Data enablement for the common good

The tremendous impact that digital services have had on governments and society has been the subject of extensive research that has documented the rapid, extensive adoption of public-sector digital services around the globe. We believe that the coming data revolution will be even more deeply transformational and that data enablement will produce a radical shift in the public sector’s quality of service, empowering governments to deliver better constituent service, better policy outcomes, and more-productive operations.

The data revolution enables governments to radically improve quality of service

Government data initiatives are fueling a movement toward evidence-based policy making. Data enablement gives governments the tool they need to be more efficient, effective, and transparent while enabling a significant change in public-policy performance management across the entire spectrum of government activities. As Exhibit 2 shows, data applications can transform operations and service delivery in everything from tax compliance and collections to economic development to healthcare to education—and much more.

To raise quality of service, optimization applications are necessary but not sufficient in themselves. Governments also need to deploy a comprehensive and open performance-management system: data enablement provides a solid fact base for policy making while allowing transparency and public accountability. With this perspective in mind, governments need to launch data initiatives focused on:

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  • better understanding public attitudestoward specific policies and identifying needed changes
  • ƒƒdeveloping and using undisputed KPIs that reveal the drivers of policy performance and allow the assignment of targets to policies during the design phase
  • ƒƒmeasuring what is happening in the field by enabling civil servants, citizens, and business operators to provide fact-based information and feedback
  • evaluating policy performance, reconciling quantitative and qualitative data, and allowing the implementation of a continuous-improvement approach to policy making and execution
  • ƒƒopening data in raw, crunched, and reusable formats.

The continuing and thoroughgoing evolution taking place in public service is supported by a true data revolution, fueled by two powerful trends.

First, the already low cost of computing power continues to plummet, as does the cost of data transportation, storage, and analysis. At the same time, software providers have rolled out analytics innovations such as machine learning, artificial intelligence, automated research, and visualization tools. These developments have made it possible for nearly every business and government to derive insights from large datasets.

Second, data volumes have increased exponentially. Every two years the volume of digitally generated data doubles, thanks to new sources of data and the adoption of digital tools. And a new explosion of data is on the horizon, thanks to the wide-scale deployment of connected devices, which are expected to increase from 10 billion in 2013 to 50 billion by 2020.1Many of those devices will be associated with smart-city programs, such as sensors embedded in streets and other public areas. By 2020, smart-city usage in European cities2will generate 100 e-bytes of data per day—four times more than the global data generated daily from all usages in 2015.

Even without the data generated by connected devices, data enablement is already making a difference. A few examples suggest just how big that difference is.

Smart defense. One large national-defense organization increased equipment and weapons-systems readiness and availability through a data-enabled redesign of spare-parts sourcing and supply strategy. Data-analytics engines provided full transparency on the performance and fully loaded costs of spare parts, while also allowing analysts to simulate the impact of modifications in sourcing and supply strategies. The redesign produced optimized expenditures equal to 10 to 12 percent of the country’s overall military operations and maintenance budget.

Smart policing. An advanced-analytics engine has enabled several major cities to improve the quality of police services and prevent threats from organized crime and terrorists. One of the tools was analysis of factors suggesting imminent gang activity, such as four or more Twitter posts from gang members within ten minutes.

More broadly, these cities integrated and analyzed open-source data (such as social media) and traditional police data to monitor public sentiment in order to provide early warning of actual or potential criminal activity and enable targeted and appropriate intervention; continuously track city-specific threats from organized crime and terrorist organizations; and monitor and preempt the potential radicalization of local populations.