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New Techniques for Analyzing Your Data to Improve Performance Predictive Analytics.

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Presentation on theme: "New Techniques for Analyzing Your Data to Improve Performance Predictive Analytics."— Presentation transcript:

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2 New Techniques for Analyzing Your Data to Improve Performance Predictive Analytics

3 Mark Takayesu Manager, Research Team Ruth Garcia Research Analyst III, Research Team Roger Onofre Research Analyst III, Research Team Bryan Prieto Chief Deputy Probation Officer, OC Probation Presenters

4 Predicting the Likelihood of Payment ■What Is Predictive Analytics? ✷ Practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. ■Used in Many Industries: ✷ Database Marketing ✷ Financial Risk Management ✷ Fraud Detection ✷ Predicting Performance

5 Predicting the Likelihood of Payment ■How Is It Used in Child Support? ✷ Predict Outcomes ( Will a case become delinquent & when ?) ✷ Predict Estimates ( Probability of Compliance (PM3) or payments ?) ✷ Major factors that influence performance in order of importance ✷ Given this information, what can we do about it?

6 Predict Performance Data Mining Identify Group of Cases In Need of Intervention Probation Population Identify Factors That Influence Performance Demographic, Performance, and Appropriate Orders Intervention Partnerships Measure Outcome Model to Affect Future Behavior

7 Predictive Analytics Project ■Barriers Study – 772 NCPs surveyed on the barriers they believe affect their ability to pay child support. ■Barriers Identified: ■Ratio of Order to Wage – addressed through the Guideline Study ✷ Keep support amount below 20% of NCPs income for maximum results ■Closer Look at Criminal History and Parole or Probation as a Barrier LanguagePublic AssistanceCriminal HistoryNCP Age at 1 st Born Education LevelVisitation LimitationsParole or ProbationRatio of Order to Wage Employment StatusSubstance Abuse HistoryIncome LevelNumber of Children

8 Survey Compliance Predictors

9 Top Ten Compliance Predictors

10 Survey Results ■12% of NCPs surveyed responded they were currently on Probation ■Parents on Probation pay 12% of current support vs. those Not On Probation paying at 51% FM3

11 Intervention Opportunities ■Analyzed performance impact of NCPs who reported having Parole or Probation as a barrier ■Opportunity - Joint collaboration between CSS and Probation Department to help these NCPs get back on their feet as a result of AB109 enacted in Oct 2011 ■As a result of this partnership, CSS staff reached out to all active Probation cases

12 Demographics ■Demographics for cases with Criminal History ✷ 21% or 14,744 of cases have Criminal History ✷ 89% are Males and 11% are Females NCP ✷ 6,648 have 1 or more cross-files ✷ 5,101 have a current support obligation paying 36% FM3 ✷ Represents $1.75 million in monthly child support ✷ 17% or 2,539 of cases are currently on active Probation

13 Performance – Criminal History ■Having Criminal History is one of the top barriers to paying support ■These cases pay at a combined 36% rate of current support ■Probationers pay even less, 28% during their transitional period

14 Appropriate Orders for Probation cases ■NCPs on Probation/Parole pay at a low rate, however, when orders are set below 20% threshold they pay at a higher rate.

15 Data Exchange from Probation ■Monthly data exchange of all active Probation cases (includes AB109 cases) ■Data elements includes (matching data highlighted) ■Probation data added to OC Case Management Tool (CMT) ■Analytical file flagged for future scoring NameAddressProbation Officer SSNEmployerType of Offense DOBDemographicsCDC Number

16 ■Monthly exchange and refresh of all active CSS cases ■Data elements Include (matching data highlighted) ■Secure file transferred to Probation ✷ Reviewed by ISO & Policy Unit to ensure no confidential and or inappropriate information was shared Data Exchange to Probation DemographicsUpcoming Court HearingFinancials Contact InfoCourt Order InfoLicense Suspension/Release EmployerProbation NumberLast Payment

17 Probation Cases ■Probation data included Type of Offense ✷ 56% of the NCPs have a Felony ✷ 28% have both a Felony and Misdemeanor

18 Performance – Criminal History ■Cases with a Misdemeanor pay at 57% ■Cases with a Felony or both drop compliance by half

19 Probation Data Match ■96% of Criminal History data is found in CSE ■Probation data matched 17% of cases allowing caseworkers to provide immediate attention

20 Additional Findings ■Found 102 or 24% of 417 NCPs had a history of Domestic Violence ■Only 12 were flagged in CSE

21 Business Practices ■Receive up to date contact information for shared participants from Probation Department ■Direct communication between CSS and Probation Officers ■Direct contact with NCPs post release to offer CSS services ■Modification of orders ■Connect NCPs to Community Resources (employment, housing, health services, etc.) ■Review for Compromise of Arrears (COAP) ■Generate IWOs and NMSNs

22 Measuring AB109 Outcomes ■7 months of data exchange (chart includes only 4 months due to financial history limitations) ■Unique cases in each population ■Increases and decreases are aligned with current circumstances

23 Pre and Post Overall Performance 2,179 cases reviewed $99,929 child support removed, -9.5% change $724, 272 arrears removed, - 2.4% change FM3 increased 1.5%, from 28.3% to 29.8%

24 Orange County Probation Department ■The Orange County Probation Department is a criminal justice agency that has provided community protection to the residents of Orange County since 1909. ■Through a balanced methodology, the organization provides protection through community security (e.g. enforcement) activities, offender accountability strategies while promoting the offender’s competency through the use of evidence based practices (i.e. cognitive education based support).

25 Orange County Probation Department ■The department mission is as follows: “As a public safety agency, the Orange County Probation Department serves the community using efficient and research supported corrections practices to: Reduce Crime Assist the Courts in Managing Offenders Promote Lawful and Productive Lifestyles Assist Victims

26 Orange County Probation Department ■The Orange County Probation Department Vision: A Safer Orange County Through Positive Change” “A Safer Orange County Through Positive Change”

27 AB 109 ■AB 109 (Adult Criminal Realignment) went into effect October 1, 2011. Probation looked to share information with Child Support Services and other stakeholder groups to improve client re-integration back into the community by: - improving/enhancing case plans and - reducing redundancy in the delivery of services.

28 Data Exchange ■Although AB 109 was the initial population, the data exchange included non-AB 109 clients.

29 Impact of Information Sharing ■CSS information brochures made available at Probation Office ■Participate at Probation Day Reporting Center ■Collaborative efforts to provide added support to CPs and NCPs who are also probation clients

30 Preliminary Findings ■Preliminary studies indicate that the offenders who were released under AB 109 and subsequently supervised by probation (i.e. Post Release Community Supervision – PCS offenders) rather than parole had a recidivism rate of about 15%. This same population if supervised by parole had a recidivism rate of approximately 20%. ■By comparison, non-AB 109 offenders recidivated at a rate of 12% during the same time frame.

31 Preliminary Findings ■Although it is too early to claim whether AB 109 is a success, the preliminary results in Orange County are positive and may speak to the success of information sharing and collaborative efforts of multiple agencies.

32 Contact Information ■Mark Takayesu (714) 347-8223 ✷ Mtakayesu@css.ocgov.com Mtakayesu@css.ocgov.com ■Ruth Garcia (714) 347-8045 ✷ Rgarcia@css.ocgov.com Rgarcia@css.ocgov.com ■Roger Onofre (714) 347-8004 ✷ Ronofre@css.ocgov.com Ronofre@css.ocgov.com ■Bryan Prieto (714) 937-4703 ✷ Bryan.Prieto@prob.ocgov.com

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