Power in Data: Turning Facts into Discoveries
Blog: Smarter CMO Solutions
Michael J Dixon - Michael J Dixon leads IBM's vision, strategy, and operations for teams active in cities around the world which are focused on a core element of IBM's long-term strategy. The integration of transport, health, public safety, energy, utilities, social services, education, and urban management are at the heart of numerous initiatives.  During an IBM career spanning 27 years, Michael has held a series of sales, management, and executive positions associated with the public sector across increasingly broad geographies. His depth of industry experience has seen him range from working with policy makers and senior executives in public-sector organizations to presenting to government leaders at APEC summits; and from advising public-sector CEOs on strategy development and project implementation to partnering with private companies to deliver associated services. 

Are Low Crime Rates Recession-Proof?

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Conventional wisdom is that crime rates typically increase with the unemployment rate. The theory is that people without jobs have the motivation and the time to commit crime. But the economic downturn we're emerging from is something of an anomaly in this respect. Not only has the crime rate not significantly increased with the unemployment rate, but violent and property crime rates have actually decreased.

To be honest, this isn't completely unexpected. Some of the most significant advancements have been achieved by capturing criminal data, which may have been collected and neglected by various agencies, and integrating all relevant data into centralized systems where it can be analyzed, accessed, and used to gain a better understanding of crime patterns. The net result: Lower crime rates.

Most cities facing crime waves tend to throw more bodies at the problem. The logic is that the more officers there are on the street, the fewer crimes are committed. But hiring more officers does not always result in lower crime rates, and given the fact that many law enforcement units are facing budget deficits, growing a police force is a prohibitively expensive solution.

Using basic analytic tools, police can analyze criminal data for various factors--such as weather, special events, time of day, etc.--to help understand where crime is committed, what times it is committed, and to plan their patrols accordingly. The more specific the data collected, the better law enforcement officers are able to actually predict and prevent crime and the less money cities will need to spend on overtime or hiring more officers.

Multiple studies have shown that emergency response times in many major cities are inadequate or are somewhat slower than they should be. There are a number of reasons why police may be delayed in arriving at a crime or accident scene, including traffic, communication problems, or a staff shortage. 

By integrating data streams from other emergency services, a computer-aided call center could immediately identify on a map where officers are in relation to a caller, the fastest routes to get to a caller, and which emergency services might be best equipped to respond to a call.

Clearly there is no easy way to eliminate crime in our cities--especially since populations are growing at a fantastic rate. Information technology will never replace police officers, but it is an invaluable tool that can help cities optimize their limited resources, while lowering crime rates and reducing expenses. This is an example of how cities are looking for new ways to deliver better services more cost effectively.


Infograph_RightRail_Promo.jpgDiscover more. Click to view our infographic on how analytics are helping police forces make our cities safer.


Making Sense of Big Data to Fight Crime

Police work is still about catching bad guys--but it's also about understanding crime patterns and acting proactively to prevent incidents before they happen.

A New Tool in Law Enforcement's Arsenal

Technology helps law-enforcement officers better predict where crimes will occur based on historical information and trends.

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