HEI Modernization Project – 90 Day Review December 22nd 2016 Reporting Period: 9/12/2016 to 12/22/2016

HEI Modernization Project Background Ninety Day Checkpoint Project Challenges Project Phase Approach Project Health Metrics Questions / Feedback Next steps Roadmap

Background Why do a 90 day review? What will we cover? Periodic update to sponsors and other ODHE leadership Share progress / challenges, adjust to feedback What will we cover? Quick project recap (for new attendees) High level accomplishments and challenges Drill into details if desired Who is the audience? ODHE Leadership Other interested ODHE parties that don’t have operational involvement with project www.oh-tech.org

Sixty Day Checkpoint Continuing refinement of the data model base on testing and business feedback. On going programming of data quality validations. Initial Data conversion program development is complete and ready for user testing Data Informatica mapping development for data movement and transformation is under way for Facilities, Academic Programs, and Enrollment file submissions. Data integration tool selection and purchase complete On going evaluation of Business Intelligence reporting tools “Don’t borrow my watch to tell me what time it is.” Avoid stating the obvious. Discovery puts us in a position to deliver on 2 and 3….it is not in and of itself a reason to do the project. Multiple sessions – Good Cross Section: Tech Functional, LeaderContributor, etc.

Ph1: Extract, Transform Load Phase Benefits Phased Project Approach Functional Technical Q2 Q3 Q4 Q1 Q2 Ph1: Extract, Transform Load 6/9/17 Q3 Enhanced reliability Performance Improvements Faster turnaround on change requests Risk mitigation (platform and staffing) Align with state security model (SSO, ID Mgt) Enhanced user interface Risk mitigation (platform and staffing) Improved audit capabilities Ph2: Report Migration 7/31/17 Contemporary analysis UI Staffing flexibility (remove SAS dependency) More efficient analysis operations Optimized data structure Logical federation of disparate sources Data Warehouse Ph3 8/7/17 Optimization Public Analytics Provide Ph3 capabilities to public Reduce public requests for data Amortize technology investments over larger user base Ph4 Data Visualization Ph5 Leading edge user tools providing next level insights Increased usage and benefit from existing data sets www.oh-tech.org

Closing Goals for Next Reporting Period Continue to refine data model based on testing results Complete development of data movement and transformation for all remaining submission files Select a Business Intelligence reporting tool Begin integration and user testing General Reminders: - According to plan (effort), we are <1/3 of the way done… There’s plenty of time to change course / approach to meet your needs! Solicit honest / open feedback on us…what do you like / not like about how we are going about things. Next Steps: Deep dive on plan assumptions and specifics Deep dive on roadmap assumptions and specifics (resourcing Pending Action Items: Still digesting usage stats / Model (JC / Jill & Joel)

Roadmap Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 SCOPE: ETL Implemented Canned Reporting Ad Hoc Reporting Public Analytics Data Visualization SCOPE: New ETL tool used to implement data loads Decommission legacy ETL programs. Implement standard, repeatable reports against new staging tables Capture usage statistics to establish prioritization. Create ad hoc reporting infrastructure Internal: SAS Substitute External: Restricted Queries Present analysis tools w/safe metadata layer developed in Phase 3 to public. Select and implement data visualization tool. Internal tool at launch Extend to trusted partners or public at large. BENEFITS: Foundational element for new DW: enhances agility, enables unified data sources on back end. Staging tables enhance traceability Systematic data checks built into solution. Reports served from new environment Standardized formats and branding. Assesses extent of Spreadsheet-ware Transparent cutover for users Consistent, safe access to data on demand. Free IT from report writing business Enable safe self-service access to data Free ODHE staff to perform higher order analytics Gain insights not readily apparent from traditional data presentation techniques Emerging technology, use cases still evolving. Three Key Principles in Building Roadmap Reduce implementation risk Bring Value Quickly Continually Learn and Adapt High Level Features  Benefits (Drawbacks) of This Approach: Phased implementation  Lower disruption to department ops Parallel systems  Lower risk, increase ability to validate Out phases introduce forward technologies on architecturally correct platform  Lower risk, get fundamentals right, then add headline features. Canned Reporting Phase begins discussions on measures and dimensions…Ad Hoc Reporting Phase cements it. Next Iteration of this: Adds Dates and STABILIZE: Phase 1 and 2 STANDARDIZE: Phase 2 and 3 OPTIMIZE: Phases 3, 4, and 5 Next Steps on Roadmap: Validate / Revise Top Level Phases (based on feedback) Drive down next level of cost estimates, resource requirements, and schedule (rough cut) Articulate connection points (and possible overlaps) between Phases.