Business Intelligence and the Digital Transformation Revolution - Unlocking Arizona's Community Corrections Data. ARIZONA DEPARTMENT OF CORRECTIONS AND BUSINESS AND DECISION

Introductions  Dwight Cloud – CIO Arizona Department of Corrections  Since Spring 2015  20+ in IT private and public  Oversight of a $24m Offender Management System  Operating budget of $1.5m  Team size of 65  Dean Allen – President of Mi-Case North America  With B&D for 16 years  Project Director for the MD OCMS implementation  Project Director for the AZ AIMS2 implementation  Vendor Chair Elect to the CTA Board  Responsible for all Public Sector Activity in the USA

FY 2016 as of 04/30/2016

FY 2015 ADC Prison Admissions by Type Total Admissions – 20,611

Founded in 1992, Publically traded Presence in 18 Countries US headquarters in Wayne, PA Corporate headquarters in Paris, France 2,500 employees (200+ in North America) Global staff to support follow the sun implementation Managed services provider for global support and ongoing maintenance In house training and Proof of Concept Labs Seasoned professionals with Industry experience

Community Corrections Center Offers structure, supervision, surveillance, substance abuse treatment and cognitive restructuring opportunities to offenders who are in technical violation of their conditions of supervised release and/or who are in need of additional structured support in order to successfully complete community supervision.

Community Corrections Center  Provides a continuum of services to facilitate an offender’s successful reintegration into society.  Builds upon the programs offenders completed while incarcerated.  Holds offenders immediately accountable for their negative actions rather than returning them to custody.  Allows offenders to build on their successes and strengths rather than repeating the cycle of release and return to custody.

Community Corrections Center  Provides a continuum of services to facilitate an offender’s successful reintegration into society.  Builds upon the programs offenders completed while incarcerated.  Holds offenders immediately accountable for their negative actions rather than returning them to custody.  Allows offenders to build on their successes and strengths rather than repeating the cycle of release and return to custody.

Data has been integral in efforts to improve re-entry & reduce recidivism  ADC utilized the performance data from SRCCC to propose another facility in Maricopa County (which includes Metropolitan Phoenix) called the Northern Regional Community Corrections Center or NRCCC.  With the successful data provided, this program was approved by the Governor and was able to fund the most recent proposed Executive Budget.

Reporting Transition from Mainframe to Mi-Case  Enterprise reporting was an immediate need and then would be able to transition into to new OMS system.  The “data mart” was built, so that agency can bridge historical data from the old system to the new system.  Trending reports will be able to go beyond the transition

TRACKING STATISTICS FOR COMMUNITY CORRECTIONS TO PRESENT THE OF SUPERVISION OPERATIONS

The goal of ADC is to reduce the return % of inmates through Community Corrections and better programming for treatment, jobs and supervision which are based on metrics.

The Challenge Information was collected both manually or through paper reports Data entered manually into spreadsheets by Parole Officers on a monthly basis Multiple different data sources All spreadsheets were ed to a central person each month who would aggregate the information Reporting was done from a single spreadsheet combining all the data sets Very time consuming and labor intensive process Decision making process was slow and based on ‘dated’ data

The Challenge Manual input from 100+ parole officers Store spreadsheets for years, execute mainframe reports to collect data Weeks to prepare spreadsheet each month Inaccurate data – Different versions of the truth Data input needed for subsections (2-3 developers time) each month No Analytics, no comparison of data, static reports only Each request for graphs or analysis manually completed upon request Logistics nightmare!

‘The’ Spreadsheet

The Objective Automation of data capture Integrate the data from across all Corrections departments Implement a data strategy for the agency Provide a set of tools to allow better analysis to understand the offender population and trends in their behavior Create a project to demonstrate to the agency the power of Business Intelligence and analytics

Outcomes Implement a simple data warehouse in which to store the Community Corrections data Including a daily point-in-time history for trending Manual process were eliminated Implements the basic concepts from which a full organizational data warehouse will grow First phase of a full data platform that will carry data and analytics forward for years to come Expanding the data warehouse will allow Arizona Department of Corrections to combine both inmate and offender data onto one reporting and analytics platform.

Approach  Data is pulled from electronic sources both internal and external to ADC.  The data is integrated and transformed such that it can be analyzed as a whole instead of a grouping of disparate datasets.  The data is loaded into the data warehouse – A common data platform where it represents a point-in-time picture of the state of the organization.  Data from the platform is consumed by user-facing applications for reporting and analytics.

Benefits of the platform  The Approach makes the common data platform agnostic to the reporting tool used, and since all logic is included in the data warehouse, presentation tools can be switched, or more than one can be used while keeping consistency within the reporting. Source Data Data Warehouse Analysis

Tool Utilized  Data Platform: SQL Server – database platform that was already being used in ADC. It houses the common data platform in relational structures  ETL – SSIS is an ETL engine. Given its ability to source many different source types, was used to extract, integrate, and transform ADC data  Presentation - QlikView – Given its speed and capabilities, used to produce visualizations of the data for ADC. Qlik sources data solely from the data warehouse.

Data Sets used for the project  Drug Testing Excel Spreadsheets provided by TASC,  SQL Server Databases Warrants database Releases database PC AIMS database  Separate systems eliminated Data Sources Data Warehouse

Approach to the implementation  The team iterated through the following steps multiple times to not only implement the warehouse and reporting, but more importantly to understand the data such that accurate and intuitive visualizations could be built 1.Speak with stakeholders about business and data needs. 2.Speak with technical staff to understand data sources to meet data needs. 3.Design and implement logic to bring data into the data warehouse. 4.Source data into QlikView and build visualizations around it. 5.Cross train agency staff for self sufficiency  Project duration was around 16 weeks duration

Challenges  The reports currently utilized by ADC were generated by multiple applications, we had to work diligently with the ADC developers to determine source of data.  Some of the statistics presented on the QlikView Dashboard don’t exist in any ADC reports, they were developed & created for this dashboard for the first time.  The offender & supervision information in the databases dates back to the 1900s. In order to create an application tuned for performance, data had to be stored in binary format to provide the management team with Analytics with a click of a button.

Result  One dashboard displays more than 25 years of data  Click to view, drill down or create 15+ graphs, calendars  Date range & Parole Officer Metrics – Instant Analytics  Accurate data from 4 databases and multiple spreadsheets  No input needed from developers  Automated, refreshed daily, Web based reporting  The Business reaction!

Some examples of the presentations  Caveat!  Due to the nature of the data – we have redacted some elements of the real data for the protection of the agency

27 ADC Metrics (Dashboard, Warrants, Parole Office & Officers)

28 ER Diagram (Composite Primary Key, Master Calendar)

Conclusion  Accelerated analysis of the data from weeks to a matter of minutes  Produced a foundation for BI that can be utilized by the whole agency  Provided a solution that can be used today and tomorrow as the agency evolves  Used a small subset of the agency to validate the approach and prove the concept  The success has spawned a second project that starts this week and has already identified multiple other projects  Unlocked existing data to facilitate business decisions

Questions