Innovations in Public Service Delivery: Issue No. 4: Predictive Analytics: Driving Improvements Using Data

Abstract

work is licensed under a Creative Commons IGO 3.0 Attribution-NonCommercial-NoDerivatives (CC-IGO BY-NC-ND 3.0 IGO) license (http://creativecommons.org/licenses/by-nc-nd/3.0/igo/legalcode) and may be reproduced with attribution to the IDB and for any non-commercial purpose. No derivative work is allowed.Any dispute related to the use of the works of the IDB that cannot be settled amicably shall be submitted to arbitration pursuant to the UNCITRAL rules. The use of the IDB's name for any purpose other than for attribution, and the use of the IDB's logo shall be subject to a separate written license agreement between the IDB and the user and is not authorized as part of this CC-IGO license. Note that the link provided above includes additional terms and conditions of the licenseThe opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the Inter-American Development Bank, its Board of Directors, or the countries they represent. TABLE OF CONTENTSC omplexity is the defining feature of an increasingly interconnected world. It underlies the greatest challenges facing the global community in the twentyfirst century, including climate change, the stability of markets, the availability of energy and resources, poverty, and conflict. 1 It is also the new reality in which governments must operate: more demanding citizens with greater awareness of their rights, better access to information through technology, and expectations of high-quality services; growing budgetary restrictions at a time when the demand for public services is on the rise; and a changing demographic composition, with important implications for service provision. In this context, government officials are pressed to devise innovative solutions to address these challenges.This complexity is reflected in the massive volume of data produced by citizens and agencies that governments must harness using predictive analytics to better understand citizens' needs and allocate public resources efficiently.What is predictive analytics? In a nutshell, it is the use of historical data to identify trends, which can be used to anticipate future needs. Some Latin American countries are already using this innovative practice to support more effective decision making through real-time situational awareness: Montevideo is following in the footsteps of Los Angeles, Santa Cruz, and Atlanta, using basic crime data (type, time, and place) to analyze patterns of criminal behavior and help the city's police force improve neighborhood patrolling schedules based on the identification of critical points of crime.2 The Government of Mexico has used data on electricity consumption to get near real-time forecasts (nowcast) of quarterly GDP, addressing the need for up-to-date estimates of economic activity to formulate and assess policies; 3 and Colombia is using data from Google web searches to infer economic activity at the sectoral level, providing alternative indicators to traditional statistics in a much timelier manner. 4 Des...

Reclaiming public service ethics through algorithms: Implications for teaching and development

“…into consideration. That public administration ethics literature has yet to incorporate any such richer conception is clear from the fact that when the literature describes human and technological relations it tends to vacillate between naive techno-utopian assurances (Dunleavy et al, 2005;Goldsmith et al, 2016;Margetts and Dunleavy 2013) and warnings of technological domination (Bruce 2001). Here the choice presented is either that technology is under our control, or that it controls us.…”

The spectrum of control: A social theory of the smart city

“…But realities of scarcity apply to political attention, problematization, and action as well. Time spent organizing to deploy a "platform for citizens to engage city hall, and each other, through text, voice, social media, and other apps" [19], is time not spent on highlighting the role of tax resistance by the wealthy in creating the very shortage of personnel that smart cities are supposed to help cure by "force multiplication" of the cities' remaining workers (Winters, 2011; Bady, 2013. Would Newark, New Jersey, need Mark Zuckerberg's donation of US$100 million to its school system, if so many others in the billionaire class had not fought so hard to reduce their own (and corporate) taxes, shelter wealth abroad, and defang regulation?…”

El uso de datos masivos y sus técnicas analíticas para el diseño e implementación de políticas públicas en Latinoamérica y el Caribe

“…Other relevant cases that did not enter the Big Data Innovation Challenge of the World Bank include two public health initiatives in Chicago and Indiana, United States [53]. Chicago improved its rodent eradication effort by carrying out a joint project with the pest control agency and using big data, while Indiana set up a high-level data center with top-notch professionals as well as investment in cutting-edge technology and information security to reduce infant mortality.…”