Practical Methods that Convert Data to Dollars™

1. Analytics in Financial Services:
Practical Methods that Convert Data to Dollars™
Jaime Fitzgerald -- Founder and Managing Partner,
Fitzgerald Analytics, Inc.
Architects of Fact-Based Decisions™
August 18th, 2011

2. “If You Like to Tweet…”
Event Hashtag: #FSIUG
Symposium Collaborators
#FSIUG @AdelphiU @Oracle
My Team
@JaimeFitzgerald @fitzanalytics @Data2Dollars
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3. Presentation Outline
1. Quick Intro
2. The Challenge
 Business Challenges
 Challenges in Addressing via Analytics
3. A Methodology That Helps: Causal Clarity™
4. Application to Your Business Models
5. From Opportunities to Results
6. Key Takeaways
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4. Introduction
Jaime Fitzgerald,
Founder @ Fitzgerald Analytics
• Find & unlock opportunities
Professional
Focus: via data, technology, people,
and processes.
Key Success Easier Ways to and Better Ways to
Factors: Find Opportunities Unlock That Potential
Principles “Begin with the End in Mind” (Covey) -> Goal Definition is Key
I Work By: “Quality is Free” (McGregor) -> Process Matters
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5. Presentation Outline
1. Quick Intro
2. The Challenge ("The Gap")
 Business Challenges
 Challenges in Addressing via Analytics
3. A Methodology That Helps: Causal Clarity™
4. Application to Your Business Models
5. From Opportunities to Results
6. Key Takeaways
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6. A Challenging Time in Financial Services
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7. “Rough Seas” in Financial Services
1
The Tide is No Longer Rising
2 3
Regulatory Currents Customer Behavior Shifting
4
Risk Management has Become Über-Strategic
5
New Competitive Threats
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8. Trends and Challenges: “Rough Seas”
Five Trends Creating “Rough Seas” in the Financial Services Market
1. The Tide is No Longer Rising: with a few exceptions—most notably parts of wealth
management—growth no longer “just happens”….you have to make it happen
The Waters are Choppy -- with today’s trends, the captain can’t leave the helm!
2. Regulatory Currents: existing models and assumptions have been upended. Lots
of “re-routing” underway to protect profits and “work around” new constraints.
3. Customer Behavior Shifting: information-empowered customers are revisiting
their options, choosing in different ways, and taking advantage of more
transparency
4. Risk Management has become Über-Strategic: always essential, it has become
do-or-die, and harder than ever as the spectrum of risks and threats grows
5. New Competitive Threats. Non-traditional players are increasingly seeking to
“poach” business from incumbent players. These sharks show up suddenly,
whether from Greenwich or from the other side of the world.
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9. Overcoming the Challenges
While these challenges threaten, those who adapt to them best will profit.
Challenge A Path to Overcoming It... Key Performance Indicators
1. Tide not  Optimize profit from existing customers  Retention Rate
rising  Avoid attrition / protect customer equity  Share of Wallet
 New rules change drivers of revenue and
 Product Profitability (driven by
“revenue replacement” during product
2. Regulatory cost for our products and operations
redesign)
Changes  “Explosion of redesigns” (Products,  Risk Mgt / Controls Performance
Processes, Policies, Reporting, etc.)
 Cost Control / Efficiency
 Retention rate
3. Customer
 Adjust to new customer buying criteria  Share of wallet
Behavior
 Customer lifetime value
 Risk Mgt / Controls Performance
4. Risk Mgt  Manage high stakes risks more robustly
(varies by business model)
 Leverage sources of differentiation
5. Competitive  Share of target segments
Threats  Foster customer loyalty to reduce  Customer experience + loyalty
defection
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10. Five Profit Engines
These Five Analytically-Driven Profit Engines are Powerful Weapons as you Compete
in Today’s Environment…
Method Keys to Profit Impact
1 Customer Lifetime  Allocate resources to your most profitable customers
 Use WITH predictive analytics to INFER WHO WILL be most
Value + Segmentation profitable in the future, not just the present.
 You won’t be right all the time, and you don’t have to be
2  Identify the drivers of customer loyalty vs. defection
Customer Retention  Target high-ROI tactics to retain most valuable customers
3 Cross-Sales /  Offer customers products they are most likely to buy
Up-Sales  Choose the optimal time, method, and terms of the offer
4  Allocate marketing spend to the highest impact efforts
Marketing ROI  Use predictive models to choose best target customers,
timing, message, and channel mix
5  Adapt to new regulations, customer preferences, and costs
New Product Design  Predict in advance the costs and benefits of product changes
 Systematically test product features to find the most
profitable designs
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11. Key to Success: Integration!
Don’t Build These Engines as Silos! Connect the Dots to Magnify Impact.
1
Customer Lifetime Value + Segmentation
2 3 Cross-Sales /
Customer Retention
Up-Sales
4
Marketing ROI
5
New Product Design
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12. Customer Profitability & Segmentation Analysis
Analysis of customer-level profitability reveals valuable insights regarding the
differences between customers
Example: Use of customer profitability analysis to determine strategies
for each unique group of customers…
Illustrative
1. Retain Best Customers
3. Rationalize Benefits vs.
Profit per Customer
2. Increase Share of Wallet Among Costs Among Least
Mid-Value Customers Profitable Customers
Customer Profitability ($/year)
Loss per Customer
Top 2nd 3rd 4th 5th 6th 7th 8th 9th Bottom Average
(Most (Least
Profitable Profitable
10%) 10%)
Profitability Deciles
(each bar represents 10% of existing customers, ranked by profitability)
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13. Profitability Management Becomes More Refined Over Time
through an Iterative Process Driven by Customer Knowledge
Build Customer Profitability Models
 Identify costs & revenues Drive Action Into Frontline Systems Face-to-
• Create consistent message Face
 Build profiles  • Create consistent individuals
Target action to message
 Feed data from Data  • Target action to individuals
Optimize product / service
internal and external Warehouse portfolio Mail
sources  Optimize product/service portfolio
 Maintain data warehouses
Phone
External New Customer Knowledge Internet
Data  Feed campaign results into data
Sources warehouses
 Test predictive accuracy of model
 Break down segment into individual
customer analyses
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14. Putting it Together: Growth and Profitability
Let’s look at four segments with different profiles, starting with their growth rates,
their size, and their profitability per customer…
80%
60%
Growth Rate in # of Customers
Profitable segment: grow faster?
40% 1 Fast-Growing,
(X-sell / Up-sell)
No Profit
(Product
20% Redesign)
2
3 Acquire More via
0% Targeted Marketing
-20 -10 0 10 20 30 40 50 60 70 80 90 100 110 120
Direct Customer Profit
-20%
-40% Our Biggest
Problem: Retention 4
Size of Bubble =
-60% Number of
Customers
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15. Integration: Connecting The Dots
A few examples of how inter-related these processes are…
1
Customer Lifetime Value + Segmentation
New Information and Insights
2 3 Cross-Sales /
Customer Retention
Up-Sales
4
Marketing ROI
5
New Product Design
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16. Why are Analytics Projects Risky?
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17. Achieving the Potential of Analytics – Closing the Gap
To profit from analytics, you need results not buzz…
1. So Much “Buzz” about the Potential of Analytics
 Best-selling books on Analytics (Competing on Analytics, Supercrunchers, etc.)
 New efforts (business units, teams, roles, initiatives)
2. When Analytics Works, the Impact is Buzz-Worthy!
 Selected firms have made analytics a source of competitive advantage
 It happens every day… just not as broadly as would be ideal
1 2 3 4
Right Focus Right Method Execution Results!
Let’s discuss the keys to increasing your odds of success…
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18. Simplify Your Analytic Process via “Causal Clarity”
Clearly defining “Cause and Effect” is the most crucial enabler of analysis that is
Find
Unlock More
 Simpler Opportunity
Easily
Faster
 More Efficient Fewer Wasted Steps
 Higher Impact Benefit /Cost
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19. Three Simplifying Concepts
To “begin with the business goal in mind,” I recommend three concepts
Term Definition
1. Point of Opportunity  An opportunity for improvement within YOUR
business model
 Defined because it impacts key drivers of your
results
2. Causal Clarity
 Clear Definition of key drivers, cause + effect in
Cause Effect your business model, business unit, etc.
 Easy to Explain to others, preferably visually
3. Causal Model
 A visual representation of “what drives results” in
Price
Revenue
your business model
Transactions  Create this, and you have achieved “Causal Clarity”
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20. Causal Models: A Simple “Base Case”
Each business model has an inherent “causal model,” but the “core branches” are
similar
Example: Drivers
of Net Profit
Revenue
less
Your Has Cost of Revenue Gross Profit
Business Operating Costs
Model less Net Profit
Marketing Other Costs
Overhead
Other
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21. What Happens If We Skip the Causal Clarity?
Why not just get to work?
…We are stuck “trying” rather than causing. We
If we don’t establish a
may “try hard but cause less” than if we find the
“causal model”…
“points of leverage” in the causal model
…It’s pretty easy. It takes careful thought, but
The Good News Is…
we are not building a spaceship…
Let’s take a look at how painless — and valuable — this can be
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22. The Good News: Establishing “Causal Clarity” is Not Rocket Science
Easy and Quick: There are 3 Main Steps
1 2 3
3 Things
To Goal Business Model Causal Model
Define:
Inputs  Usually net profit  Products / services  Aka “drivers tree”
To  Can be anything!:  Distribution  Makes the causal
Use: – Marketing ROI  Target customers model visual
– Non-profit impact  At what price
– Customer  Cost structure
satisfaction  Known KPIs and
– Etc. rationale for them
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23. The “Point of Opportunity” Concept Illustrated
Has “Causal Creating
Your Business
Model” A Point of
Model
(aka Drivers) Opportunity
Returning to the causal model above on the previous slide,
let’s find a concrete point of opportunity
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24. A Point of Opportunity
Here is an opportunity to enhance ROI on Marketing + Sales efforts:
Point of Opportunity: “Efficiency of New Client Acquisition”
Key Driver / KPI: Acquisition Cost per New Client
Formula: [spending on new client marketing]/[# New Clients)
Transactions Price per
per Client Transaction
X
# of Clients Volume
Sales and
Marketing
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25. What We Need to Get Practical
To get practical about analytics, we need three things…
What We Need Definition
1. Causal Clarity re: Your  How You Make Money
Business Model  Key Drivers of Results
2. Definition of Your Points  Gaps vs. Potential
of Opportunity  Room for Improvement
3. A Plan to Capture the  Insight You Need
Opportunity  Method to Get It
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26. Planning Your Analysis
Planning starts with the goal, the “point of opportunity”
Your Point of Opportunity (Decision or Process)
Translates to
Insights or Information Required
Which drives
Analysis Methods Required to Create this Information
Allowing definition of
Required Data
And selection of the right
Tools, Platforms, Technology, People, and Processes
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27. Summary of Key Takeaways
We hope you will benefit from the concepts shared today
For All 1. Begin Your 2. Define + 3. Identify 4. Define the 5. Keep
Attendees Business Agree on Points of info needed analysis as
Model the Causal Opportunity to unlock simple as
Model the oppor- possible…
tunity
Tips By Executives Leadership
Role:  Establish “causal clarity” visually so that everyone understands
 Encourage teams to use this context to prioritize and target effort
 Expect recommendations to be justified by their impact on key drivers
Business Professionals Technology Professionals
 Identify points of opportunity  Insist upon understanding the
before investing time in analytic business context and causal logic
details of requests for analytic systems
and effort
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28. Invitation to Two Free Communities
The Practical Analytics Portal
Our Mission
This is a great place to To "democratize analytics" by
sharing knowledge and tools.
learn and network with
other professionals in Our Vision
analytics, both specific to The potential of analytics "within
Financial Services, and reach" to an exponentially larger
Beyond community of professionals.
To Join: To Join: email me
http://www.meetup.com/Analytics jfitzgerald@fitzgerald-analytics.com
-and-Data-in-Financial-Services/ for an invitation
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29. Analytics Democratized™
To Join:
Text “Analytics” to 41242
….or find us on Facebook & Twitter
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30. Q&A
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31. “Bonus Slides”
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32. Background: Types of Questions Analytics May Answer
Past Present Future
What happened? What is happening What will happen?
Information now?
(Reporting) (Alerts) (Extrapolation)
What’s the
How and why What’s the next best/worst that
did it happen? best action? can happen?
Insight
(Modeling, (Recommendation) (Prediction,
experimental optimization,
design) simulation)
We are about to get practical, let’s keep the following in mind…
Source: Tom Davenport in “Analytics at Work”, Harvard Business School Press
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33. One More Framework: Value vs. Volume
In some cases, analytics makes a single high stakes decision better. In other cases,
we “make it up in volume”
High
High-Value, Low-Volume
Value Decisions
Economic Impact of
Example: M&A, capital investment,
Individual Decision
strategic market positioning
Medium-Value, Medium-Volume
Decisions
Example: Product development and
pricing, customer segmentation, and
targeting
Low-Value, High-Volume Decisions
Example: Loan approval, customer
cross-sell offer, customer upgrade request,
prospect marketing offer assignment
Low
Value
Low Volume Decision Volume High Volume
Source: Neil Raden and James Taylor in “Smart Enough Systems,” Prentice Hall.
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34. Financial Services Business Models
To get practical, let’s establish causal clarity for several key business models in
Financial Services
Core Products / Key Drivers
Business Model
Services (illustrative)
 Customer acquisition,
 Deposit Products
1. Retail Financial retention, and profitability
 Loan Products
Services  Product pricing
 Investment Products
 Share of wallet
2. Commercial /  Debt Financing
 Fee structure / yields
 Institutional Financial Services
Business Banking /  Volume
(e.g. for Money Managers)
Financial Services  Cost efficiencies
 Cash Management
 Proprietary trading  Risk-adjusted returns
3. Trading  Market-making  Transaction spreads
 Trade execution  Cost efficiencies
 Underwriting  Deal flow
4. Investment
 M&A  Deal completion rates
Banking  Other advisory services  Fee structure
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35. 1. Retail Financial Services Illustrative Example
Products
Point of Increase ROI on Marketing Spend 1. Deposits
Opportunity: BY Decreasing Acq. Cost / Customer*
Key Driver / KPI: Acquisition Cost per New Client 2. Investments
Formula: [spend on new client marketing]/
3. Loans
[# New Clients)
Products per Profit per
Client Product
Allocation of X
Marketing $
# of Clients Volume
*2nd Order Causality + Pt of Opportunity
* P = Profit per year per customer, n=number of years the customer stays
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36. 2. Commercial/Business Banking / FS Illustrative Example
Point of Grow Fees BY Increasing “Share of
Opportunity: Wallet” from Corporate Clients
Key Driver / KPI: Share of Wallet (“SOW”)
Formula: [Total Fees from Client]/[Total Client Fees
on Products YOU offer, via ALL providers]
Customer
Experience Share of
Optimization Marketing Wallet
Customer X
Better Outreach Loyalty
via Predictive Total Size of
Analytics Client benefit Wallet
of using your
• Everything ok? platform more The size of the
• You would benefit exclusively pie we are
from product X sharing….
* “Total Client Fees” includes spending on ALL companies that offer the same or similar products/services
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37. 3. Trading Illustrative Example
Point of
Maximize Alpha!
Opportunity:
Key Driver / KPI: Risk-Adjusted Return
Formula: Alpha
Volume: #
Trading
Trade-able
Quality of Real- Profits
Opportunities
Time Decision X Less…
Models + Tools Quality:
“Cost of
Profit per
Discovery”
Opportunity
1. Accuracy of “Triggers”
2. Cost of False Positives How “Big” are Investments in
3. How well do models these Trades Finding these
adjust to changed Opportunities
world?
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38. 4. Investment Banking Illustrative Example
Point of
Increase Profit per Employee
Opportunity:
Key Driver / KPI: Return on Human Capital (“HCROI”)
Formula: [NET Profit] / [# Employees]
Staff & Team
Profit per Gross Profit Net
Staff + Team Person-Hour Profit
Effectiveness X Less…
“Other Investments in
# Hours
Staff Performance”
1. Resource allocation
(Who does what. Why?) • Cost of analysis
2. Re-use of IP: How well do we • Cost of training
re-purpose? • Cost of new systems
3. Task Value to Cost: (e.g. knowledge mgt + workflow)
How much waste?
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