Subject: Management info systems CA Beyond Street Smarts: Data-Driven Crime Figh
ID: 393422 • Letter: S
Question
Subject: Management info systems CA Beyond Street Smarts: Data-Driven Crime Fighting n a Saturday afternoon last summer, Mark Rasch to his baseball game at a park in C . The ballpark is located in an area that h Marynth a two-hour limit. Rasch was forced to eorgetow upgrade IT systems by the Y2K frenzy, Berkow says. "By Pannt that was a bit of a hike from the ball field. lHe le says. That and CompStat led to a movement ng zone 2000-2 2001, everybody had some level of digital informa- spot closer to the park and moved his car there. ed an opening later known by the initials IL.P which stand for rhe game ended, Rasch packed up, and was read when he noticed a parking enforcement officer tickets. "I'm OK, right?" he asked, assuming that The concept is simple: Leverage data to help position limited police resoarces where they can do the most good. uritins he had moved his car she wouldn't know he'd been ment, Berkow says, from the reactive, It's an effort to be more proactive, to "change the environ- in the zone longer than two hours. vithin the zone. Fortunately, she didn't write him a ticket, inals is ho is a lawyer and a cyber-security consultant, a little persistent prolific offenders. Past criminal Wrong. The officer not only knew that he had moved but also when and how long he'd been parked methods of the past. To a great extent, data are about the context of crimi- crime," says Berkow. Police refer to that group as PPOs future problems. When Berkow was chief in Savannah, his nal behavior. "We know about to pull out. But the encounter left that the same small group of crim- for Rasch, spooked at the realization of just how much information domestic violence, can be a strong indicator of potential law enforcement is generatin If there was a time when law-enforcement agencies department went through data on recent homicide cases suffered from an information deficit, it's passed. Of the and noticed an interesting data point: Of 20-some arrests than 18,000 law-enforcement agencies across the for homicide, 18 of those people had prior arrests for biggest city agencies have sophisticated data warehouses, enforcement officials often refer to the need for "ac- nal justice agencies are ng the same data-related with geographical informtion systems, in support of what's ing standards for inte and exploiting those data analysis technology from business intelligence vendor more United States, the vast majority has some form of technol- n of firearms. "We started this very detailed r ogy for collecting crime-related data in digital form. The every aspect of our gun arrests," he says. tionable information." One of the first ways police agencies law-enforcement and crimi- used incident-report data in digital form was in conijunction and even the most provinciel are database savvy. So it's not surprisin known as electronic crime mapping, or hot-lot analysis. Cognos (now part of IB.M) a few years ago. The first proj- tool in conjunction with a new geographic-based resource eriencing for years: en- developing and enforc- problems that CIOs li- Police in the city of Edmonton, Alberta, brought suring data quality and digital resources in the isos etbective 1990s in New York City. It was there that police chief William The era of data-driven iaw eniorcement began in the early ect police officials concentrated on was using the reporting Giuliani with a radical approach to policing that came to be business analyties reports became a key component of how known as CompStat. CompStat put an emphasis on leveraging we deployed policemen around the city," says John Warden, yment model being implemented by the agency."Oar y elected mayor Rudolph new Bratton a--accurate, detailed, and timely-to optimize police work. staff sergeant in the business performance section of the uting, a newly launched division of security firm Altegrity tivity according to both geographic area and comparative as second-in-command to Bratton in Los Angeles after ied policing is what's referred to as predictive policing Edmonton Police Serv Police departments are powerful collectors of data," ays Michael Berkow, president of Altegrity Security Con- ASC last month, Berkow was chief of the m police department, and before that he Now the agency is using the data to plot criminal ac- history. "We're really delving into those analytics in terms led policing is what's referred to as predictive polici place and tim e," says Warden. The holy grail of information- inah-Chatha ratton left New York to be chief of the LAPD being able to predict where and when crimes mayExplanation / Answer
1. Law enforcement agencies are increasingly deriving benefits from the use of technology which is enabling the law enforcement agencies to generate information and the use the information in a manner that will enable them to enforce the law in a more effective manner. The law enforcement agencies are in a position to better fight crimes due to use of technologies. For instance data collected by the police department is about the context of criminal behavior. The police department can use sophisticated tools like SPSS to determine persistent prolific offenders and use data of past criminal behavior to predict potential future crimes and problems.
Some of the examples are cops using data to determine the pattern of truck theft (the cops determined that truck theft happened only on weekends and is prevalent in certain areas like Los Angeles basin, Atlanta and Miami), use of data maps to determine areas that are more prone to criminal activities etc.
2. Data related issues faced by law enforcement agencies are similar to the issues being faced by companies. First of all large volumes of data are generated both by law enforcement agencies as well as companies. Secondly both law related agencies and companies face privacy and security concerns. In terms of differences data is not well integrated between organizations in case of law enforcement agencies while the level of integration is much higher for companies. The problems come from that fact that these programs face issues like insufficient funding and improper and inadequate planning.
3. The information can be analyzed in several ways and for several purposes. I can use the information to see the patterns and evaluate the patterns to determine high crime areas. This will help me to secure the safety of my family as I will ensure that they do not go to the high crime areas. Secondly I will rent a house that is located in a low crime area.