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Policy, planning, intelligence and foresight in government organizations

Policy, planning, intelligence and foresight in government organizations Purpose– The purpose of this paper is to propose a low-cost, high return model for implementing a programmatic foresight function that is collaboratively integrated with the organization’s existing policy, planning and intelligence (or policy research) functions. Focusing on government agencies, especially those supporting liberal democratic governments, the purpose of the current paper is to propose a new, practical, low-cost and high-return model for implementing a programmatic strategic foresight function that is collaboratively integrated with the organization’s existing policy, planning and intelligence functions. The paper describes the relevant organizational considerations and options for structural adjustments, and suggests how the proposed model can maximize decision-making effectiveness without disrupting pre-existing structures, operations and products. The paper further discusses the necessity and involvement of a central government foresight agency and a non-hierarchical distributed network linking the foresight units. Design/methodology/approach– Possible solutions are considered with respect to costs of development and implementation, risk (likelihood, consequence and uncertainty) of the new function’s failure, direct negative or positive effect on the performance of existing functions, the level of cross-organizational involvement in or collaboration with the new function, the level of cross-organization tangible benefits and the level of vertical involvement, especially at the executive level. Findings– With few exceptions, the implementation of foresight by governments has not been at all methodical, but has followed many different paths, where it has occurred at all. The approach proposed in this paper – establishing a central foresight agency, propagating individual agency-based small programmatic foresight units and virtual teams and creating a non-hierarchical distributed network to link all of them – appears to best meet the success criteria set out in the paper. Research limitations/implications– Governments, especially liberal democratic ones, and their agencies that have previously shied away from methodically implementing strategic foresight or that have attempted to do so without real success now have an approach that is likely to produce the desired results. Practical implications– The paper creates a sound framework for governments, especially liberal democratic ones, and their agencies to consider and proceed with the implementation of foresight functions and networks to support them. Originality/value– The proposed approach is entirely new and generally challenges current practices. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png foresight Emerald Publishing

Policy, planning, intelligence and foresight in government organizations

foresight , Volume 17 (5): 23 – Sep 14, 2015

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1463-6689
DOI
10.1108/FS-12-2014-0081
Publisher site
See Article on Publisher Site

Abstract

Purpose– The purpose of this paper is to propose a low-cost, high return model for implementing a programmatic foresight function that is collaboratively integrated with the organization’s existing policy, planning and intelligence (or policy research) functions. Focusing on government agencies, especially those supporting liberal democratic governments, the purpose of the current paper is to propose a new, practical, low-cost and high-return model for implementing a programmatic strategic foresight function that is collaboratively integrated with the organization’s existing policy, planning and intelligence functions. The paper describes the relevant organizational considerations and options for structural adjustments, and suggests how the proposed model can maximize decision-making effectiveness without disrupting pre-existing structures, operations and products. The paper further discusses the necessity and involvement of a central government foresight agency and a non-hierarchical distributed network linking the foresight units. Design/methodology/approach– Possible solutions are considered with respect to costs of development and implementation, risk (likelihood, consequence and uncertainty) of the new function’s failure, direct negative or positive effect on the performance of existing functions, the level of cross-organizational involvement in or collaboration with the new function, the level of cross-organization tangible benefits and the level of vertical involvement, especially at the executive level. Findings– With few exceptions, the implementation of foresight by governments has not been at all methodical, but has followed many different paths, where it has occurred at all. The approach proposed in this paper – establishing a central foresight agency, propagating individual agency-based small programmatic foresight units and virtual teams and creating a non-hierarchical distributed network to link all of them – appears to best meet the success criteria set out in the paper. Research limitations/implications– Governments, especially liberal democratic ones, and their agencies that have previously shied away from methodically implementing strategic foresight or that have attempted to do so without real success now have an approach that is likely to produce the desired results. Practical implications– The paper creates a sound framework for governments, especially liberal democratic ones, and their agencies to consider and proceed with the implementation of foresight functions and networks to support them. Originality/value– The proposed approach is entirely new and generally challenges current practices.

Journal

foresightEmerald Publishing

Published: Sep 14, 2015

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