Transcript Data Governance _ Mark Johnston

Transforming Your Operations
The Role of Data Governance
Presented By: Mark Johnston, Product Adoption Manager
August 13, 2014
Agenda
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Why Data Governance?
What is it?
Who should care about Data?
How do you do Data Governance?
Where do we go from here?
About Us
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.
• 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
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” …
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
What Is It?
Data Governance = Data Integrity
Control
Compliance
Confidence
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
What Is It?
Information Sources
Elements of Governance
Results
Users
Business
Process Owner
Positional, Delimited,
or Freeform Records
& Reports
Spreadsheets
Data Quality
Web-Based
Viewing of
Controls
IT Controls Team
Reconciliation
Relational
Database
Data Controls
ERP
Email Alerts
Compliance
Teams
Monitoring
XML
Message
Queues
Reporting
Internal Audit
Freeform
Reports
Analytics
Management
Analytics
Binary
Data from
Apps
3rd Party
Controls
Finance Teams
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 Analytics
Prescription: 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 Analytics
Prescription: 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 Analytics
Prescription: 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 Analytics
Prescription: 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
Driving Risk & Opportunity Outcomes
Usage
Customer
Onboarding
Risk/Opportunity
Usage Risk
Customers
Acquisition
Up-Sell
Cross
Sell
Churn
Revenue
Bad Debt
Retention
/Risk
Collect
/Retain
Operations
Analytics + Controls + Visibility
Review
Statements
Billing
Process
Settlements &
Payments
Credits/
Vouchers
Reporting
Financial
Regulatory
Compliance
Driving Outcomes with Rules & Analytics
Exception Management
Process
Controls
Data Quality
Controls
Advanced Visualization
Statistical
Analytics
High Volume (Big Data) Sources
Predictive
Analytics
Real Time Feeds
Prescriptive
Analytics
Cloud
Data Governance Coverage
Executives
Data
Generation
Analytics/
Outcomes
Operations
How Do You Do Data Governance?
Priorities
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Set organization-wide, clear business objectives
Align data needs and governance with the achievement
of these objectives
People
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Obtain executive sponsorship
Align operational management
Create cross-functional teams (business and IT)
Process
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End-to-end
Data domain mapping, MDM, EDM, Process modeling,
Risk Analysis
Controls, Monitoring, Analytics, Operationalization
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
Putting It All Together
Questions?