政府通过数据驱动决策实现卓越

The Government Summit Thought Leadership Series03This paper provides a comprehensive introduction todata-driven decision making in the public sector andhow the use of smart applications can enable govern-ment entities in the Middle East to improve their op-erational efficiencies through faster, evidence-baseddecision making and rank them among global gov-ernment leaders. We demonstrate the power of datausage by high-lighting the success in corporate worldfollowed by a deep-dive into specific applicationswithin law enforcement and healthcare sectors. Alsowe provide an overview of analytics muscle employedin the 2012 U.S. Presidential election. Finally we illus-trate how service delivery can be improved acrossdifferent citizen-facing ministries like utilities, educa-tion, transportation etc by using data driven decisionmaking approach. We end our paper with key stepsfor consideration while embarking on the journey ofgoverning with insight. Executive Summary 0506061820Contents04The Government Summit Thought Leadership Series Effects of InformationExplosionData-Driven Decision Makingin the Private SectorData-Driven Decision Makingin the Public SectorSmart Policing for Reducing CrimeImproving the Government Healthcare System Using DDDAnalytics Takes Center Stage in the U.S. Presidential CampaignUbiquity of DDD in Modern Public ServiceReferencesRelevance of DDD for Middle EastGovernment Entities The Government Summit Thought Leadership Series05Effects of InformationExplosionIn the past two decades, the world has witnessed an unprece-dented information explosion thanks to digitization and broaderaccess to the Internet and cell phones. These developments havechanged our lives for the better. It’s difficult to imagine that atone time not long ago we didn’t use a laptop or cell phones as asearch tool for answers to our questions or browsed our favoritewebsites. Today, we are all smarter, faster, and more connect-ed than ever. Former Google CEO Eric Schmidt once famouslyclaimed that “Every two days we now create as much informa-tion as we did from the dawn of civilization up until 2003”.The increasing use of technology in society has led to a dramaticincrease in the amount of electronic data being generated. Untila few years ago, corporate databases were measured in the rangeof tens to hundreds of gigabytes, but nowadays multi-terabyteor even petabyte databases are quite common. Large databaseshave left the traditional approach to decision making based ongut feeling redundant. Moreover, much of the data generatedtoday from tweets and blogs is not in a structured format. Trans-forming such data into a usable format and linking it with otherdata for later analysis is a major challenge.Data retrieval, storage, modeling, and analysis are additionalchallenges which require more sophisticated statistical tech-niques to generate useful insights and anticipate what will hap-pen based on the trends in the data. To succeed with analyticalefforts, we need skilled individuals to perform the analysis, dis-cern which questions to ask related to data, gauge the limita-tions of the data, and present the results. This usually requires anunderstanding of statistics, knowledge of computing, and oftena bit of social science, as well. In the end, the presentation of theoutput and the conclusion by non-technical domain experts iscritical for deriving actionable insights.Data Driven Decision Making involves integrating dispa-rate data sources to form a common pool of data, ap-plying combination of statistical and optimization tech-niques to uncover hidden insights, and use it to takeinformed decisions.Data Driven Decision Making is referred by many dif-ferent terminologies ranging from Analytics, PredictiveModeling, Statistical Analysis, Optimization models, DataMining, Business Intelligence, and in recent period BigData. All these terms are closely related and complemen-tary to the goal of informed decision making. Data-DrivenDecision Makingin the Private SectorData-DrivenDecision Makingin the Public SectorThe explosion of electronic data volumes has led to several chal-lenges. However, many businesses including Wal-Mart, Amazon,and Proctor & Gamble have aggressively worked to uncovermeanings hidden in all this newly-created data and have man-aged to achieve success for their customers, employees, andshareholders alike. Researchers have calculated that data-drivendecision making (DDD) is responsible for a 5%-to-6% increasein productivity and output as well as significantly higher profit-ability and market value.Businesses organizations across multiple sectors are utilizingbusiness analytics to gain a better understanding of customerbehavior and make more informed decisions to manage perfor-mance. More specifically, business analytics is being used by theprivate sector to drive proactive demand forecasting, take theright course of action, manage risk, and increase profits as wellas customer satisfaction.Private-sector organizations hav