Big Data Analytics: Crime Fighting

Big data analytics can have a profound effect on the success of a business. Several case studies regarding this success can be found. This post will introduce and examine the content of the case study, explain what were the key problems that needed to be resolved, and identify key components that lead to the case’s success.

Advertisements

Case Study: Miami-Dade Police Department: New patterns offer breakthroughs for cold cases. 

Introduction:

Tourism is key to South Florida, bringing in $20B per year in a county of 2.5M people.  Robbery and the rise of other street crimes can hurt tourism and a 1/3 of the state’s sale tax revenue.  Thus, Lt. Arnold Palmer from the Robbery Investigation Police Department of Miami-Dade County teamed up with IT Services Bureau staff and IBM specialist to develop Blue PALMS (Predictive Analytics Lead Modeling Software), to help fight crime and protect the citizens and tourist to Miami-Dade County. When testing the tool it has achieved a 73% success rate when tested on 40 solved cases. The tool was developed because most crimes are usually committed by the same people who committed previous crimes.

 Key Problems:

  1. Cold cases needed to be solved and finally closed. Besides relying on old methods (mostly people skills and evidence gathering), patterns still could be missed, by even the most experienced officers.
  2. Other crimes like, robbery happen in predictable patterns (times of the day and location), which is explicit knowledge amongst the force. So, a tool shouldn’t tell them the location and the time of the next crime; the police need to know who did it, so a narrowed down list of who did it would help.
  3. The more experienced police officers are retiring, and their experience and knowledge leave with them. Thus, the tool that is developed must allow junior officers to ask the same questions of it and get the same answers as they would from asking those same questions to experienced officers.  Fortunately, the opportunity here is that newer officers come in with an embracing technology whenever they can, whereas veteran officers tread lightly when it comes to embracing technology.

Key Components to Success:

It comes to buy-in. Lt. Palmer had to nurture top-down support as well as buy-in from the bottom-up (ranks).  It was much harder to get buy-in from more experienced detectives, who feel that the introduction of tools like analytics, is a way to tell them to give up their long-standing practices and even replace them.  So, Lt. Palmer had sold Blue PALMS as “What’s worked best for us is proving [the value of Blue PALMS] one case at a time, and stressing that it’s a tool, that it’s a compliment to their skills and experience, not a substitute”.  Lt. Palmer got buy-in from a senior and well-respected officer, by helping him solve a case.  The senior officer had a suspect in mind, and after feeding in the data, the tool was able to predict 20 people that could have done it in an order of most likely.  The suspect was on the top five, and when apprehended, the suspect confessed.  Doing, this case by case has built the trust amongst veteran officers and thus eventually got their buy in.

 Similar organizations could benefit:

Other policing counties in Florida, who have similar data collection measures as Miami-Dade County Police Departments would be a quick win (a short-term plan) for tool adoption.  Eventually, other police departments in Florida and other states can start adopting the tool, after more successes have been defined and shared by fellow police officers.  Police officers have a brotherhood mentality and as acceptance of this tool grows. Eventually it will reach critical mass and adoption of the tool will come much more quickly than it does today.  Other places similar to police departments that could benefit from this tool is firefighters, other emergency responders, FBI, and CIA.

 Resources:

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s