Copyright © 2009, SAS Institute Inc. All rights reserved.
Strength in
Numbers: ACE!
Predictive Analytics World
October 2009
Copyright © 2009, SAS Institute Inc. All rights reserved.
Discussion Topics
Fostering Analytic Competency & Culture
Analytics & Innovation: Best Practices (examples where an analytic view can yield better results)
Options for Analytic Bandwidth
Copyright © 2004, SAS Institute Inc. All rights reserved.
Copyright © 2009, SAS Institute Inc. All rights reserved.
What is an Analytic Center of Excellence?
A resource to facilitate use of analytics across functional and geographic areas of the enterprise.
A central point for
developing and evolving analytic infrastructure
promoting collaboration and analytic best practices
driving growth, cost reduction, and profitability
A means to support strategy and operations through objective analysis.
Fostering Analytic Competency & Culture
Copyright © 2009, SAS Institute Inc. All rights reserved.
“Change is the one constant.” -Heracleitus
Address, assess and evolve your analytic infrastructure
People
Process
Technology
Culture
Fostering Analytic Competency & Culture
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People: Optimize Use of Scarce Analytic Talent
Promote collaboration & sharing
Internal presentations
Guest speakers
Assignments to cross-pollinate and collaborate on strategic projects
Recognize specialized skills and experience
Numerically
ChallengedHighly Creative Problem
Solvers / Numerati
Fostering Analytic Competency & Culture
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Fostering Analytic Competency & Culture
Process: Assess & Evolve for Efficiency/Effectiveness
Business processes cross departmental boundaries
Limited-to-no central view, coordination or repeatability
Some analysis never done—no assigned resource or clear priorities
Manage, monitor & archive models (knowledge management)
Commit to ongoing experimentation, training learning
Measure the effectiveness of your efforts
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Fostering Analytic Competency & Culture
Technology: The easy part!
Challenges Keeping current
Knowing and assessing options
Should you take advantage of in-database analytics & scoring?
Is your analytic workbench optimized for productivity?
Do you have the capabilities to best solve old & new problems?
…
Copyright © 2009, SAS Institute Inc. All rights reserved.
Culture: Does your organization have a learning culture?How many decisions are data / analytics-driven?
How are high-risk decisions made?
How old are processes driving key decisions?
Is the answer to “Why don’t we try something new…?”
Fostering Analytic Competency & Culture
Copyright © 2009, SAS Institute Inc. All rights reserved.
Analytics & Innovation
“But we’ve always managed risk in silos…”
“The biggest failure…is the lack of consolidating individual risk models and being able to audit them.” -Dr. Sam Savage
“Incentives are a main culprit.” -Andrew Freeman, McKinsey & Co
“Effectiveness of risk management is almost never measured.” -Douglass Hubbard
No experimentally verifiable evidence that many risk management methods are effective
Some that have been measured don’t work.
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Analytics & Innovation
Ideas for Risks & Modeling Them
Consider 4 completeness perspectives
Internal
External
Historical
Combinatorial
Do a Pre-Mortem (Gary Klein)
Look to risks from others
Include everyone
Do peer reviews
“Research has shown that the extent of errors in spreadsheet calculations is
probably far beyond what most managers would like to believe.” -Douglass Hubbard
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Analytics & Innovation
“But we’ve always politicized forecasting.”Webinar Today: What Management Needs to Know About Forecasting
Table 2. Calculating Value Added at Cisco
AnalystForecast Accuracy
Naïve Accuracy
Value Added
A 75% 80% -5%B 60% 60% -
C 55% 50% 5%For further discussion of this topic, see Michael Gilliland, "Fundamental Issues in
Business Forecasting," Journal of Business Forecasting, Summer 2003
Source: Cisco
“…the analytics team can market its success and demonstrate its
competency to bring analytic insights, skills and techniques to managing
other business processes within Cisco.”
Source: Gartner RAS Core Research Note G00167426 Case Study: Cisco Improves Demand Forecast Accuracy
With Advanced Analytics, Domain Expertise and a Consensus Process, Bill Hostmann, 2 October 2009
Copyright © 2009, SAS Institute Inc. All rights reserved.
Investors had reason to smile last week. As expected, neither rising energy costs nor high short-term interest rates stopped a stream of strong second-quarter earnings news. And the Federal Reserve chairman,
Alan Greenspan, added to the cheer on Thursday, when traders interpreted his comments as a signal that the economy was slowing and that the Fed might be done raising rates, at least for a while.
That news sent the Nasdaq composite up more than 3 percent, putting it back into positive territory for the year, and the Dow industrials and Standard & Poor's 500 also rallied. So for at least one weekend, Wall
Street's biggest concern is likely to be nothing more than the weather in the Hamptons.
All in all, the picture is pretty, said Abby Joseph Cohen, chief market strategist at Goldman Sachs. With the economy slowing a bit but earnings still strong, she thinks the S.& P. 500 could hit 1,575 by the end of the
year, a 5 percent gain. ''Second-quarter numbers have been quite good,'' she said.
Agreed. But that is not the whole story. After all, the fundamentals were just as good three months ago, when the Nasdaq plunged into a sickening tailspin that pushed it from 5,000 to 3,300 in a matter of weeks,
leaving many investors bruised and some broke.
Person
PersonPublic Company
GS, NYSE
Organization
Organization
Organization
Organization
Analytics & Innovation
“But we’ve always manually tagged these documents.”
Automatic Metadata Extraction/Tagging for Better Search
Use entity extraction to better define metadata and taxonomies.
Facilitate more relevant search results.
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“But we’ve always used [method x] to model customer attrition.”
Know when not just if a customer will leave, upgrade, default…
Forecast attrition and other events of interest
Estimate future expected life-time value of customers
Prospect
Acquisition
Cost
Revenue
Generation
Servicing
Costs
X-/Up Sell
Promotion
Migration
Attrition
Prevention
Revenue & Profit
Modeling
Segmentation
Enhanced
Analytics
Targeted
Campaigns
Bad Debt…
Fraud Detection
Win-back
V
A
L
U
E
Base
Management
ACQUISITION CONVERSIONVALUE
ENHANCEMENTRETENTION RE-ACTIVATION
LIFE CYCLE
Less Profitable Lifecycle
Profitable Lifecycle
Analytics & Innovation
Past
Current
Potential
Copyright © 2009, SAS Institute Inc. All rights reserved.
“But we’ve always had text-heavy, tabular, tree-killing reports.”
Help the data tell the story—visually!
Put the data in context for the intended audience.
Analytics & Innovation
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Options for Analytic Bandwidth
Analytic Center of Excellence for optimal resource utilization
Optimized analytic workbench
In-database analytics & scoring
Automation where appropriate
Analytic Community expands beyond your organization
External consultancies (like many who are here!)
Proof-of-Value projects
Hosted options (with ability to transfer on-premise if desired)
Opportunities to collaborate with Academia
…
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Executive Sponsorship & Priority
Data Quality & Availability
Data (measurements) as a strategic asset
Measurement (data collection) as a process
Talent Acquisition & Management
Provide opportunities to try new things
Career paths for individual contributors
ACE Structures & Rules of Engagement
Consolidated, Coordinated, or Federated
Senior management requests projects, directs priorities
Analytic governing body manages priorities and engages others as appropriate
Measure the effectiveness of your efforts!
Other Considerations for Analytic Bandwidth
Copyright © 2009, SAS Institute Inc. All rights reserved.
Many Goals of Analysis
Explore
Explain/Describe/Clarify
Decide
Predict
Understand
Forecast
Visualize
Optimize
Minimize/Maximize
Group/cluster/segment/categorize
Allocate/distribute
SimulateDesign
Monitor
Manage Share
Estimate/approximate
Schedule
Locate
Detect
RevealBalance
Experiment/learn
PreventQuantify Substantiate
Evaluate
Manage
Formulate
Innovate Inform
Streamline/simplify/distill
Guide
PricePromote
DiscountWeight
Adjust
Defer
Recover
Suspend
Recognize
Compensate
Collaborate
SupportAugment
CoordinateRecommend
ImplementScoreDeploy
Solve
Experience is inevitable. Learning is not. -Paul J.H. Schoemaker
Discover
Act
Anticipate
Hedge
Simulate
Illuminate
Eliminate
Contain
Understand
ReduceDecide
Constrain
Justify
Model
Conserve
Limit
Recycle BetterFind
Filter
Isolate
Pinpoint
Improve
Copyright © 2009, SAS Institute Inc. All rights reserved.
Question for You
At Predictive Analytics World in February 2009
Andreas Weigend asked:
What are the bottlenecks to doing analytics at your organization?
Data Integration
Data Quality
Documentation About What the Data Mean
Mentality of Some People
Communication
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