Predictive Analytics in Action Los Angeles County
Los Angeles County 4,083 sq. miles largest county in US 10 million residents 2 million children 17.1% living below poverty level Unemployment rate 8.1-9.0%
Los Angeles County Child Support Service Department (CSSD) Our mission is to enrich our community by providing child support services in an efficient, effective and professional manner, one family at a time. 6 Division Offices 280,000 cases Half a million children served
Goal: Optimize Performance Increased Collections Maximize Use of Resources Descriptive Predictive Prescriptive Operational Reports Monthly Statistics Action / Work List Statistical Analysis Forecasting Data Modeling Scoring Tailored Service Delivery Case Segmentation
Caseload Management Business Model Assessment Assess current distribution of cases and its impact on collections Identify different procedures for case distribution that optimize case performance Current Business Model Intake Caseload
Classification Model using IBM Software Data Mining Exploratory data analysis Identify patterns in data Select predictors Analyze Use training data to develop model Bring new data to model Assess model s ability to predict Deployment Finalize model Predict new cases using model Revise model as needed
Classification Model Select a Target Variable Paying at (70% of support monthly) Select Input Variables NCP info, Case Info, Arrears/CS Amount Model Data Run new, unscored data Assess model, introduce new variables
Case Scoring Predicts case outcome at any stage good for existing and new cases Scores cases to define level of case complexity, identifies payment barriers 40.00% Results: Measurable and visual identification of case complexity, cases that are mostly likely to result in favorable outcome Uses: Prioritize action/worklist, identify variables/elements that act as payment barriers 20.00% 0.00% 0 1 2 3 4 5 6 7 8 9
Scoring Goals/Objectives Understand our caseload better Identify areas for improvement Prioritize cases based on predicted outcome Customize enforcement remedies for each case Lessons Learned: Data is dirty and noisy Modelers must understand practical business practices Need to see past the numbers for insight
Caseload Management Assessment Phase 1 Phase 2 Phase 3 Phase 4 Assess current caseload management model Identify opportunities for improvement Segment caseload for analysis Segment caseload for pilot
Current Model Case Management Time consuming Locate Specialty INTAKE Needs to improve case performance Occasional Establishment Arrears Only Accounts for nearly 50% of the average caseload Zero Order Paying Monitor for compliance Non-Payers Enforcer
Case Segmentation Assign caseloads by segmentation; grouping cases with similar needs Improve efficiency by utilizing tailored strategies by segment type Increases a caseworkers ability to work pro-actively with more direction and with a focused approach Segmentation: A marketing strategy that involves dividing a broad target market into subsets of consumers who have common needs and priorities. Results in designing and implementing strategies to target specific subsections.
Cluster Analysis using IBM Software Created groups based on cases that performed similarly We further re-fined groups to account for business practices
Proposed Model Case Segmentation INTAKE Occasional Payers Paying ARREARS ONLY ESTABLISH Zero Orders Non- Payers
Benefits - Segmentation Occasional Payers Zero Order Cases Paying Cases Non- Payers Similar to working a specialized list, cases in quadrants share similar needs Improves ability to work pro-actively Less variety in enforcement techniques that are applied, improves focus and efficiency
Introduction to Quadrants Focused-Approach to Case Management Irregular payments Pays via cash, levies, intercept Underemployed Occasional Payers Paid at least one payment in FFY Paying Cases paying at least 70% of the order amount in FFY Pays via IWO Active Employer Rarely late or non-compliant Medical Only Reserved Order Locate issues Upward Modification Incarcerated Unable to work Zero Order Cases Order amount is reserved/$0 Non-Payers No payments toward order in last FFY High arrears balance No active employer Rarely complies Locate issues
Strategic Enforcement Remedies Identify enforcement strategies/techniques that are prescribed to the individual case Apply needs-based enforcement strategies Review for modifications Referral-out to services Early Intervention Monitor compliance Outbound calls to NCP/Employer Review for upward modifications Review for closure Monitor for change in circumstance (GR, Incarceration) Negotiate Close eligible cases Downward modifications Referrals to employment programs ORAP Contempt
Pilot Division 6 - Antelope Valley Higher case complexity Occasional Payers 1400 cases 7 CSO Average caseload = 200 Paying Cases 2100 cases 3 CSOs Average caseload = 700 Zero Order Cases 4200 cases 6 CSOs Average caseload = 700 Non-Payers 1400 cases 7 CSOs Average caseload = 200 Higher case complexity
Questions? Need More Information? Feel free to contact us. Sara Gaeta-Anguiano Chief, Predictive Analytics LA CSSD Sara_gaeta-anguino@cssd.lacounty.gov