Advertisement

The Adaptive Problem Sensing and Solving (APSS) Model and Its Use for Efficient TRIZ Tool Selection

  • Alexander CzinkiEmail author
  • Claudia Hentschel
Chapter

Abstract

In increasingly complex environments, TRIZ offers a versatile set of tools and processes for problem solving. However, when it comes to defining which TRIZ tool(s) should be used in a given problem situation, many TRIZ users appear to be uncertain and seem to follow personal preferences rather than a structured process. The Adaptive Problem Sensing and Solving (APSS) Model provides a general process that is applied for TRIZ tool selection here. Based on the Cynefin framework, which allows sensing the characteristics of a problem situation, the authors suggest identifying which of the domains are actually available and provide strategies on how to extend the number of available domains. The user can set up the problem-solving process such that the solutions will more likely satisfy the respective expectations on the solution.

References

  1. Brougham, G. (2015). The Cynefin mini-book – An introduction to complexity and the Cynefin framework. Poland: C4Media.Google Scholar
  2. Czinki, A., & Hentschel, C. (2016a). Adaptive Problem Sensing and Solving Model (APSS-model) inspired by the cynefin framework and its application to TRIZ. Proceedings of the TRIZ future conference TFC 2016, Wrocław, 6 pages.Google Scholar
  3. Czinki, A., & Hentschel, C. (2016b). Solving complex problems and TRIZ. In I. Belski (Ed.), Structured Innovation with TRIZ in Science and Industry – Creating Value for Customers and Society, S (pp. 27–32). Amsterdam: Elsevier B.V.Google Scholar
  4. Fischer, A., Greiff, S., & Funke, J. (2012). The process of solving complex problems. The Journal of Problem Solving, 4(1), 19–42.CrossRefGoogle Scholar
  5. Funke, J., Fischer, J., & Holt, D. V. (2018). Competencies for complexity: Problem solving in the twenty-first century. In E. Care et al. (Eds.), Assessment and teaching of 21st century skills, educational assessment in an information age (pp. 41–53). Cham: Springer International Publishing.Google Scholar
  6. Hentschel, C., & Czinki, A. (2016). Taming complex problems by systematic innovation. In L. Chechurin (Ed.), Research and practice on the theory of inventive problem solving (TRIZ) – Linking creativity, engineering and innovation (pp. 77–93). Berlin: Springer International Publishing.CrossRefGoogle Scholar
  7. Kurtz, C. F., & Snowden, D. J. (2003). The new dynamics of strategy: Sense-making in a complex and complicated world. IBM Systems Journal, 42(3), 462.CrossRefGoogle Scholar
  8. Rokosch, U. (2011, Auflage 2). Airbag und Gurtstraffer. Würzburg: Vogel Industrie Medien.Google Scholar
  9. Sargut, G., & McGrath, R. (2011). Learning to live with complexity. Harvard Business Review, 89(9), 68–76.Google Scholar
  10. Snowden, D. J., & Boone, M. E. (2007, November). A leader’s framework for decision making. Harvard Business Review, 85(11), 68–76, 9 pages.Google Scholar
  11. Waldrop, M. M. (1992). Complexity – The emerging science at the edge of order and chaos. New York: Simon & Schuster Paperbacks.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2019

Authors and Affiliations

  1. 1.University of Applied Sciences AschaffenburgAschaffenburgGermany
  2. 2.University of Applied Sciences HTW BerlinBerlinGermany

Personalised recommendations