Theory of Communication, The Bell System Technical Journal, Vol. 27, pp. 379-423 and 623-656, 1948.