Risk-Driven Design Processes: Balancing Efficiency with Resilience in Product Design

  • J. Oehmen
  • W. Seering


Current design methods and approaches focus on increasing the efficiency of the product design system by, for example, eliminating waste and focusing on value creation. However, continuing failures in the development of complex, large scale products and systems point towards weaknesses in the existing approaches. We argue that product development organizations are hindered by the many uncertainties that are inherent in the process. Common management heuristics ignore uncertainty and thus overly simplify the decision making process. Creating transparency regarding uncertainties and the associated risks (i.e. effect of uncertainties on design objectives) is not seen as an explicit priority. Consequently organizations are unable to balance risk and return in their development choices. Product development processes do not emphasize reduction of risks, particularly those risks that are apparent early in the process. In addition, the resilience of the PD system, i.e. its ability to deliver on-target results under uncertainty, is not deliberately designed to match the level of residual uncertainty. This chapter introduces the notion of Risk-Driven Design and its four principles of 1. Creating transparency regarding design risks; 2. Risk-driven decision making; 3. Minimizing uncertainty; and 4. Creating resilience.


Product Design Input Factor Product Development Process Unit Production Cost Cost Overrun 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



The authors thank Alison Olechowski, Eric Rebentisch, Mohamed Ben-Daya and Günter Lessing for their thoughtful comments, as well as the Lean Advancement Initiative (LAI) at MIT and the MIT-KFUPM Center for Clean Water and Energy for their funding support.


  1. Chalupnik MJ, Wynn DC, Clarkson PJ (2009) Approaches to mitigate the impact of uncertainty in development processes. Proceedings of the International Conference on Engineering Design, ICED’09, 24-27 August, Stanford, CAGoogle Scholar
  2. de Weck O, Eckert C (2007) A classification of uncertainty for early product and system design. MIT Engineering System Division - Working Paper Series - ESD-WP-2007-10Google Scholar
  3. GAO (2010) Defense Acquisitions - Managing Risk to Achieve Better Outcomes (GAO 10-347T). United States Government Accountability Office, Washington, D.C.Google Scholar
  4. Griffin A, Page AL (1996) PDMA Success Measurement Project: Recommneded Measures for Product Development Success and Failure. Journal of Product Innovation Management 13 (6):478-496CrossRefGoogle Scholar
  5. Haimes YY (2009) Risk Modeling, Assessment, and Management. 3rd edn. Wiley, Hoboken, NJGoogle Scholar
  6. Halpern JY (2005) Reasoning about Uncertainty. MIT Press, Cambridge, MAGoogle Scholar
  7. ISO (2009) ISO 31000:2009(E) - Risk management - Principles and guidelines. International Organization for Standardization, GenevaGoogle Scholar
  8. Kaplan S, Garrick BJ (1981) On the quantitative definition of risk. Risk Analysis 1 (1):11-27CrossRefGoogle Scholar
  9. Knight FH (1964) Risk, Uncertainty and Profit. Augustus M. Kelley, New York, NYGoogle Scholar
  10. Krishnan V, Ulrich KT (2001) Product Development Decisions: A Review of the Literature. Management Science 47 (1):1-21CrossRefGoogle Scholar
  11. Lindley DV (2006) Understanding Uncertainty. Wiley, Hoboken, NJCrossRefMATHGoogle Scholar
  12. McManus H, Hastings D (2005) A Framework for Understanding Uncertainty and its Mitigation and Exploitation in Complex Systems. Fifteenth Annual International Symposium of the International Council on Systems Engineering (INCOSE), 10 July to 15 July 2005, Rochester, NYGoogle Scholar
  13. Morgan MG, Henrion M (1992) Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. Cambridge University Press, Cambridge, UKGoogle Scholar
  14. Oehmen J, Ben-Daya M, Seering W, Al-Salamah M (2010) Risk Management in Product Design: Current State, Conceptual Model and Future Research. Proceedings of the ASME 2010 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2010Google Scholar
  15. Paté-Cornell ME (1996) Uncertainties in risk analysis: Six levels of treatment. Reliability Engineering & System Safety 54 (2-3):95-111CrossRefGoogle Scholar
  16. Pich MT, Loch CH, de Meyer A (2002) On Uncertainty, Ambiguity, and Complexity in Project Management. Management Science 48 (8):1008-1023CrossRefGoogle Scholar
  17. Radner R (2000) Costly and bounded rationality in individual and team decision-making. Industrial and Corporate Change 9 (4):623-658CrossRefGoogle Scholar
  18. Simon HA (1997) Administrative behavior: a study of decision-making processes in administrative organizations. 4th edn. Free Press, New YorkGoogle Scholar
  19. Sommer SC, Loch CH, Pich MT (2008) Project risk management in new product development. In: Loch CH, Kavadias S (eds) The Handbook of New Product Development Management. Elsevier, Oxford:439-465Google Scholar
  20. Taleb NN (2010) The Black Swan: The Impact of the Highly Improbable. 2nd edn. Random House Google Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • J. Oehmen
    • 1
  • W. Seering
    • 1
  1. 1.Massachusetts Institute of TechnologyCambridgeUSA

Personalised recommendations