Today, federal and state government agencies are squeezed by tighter budgets and growing legislative scrutiny. They need to make objective and rational decisions but are often constrained by siloed data and uncoordinated systems.
At the same time, they are becoming increasingly aware of the potential value that can be gained from data analytics. Data Analytics allows federal agencies to combine silos of collected data to determine the exact metrics for its programs, provide better services to citizens and employees, and make informed budgetary decisions.
How can government agencies shift their focus to fulfilling their mission, rather than manually churning numbers? Keep reading this list of Vijay Computer Academy.
1. Quick and improved decision making
When trends and other insights locked in data are identified, it becomes easier and faster to make organizational decisions through data analytics. This is achieved by processing the generated real-time data using streaming tools and other technologies. If these tools are not available, decision making can revert to guesswork or total avoidance of the decision-making process.
2. Increase financial visibility
Data visualization tools can proactively deliver government agency–wide financial insights through intuitive dashboards, which are accessible to program control officers, comptrollers, agency resource managers and decision makers at all levels. They have the ability to ask questions and obtain reliable, detailed information to make more informed decisions, often faster than before.
3. Eliminating fraud, removing waste and abuse
One of the core benefits of data analytics in governments has been eradicating fraud. Also, organizations can remove internal waste by identifying discrepancies. Depending on the missions, the agencies can eradicate abuse and fraud caused by parties or the people they serve.
4. Anti-money laundering
Data analytics are being used to prevent money laundering and financial crimes, directly impacting terrorist organizations or unfriendly foreign governments that use illicit financial activities to fund their operations.
5. Improved transparency and cost reduction
Many government tax agencies store personal information, which is replicated in the entire public sector. Citizens are continually required to fill forms to collect data that the government already has. Providing pre-filled forms can help to speed up the processing time and also reducing errors in the collected information. In addition, government agencies that can consolidate their data and analysis tools will immensely reduce infrastructure and operational costs.
Governments that avail their big data sets allow for a free flow of information, improves transparency, and build trust with their citizens. A transparent and accountable data processing allows citizens to monitor the effect of the government’s expenditure and compel the government to spend wisely.
6. Reduced crimes and security threats
Data analytics can help state government departments in uncovering crimes and other illegal activities that pose a security threat in society. This analysis would also assist local and state governments to work jointly in reducing all types of criminal activities in the community, spotting abnormal behavioral patterns indicating fraudulent activities. Applying an information-centric approach built on different data sets helps in improving the effectiveness and efficiency of the criminal justice system.
7. Workforce effectiveness
Government agencies can better understand the workforce gaps that could develop as employees either retire or leave for the private sector. Ensuring that new employees can fill the gaps, and introducing ways to retain employees, agencies can continue to operate effectively. If data is stored in a central location, it becomes easy for all government agencies to access the information from a shared pool. This also helps in reducing inefficiencies and ensure only correct data is used and analyzed.
8. Improved emergency response
Data analytics can be used to respond to hazardous natural disasters, detect health issues, prevent water scarcity problem, and coordinate thousands of displaced people. For example, during COVID-19, analytics was used to determining the areas that needed quick help and better resource allocation.
9. Public transport policy
The transport authority is able to collect real-time traffic data from various sources such as road surface sensors, traffic cameras, in-vehicle GPS, and SNS messages. Data analytics techniques allow the transport authority to process and analyze these data to provide drivers with real-time information about traffic congestion.
When data on traffic density, volume, and speed are integrated with weather conditions and road quality, the transport authority can predict the risk of accidents and, accordingly, alert drivers to be cautious. This kind of a big data-driven intelligent transportation system is one component of smart city infrastructure.
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