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Imagining Futures – A generative scenario-based methodology to improve planning and decision-support systems for policymakers

Authors: Dutt, Vaibhav; Sil, Srijan; Krishna, Harsha; Palavalli, Bharath;

Imagining Futures – A generative scenario-based methodology to improve planning and decision-support systems for policymakers

Abstract

This study proposes a generative scenario-based methodology to improve planning and decision support systems that help policymakers in a given urban context, to imagine futures, to advance towards integrating government functions, and to identify pathways to get there. To demonstrate the same, we developed a scenario-based simulation platform, named ‘Simulogue’. The tool is set in Chennai, India, and is designed as a platform for integrated governance through a facilitated dialogue between various stakeholders involved with governing Chennai. The dialogue is based on various future scenarios that each stakeholder develops and is able to negotiate with their peers. A futures-based approach helps to improve decision-making by (i) facilitating the integration of diverse public institutions and collaboration between stakeholders by defining specific goals and evaluation parameters by stakeholders themselves and (ii) incorporating intangible data with regards their interaction and decision-making into the decision support system. Scenario-based planning enables stakeholders to explore different situations they would like to plan for. It enables them to articulate their goals and constraints with respect to the functions they perform. As a result, planning outcomes can be designed that stem from policymakers themselves. To be able to do so accurately, we must capture all relevant data such as data on resource-access, control, regulation and use as well as qualitative data on interaction amongst stakeholders. Through a combination of stakeholder-led workshops and developing an agent-based simulation tool, we bring together data, people, processes and constraints, presented in the form of future scenarios that policymakers must identify and work towards.

Keywords

Simulation-platform, Scenario-based, Integrated-governance, Generative, Decision-support

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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