The Maturity Model of Corporate Foresight

  • René Rohrbeck
Part of the Contributions to Management Science book series (MANAGEMENT SC.)


Companies wishing to improve their management practices often take the approach of comparing themselves to others, particularly companies that are known to be good at certain practices. This approach – known as benchmarking – has been applied to almost all areas of management, including procurement, research and development (R and D) (Dutta et al. 2005:277), production, marketing, and sales (Mittelstaedt 1992:310). The usefulness of benchmarking arises from the possibility of (1) gaining knowledge about how good one’s own management practices are in comparison to others, and (2) being able to learn from others and improve one’s management practices. To use a definition from Camp (Camp 2003:12):


Information Usage External Network Maturity Level Corporate Culture Emission Trading Scheme 
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.


  1. Ament RH (1970) Comparison of delphi forecasting studies in 1964 and 1969. Futures 2(1):35–44CrossRefGoogle Scholar
  2. Andriopoulos C, Gotsi M (2006) Probing the future: mobilising foresight in multiple-product innovation firms. Futures 38(1):50–66CrossRefGoogle Scholar
  3. Becker P (2002) Corporate foresight in Europe: a first overview working paper European Commission. European Commission, Brussels, p 31Google Scholar
  4. Blackman DA, Henderson S (2004) How foresight creates unforeseen futures: the role of doubting. Futures 36(2):253–266CrossRefGoogle Scholar
  5. Blass E (2003) Researching the future: method or madness? Futures 35(10):1041–1054CrossRefGoogle Scholar
  6. Burmeister K et al (2002) Zukunftsforschung und Unternehmen – Praxis, Methoden, Perspektiven. Druck- und Verlagskooperative stattwerk e. G, EssenGoogle Scholar
  7. Burmeister K, Neef A, Meyers B (2004b) Corporate Foresight: Unternehmen gestalten Zukunft. Murmann Verlag, HamburgGoogle Scholar
  8. Camp RC (2003) Best practice benchmarking: the path to excellence. GBN Rev 2003/2004:12–17Google Scholar
  9. Chermack TJ (2005) Studying scenario planning: theory, research suggestions, and hypotheses. Technol Forecast Soc Change 72(1):59–73Google Scholar
  10. Chermack TJ, Lynham SA, Ruona WEA (2001) A review of scenario planning literature. Futures Res Q 17(2):7–31Google Scholar
  11. Chermack TJ, van der Merwe L, Lynham SA (2007) Exploring the relationship between scenario planning and perceptions of strategic conversation quality. Technol Forecast Soc Change 74(3):379–390CrossRefGoogle Scholar
  12. Daft RL, Weick KE (1984) Toward a model of organizations as interpretation systems. Acad Manage Rev 9(2):284–295Google Scholar
  13. Daft RL, Sormunen J, Parks D (1988) Chief executive scanning, environmental characteristics, and company performance – an empirical-study. Strateg Manage J 9(2):123–139CrossRefGoogle Scholar
  14. Davis A (2008) Barrieren bei der Implementierung von Corporate Foresight im Unternehmen und im Strategischen Management Fakultät für Wirtschaftswissenschaften, Institut für Wirtschaftspolitik und Wirtschaftsforschung (IWW). University of Karlsruhe, Karlsruhe, p 245Google Scholar
  15. Day GS, Schoemaker PJH (2004b) Driving through the fog: managing at the edge. Long Range Plann 37(2):127–142CrossRefGoogle Scholar
  16. Day GS, Schoemaker PJH (2005) Scanning the periphery. Harv Bus Rev 83(11):135–148Google Scholar
  17. Deutsch CH (2008) At Kodak, some old things are new again New York times. New York Times, New YorkGoogle Scholar
  18. Donaldson L (1999) The normal science of structural contingency theory. In: Clegg S, Hardy C (eds) Studying organization: theory & method. Sage Publishing, LondonGoogle Scholar
  19. Dutta S, Narasimhan O, Rajiv S (2005) Conceptualizing and measuring capabilities: methodology and empirical application. Strateg Manage J 26(3):277–285CrossRefGoogle Scholar
  20. EIRMA (1998) Technological roadmapping. Delivering business vision working group reports. European Industrial Research Management Association, ParisGoogle Scholar
  21. Fine CH (1998) Clockspeed: winning industry control in the age of temporary advantage. Perseus Books, Reading, MAGoogle Scholar
  22. Gáspár T, Nováky E (2002) Dilemmas for renewal of futures methodology. Futures 34(5):365–379CrossRefGoogle Scholar
  23. Godet M, Roubelat F (1996) Creating the future: the use and misuse of scenarios. Long Range Plann 29(2):164–171CrossRefGoogle Scholar
  24. Gordon TJ, Glenn JC (2003) Futures research methodology. Millennium Project of the American Council of the United Nations University, New YorkGoogle Scholar
  25. Gordon TJ, Hayward H (1968) Initial experiments with the cross impact matrix method of forecasting. Futures 1(2):100–116CrossRefGoogle Scholar
  26. Groenveld P (1997) Roadmapping integrates business and technology. Res Technol Manage 40(5):48–55Google Scholar
  27. Helmer O (1972) Cross-impact gaming. Futures 4(2):149–167CrossRefGoogle Scholar
  28. Höjer M, Mattsson L-G (2000) Determinism and backcasting in future studies. Futures 32(7):613–634CrossRefGoogle Scholar
  29. Humphrey WS (1989) Managing the software process. Addison-Wesley, Reading, MAGoogle Scholar
  30. Jain SC (1984) Environmental scanning in United-States corporations. Long Range Plann 17(2):117–128CrossRefGoogle Scholar
  31. Jasner C (2006) Walk of pain. McKinsey Wissen 17(1):44–49Google Scholar
  32. Kahn KB, Barczak G, Moss R (2006) Perspective: establishing an NPD best practices framework. J Prod Innov Manage 23(2):106–116CrossRefGoogle Scholar
  33. Katz R, Allen TJ (1982) Investigating the not invented here (NIH) syndrome – a look at the performance, tenure, and communication patterns of 50 R-and-D project groups. R D Manage 12(1):7–19CrossRefGoogle Scholar
  34. Krystek U (2007) Strategische Frühaufklärung. Zeitschrift für Controlling & Management 2007(Sonderheft 2):50–58Google Scholar
  35. Lichtenthaler E (2002) Organisation der Technology Intelligence – Eine empirische Untersuchung der Technologiefrühaufklärung in technologieintensiven Grossunternehmen. Verlag Industrielle OrganisationGoogle Scholar
  36. Lichtenthaler E (2005) The choice of technology intelligence methods in multinationals: towards a contingency approach. Int J Technol Manage 32(3–4):388–407CrossRefGoogle Scholar
  37. Lichtenthaler U (2008a) Integrated roadmaps for open innovation. Res Technol Manage 51(3):45–49Google Scholar
  38. Lischka J-M, Gemünden HG (2008) Technology roadmapping in manufacturing – a case study at Siemens power generation. Int J Technol Intell Plann 4(2):201–214CrossRefGoogle Scholar
  39. Lucas HC, Goh JM (2009) Disruptive technology: how Kodak missed the digital photography revolution. J Strateg Inf Syst 18(1):46–55CrossRefGoogle Scholar
  40. Mietzner D, Reger G (2005) Advantages and disadvantages of scenario approaches for strategic foresight. Int J Technol Intell Plann 1(2):220–230CrossRefGoogle Scholar
  41. Mittelstaedt RE (1992) Benchmarking: how to learn from best-in-class practices. Natl Prod Rev 11(3):301–315CrossRefGoogle Scholar
  42. Möhrle MG (2004) TRIZ-based technology-roadmapping. Int J Technol Intell Plann 1(1):87–90Google Scholar
  43. Möhrle MG, Isenmann R (2005) Technologie-Roadmapping – Zukunftsstrategien für Technologieunternehmen. Springer-Verlag GmbH & Co. KGGoogle Scholar
  44. Müller A (2008) Strategic Foresight – Prozesse strategischer Trend- und Zukunftsforschung in Unternehmen. Universität St. Gallen, St. Gallen, Switzerland, p 425Google Scholar
  45. Nick A (2008) Wirksamkeit strategischer Frühaufklärung – Eine empirische Untersuchung Fakultät für Technologie und Management. Berlin, University of Technology, Berlin, p 232Google Scholar
  46. Ono R, Wedemeyer DJ (1994) Assessing the validity of the Delphi technique. Futures 26(3):289–304CrossRefGoogle Scholar
  47. Oriesek DF, Friedrich R (2003) Blick in die Zukunft. Harv Bus Manager May: 65–72Google Scholar
  48. Paap J, Katz R (2004) Anticipating disruptive innovation. Res Technol Manage 47:13–22Google Scholar
  49. Petrick IJ, Echols AE (2004) Technology roadmapping in review: a tool for making sustainable new product development decisions. Technol Forecast Soc Change 71(1–2):81–100CrossRefGoogle Scholar
  50. Phaal R, Farrukh CJP, Probert DR (2004a) Collaborative technology roadmapping: network development and research prioritisation. Int J Technol Intell Plann 1(1):39–54Google Scholar
  51. Phaal R, Farrukh CJP, Probert DR (2004b) Technology roadmapping – a planning framework for evolution and revolution. Technol Forecast Soc Change 71(1–2):5–26CrossRefGoogle Scholar
  52. Porter ME (1980) Competitive strategy: techniques for analyzing industries and competitors. Free Press, New YorkGoogle Scholar
  53. Porter AL et al (2004) Technology futures analysis: toward integration of the field and new methods. Technol Forecast Soc Change 71(3):287–303CrossRefGoogle Scholar
  54. Prahalad CK (2004) The blinders of dominant logic. Long Range Plann 37(2):171–179CrossRefGoogle Scholar
  55. Quist J, Vergragt P (2006) Past and future of backcasting: the shift to stakeholder participation and a proposal for a methodological framework. Futures 38(9):1027–1045CrossRefGoogle Scholar
  56. Reger G (2001a) Strategic management of technology in a global perspective: differences between European, Japanese and US Companies. In: Kocaoglu DF, Anderson TR (eds) Technology management in the knowledge era. PortlandGoogle Scholar
  57. Reger G (2006) Technologie-Früherkennung: Organisation und Prozess. In: Gassmann O, Kobe C (eds) Management von Innovation und Risiko. Quantensprünge in der Entwicklung erfolgreich managen. Springer, Berlin, pp 303–330CrossRefGoogle Scholar
  58. Rollwagen I, Hofmann J, Schneider S (2008) Improving the business impact of foresight. Technol Anal Strateg Manage 20(3):335–347CrossRefGoogle Scholar
  59. Rowe G, Wright G (1999) The Delphi technique as a forecasting tool: issues and analysis. Int J Forecast 15(4):353–375CrossRefGoogle Scholar
  60. Rowe G, Wright G, McColl A (2005) Judgment change during Delphi-like procedures: the role of majority influence, expertise, and confidence. Technol Forecast Soc Change 72(3):377–399CrossRefGoogle Scholar
  61. Ruff F (2006) Corporate foresight: integrating the future business environment into innovation and strategy. Int J Technol Manage 34(3–4):278–295CrossRefGoogle Scholar
  62. Sawyerr OO (1993) Environmental uncertainty and environmental scanning activities of Nigerian manufacturing executives – a comparative-analysis. Strateg Manage J 14(4):287–299CrossRefGoogle Scholar
  63. Schoemaker P (1993) Multiple scenario develoment: its conceptual and behavioral foundation. Strateg Manage J 14(3):193–213CrossRefGoogle Scholar
  64. Schoemaker PJH, Heijden CAJMvd (1992) Integrating scenarios into strategic planning at Royal Dutch/Shell. Plann Rev 20(3):41–46CrossRefGoogle Scholar
  65. Schwarz J (2005) Pitfalls in implementing a strategic early warning system. Foresight 7(4):22–30CrossRefGoogle Scholar
  66. Schwarz JO (2009) Business wargaming: developing foresight within a strategic simulation. Technol Anal Strateg Manage 21(3):291–305CrossRefGoogle Scholar
  67. Schwenk CR (1984) Cognitive simplification processes in strategic decision making. Strateg Manage J 5:111–128CrossRefGoogle Scholar
  68. Slaughter RA (1997) Developing and applying strategic foresight. ABN Rep 5(10):13–27Google Scholar
  69. Slaughter R (1999) Futures for the third millenium: enabling the forward view. Prospect, St. LeonardsGoogle Scholar
  70. Taylor A, Helfat CE (2009) Organizational linkages for surviving technological change: complementary assets, middle management, and ambidexterity. Organ Sci 20(4):718–739CrossRefGoogle Scholar
  71. Tripsas M, Gavetti G (2000) Capabilities, cognition, and inertia: evidence from digital imaging. Strateg Manage J 21(10–11):1147–1161CrossRefGoogle Scholar
  72. Tsoukas H, Shepherd J (2004b) Managing the future: foresight in the knowledge economy. Blackwell, Malden, MAGoogle Scholar
  73. Van der Heijden K (2005) Scenarios: the art of strategic conversation. Wiley, Chichester, West SussexGoogle Scholar
  74. Visser MP, Chermack TJ (2009) Perceptions of the relationship between scenario planning and firm performance: a qualitative study. Futures 41(9):581–592CrossRefGoogle Scholar
  75. Watman K (2003) War gaming and its role in examining the future. Brown J World Aff 2003(10):51–61Google Scholar
  76. Weimer-Jehle W (2006) Cross-impact balances: a system-theoretical approach to cross-impact analysis. Technol Forecast Soc Change 73(4):334–361CrossRefGoogle Scholar
  77. Winter SG (2004) Specialised perception, selection, and strategic surprise: learning from the Moths and Bees. Long Range Plann 37(2):163–169CrossRefGoogle Scholar
  78. Wolff MF (1992) Scouting for technology. Res Technol Manage 35(2):10–12Google Scholar
  79. Yasai-Ardekani M, Nystrom PC (1996) Designs for environmental scanning systems: tests of a contingency theory. Manage Sci 42(2):187–204CrossRefGoogle Scholar

Copyright information

© Physica-Verlag HD 2010

Authors and Affiliations

  1. 1.Department for Innovation and Technology ManagementTU BerlinBerlinGermany

Personalised recommendations