Weitere ähnliche Inhalte Ähnlich wie 201208 NAMIC Operations: Analytics: A Cross-Functional Solution to Information Overload (20) Mehr von Steven Callahan (20) Kürzlich hochgeladen (20) 201208 NAMIC Operations: Analytics: A Cross-Functional Solution to Information Overload1. Analytics: A Cross-Functional
Solution to Information Overload
Presented to:
2012 NAMIC Operations Seminar
Charleston, S.C.
August 23, 2012
Presented by:
Steve Callahan, CMC
Practice Director
Robert E. Nolan Company
2. Today’s Discussion
Why Analytics
Recent Survey Results
Case Studies
Final Thoughts
Questions
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 2
3. Analytics One of Top 5 Technology Topics
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 3
4. How Do the Top 5 Compare Today
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 4
5. Business Results Driven Priorities
Admin / Legacy System Functional, Flexible, Supportable, Reliable
Analytics / BI Optimal Information Driven Decisions
Mobile Computing Service Delivered in Customer’s Hands
Big Data Incorporate All Data into Decisions
Cloud Computing Evaluate Universal Access / Variable Cost
Most Companies Have or Are Addressing Legacy Systems
Next Step is Analyzing Discrete Data and Focusing Decisions
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 5
6. 2011 Survey: Most Decisions Rely on Experience and “Gut”
82% 60%
Robert E Nolan Company Executive Survey, 2011 6Robert E. Nolan Company
©
| Page 6
Analytics: A Cross-Functional Solution to Information Overload
June 2012
7. Retrospective Based on Experience versus Predictive
MY REAL-TIME
ANALYSIS TELLS ME
IT’S SMOOTH SAILING
7Robert E. Nolan Company
©
| Page 7
June 2012
8. More Informed Decisions Improves ROI
IDC Research
Leveraging the Foundations of Wisdom:
The Financial Impact of Business Analytics (© IDC) showed
30% tremendous
25% gains –
20% 10 Years Ago
15% (2002)
10% Median ROI:
5% Predictive: 145%
NonPredictive 89%
0%
1-50% 51-100% 101-500% 501-1000% >1,000%
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 8
9. 2011 Survey: Leadership Decisions Moving To Data Driven
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 9
10. 2011 Survey: Analytics Used Across Wider Variety of Areas
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 10
11. Analytics Capability Maturity Evolution
5
Tools and data rapidly evolving
Most 4 Continuous improvement loop
Companies
Here 3 Direct Link to Decision Making
Applied Across the Organization
Advanced Analytics Tools
2
Integrated Data
Limited Link to Decision Making
1 QA Standards Applied
Basic Analytical Tools
Limited Data Integration
Basic Data
Minimal QA
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 11
12. A Different View: From Reporting to Data Innovation
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 12
13. Relative Adoption by LOB
25.00%
20.00%
15.00%
10.00%
Predictive
5.00%
Retrospective
0.00%
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 13
14. Top Line Revenue is Improved As Well
Carriers effectively using predictive analytics achieved:
•1% improvement in profit margin
•6% improvement in year on year customer retention
Carriers not fully using predictive analytics:
•Dropped 2% in profit margins
•Decreased 1% in year on year customer retention
Higher on the Capability Maturity Curve = Better Results:
•Top 20% : 27% Year on Year Growth in Revenue
•Middle 50% : 12% Year on Year Growth in Revenue
•Bottom 30% : 1% Year on Year Growth in Revenue
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 14
15. Summary Key Benefits of Analytics
Gain deeper, more relevant business insights to inform decisions
Bring predictive analysis and regression modeling to entire organization
Use analytics to identify and determine options for industry challenges
Effectively and proactively manage risks
Strengthen data governance at each level of the organization
Reduce costs through more accurate, data-driven decision-making
Use analytic capabilities and outcomes for change management
Create a culture that thrives on fact-based decisions versus “gut”
Analytics: A Cross-Functional Solution to Information Overload © 15
Robert E. Nolan Company | Page 15
16. Yet Companies Struggle to Implement
Most frequent reasons companies struggle with analytic initiatives:
•Too much management, not enough leadership
•Limited support and buy-in at multiple levels within the organization
•No guiding purpose or vision for people to rally around
•Overemphasis on technology implementation/success criteria
•Business benefits are too fuzzy to articulate and communicate clearly
•No consistent communication or messaging to stakeholders
•Poor identification of stakeholders and influencing factors
•Compensation structures and incentives not aligned
Robert E Nolan Company Executive Survey, 2011 © 16
Robert E. Nolan Company | Page 16
Analytics: A Cross-Functional Solution to Information Overload
June 2012
17. And the Barriers Are Diverse
Survey Comments on Barriers to Growth in Use of Analytics
“Resistance comes from most experienced, those requiring 100% accuracy”
“Access to critical data that is not captured in the system but is on paper”
“Getting away from tribalism, managing by anecdote and subjective decisions”
“Availability of resources and the money necessary to do it right”
“Data is spread all over and difficult to integrate or consolidate”
“Privacy will become a major issue as external data sources drive decisions”
Robert E Nolan Company Executive Survey, 2011 © 17
Robert E. Nolan Company | Page 17
Analytics: A Cross-Functional Solution to Information Overload
June 2012
18. With Opinions Varying Greatly
“The importance placed on analytics will grow, however there will be
a disproportionate reliance placed on results, until management
learns that garbage in/garbage out continues to cast its shadow.“
“It really doesn’t matter as most data currently produced comprises
the basis for most uses necessary. Advanced techniques do not
therefore produce ‘advanced’ data - the numbers are the numbers
no matter how produced. Indeed, give me a room full of ladies in
green eyeshades and Marchant calculators and maybe a punch
card reader or two and I could be perfectly happy with managing
the business, no matter how complex.“
“Those companies that do not embrace technology and analytics will
be left behind in the dust of those companies that do. “
Analytics: A Cross-Functional Solution to Information Overload
©
Robert E. Nolan Company | Page 18
19. Common Barriers to Using Analytics
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 19
20. Analytics is One Tool in the
Retroactive
Entire Product Life Cycle Production
Research Operations
Internal and
Feedback
External Data Predictive
Acquisition and Analysis
Cleansing
A clear but specific Exception
Conversion and
Formatting
vision enables a Handling and
Workflow
manageable project
Rule and Rate
Client and
Account Centric
structure with iterative Automation and
Integration deliveries. Enforcement
Population External Data
Analysis and Acquisition
Segmentation
Product Development & Assembly
Underwriting Rule and Rate Product / Forms Rule and Rate
Pattern and Data Rate Design and
Rules Design Model Prediction Creation Production
Analysis Modeling
and Modeling and Optimization and Assembly Roll Out
Iterative Process
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 20
21. Transforming Product Development
Improved use of analytics can be organized so that the key plan
areas can be developed along three parallel tracks.
Data Production
Product Processing
Evaluation
Development Integration
and Analysis
Current Data Modeling and Rates and Rules
Evaluation Analytic Tools Integration
Data Cleansing and Rules Engines Predictive Analysis
Alignment Rating Engines Models
Market Segmentation Product Workflow and
Assembly
Analysis Exception Process
Process
External Data Legacy Integration
Integration and
Aggregation Management “Dashboard”
Trend Analysis Tools Performance Development
and
and Modeling Scalability
Analytics: A Cross-Functional Solution to Information Overload
©
Robert E. Nolan Company | Page 21
22. Case Study A: Prospect Scoring
Scoring of prospects based on conversion and
Psycho- value, marketing strategy developed to match
graphic
Data Potential Value
Text High value, High value, High value,
Low Medium High
Data conversion, conversion, conversion,
2nd Priority Top Priority Top priority
Predictive Potential Good value, Good value, Good value,
Web Analysis Future Low Medium High
Log conversion, conversion, conversion,
and Value of Low Priority 2nd Priority Top Priority
Data Modeling Customer
Low value, Low value, Low value,
Low Medium High
Survey conversion, conversion, conversion,
Data Low Priority Low Priority 2nd Priority
Purchased Low Medium High
Data Propensity to Convert
Analytics: A Cross-Functional Solution to Information Overload
©
Robert E. Nolan Company | Page 22
23. Case Study B: Agency Management
60% of customers would switch carriers if so advised by their agent.
(Source: JD Power & Associates)
33%+ of agents are likely to change insurance carriers.
(Source: National Underwriter and Deloitte)
Insurers better manage their agents achieve competitive advantage.
New customers have high acquisition costs, retaining one more profitable.
New agents have high acquisition expenses and pose a greater risk of
inferior retention rates, resulting in lower profits.
Monitoring effectiveness of agents provide early warning that an agent may
be about to leave, triggering action and market differentiation.
Predictive scorecards tie traditional features like traffic lights and
speedometers to powerful analytics.
Dashboard visuals provided at-a-glance access to the current status of new
KPIs, with automatic alerts for underperforming objectives and strategies.
Implemented an agency dashboard based on new KPI’s that were
modeled with a predictive analytics tool.
Analytics: A Cross-Functional Solution to Information Overload 23
©
Robert E. Nolan Company | Page 23
June 2012
24. Case Study B: Agency Management
© 24
Robert E. Nolan Company | Page 24
Analytics: A Cross-Functional Solution to Information Overload
25. Case Study C: Loss based Pricing
Territory average loss ratios
generate prices that are too high
for some and too low for others.
$812.50
Detailed risk
$438.00 analytics generate
more accurate loss
cost estimates by
$1187.00
discrete segments
of business.
Result: More equitable and competitive risk adjusted pricing.
ISO Price Analyzer Tool used for graphics
© 25
Robert E. Nolan Company | Page 25
Analytics: A Cross-Functional Solution to Information Overload
26. Case Study D: Retention Strategies
Step 1: Determine Life time Value
Post Purchase
Activity –
Increases in Future
predictive value Value
over time as
behavioral
patterns
develop
Predictive
Analysis
Customer behavior
shifts focus from
Time of current to future
Purchase value
Demographics Current
-Loses predictive Value
value over time
as relevance is
superseded by
inforce behaviors 26
Robert E. Nolan Company | Page 26
©
Analytics: A Cross-Functional Solution to Information Overload
27. Case Study D: Retention Strategies
Step 2: Predict Potential Lapse
Source of Business
influences lapse tendencies
based on channel behaviors
Predictive
Analysis –
Model
Channel
Transaction behavior and
influences lapse tendencies
per consumer behaviors Consumer
Behaviors
© 27
Robert E. Nolan Company | Page 27
Analytics: A Cross-Functional Solution to Information Overload
28. Case Study D: Retention Strategies
Step 3: Develop Strategy Matrix
Match effort to
risk and value –
•High value low
risk gets medium
effort, save money
on retaining low
risk customers
•Low value
customers get low
cost efforts
across the board
•Targeted high
efforts on high
value / high risk
© 28
Robert E. Nolan Company | Page 28
Analytics: A Cross-Functional Solution to Information Overload
29. Case Study E: Claims Fraud
• About 10% of all insurance claims are fraudulent.
• Annual fraud losses for P&C industry total $30B in US alone.
• Need to detect unknown patterns of financial fraud.
• Keep track of new fraud schemes.
• Unsure exactly what to look for.
• Rules: Captures fraud on known patterns previously used
Ex: Two claims in different time zones within short window
• Anomaly Detection: Detect unknown patterns (ind & aggr)
Ex: Statistics (mean, std dev, uni/multivariates, regression)
• Advanced Analytics: Detect complex patterns
Ex: Knowledge discovery, data mining, predictive assessment
• Social Network Analytics: Determine associative links
Ex: Knowledge discovery via associative link analysis (entity
map)
Analytics: A Cross-Functional Solution to Information Overload
©
Robert E. Nolan Company | Page 29
30. Automated Fraud Detection Points
Re-estimate duration
Prioritized investigation SIU Reassess loss reserving
Focus on organized Prioritize resources
fraud Fraudulent rescoring
Minimize claim padding Review litigation
Reduce false positives propensity
Fraud Referrals Fraud Referrals
FNOL Assign Evaluate Update Close
Claim Claim Claim Claim
Fast Track
Predict duration Claim Cross-sell options for
Forecast loss reserves Negotiate / satisfied customer
Customer retention
Optimize fast track Initiate
claims
Prioritize resources Services Identify salvage and
Fraudulent scoring subrogation opportunities
Initiate Indicate deviations
Litigation propensity Reports on overrides
Settleme
© 30
Robert E. Nolan Company | Page 30
Analytics: A Cross-Functional Solution to Information Overload
nt
31. Claims Analytics:
Fraud Red Flag Dashboard
Analytics: A Cross-Functional Solution to Information OverloadCourtesy of Attensity © 31
Robert E. Nolan Company | Page 31
June 2012
32. Other Brief Claims Examples
Optimized Claims Adjudication process.
Using data mining to cluster and group claims by loss characteristics
(such as loss type, location and time of loss, etc.).
Claims scored, prioritized and assigned by experience and loss type.
Higher quality, more consistent, and faster claims handling.
Adjuster Effectiveness Measurement.
Adjusters typically evaluated based on an open/closed claims ratio.
Analytics create key performance indicator (KPI) reports based on
customer satisfaction, overridden settlements and other metrics.
Claims using attorneys often 2X settlement and expenses.
Analytics help determine which claims are likely to result in litigation.
Assign to senior adjusters to settle sooner and for lower amounts.
Analytics: A Cross-Functional Solution to Information Overload 32
©
Robert E. Nolan Company | Page 32
33. Case Study G:
Life Underwriting via App + Social Data
Second child born last year Actively
High investment risk tolerance pursue for
Lived in home 2 years issuance of a
Owns home preferred
Commuting distance 1 mile policy without
Reads Design and Travel Magazines requiring
Urban single cluster fluids or
Premium bank card medical
Good financial indicators records.
Active lifestyle: Run, Bike, Tennis, Use strong
Aerobics
Health food choices retention
Little to no television consumption tactics.
Life UW using a GLM predictive model to assess risk:
Use info on app plus social data, No fluids or files
Integrate 3rd party publicly available information.
© 33
Robert E. Nolan Company | Page 33
Analytics: A Cross-Functional Solution to Information Overload
34. Case Study:
Life Underwriting via App + Social Data
Current residence four years Do not send
Lived in same hometown 15 years offers. Do not
Currently renting pursue
Commuting distance 45 miles
Works as administrative assistant aggressive
Divorced with no children retention
Foreclosure/bankruptcy indicators strategies. If
Avid book reader applies,
Fast food purchaser pursue
Purchases diet, weight loss equipment additional
Walks for health medical
High television consumption records and
Low regional economic growth
tests.
Light wine drinker
In a test over 30,000 applicants, behavioral and lifestyle
factors provided 37% of the risk assessment influence and
performed as well as additional, more intrusive medical
tests and fluids.
Analytics: A Cross-Functional Solution to Information Overload
©
Robert E. Nolan Company | Page 34
35. Types of third party marketing data
Deloitte Predictive Model for Life
© 35
Robert E. Nolan Company | Page 35
Analytics: A Cross-Functional Solution to Information Overload
36. Life Underwriting Savings:
Using 3rd Party Data versus Medical Data
Deloitte Predictive Model for
Life © 36
Robert E. Nolan Company | Page 36
Analytics: A Cross-Functional Solution to Information Overload
37. Workers Comp already has a track
record of using Social Data
© 37
Robert E. Nolan Company | Page 37
Analytics: A Cross-Functional Solution to Information Overload
38. Social Analytics:
Customer Engagement Dashboard
Automatically monitor
social conversations
Filter out irrelevant
posts
Analyze posts to extract
key insights
Engage customers with
proactive outreach
Improve experience
customers are having
on the site
Improve brand image
and emphasize
business legitimacy
Analytics: A Cross-Functional Solution to Information Overload © 38
Robert E. Nolan Company | Page 38
39. Social Analytics:
Conversation Sentiment Tracking
Courtesy of Attensity
Analytics: A Cross-Functional Solution to Information Overload © 39
Robert E. Nolan Company | Page 39
40. Social Analytics:
Website Sentiment by LOB
Courtesy of Attensity
Analytics: A Cross-Functional Solution to Information Overload © 40
Robert E. Nolan Company | Page 40
41. Available Third Party Data is Extensive
Third party marketing datasets are often used to develop the predictive
models, they include over 3,000 fields of data, contain no PHI, are not
subject to FCRA requirements, and do not require signature authority.
The match rate with insured’s is typically around 95% based only on
name and address. Third party marketing data includes:
Survey Data:
•Self-reported information
Rewards programs •Contains many lifestyle elements
Magazine subscriptions Basic demographics
Email lists •Age, sex, number & ages of kids, marital
Websites status
Grocery store cards •Occupation categories, education level
Book store cards Financial information
Public records •Income level, net worth, savings, investments
•Home value, mortgage value, credit card info
Lifestyle data
•Activity: running, golf, tennis, biking, hiking,
etc. Robert E. Nolan Company | Page 41
©
•Inactivity: TV, computers, video games,
42. Social Analytics:
Overall Sentiment Ratings Dashboard
Analytics: A Cross-Functional Solution to Information Overload © 42
Robert E. Nolan Company | Page 42
43. Social Analytics:
Competitive Sentiment Dashboard
Courtesy of Attensity © 43
Robert E. Nolan Company | Page 43
Analytics: A Cross-Functional Solution to Information Overload
June 2012
44. Closing Notes: Bloomberg Qualitative Research Findings
Analytics rapidly advancing past “emerging stage”
Organizations proceeding cautiously in adoption
Business experience driving factor in decision making
Analytics for big issues, focus on improving bottom line
Key adoption challenges:
– Data quality, acquisition, integration
– Many carriers lack proper analytical talent
– Culture critical
– Executive sponsorship key
– Start small, work big
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 44
45. 3 Guidelines to Implementing Analytics
1. Have executive sponsored roadmap clearly outlining:
What resources will be needed for how long,
Where and when predictive analytics will be used,
Which tools will be used, and
How will success be measured.
1. Use data that is comprehensive, accurate, and current.
Not necessarily 100%, some have used only 70%.
Must be representative.
§ Staff with talented and engaged people.
1. Completely understand business problem, proficient with analytics.
2. Every person does not have to meet both qualification.
3. A team can be used with some business and some analytics experts.
Analytics: A Cross-Functional Solution to Information Overload 45
©
Robert E. Nolan Company | Page 45
June 2012
46. Questions?
Thank You...
Steve Callahan, CMC
Practice Director
steve_callahan@renolan.com
www.linkedin.com/in/stevenmcallahan
@stevenmcallahan
(206) 619-7740
Analytics: A Cross-Functional Solution to Information Overload ©
Robert E. Nolan Company | Page 46