Generating networks for strategic planning by successive key factor modification

Abstract

Scenario planning is the most widely used member of a family of strategic planning 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 seen the future as a network of states around which movement can take place under the control of various parties. This requires a richer homogeneous set of scenarios and Rhyne's Field Anomaly Relaxation (FAR) technique has served as the basis for that state generation process. FAR has some disadvantages. It can be cumbersome and, more importantly, the discriminants of the states are unchanged throughout each cycle of the process. It operates by establishing a large number of possible futures and then clustering these into coherent sets. An alternative approach is presented which grows neighbouring states step by step from existing, plausible self-consistent states. A network of locally related states is thereby established on which basis transition-based planning can be carried out. The relationship of the method to FAR is described, and its use illustrated by an example.