The role of data analysis in public administration

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There are few organizations in the U.S. and worldwide that, as of 2017, don’t employ data analytics in one way or another. Those that operate in the arena of public service, such as nonprofit foundations or agencies at all levels of government, are no exception. Individuals employed by these groups interact with such data on a fairly regular basis, even if they are not directly involved with its collection or maintenance.

Understanding the functions and value of this data, if not necessarily all of its specific ins and outs, will clearly be a must for those who work as public servants, particularly within local, state, or federal government departments. Staffers handling tasks on the administrative side of things must develop a keen eye for extracting actionable conclusions from the information that analytics provide. If interested in pursuing such a career path, would-be public administration employees may benefit considerably from the online Master of Public Administration degree program at Rutgers University, which addresses data analysis and tangential subjects including economics and finance.

The emergence and spread of data analytics

In some ways, counting statistics are as old as the abacus, the earliest of which emerged in 2400 B.C.E. among the Babylonian civilization. But the quantification, documentation, and examination of numbers we know of today is rooted in the 20th century, with the efforts of the mathematician Andrei Nikolaevich Kolmogorov. In 1933, he created the foundational tenets of modern probability theory.

According to a dissertation on the subject by Glenn Shafer and Vladimir Vovk, Kolmogorov’s work helped disassociate statistical analysis from various philosophical and political schools of thought to which Soviet-era mathematics had been attached, thus bolstering its global scientific objectivity. This would contribute to the development of game theory and other models for examining statistics that are still in wide practice today. Predictive analytics, in particular, is the apotheosis of probability theory.

In its layout of analytics’ evolution, the International Institute for Analytics explained that UPS created the first corporate analytics project in the 1950s. That project and its processes established the blueprint for analytics’ earliest era. These systems focused almost entirely on the warehousing of historical data, and weren’t put toward tasks like marketing the way they are now, in no small part because analysis itself could take as long as several months. Fast-forward to the dot-com boom of the late 1990s and early 2000s, out of which many soon-to-fail startups emerged—but so did Yahoo, eBay, Google, and Amazon. These eventual computing and e-commerce giants based much of their operations on algorithms that originated in the rapid collection and quantification of customer information. The methodologies are considerably more complex now, but the essential functions remain much the same.

The internet of things, coined by consumer behavior consultant Kevin Ashton in 1999, in many ways represents the newest evolution of analytics. The term invokes the continuous interaction of devices (smartphones, appliances, cars, household utilities, and much more) with the internet at large. Harnessing the multitudes of data that result from these daily digital transactions is a productive use of analytics in the corporate sphere, but can have immensely valuable applications in public service as well.

Positive and negative analytics use within public administration

Governments have been creating and collecting records for centuries, as any visit to the Library of Congress or the National Archives in Washington, D.C. will show. But in terms of putting all of that information to actionable use, some agencies have been more ahead of the curve than others.

The Violent Criminal Apprehension Program (VICAP) database is managed by the Federal Bureau of Investigation and accessible with permission by state and local police forces liaising with the agency. It stands out as a major example of such an application not living up to its potential. VICAP collects data from case files of violent crimes taking place throughout the U.S., and aggregates it, cross-referencing as necessary with other cases to search for patterns or any additional similarities. This, in theory, enables greater streamlining of the investigative processes used to find and apprehend the most violent and dangerous criminals imaginable. However, The Atlantic reported that budget and staffing cuts hamstrung the program starting in the 1990s, just 10 years after its implementation. Canada’s take on a similar analytics engine, the Violent Criminal Linkage Analysis System, for its part, has experienced considerable success.

By contrast, the Open Government Partnership (OGP), a multinational coalition represented by more than 70 countries on every inhabited continent, serves as a highly successful example of how data mining and sharing can be extremely beneficial for public service and administration. Not only do member nations labor to share data with one another, but much of the information fostered through its initiatives—which involve the most state of the art analytical models—is made available to the general public. The OGP notes in its mission statement that these data culling and distribution efforts have the potential to “promote transparency, empower citizens, fight corruption, and harness new technologies to strengthen governance.”

Ongoing analytics efforts in public service

The most visible data aggregation project within the government of the U.S., for the average citizen, is probably the Census Bureau. Its Population and Housing Census takes place once every decade, but the agency conducts dozens of additional surveys on more specific subjects at intervals ranging between one and five years. Once field reports are appropriately quantified and examined through methods both automated and manual, the resulting data is made available online.

This information can be used for any layperson’s research needs or casual edification, but also has value on a scale affecting the entire nation: The 435 seats in the House of Representatives are divided among the 50 states based on their respective population totals—it’s why Wyoming only has one representative in the lower house of Congress and California has 53. U.S. government data is centralized to an even more comprehensive degree on its website, an initiative beginning under the administration of President Barack Obama.

Smaller-scale analytics projects

The 2014 big data analytics initiative undertaken by Indiana’s state government exemplifies the sort of work that an MPA degree program graduate might take part in during the early stages of their careers. According to a Forbes Insight report, then-Governor Michael Pence requested that state agencies share data among each other as their needs required through an organized network. Pence ordered the necessary budgeting to acquire computing platforms that could handle information at such high volumes. Government efforts implemented as a result of analytics collection included a variety of education and labor force initiatives.

Every government is different, so current graduate-level public administration students cannot know for certain where their labors will take them and how they will end up interacting with big data. But the broad spectrum of purposes noted above makes it highly likely that analytics will be a part of their career, and taking the time to understand its functionality will be essential.

Learn More

The School of Public Affairs and Administration at Rutgers University-Newark, provider of the online Master of Public Administration, is accredited by the NASPAA. Before a program becomes eligible for accreditation by the NASPAA, its parent school must be recognized by a regional, national or international agency. Rutgers, The State University of New Jersey, is accredited by Middle States Commission on Higher Education and is a member of the Association of American Universities.

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