Generating networks for strategic planning by successive key factor modification

Scenario planning is the most widely used member of a family of strategic p lanning approaches which use discrete states to explore management issues. Conventional approaches to scenario-based planning emphasise the clarity of using a small number of extrapolations from the present. Recent work has s een the future as a network of states around which movement can take place under the control of various parties. This requires a richer homogeneous se t of scenarios and Rhyne's Field Anomaly Relaxation (FAR) technique has ser ved as the basis for that state generation process. FAR has some disadvanta ges. It can be cumbersome and more importantly, the discriminants of the st ates are unchanged throughout each cycle of the process. It operates by est ablishing a large number of possible futures and then clustering these into coherent sets. An alternative approach is presented which grows neighbouri ng states step by step from existing, plausible self-consistent states. A n etwork of locally related states is thereby established on which basis tran sition-based planning can be carried out. The relationship of the method to FAR is described, and its use illustrated by an example.