1. Lowering Recidivism With Performance Measurements/EBP and Predictive Technology
Presented by:
Charlie Granville
CEO, Capita Technologies
Chris Baird
Former Director of Research, National Council on Crime and Delinquency

2. Charlie Granville Chris Baird CEO, Capita Technologies
15 years experience designing and building criminal justice systems that enable and support Evidence-based Practices
Expert on predictive analytics
Chris Baird
Former Director of Research, National Council on Crime and Delinquency
Created the National Institute of Corrections Model Probation and Parole program

3. Why EBP & Predictive Methodologies
A well-designed, automated system provides an opportunity to significantly advance the Corrections field.

4. The Impact of Evidence-Based Practices
An organization with the right knowledge, experience and Evidence-Based Practices can provide services that have a positive impact on changing human behavior resulting in lower violations and recidivism rates.

5. Missing From Many Systems
Method(s) to determine Best Practices
Tracking to measure use
Ability to share and utilize Evidence

6. Recidivism Rates Are Through the Roof
Source: Bureau of Justice Statistics: Recidivism of Prisoners Released in 30 States in 2005: Patterns from 2005 to 2010

7. Reducing Recidivism by Only 10% Can Save Millions – Even Billions
$635 Million First Year Savings in Corrections Alone
- State of Recidivism 2011, Pew Research
Does not include additional savings from:
Direct Costs – Police, Sherriff, Court Costs
Indirect Costs – Lost Productivity, Victim Costs, other Social Costs
Total savings reaches
$10 Billion over first 5 years

8. States Have Shown Recidivism Can Be Reduced
-9.1%
-9.4%
-5.8%
-8.9%
-7.1%
-19.3%
-17.9%
-10.0%
Council of State Governments Justice Center, Reducing Recidivism: States Deliver Results (New York: Council of State Governments Justice Center, 2014)

9. What Did They Do? Tailored approaches to individual needs
Provided continuity of care from incarceration to community
Expanded use of risk assessments
Data collection and performance measurement
Fidelity to evidence-based practices
Council of State Governments Justice Center, Reducing Recidivism: States Deliver Results (New York: Council of State Governments Justice Center, 2014)

10. Today, We Aren’t Tracking What Works
“For most correctional programs, the only evidence available is evidence that they exist.” - Dennis Wagner, NCCD Director of Research
Does the program exist? ?
Did the program positively impact offenders? ?
Was an individual case plan successful? ?
Did different officers work better with different offenders?

11. Evidence Based Practices Make The Difference
2. Analyze & Adjust
3. Put Into Practice
1. Collect
Evidence
“We think one of the most important parts of [our state’s reforms] is data collection and evidence-based practices, essentially making sure we’re spending money where results are predictable and the best results will be achieved.”
-Georgia Governor Nathan Deal

12. Data is King: Collect All The Evidence
Risk and Need Assessments
Case Plans
Offender Demographics
Location of Home
Classifications
Family History
Education Level
Institutional Behavior
Employment
Contacts
Offense Information
Sanctions and Violations
Criminal History
Program Costs
Programs and Interventions

13. Key Factors in Data Collection
Quantity
Quality
Structured Data

14. Bottom Line “If you can't measure it, you can't improve it.”
- Peter Drucker

15. Step 2: Analyze and Adjust
Analyzing and Adjusting Requires
The Collected Evidence
Functional Domain Expertise
Computerized System to Manage Data, and Analyze Processes and Store Best Practices

16. Step 2: Identify Group Characteristics
Gender =
Offender Data
EBP Group Library
Age= x-y
Ethnicity =
Risk Scores =
Social Attitude
Family
Mental/Medical
Education/skills
Dependencies
Influencers
Aggression
Repeat offender
Crime Type =
Violent, nonviolent
Class type
Modeling
Analysis
Other…
Industry recidivism knowledge
Performance
Group 1
Positive Behavior

17. Step 2: Analyze and Adjust
What to Analyze
Contact Compliance
Provider Performance: Completion %, Recidivism Rate, Duration
Officer Performance
Rewards, Sanctions, Violations
Recidivism Rate

18. Step 2: Analyze and Adjust
What to Adjust
Contact Frequency
Sanctions and Violations
Programs and Providers
Caseloads
Measurements

19. Step 3: Put Into Practice
Retrain
Update computerized systems to reflect new knowledge
Reallocate resources
Modify EBP documentation

20. The Next Step in the Puzzle: Predictive Analytics

21. What is “Predictive Analytics”?
“Predictive analytics uses algorithms to find patterns in data that might predict similar outcomes in the future.”
- Forrester Research
Enabled by Big Data (Requires Lots of Evidence)
Dynamic (Changes Based on Historical Evidence)
Requires Technology

22. What Agencies Will Be Able to Do
Uncover Patterns That Were Previously Hidden
Examples:
Identify when someone is likely to re-offend
Improve program selections for individuals
Identify if a program is working for specific offender
Improve officer assignment
Improve supervision policies and procedures
Improve use of funds

23. Predictive Analytics Requirements
A Strong Model
Known Outcome

24. Building Robust Models
Know historical data
Know historical outcomes associated with that data
Build a model
Use it to predict future events based on new data

25. Dynamic Decision Making
Dynamically create and provide guidance and creation for your most important planning and supervision decisions.

26. Preparing Your Agency Collect Structured Data and Outcomes
Identify Outcomes You Want to Predict
Benchmark Where You
Are Today

27. Closing Thoughts
Statistics are only as good as their source and collection process
Large data samples are critical for continuous measurements to dynamically improve Best Practices
Utilizing Best Practices is the missing piece of the puzzle
With the right approach to information and automation, it can now be done routinely

28. Questions