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Big Data and Government Combine to Drive Public Sector Programs

March 23, 2022
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The World Bank explains ‘big data’ as, “a term widely used to describe the exponential growth of data, particularly the data flowing from ubiquitous mobile phones, satellites, ground sensors, vehicles and social media. It also explains the rise of the computing technologies and algorithms that harness big data for valuable insights.”1

Loosely defined, big data comprises the vast amount of information stored on mobile devices, computers, servers and in data warehouses around the world, and the results of this data’s use by computer algorithms to build useful models and deliver insights into daily life. Any kind of analog or digital data is included within the big data model, including personal identification data, raw closed-circuit television footage, medical records, financial transactions and information from global positioning systems and climate sensors.

Artificial intelligence (AI)-enhanced computer algorithms are often useful in parsing and sorting massive amounts of disparate data from a wide variety of sources, finding patterns and making connections much more quickly than any human could.1

Big Data and Government Services

With increasing frequency, governments around the world are capitalizing on the vast amount of information they collect to drive public services. This convergence between big data and government now presents several benefits to the public sector in the form of enhanced analytics, automation, transparency and efficiency. Services can be delivered more quickly while using fewer resources and giving the customer a more personalized experience.2

In the public sector, big data can be leveraged to bolster national security, improve service delivery, mitigate financial crimes and improve health services.

Read on to learn more about how government is using big data to improve public services.3

Big Data and Government Solutions in the Public Sector

The following examples are indicative of how big data and government services combine to deliver significant benefits to the public.

Emergency Response


In recent years, governments have relied on big data to heighten and improve response to emergencies such as natural disasters. When combined with satellite mapping and social media reports, the information gathered from mobile devices has proven highly effective in coordinating rapid relief efforts. The non-profit organization Ushahidi used big data to improve the response of emergency teams during the 2010 earthquake in Haiti, resulting in the rescue of many injured and displaced victims.4

In the wake of the 2013 Typhoon Haiyan disaster in the Philippines, the use of solutions driven by big data and government once again helped reduce the death toll:5

  • By using a combination of algorithms and analyzing thousands of tweets for certain keywords, Patrick Meier, co-founder of Harvard’s Humanitarian Initiative, provided rescuers with a detailed, data-driven map of the areas they should target first and the quickest ways to reach them
  • The United Nations relied on Meier’s data to firm up its own massive rescue efforts
  • Disaster Relief International (DRI) used big data analysis to improve disaster response efforts by determining where help was needed most and using real-time tracking of assets and personnel, all at the click of a button
  • Responders used GPS-enabled satellite communicators to conduct health and structural needs assessments

Financial Crimes


Big data is already being used to great effect by the financial sector to combat money laundering and the financing of terrorist organizations. Governments are now following the lead of financial institutions and adopting big data to fight terrorism financing, corruption and white-collar crimes such as financial fraud and tax evasion. Government agencies such as the Financial Crimes Enforcement Network (FinCEN) and the Financial Action Task Force (FATF) use big data to monitor and combat financial crime, which itself is often committed with the help of big data.6

Employee and Workforce Forecasting


Predictive analytics is an area of big data that can provide a glimpse into future trends. It helps organizations identify, for example, growing dissatisfaction among employees, departments that lack effective management and teams that could benefit from better training.7

Big data delivers critical forecasting insights into areas of the workforce that may soon experience employee shortages, giving the government time to mitigate any socio-economic fallout. By using behavioral analysis combined with employee engagement metrics and supplemental information, data scientists can employ predictive analytics to build highly accurate forecasting models.

Substance Abuse


In 2017, Forbes Magazine reported on how big data was being used by state Medicaid programs to gain understanding into the ways prescription fraud could contribute to the country's opioid crisis. Further solutions combined a wealth of data from law enforcement and healthcare providers to develop a strategy to combat the crisis.8

Today, the combination of big data and government solutions continues to address substance abuse and reduce the number of deaths related to overdoses and drug use. It's an area that faces particular challenges as substance abuse victims often lack access to stable housing, healthcare and employment—areas in which the most information is often collected. State-level integrated databases employed in Massachusetts, Maryland and Pennsylvania are helping to map behavioral patterns and provide an information-sharing platform. Used to link individuals between multiple administrative data systems, these databases create the potential to understand how people interact with healthcare and other governmental systems.9

Inter-Departmental Transparency


“Under pressure to fight corruption, hold public officials accountable, and build trust with citizens, many governments pursue the quest for greater transparency.”10 As noted in the article Design Principles for Creating Digital Transparency in Government, such a quest is an excellent opportunity for government departments to work together more efficiently, reducing administrative costs and saving time.

Unfortunately, raw data alone is not usually presented in a way that is sufficiently understandable to those who read or hear it. To help master that challenge, data-driven solutions supported by big data, AI and data analytics have been highlighted as technologies that could help improve transparency and understanding between departments and the general public. Published in 2021 in the Government Information Quarterly, the article noted above outlines the authors’ use of the Design Science Research approach to arrive at a set of principles for digital transparency. This five-step research process delivers rich insight into overcoming the social, political, legal and ethical barriers to digital transparency, and ways in which the government can use big data to implement these solutions and improve public services.10

In a challenging world, be part of the solution.

As the collaboration between big data and government continues to grow with the aim of improving public services, use your expertise to advance the greater good.

Become a trusted public service authority in Kent State’s online Master of Public Administration and Postbaccalaureate Certificate in Nonprofit Management programs. The robust online curriculum is designed for working professionals like you—those with the motivation to advance their public service careers while serving local communities and the world community at large.

Sources
  1. Retrieved on February 17, 2022, from publicsectornetwork.co/insight/public-sector-big-data-case-studies/
  2. Retrieved on February 17, 2022, from link.springer.com/chapter/10.1007/978-3-319-21569-3_11
  3. Retrieved on February 17, 2022, from sas.com/en_us/insights/articles/big-data/big-data-government.html
  4. Retrieved on February 17, 2022, from safetymanagement.eku.edu/blog/4-ways-big-data-is-revolutionizing-emergency-management/
  5. Retrieved on February 17, 2022, from blogs.sap.com/2013/11/20/big-data-to-the-rescue/
  6. Retrieved on February 17, 2022, from jstor.org/stable/pdf/resrep03719.8.pdf
  7. Retrieved on February 17, 2022, from aihr.com/blog/predictive-analytics-human-resources/
  8. Retrieved on February 17, 2022, from forbes.com/sites/forbestechcouncil/2017/10/02/using-big-data-medical-analytics-to-address-the-opioid-crisis/?sh=1488952b142c
  9. Retrieved on February 17, 2022, from ideahub.org/research-data/big-data-analytics-to-tackle-substance-use-disorders/
  10. Retrieved on February 17, 2022, from sciencedirect.com/science/article/pii/S0740624X20303294