1. Transforming Your Operations Presented By: Mark Johnston, Product Adoption Manager The Role of Data Governance August 13, 2014

2. Agenda Why Data Governance? What is it? Who should care about Data? How do you do Data Governance? Where do we go from here?

3. About Us We provide real-time end-to-end process level performance measurement and visibility Gain real-time operational insight into errors and process inefficiencies caused by disparate systems and product silos Automate reporting, reconciliations, and controls across your critical business processes Infogix partners with leading companies to help them realize immediate and long-term operational transformation through the implementation of our various products and services. Customers realize the full value of the Infogix solution set when they leverage these solutions in a continuous cycle of operational improvement.

4. Why Data Governance? “The Business doesn’t care about data” … they do care about outcomes as a result of good data … … business expectations don’t match results of data governance or IT deliverables … … isn’t seen as a priority since its seen as “techy” …

5. Why Data Governance? “IT should worry about data” … good data and analysis drives outcomes … … cross-functional ownership of data works best … Deliver business results Minimize Risk Maximize Opportunity Drive Innovation

6. What Is It? Data Governance = Data Integrity ControlComplianceConfidence Information, Access controls, File/Log monitoring, SOD, Fraud Detection, Firewall/Security monitoring, Reconciliation Regulatory Compliance, Audit Visibility, Real-time alerting, System independent, Cross system, Continuous

7. What Is It? Information SourcesElements of GovernanceResultsUsers Positional, Delimited, or Freeform Records & Reports Relational Database XML Binary Data from Apps Spreadsheets ERP Message Queues 3 rd Party Controls Data Quality Reconciliation Data Controls Monitoring Reporting Analytics Web-Based Viewing of Controls Email Alerts Freeform Reports Analytics Business Process Owner IT Controls Team Compliance Teams Internal Audit Management Finance Teams

8. From Data to Outcomes In Canada, the likelihood that a prepaid subscriber will move to postpaid service increases by more that twice if the prepaid subscriber receives more than 24 calls in a 3 month period. Predictive AnalyticsPrescription: Make Offer Average claim due to fraud doubles in pharmacies which have fulfilled prescriptions for patients who were deceased at least 6 months before the prescription was filled. Predictive AnalyticsPrescription: Surveillance Chase has harnessed the power of predictive analytics to make data-driven decisions about its consumer loan and myriad other lines of business. From its analytics efforts, Chase understood the value of customer characteristics and smartly ascertained which customers qualified for its "lower your mortgage" valued-customer program. Predictive AnalyticsPrescription: Select Customers Citycell found a correlation between the purchase of prepaid phones and civil unrest in the Congo. When there was unrest the people wanted to move their money to US dollars which is the currency of the phone. Predictive AnalyticsPrescription: Early Intervention A large Australian bank was able to increase its revenues by over 20% and increase its customer satisfaction score by using existing customer data to offer relevant products (balance transfers, increase in credit limit, insurance) each time a customer called to activate a new credit card. Predictive Analytics Prescription: Make Offer

9. Driving Risk & Opportunity Outcomes AcquisitionUsageChurnBad DebtCustomer Onboarding Risk/Opportunity Usage Risk Up-Sell Cross Sell Revenue Retention /Risk Collect /Retain ReviewProcessReporting StatementsBilling Settlements & Payments Credits/ Vouchers Financial Regulatory Compliance Analytics + Controls + Visibility Customers Operations

10. Driving Outcomes with Rules & Analytics Process Controls Data Quality Controls Statistical Analytics Predictive Analytics Prescriptive Analytics High Volume (Big Data) Sources Real Time Feeds Cloud Exception Management Advanced Visualization

11. Data Governance Coverage Executives Operations Data Generation Analytics/ Outcomes

12. How Do You Do Data Governance? Priorities Set organization-wide, clear business objectives Align data needs and governance with the achievement of these objectives People Obtain executive sponsorship Align operational management Create cross-functional teams (business and IT) Process End-to-end Data domain mapping, MDM, EDM, Process modeling, Risk Analysis Controls, Monitoring, Analytics, Operationalization

13. Where Do We Go From Here? Minimize Risk Compliance Fraud Error Prevention Maximize Opportunity New Customers/Channels New Revenue Sources Stopping Leakage Drive Innovation New Business Models Extended Enterprise Digital Economy/Big Data

14. Putting It All Together

24. Questions?