Abstract
Policy analytics has emerged as a modification of traditional policy analysis, where the discrete stages of the policy cycle are reformulated into a continuous, real-time system of big data collection, data analytics, and ubiquitous, connected technologies that provides the basis for more precise problem definition, policy experimentation for revealing detailed insights into system dynamics, and ongoing assessment of the impact of micro-scale policy interventions to nudge behaviour towards desired policy objectives. Theoretical and applied work in policy analytics research and practice is emerging that offers a persuasive case for the future possibilities of a real-time approach to policymaking and governance. However, policy problems often operate on long time cycles where the effect of policy interventions on behaviour and decisions can be observed only over long periods, and often only indirectly. This article surveys examples in the policy analytics literature, infers from those examples some characteristics of the policy problems and settings that lend themselves to a policy analytics approach, and suggests the boundaries of feasible policy analytics. Rather than imagine policy analytics as a universal replacement for the decades-old policy analysis approach, a sense of this boundary will allow us to more effectively consider the appropriate application of real-time policy analytics.
Highlights
Policy analytics has emerged in recent years as a modification of the traditional policy analysis approach, wherePolitics and Governance, 2018, Volume 6, Issue 4, Pages 5–17 the discrete stages of the policy cycle are being reformulated into a continuous, real-time system of big data collected from ubiquitous, connected technologies, assessed using advanced data analytics
When coupled with growing capacities in data analytics, policy analytics provides a basis for more precise problem definition, detailed insights into system dynamics, and ongoing assessment of the impact of micro-scale policy interventions to nudge behaviour towards desired policy objectives (Daniell, Morton, & Insua, 2016; De Marchi, Lucertini, & Tsoukiàs, 2016; Höchtl, Parycek, & Schöllhammer, 2016; Kitchin, 2014; Lazer et al, 2009; Mergel, Rethemeyer, & Isett, 2016; Tsoukias, Montibeller, Lucertini, & Belton, 2013)
We present a scan of recent policy analytic examples, leading to the identification of some characteristics of policy issues that are amenable to a policy analytics approach and—by extension—some types of policy issues that are not suitable to a continuous, realtime system of big data and data analytics, concluding with some guidance as to when policy analytics might be considered an appropriate approach
Summary
Policy analytics has emerged in recent years as a modification of the traditional policy analysis approach, where. Our guiding research question asks what types of policy problems are amenable to ‘fast’ feedback control systems facilitated by big data and analytics, and which require a deeper, patient, ‘slower’ more deliberative approach to problem definition, analysis, decision-making, implementation, and evaluation (Kahneman, 2011). To pursue this question, we undertake a survey of the literature in policy analytics theory and practice, deriving from that the features of policy problems and their settings that characterize the range of policy issues to which policy analytics can reasonably be applied, leading towards a sketch of the boundaries of policy analytics. Rights, concerns that should temper any unexamined enthusiasm for policy analytics
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