The strategic strength of weak signal analysis

Abstract Foresight can be seen as a social cognition process involving a complex set of methods and interactive processes intended to assist policy in becoming more adaptive and forward-oriented in unpredictable environments. As a form of foresight raw material, “weak signals” can be thought of as gross, unstructured, fragmented, incomplete and inadvertent environmental data that may be refined into valuable information regarding context and further be articulated into strategically actionable knowledge. As advanced indicators that precede significant discrete one-off events and/or novel developments in the rate and direction of trends, their analysis has the potential to facilitate the real-time alignment between organisational decision-making and changing external circumstances. These predictors of future change pose fundamental problems of identification and interpretation and represent a challenge to established mental models. Thus, the practical significance of weak signals is that they can be transformed into meaningful insight for policy action. Such a value, however, does not materialise automatically. Realising this potential requires a degree of tolerance and fluidity of the collective cognitive frameworks by which weak signals can be apprehended, assessed and acted upon. This paper aims at covering the scope of perceptions and actions typically involved in the tracing and tracking of this shaping process.

[1]  Daniel A. Levinthal,et al.  The myopia of learning , 1993 .

[2]  Jari Kaivo-oja,et al.  Venturing into the Wilderness Preparing for Wild Cards in the Civil Aircraft and Asset-Management Industries , 2009 .

[3]  Imre Lakatos,et al.  The methodology of scientific research programmes: Contents , 1978 .

[4]  J. March Rationality, foolishness, and adaptive intelligence , 2006 .

[5]  Pierre Rossel,et al.  Methods to find weak signals for foresight and scenario planning. , 2004 .

[6]  Jan Fagerberg The potential of benchmarking as a tool for policy learning , 2003 .

[7]  Max Tegmark,et al.  Many lives in many worlds , 2007, Nature.

[8]  T. Kuhn,et al.  The Structure of Scientific Revolutions. , 1964 .

[9]  K. Arrow The limits of organization , 1974 .

[10]  H. Igor Ansoff,et al.  Implanting Strategic Management , 1984 .

[11]  H. Ansoff,et al.  Managing Strategic Surprise by Response to Weak Signals , 1975 .

[12]  Pierre Rossel,et al.  Weak signals as a flexible framing space for enhanced management and decision-making , 2009, Technol. Anal. Strateg. Manag..

[13]  D. Henderson The Fortune encyclopedia of economics , 1993 .

[14]  Jari Kaivo-oja,et al.  Wild cards, weak signals and organisational improvisation , 2004 .

[15]  J. Metcalfe Equilibrium and Evolutionary Foundations of Competition and Technology Policy: New Perspectives on the Division of Labour and the Innovation Process , 2009 .

[16]  Sidney G. Winter,et al.  Specialised Perception, Selection, and Strategic Surprise: Learning from the Moths and Bees , 2004 .

[17]  R. Posner,et al.  Intelligence Failures: An Organizational Economics Perspective , 2005 .

[18]  M. Dertouzos,et al.  Made in America: Regaining the Productive Edge , 1989 .

[19]  Ephraim Kam,et al.  Surprise Attack: The Victim's Perspective , 1988 .