Data-Driven Government

Contrary to popular belief, governments have suffered from excess data- not a lack thereof. Before IT, as we know it today, revenue agencies used to rely solely on paper to store data files, most of it never to be used again. While we have come a long way from paper dependency, we still have much to tackle in achieving a truly data-driven government.

What is Data-Driven Government?
Data-driven government is where actionable information (data that can be used to make specific business decisions) is available for all critical decisions. The benefits include sound governance and control; optimized fraud and error detection; and improved services.

Yet in 2013, an IBM study revealed that only 50 percent of managers made more than half of their decisions based on data analytics. This is partly because the necessary data capabilities are simply not available. But it also shows that government agencies, particularly revenue agencies, have yet to fully implement data strategies in their analytics.

Challenges
But why is that? According to the same IBM report, there are two main challenges: privacy and choosing data. Government agencies must manage these challenges in order to transform into more data-driven agencies.

Privacy: When implementing data strategies, one of the first obstacles that always comes up for government is privacy. As we all know, government has a responsibility to protect individuals’ privacy and security. This has become increasingly difficult in an era where data allows us to access boundless sources of information about people. Government agencies must be especially prudent in their data strategies, which may be why many of these agencies are reticent to create more sophisticated data analytics programs.

While it can be difficult to navigate between sophisticated data analytics and individual privacy, some government agencies have been able to address this challenge. For example, the IRS has been using data analytics to enhance compliance activities for 40 years. They also use their data to understand taxpayer behavior as well as educational needs and services based on categories such as occupation, age group, and postal code. When revenue agencies use data wisely in protecting and serving the public, there is hope for government to achieve a balance between privacy and becoming more data-driven.

Choosing Data: The other major challenge is that government organizations, particularly revenue agencies, are not taking full advantage of data that is available to them. However, government doesn’t have to use all of its data, just the valuable bits. So how does government choose which data to use and manage? Govies can start by choosing data from within, outside, and across borders.

The first area for each government/revenue agency is to capture internal data electronically. This lowers the cost of data capture while making it easier to keep track of filing systems. Secondly, government should not only take advantage of its internal data, but also outside data. For example, commercial business information services have been highly useful, as well as sharing government data over national borders. Sharing data internationally does not come without its challenges, but many international data exchange treaties have been established to help countries navigate privacy while sharing better data in relation to customs, taxation, and social services.

The Path Forward
So how do government agencies become more data-driven? IBM recommends first considering the role data and analytics should play in the strategic plan for the agency’s future. Government agencies should adopt enterprise data strategies to accompany analytics strategies.

The following analytical tools can help you become more data-driven in the following ways:

• Identity analysis tools: Determine who is who to help prevent identity theft and establish relationships between different entities.
• Visualization tools: Show analysis results in charts and graphs on maps.
• Unstructured data analysis: Detect patterns or trends in internal unstructured files, Internet, and social media data sources.
• Cognitive analysis tools: Provide advanced analysis of both structured and unstructured data based on machine learning and intelligence.
• Information dashboards: Extract and present the information needed for various purposes, such as management.
• Analytical tools for auditors and analysts: Provide a workbench for individuals with responsibilities such as auditing or research.
• Social sentiment analysis tools: Assess social media to detect patterns of what is being said about agencies so they can better understand their communities as well as the broader perception of their program and services.

All of these tools can play a big part in helping to make revenue management agencies smarter. Used to their fullest extent, they can also overcome many of the challenges related to navigating privacy and choosing data programs. Though these are no small challenges, what’s clear is that a data-driven government is a better government.

Need more help getting your organization data-driven? Check out our upcoming smarter buildings online training on July 14th at 2pm ET. Learn how governments are becoming more data-driven to improve building management.

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