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The presentation is based on a literature review regarding some common foresight methods. Furthermore, an innovation management perspective is taken to analyze potential contributions of foresight methods, thereby considering also e.g. psychological biases.
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AIT Austrian Institute of Technology
Djordje Pinter
Applications, Limitations and Effects of Corporate Foresight
Methods – Towards an Evaluation Framework for
Innovation Management
XXIV ISPIM Conference,
Helsinki, Finland: 16-19 June 2013
Corporate Foresight – Definition and Research Objectives
Corporate foresight is a function (e.g. Slaughter 1998), process (e.g. Reger
2001) or capability (e.g. Major et al. 2001) enabling firms to adapt and
innovate by assessing weak signals using specific methods.
Definition
• Lacks a framework for evaluating methods (corporate setting)
• Lacks consideration of human cognition and psychology
• Lacks adaptation to innovation management stages
2
Research
Corporate Foresight and Innovation Management
• Uncertainty avoidance
• Identifying weak signals for disruptions
• Identifying market developments and niche emergence
• Improving portfolio management
• Fostering creativity
• Giving prospective and framing
• Evaluating opportunities and solutions during earliest stages
• Reinforcing learning processes
Benefits for Innovation Management
3
Corporate Foresight and Innovation Management –
Aligning Models
Screening Interpretation
& Creation Response
SCREENING &
IDEA GENERATION SELECTION
DEVELOPMENT
& TESTING
COMMERCIALI-
SATION & LAUNCH
Identification of customer needs,
risks, new technologies &
competitive intelligence
Commitment, internal
& external
communication
Evaluation, options, solutions,
adaption of existing projects
Identification Communication Learning
Organizational
learning
processes
Source: Author's representation based on: (Daft and Weick, 1984; Leitner, 2013).
4
Corporate Foresight and Innovation Management –
Evaluation Criteria
5
1. Creativity:
• Fostering ideas, visioning etc.
2. Information processing capability:
• Amount of variables, type of linkages, interactions etc.
3. Complexity absorption:
• Ability for technology assessment, capturing dynamics of systems etc.
4. Execution:
• Simplicity of execution, stimulation of learning, tacit to explicit
knowledge transformation capability etc.
5. Robustness and sensitivity:
• Sensitivity to information input, sensitivity to cognition and group
biases etc.
6. Acceptance:
• Degree of participation, communicability of results etc.
Source: Author's work based on: (Müller, 2008 p. 52; Reger, 2006 p. 318)
Corporate Foresight and Innovation Management –
Methods Review I
Anonymity of responses
Controlled feedback
Enhancing capabilities with
complex problems reduces group
biases, but still e.g. confirmation
biases
Creativity is limited (“reinforced
ideas“)
Execution process: time
consuming & discrete black box
Information interplay is limited
Room for creative interplay
Improves decision-making
Overcoming overconfidence and
tunnel vision
Easily communicable
Suitable for long term analysis
Several group and cognition
biases in play
Prone to influences
Very limited information
processing capacity
Scenario Delphi
6
Source: (Varum and Melo, 2007; Schoemaker, 1993, 1995; Lichtenthaler, 2005; Cialkowska et al., 2008; Day and Bobeva, 2005; Helmer, 1983; Landeta, 2006; Linstone and Turoff,
1975; Rowe and Wright, 1999; Yousuf, 2007; Ecken et al. 2011).
Corporate Foresight and Innovation Management –
Methods Review II
High information processing
capability (unbiased)
Absorb complexity and dynamics
Transparency of mental models
Enhances organizational learning
Risk of resource intensity
Trade-of: participation vs.
execution
Scepticism towards quantitative
modelling hinders acceptance
Excellent possibility of
participation
Acceptance of results
Structures innovation processes
Increases competitive power
• Focus on execution
Creative room is limited
Linear relationship model
(predominant)
Limited information processing
Roadmaps Simulations
7
Source: (Da Costa et al. 2003, 2005; Lichtenthaler, 2008; Lischka and Gemunden, 2008; Petrick and Echols, 2004; Phaal et al., 2004; Drucker 2004).
Corporate Foresight and Innovation Management –
Exemplified Evaluation
RoadmappingScenario
DelphiSimulations0
1
2
3
4
5
Roadmapping
Scenario
Delphi
Simulations
8
Source: own.
Corporate Foresight and Innovation Management –
Conclusion and Suggestion
SCREENING IDEA GENERATION
& SELECTION
DEVELOPMENT
& TESTING
COMMERCIALI-
SATION & LAUNCH
Delphi technique
Scenarios
Simulations
Roadmaps
o
t
h
e
r
o
t
h
e
r
9
Combining methods enhances potential benefits for innovation management
Source: Author's representation based on: (Cooper, 1990).
AIT Austrian Institute of Technology your ingenious partner
Djordje Pinter
Austrian Institute of Technology
Foresight & Policy Development
References I Cialkowska, M., Adamowski, T., Piotrowski, P., Kiejna, A., 2008. What Is the Delphi Method? Strengths and
Shortcomings. Psychiatria Polska 42, 5–16.
Cooper, R.G., 1990. Stage-Gate Systems: A New Tool for Managing New Products. Business Horizons 33,
44–54.
Da Costa, O., Boden, M., Punie, Y., Zappacosta, M., 2003. Science and Technology Roadmapping: from
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Daft, R.L., Weick, K.E., 1984. Toward a Model of Organizations as Interpretation Systems. The Academy of
Management Review 9, 284–295.
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Thinking in Management (icstm) Held at the University of Pennsylvania May 19–24, 2004.
Ecken, P., Gnatzy, T., von der Gracht, H.A., 2011. Desirability Bias in Foresight: Consequences for Decision
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Helmer, O., 1983. Looking Forward: A Guide to Futures Research. Sage Publications.
Landeta, J., 2006. Current Validity of the Delphi Method in Social Sciences. Technological Forecasting and
Social Change 73, 467–482.
Leitner, K.-H., 2013. Presentation of the Foresight & Policy Development Department, AIT at Infineon.
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References II Linstone, H.A., Turoff, M., 1975. The Delphi Method: Techniques and Applications. Addison-Wesley Pub.
Co., Advanced Book Program.
Lischka, J.-M., Gemunden, H.G., 2008. Technology Roadmapping in Manufacturing: A Case Study at
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Major, E., Asch, D., Cordey-Hayes, M., 2001. Foresight as a core competence. Futures 33, 91–107.
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Slaughter, R.A., 1998. Futures Studies as an Intellectual and Applied Discipline. American Behavioral
Scientist 42, 372–385.
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Competitiveness. Presented at the 3rd University of Strathclyde Conference “Foresight - Learning the
Future faster,” Glasgow, UK.
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