Policy, planning, intelligence and foresight in government organizations
Policy, planning, intelligence and foresight in government organizations
Schmidt, John Michael
2015-09-14 00:00:00
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.pngforesightEmerald Publishinghttp://www.deepdyve.com/lp/emerald-publishing/policy-planning-intelligence-and-foresight-in-government-organizations-zR330V6qHy
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.
Journal
foresight
– Emerald Publishing
Published: Sep 14, 2015
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