Data Driven Insight: The Power of Business Analytics

Data-Driven Insight: The
Power of Business
Analytics
David M. Wallace
Global Financial Services Marketing Manager
SAS

Copyright © 2011, SAS Institute Inc. All rights reserved.

Agenda

 Introduction: The Economy and Credit Unions
 The Case for Business Analytics
 Succeeding with Business Analytics
 Getting Started with Business Analytics

2


The Economy: Where Are We Heading?
2.3%

2.0%

Source: The Wall Street Journal, Economic Forecasting Survey, June 2012. n = 53 3


Copyright © 2012, SAS Institute Inc. All rights reserved. 1

The Economy: Where Are We Heading?
.85%

7.9%

Source: The Wall Street Journal, Economic Forecasting Survey, June 2012. n = 53 4


Credit Unions: Where Are We Now?

Q1 Loan Originations Up 24.7% to $72.5B
Credit Unions First Mortgage Market Share 3rd at 8.2%
Core Deposits Growing at Double Digit Pace 1

Source: Callahan & Associates, 1st Quarter Trendwatch, May 2012 1 Regular shares up 11.9%; share drafts up 16.2% YTD 2012 vs. 2011 5


Credit Union Challenges

 Regulatory requirements
 Risk management and fraud prevention
 Changing member preferences
 Financially stressed member base
 Consistency of member experience
 Improving operational efficiency

Source: Nicole Sturgill, CEB TowerGroup, May 2012 6



Member Experience is Priority One

Source: Forrester Research, The Customer Experience Index, 2012, January 2012 7


Measuring Member Experience

Source: Forrester Research, The Customer Experience Index, 2012, January 2012 8


Forrester Customer Satisfaction Index –
Good News for Credit Unions!
CXi Score
USAA (bank) 89
USAA (credit card provider) 84
Any other credit union* 83
USAA (insurance provider) 83
Any other regional or local bank 80
Morgan Stanley Smith Barney 77
ING Direct 77
BB&T 77
Discover 77
Fifth Third Bank 77
70 75 80 85 90
Source: Forrester Research, The Customer Experience Index, 2012, January 2012
* No specific credit unions were identified in survey 9



The Case for Business Analytics

10


Defining Business Analytics

“…the broad use of data and quantitative analysis for
decision-making within organizations. It encompasses
query and reporting, but aspires to greater levels of
mathematical sophistication. It includes analytics, of
course, but involves harnessing them to meet defined
business objectives. Business analytics empowers
people in the organization to make better decisions,
improve processes and achieve desired outcomes. It
brings together the best of data management, analytic
methods, and the presentation of results—all in a
closed-loop cycle for continuous learning and
improvement.”

Source: Thomas H. Davenport, The New World of Business Analytics, March, 2010 11


What Exactly is Business Analytics
and How Can It Help?
“Business analytics is, simply put, the application of
analytical techniques to resolve business issues. It
provides organizations with a framework for decision
making, helping organizations solve complex business
problems, improve performance, drive sustainable
growth through innovation, anticipate and plan for
change while managing and balancing risk.”

“If you break it down it’s all about enabling effective
decision making.”

Source: Jim Davis, Business analytics: helping you put an informed foot forward, April, 2010 12



5 Stages of Analytical Maturity

Source: Thomas H. Davenport, Competing on Analytics 13


Business Analytics vs. Business Intelligence

Business Intelligence

Business Analytics

14




Business Analytics

What happened?

What will happen next?

15





Business Analytics

What happened?

What will happen next?

Reactive Decision Making

Proactive Decision Making

16


Companies are looking to business analytics
to help solve big issues

Source: Bloomberg Business Week, The Current State of Business Analytics: Where Do We Go From Here? August 2011. n = 930. 17


Which of the following would you consider to be
business analytics capabilities/tools?




Which of the following describes the use of
business analytics across your organization?



Companies are still turning the corner on
analytics investments



Business Analytics Functions and Tools
Functions Very Effective Users Other Companies
Strategy/Planning 78% 55%
Finance 69% 49%
Marketing 68% 48%
Sales 64% 44%
Information Technology/Management 64% 48%
Operations/Supply Chain Management 60% 41%
Product Development 57% 34%
Customer Service/Support 54% 37%
Human Resources 40% 29%

Tools Very Effective Users Other Companies
Spreadsheets 74% 59%
Business reporting/KPIs/dashboards 72% 52%
Forecasting 71% 50%
Query and Analysis 57% 35%
General statistics 53% 37%
Data/Text Mining 50% 36%
Simulations and scenario development 46% 27%
Model management 43% 24%
Optimization 43% 24%
Web analytics 34% 23%
Interactive data visualization 31% 15%
Social media analytics 22% 21%
Text/audio/video analytics 16% 12%
None of the above 1% 2%

Source: Bloomberg Business Week, Making Business Analytics Work: Lessons from Effective Analytics Users, May 2012. n = 930. 21



Business Analytics Reliance and
Effectiveness



Ready Access to Data and Analytics Tools



Executive Buy-in and Positive Impact




The What and the How

Succeeding with Business Analytics

25


Managing and Integrating Data

 What – data from core and operational systems
 FIS, Fiserv, Harland, Jack Henry, Open Solutions, etc.
 The gap
 Repository needed to assemble/integrate data for BI, reporting
and analytics
 How – use pre-built industry data model as repository of
key data from core systems
 Use as integration hub for analytics and reporting
 Included data integration/data quality tools for reliable data

26


Industry Data Model

Analytical
Financial Financial Financial Banking Insurance Customer
Models &
Products Instruments Accounts Accounts Accounts Intelligence
Scoring

SAS Detail Data Store for Banking – Single Version of the Truth

Risk Factors
Operational Financial Financial Risk Financial Risk Factors Market Data
& Model
Loss Events Parties Reporting Mitigants Positions & Models & Quotes
Assessment

27



Integrating Data for Analytics and Reporting

28


Executive Dashboard

29


Growing Members & Member Relationships

 What – need to grow and retain members; grow member
relationships
 The Gap – which members, what channel(s), gathering
non-members
 How – evolving to analytically driven marketing
 More relationships with current members
 Reach through multiple channels
 Members  your advocates through social media
 New members

30



Evolution of Financial Services Marketing
Expectation
Expectation
Deliver a consistent
Integrated, multi-
positive member
channel in/outbound
experience across
conversations in real-
the credit union
time
The Marketing
Campaign
The
The Member
Brand Experience

Responsibilities
Expectation
Sustain brand
health in a rapidly Insights
changing virtual
world and
Analytics

Expectation
Unearth and dynamically
manage insights to drive
action
31


Financial Services Marketing Best Practices

Strategic Segmentation Campaign Execution
 Analytical and Operational  Collaborative Marketing
Profiling
 Channel Coordination
 Predictive and Analytical
Modeling  Coordinate Inbound and
Outbound Marketing
 Member State Changes
 Decision Optimization
 Event Triggering
 Marketing Campaign
 Real-Time Decisioning Optimization

Source: BAI Research, The New Dynamics of Consumer Banking Relationships: Segment-Driven Perspectives, April 2012
32


Segmentation: Starting Point for the Member
Engagement Strategy

Member Segmentation

Drives

Initiatives

Enables

Member
Insight
Capabilities

33



Driving Results Through Segmentation
Who are our
targeted member
groups?

What are their key
Which treatments
characteristics &
offers to present Member Strategy
value
to each segment?
propositions?

Who are our most
valuable member
segments?

Key Outputs
• Differentiate members based on segments
• Segment treatment strategies
• Marketing optimization (based on resources)
34


Refreshing Member Segmentation
Member Data Sources

Existing Member Existing Member Existing Member
Segment 1 Segment 2 Segment 3

Analytical Segmentation

Marginalized Disengaged Satisfied Sophisticated Struggling
Middles Skeptics Traditionalists Opportunists Techies

Campaigns, Offers, Interactions

Segment names from: BAI Research, The New Dynamics of Consumer Banking Relationships: Segment-Driven Perspectives, April 2012. 35


Member Insight Analytics

36



Improving Member Experience

 What – monitor behavior on CU web sites; monitor
comments from social media
 The gap – internal & external data needs to be
integrated to get true picture of member experience
 The how – customer experience analytics; social media
analytics

37


Customer Experience Analytics

38


Social Media Key Performance Indicators
Ways to filter data Historic volume reports with sentiment

Hashtag listing (sort by columns)

Detailed Sentiment by Type, Source, and Site.

Data is compared against historical trend lines, using
statistical rules and predefined business rules to understand
if the movement is significant and relevant to the business.
Top Sites by volume (sort by type) Drill to document detail is available throughout this portal.
39

SAS Proprietary & Confidential Copyright © 2011, SAS Institute Inc. All rights reserved.


Real Time Twitter Analysis Intra-day volume reports with sentiment
Multiple tabs for each unique Twitter query

Tweet Report (sort by columns)

Real Time look into Twitterverse “buzz”
around a certain topic
40
Signifies Twitter handle

SAS Proprietary & Confidential Copyright © 2011, SAS Institute Inc. All rights reserved.

Analyzing Credit Union Performance

 What – bringing data together for KPIs and dashboards;
doing advanced analytical analysis
 The gap – how to get started?
 The how –CU dashboard, office analytics, rapid
predictive modeler

41


Office Analytics

42



Predictive Modeling for Business Analysts

43


Credit Union Dashboards

44



45




46


Getting Started with Business
Analytics

47


10 Practical Steps for Making Analytics Work

1. Expand the use of business 6. Deploy the necessary
analytics where feasible. analytical technology.
2. Integrate analytics across 7. Develop formal data-
the organization. management processes.
3. Deploy analytics on specific 8. Secure executive support.
business tasks.
9. Deliver and communicate
4. Use a variety of analytics value.
tools, including more
sophisticated ones. 10. Hire and develop the right
analytical talent.
5. Create a data-management
strategy that includes ready
access to data.




Establishing a Solid Foundation for
Analytics
 Get executive buy-in
 Essential to success
 Use a pilot to demonstrate the benefits
 Establish an analytics culture
 Show skeptics how analytics translates to business decisions
 Tie analytical outcomes to strategic business issues
 Identify your analytical talent
 Who can pose analytical questions?
 Who has the desire to move from “amateur” to “semi-pro”
 Tap into the right tools

Source: IT Business Edge, You’re Never Too Small for Business Analytics, September 2011
49


4 Keys to Analytical Talent

1. Put talent before technology
 Maximize analytics tool investments by getting talent in place
first
2. Emphasize “soft” skills in addition to technical skills
 Critical thinking and problem solving capabilities
 “ability to deal with the world through an analytical lens”
3. Invest in ongoing staff development
 Training existing employees  creating a fact-based decision
culture
4. Be creative when looking outside for new talent
 Go beyond traditional areas (examples: engineering, math)
 Partner with local universities; tap provider resources
Source: Bank Systems & Technology, 4 Keys to Building an Analytical Workforce, February 2012 50


What to look for in a business analytics
solution
 Robust visualization
 Support for advanced analytics
 Prebuilt analytical models and task support
 Suited for range of users
 Ease of use
 Balance of user autonomy and IT control
 Modular
 Fully integrated
 Availability of training and technical support
 Low total cost of ownership

Source: IT Business Edge, You’re Never Too Small for Business Analytics, September 2011
51



In Summary

52


Thank You!
David.M.Wallace@sas.com


Resources
 Business analytics: helping you put an informed foot forward (included in Business Analytics Insights). Jim Davis.
Available from SAS*.
 The New World of Business Analytics. Thomas H. Davenport. Available from SAS*.
 The Current State of Business Analytics: Where Do We Go From Here? Bloomberg Business Week. Available from
SAS*.
 Making Business Analytics Work: Lessons from Effective Analytics Users. Bloomberg Business Week. Available from
SAS*.
 The New Dynamics of Consumer Banking Relationships: Segment-Driven Perspectives. BAI Research. Available from
SAS*.
 Driving Profitable Growth for Marketers series. Available from SAS*.
 Part One – The Thought Leader Perspective
 Part Two – The Practitioner Perspective
 Part Three – Technologies Available to Marketers
 Part Four – Best Practices and Lessons Learned from Marketers
 4 Keys to Building an Analytical Workforce. Bank Systems & Technology, February 2012.
 Fuel Marketing Effectiveness with Customer Analytics. Available from SAS*.
 Getting Your Money’s Worth with Analytics. Available from SAS*.
 Redefining Customer Value: Corporate Strategies for the Social Web. Economist Intelligence Unit. Available from SAS*.
 Five Ways to Drive More Profitable Marketing. Available from SAS*.
 You’re Never Too Small for Business Analytics. IT Business Edge. Available from SAS*.
 Big Data Meets Big Data Analytics. Available from SAS*.
 Banking on Analytics: How High-Performance Analytics Tackle Big Data Challenges in Banking. Available from SAS*.
 The Power of Personalizing the Customer Experience. Available from SAS*.
 Analytics 101. Available from SAS*. * Free registration 54



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