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The need for analytics in government decision-making

A few weeks before the 9/11 terrorist attacks, authorities in Minnesota detained Zacarias Moussaoui for immigration-related issues. Moussaoui, known now as one of the masterminds of the attacks, was arrested with a laptop, two knives, Boeing 747 training manuals and flight simulator software.

Moussaoui’s detainment was one of several clues that foreshadowed the terror attacks; one, however, that officials were unable to piece together. As the 9/11 Commission would later discover, intelligence officials had already detained and questioned an al-Qaeda operative who said he trained with Moussaoui in a camp in Afghanistan.

The ability to connect Moussaoui and the items in his possession with the stories from this al-Qaeda operative could have disrupted, if not derailed, the 9/11 attacks.

“The U.S. government has access to a vast amount of information ... the storehouse is immense,” the 9/11 Commission wrote in 2004. “But the U.S. government has a weak system for processing and using what it has.”

The government has made much progress since then, including better coordination, oversight and information gathering. But while agencies are awash in more data than ever, they still struggle to make important connections.

Part of that challenge is in fielding the best technology. However, human nature — specifically, judgment bias — also can undermine decision-making.

Moving past bias

These biases are likely not intentional, but rather part of the human condition that skews our decision-making by our own personal experiences, influences and limitations. Each of us comes with a litany of biases that create cognitive limitations. Understanding these limitations can help leaders take steps to combat them.

That said, simply understanding human limitations to decision-making isn’t enough.

By now, agencies should have technical support for the vast quantities of data they are holding. That’s where data analytics comes in. Data analytics can step in where humans struggle to make sense of large amounts of data to make sound, defensible decisions for positive outcomes and efficient operations.

Digging in to analytics

Analytics can make sense of large amounts of data, finding connections that human analysts miss. Through data mining, forecasting and predictive analysis, such programs can provide the statistical basis for a decision.

Maybe the data tells a different story than what is imagined, or maybe it confirms a previous belief. Either way, analytics can add authority to the decision-making process, helping guide human behavior.

Let’s look at some examples:

  • Data management. It would be easy if all data was collected the same way, using the same standards, but that is not the case. Data management helps bring together disparate data sets, making them easier to use and understand. This method is especially helpful for large federal departments that must collect and use information from a large variety of data sources. Often, simply collecting and organizing an agency’s data can go a long way toward increasing evidence-based decision-making and help to challenge bias.
  • Data visualization. Once data has been organized and managed, it can be turned into a visual representation to help make sense of very large and very small numbers in context and in relationship to each other. The human brain is built to more intuitively process and understand visual representations more than numbers, so using data visualization can help put difficult data into an easy-to-understand concept. Visual representations of information help us to combat judgment bias by organizing complete information into a unified view that permits easier and more intuitive comparisons for evidence-based decision-making.
  • Anomaly detection. Often, what agencies most want from data is to find the pieces of information that stand out. This might be a fraudulent benefits claim or a tax return based on identity theft. The ability to flag anomalies also can be used to analyze cybersecurity trends. For example, is an employee’s account being used to access information at an odd time from an odd location? That may signal a larger problem. Using analytics to find anomalies greatly improves the human brain’s signal-detection capabilities. Analytics-driven anomaly detection improves the evidence basis for decision-making and helps us mitigate the impacts of judgment bias.

The path forward

Federal agencies face a difficult task. They oversee large budgets and often have life-or-death responsibilities. All of this comes under intense scrutiny from lawmakers and the public. Making the right decision is not always easy, even when intentions are in the right place.

Analytics can help bring clarity and evidence to the decision-making process. Analytics not only provide insights that can limit the impacts of human biases, but also serve as justification for action. Analytics can help ensure that government officials make the best, fastest and lowest-cost decisions based on the best available data and evidence.

Steve Bennett, Ph.D., currently the director of SAS’ Global Government Practice, is the former director of the National Biosurveillance Integration Center within the Department of Homeland Security.

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