Soft Systems Methodology

A Metaphor for the Process of Data Analysis
  • Peter D. C. Bennetts
  • A. Trevor Wood-Harper


Although early work on methods of data analysis allowed for an interpretative approach, most current texts appear to take a purely positivistic approach. This latter approach can give rise to the following problems. Firstly, there is an expectation that the descriptions agreed represent reality rather than a means of discussing reality. Secondly, different viewpoints cannot always be reconciled or accommodated. Thirdly, objects are thought to have measurable attributes and are seen as existing independently of an observer. Lastly, politics are ignored.


Soft System Methodology Interpretative Approach Information System Development Software Quality Assurance Information System Development 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Checkland, P.B., 1981, Systems Thinking, Systems Practice, John Wiley & Sons: Chichester.Google Scholar
  2. Checkland, P. and Scholes, J., 1990, Soft Systems Methodology in Action, Wiley: Chichester.Google Scholar
  3. Ford, J., 1975, Paradigms and fairy tales — an introduction to the science of meanings, Vols. 1 & 2: Routledge and Kegan Paul, London.Google Scholar
  4. Hirschheim, R., Klein, H. K. and Lyytinen, K., 1995, Information Systems Development and Data Modeling — Conceptual and Philosophical Foundations, Cambridge University Press: Cambridge.CrossRefGoogle Scholar
  5. Hitchman, S., 1995, The Development and Evaluation of a Knowledgebase Approach to a Method for the Analysis and Design of Commercial Computer Systems, PhD Thesis, Bristol University.Google Scholar
  6. Hitchman, S. and Bennetts, P.D.C., 1994, The Strategic Use of Data Modelling and Soft Systems Thinking, in: Information System Methodologies 1994, (Lissoni, C., Richardson, T., Miles, R., Wood-Harper, T. and Jayaratna, N., eds.), p. 331-336.Google Scholar
  7. Hitchman, S. and Bennetts, P.D.C., 1995, Using Quality Issues in Inquiring Systems to Improve the Understanding and Use of Data Models, in: Information System Methodologies 1995, (Jayaratna, N., Miles, R., Merali, Y. and Probert, S., eds.), p. 293-300.Google Scholar
  8. Kuhn, T.S., 1970, The Structure of Scientific Revolutions (2nd edition: enlarged), The University of Chicago Press, Chicago.Google Scholar
  9. Lewis, P., 1994, Information-Systems Development, Pitman Publishing: London.Google Scholar
  10. Lyytinen, K. and Hirschheim, R., 1987, Information systems failures — a survey and classification of the empirical literature, Oxford Surveys in Information Technology, 4: 257–309.Google Scholar
  11. Little, S.E., 1993, The Organizational Context of Systems Development, in: Human, Organizational and Social Dimensions of Information Systems Development, (Avison, D., Kendall, J. E., and DeGroes, J. I. eds.), p. 439–454, Elsevier Science Publications B. V. North Holland.Google Scholar
  12. Newman, M., 1989, Some Fallacies in Information Systems Development, Int. J. of Information Management, 9: 127–143.CrossRefGoogle Scholar
  13. Vidgen, R., Wood-Harper, T. and Wood, J.R.G., 1993, A Soft Systems Approach to Information Systems Quality, Scandinavian Journal of Information Systems, 5: 97–112.Google Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Peter D. C. Bennetts
    • 1
    • 2
  • A. Trevor Wood-Harper
    • 1
    • 2
  1. 1.Department of Information TechnologyCheltenham and Gloucester College of Higher EducationThe Park, Cheltenham, GloucestershireUK
  2. 2.Department of Mathematics and Computer ScienceUniversity of SalfordSalfordUK

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