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SPSS, an IBM (NYSE: IBM) Company, today announced that the Florida State Department of Juvenile Justice selected IBM predictive analytics software to better understand, predict behaviors and properly assign rehabilitation programs for the state’s juvenile justice system.
More than 85,000 youth enter the juvenile justice system in Florida each year for varying degrees of offenses – from drug abuse to robbery or property crimes. As each youth enters the system for a different reason and with varying backgrounds, the best program for positive rehabilitation is very specific – what may wo
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Armonk-- - 14 Apr 2010: SPSS, an IBM (NYSE: IBM) Company, today announced that the Florida State Department of Juvenile Justice selected IBM predictive analytics software to better understand, predict behaviors and properly assign rehabilitation programs for the state's juvenile justice system.
More than 85,000 youth enter the juvenile justice system in Florida each year for varying degrees of offenses – from drug abuse to robbery or property crimes. As each youth enters the system for a different reason and with varying backgrounds, the best program for positive rehabilitation is very specific – what may work for one juvenile may not work for another. The goal of the collaboration with IBM is to apply analysis to predict the best programs and rehabilitation for each juvenile offender based on their crime and background.
Mark Greenwald, chief of research and planning at the Florida Department of Juvenile Justice, said, “The State of Florida believes that if youth are rehabilitated with effective prevention, intervention and treatment services early in life, juveniles will not enter the adult corrections system. Our goal is to ensure juveniles do not return to the system. IBM SPSS predictive analytics will allow our organization to refine our current practice and better intervene in juvenile lives earlier to help them become — and stay — law abiding citizens.”
The organization selected IBM predictive analytics to improve its existing screening and placement process. With the new analytics system in place, Florida Department of Juvenile Justice will analyze key predictors such as past offense history, home life environment, gang affiliation and peer associations to better understand and predict which youths have a higher likelihood to reoffend.
With that information, the organization can more effectively place specific segments of juveniles into the best programs for rehabilitation. For example, juveniles identified as having a higher likelihood for re-offense can be placed in a more focused program, such as one that addresses issues on substance abuse or mental health, if appropriate to the need. Additionally, the organization will direct those youth with a lower chance of re-offense to a less restrictive program, again providing services better tailored to meet their rehabilitative needs.
Prior to predictive analytics, the organization used Excel for basic analysis on projections for the number of delinquency cases they would take in, which had limited functionality. They selected IBM SPSS predictive analytics due to the ease of use and the advanced analytic capabilities.
The organization will now utilize the new predictive analytics system as a component in many of the performance measurement analyses conducted and distributed to agency staff throughout the year. These reports assess the future of delinquency cases to evaluate what juvenile crime trends may look like in the immediate future. This information will help the organization to better plan and project staffing and other resource needs.
IBM recently also announced that the Ministry of Justice in the United Kingdom uses predictive analytics to assess the likelihood of prisoners reoffending upon their release to help improve public safety. With predictive technology from IBM, the Ministry of Justice is analyzing hidden trends and patterns within the data. IBM SPSS predictive analytics has helped identify whether offenders with specific problems such as drug and alcohol misuse are more likely to reoffend than other prisoners.