Using Neural Networks for Generic Strategic Planning

  • Ray Wyatt


This paper argues the scarcity of strategic planning software is due to Western philosophical traditions which see strategy hypothesising as a mysterious, intuitive process that resists analysis and computerisation. But progress is possible if one extracts, from the tactical planning literature, eight key, generic, strategy-evaluation criteria. An experiment then tests whether scores on such criteria can be used to power machine learning of overall strategy desirabilies, and whether such learning is better achieved using multiple regression analysis or a simulated neural network. Both methods were successful, but the neural network was clearly the most accurate. It therefore constitutes a promising basis for self-improving, strategic planning software.


Neural Network Marginal Return Criterion Score Tactical Planning Strategy Score 
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.


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Copyright information

© Springer-Verlag/Wien 1995

Authors and Affiliations

  • Ray Wyatt
    • 1
  1. 1.The University of MelbourneParkvilleAustralia

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