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Guidance and results for the data-rich, yet information-poor.

Predictive Analytics Helps Law Enforcement

LawEnforcementHere’s another great example of the power of well-designed predictive analytics projects. Wai-Ming Yu of Information Week recently covered how predictive analytics helps police officers improve public safety.

The effort is not without challenges. Like most organizations, law enforcement often finds itself in the position of being “data rich but information poor.” Yu describes a complex array of data sources, from social media networks to CCTV footage, and rightly identifies much of what police departments have to work with as “noise.”

Additionally, law enforcement must grapple with privacy concerns. Data mining has gotten a lot of bad press from people who don’t entirely understand what it does and who are concerned that it might violate their civil liberties.

In spite of these challenges, law enforcement agencies who are taking on these projects are seeing measurable results.

Predictive analytics techniques that build on information shared between different police services, courts, prisons and other organizations can help identify locations where crimes are most likely to occur, helping officers identify offenders and even prevent future criminal activity.

Law enforcement services in the US and overseas are using predictive analytics to conduct investigations more efficiently, deploy the right people where they are needed, examine security threats and behavior patterns, and deliver intelligence to officers when and where they need it.

Results include crime rate decreases of up to 30%.

This is an evolving process. The improvements and practical applications happen as a series of projects and incremental adjustments. There is a constant data preparation process that must take place as well.

There’s also a need for constant training. The police force has to be trained on the proper use of the insights revealed by the data, and must receive further training if they want to open up new projects. Otherwise they run the risk of creating projects that don’t work or which provide false insights–something that law enforcement can ill afford.

In truth, no organization can afford to skimp on training if they want to see the kinds of results that data mining has to offer. And that’s where TMA comes in.

Whether you need to decrease shrink or increase profits, data analytics has something for you, as long as you learn the strategic techniques that help you avoid the biggest pitfalls.

Ready to get started? Register now for the very next session of TMA’s free webinar: Data Mining: Failure to Launch.

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