Download - Swoc21 Feb08 Amig

SWOC DAMA 2008 Showcase atSWOC DAMA 2008 Showcase at American Modern Insurance American Modern Insurance

February 21, 2008

Showcase AgendaShowcase Agenda Background/Business Case

20 minutes Sandy Wagner

Data Warehouse – AIIM 20 minutes Latha Subramanian

Data Model – AIIM 20 minutes Duke Ganote

Information Management – AIIM20 minutes Dan Daly

Q& A – Duke/Sandy/Latha/Dan 20 minutes

American Modern InsuranceAmerican Modern InsuranceCompany BackgroundCompany Background

Founded in 1938 as a consumer finance company

Provider of highly focused, specialty insurance products

Positioned to grow into a multi-billion dollar organization

Entrepreneurial spirit & deep commitment of employees

Approximately 1200 employees country-wide, with 1000

employees in eastern Cincinnati area (Amelia)

American Modern InsuranceAmerican Modern InsuranceCompany BackgroundCompany Background

The organization believes that the strategic The organization believes that the strategic deployment of technology can help it achieve, and deployment of technology can help it achieve, and sustain, a competitive advantage. sustain, a competitive advantage.

As stated in its Operating Principles, “Our As stated in its Operating Principles, “Our investment in information technology is part of a investment in information technology is part of a carefully planned strategy to ensure that American carefully planned strategy to ensure that American Modern's company-wide infrastructure is among Modern's company-wide infrastructure is among the most advanced in the specialty insurance the most advanced in the specialty insurance industry.” industry.”

American Modern InsuranceAmerican Modern InsuranceInitiative BackgroundInitiative Background

In 2000, American Modern embarked upon long-range initiative, coined “modernLINK,”

Business and IT collaboration Business case and funding

Three prongs: Web-enable insurance transaction processing Replace aging legacy processing systems Develop a Knowledge Management architecture

American Modern InsuranceAmerican Modern InsuranceBusiness CaseBusiness Case

The anticipated returns of this business case were: 20% annual increases in directly-attributed new

business 37% of Policy and Partner Administration moved from

existing internal units directly to point of service 25% improvement in current Product Review and

Management cycle time 21% improvement in Product Filings cycle time 2% reduction in total loss ratio directly attributed to

modernLINK initiative

American Modern InsuranceAmerican Modern InsuranceBusiness CaseBusiness Case

These returns would yield a significant recurring annual benefit through additional premium, increased profit, and decreased expenses

Almost 50% of these benefits would be attained through better knowledge/data management, richer data segmentation, and improved data and risk selection

John Hayden, President and CEO, American Modern states: We must have accurate data about the risks we insure today if

we are to ever be successful in establishing The Right Rate for Every Risk we choose to insure in the future.

American Modern InsuranceAmerican Modern InsuranceKnowledge Management RoadmapKnowledge Management Roadmap Enterprise Data Model Operational Data Store Enterprise Data Warehouse Themed analytic data marts Enterprise reporting portal Metadata management Data Stewardship

American Modern InsuranceAmerican Modern InsuranceKnowledge Management ResultsKnowledge Management Results

Business users can: Make informed decisions Respond quickly to new business initiatives Create new opportunities

Business users are: Moving from data collectors to data consumers Asking “why” instead of “what”

American Modern InsuranceKnowledge Management Results

Retention – Joe David. In the last four years, we have leveraged the corporate reporting tools to develop a series of targeted strategies that have allowed us to improve retention by nearly eight points, which equates to annualized premium of nearly $60 million

Claims. Integration of 3rd party Claim data - Heather Bolyard. This one-month sample of data for one material has identified a potential indemnity reduction of $70,000.

Reserving – Gene Stetler. The new Loss Reserving data store from the Enterprise Data Warehouse has enabled process efficiencies, thus allowing us to predict our reserving needs with accuracy.

Product – Kevin Randall. The implementation of American Modern's data warehouse has been a significant part of the successful launch of the company's right rate for every risk initiative

American Modern Insurance2007 Awards and Recognition

In 2007, American Modern received two awards from Computerworld:

Laureate - The laureate status for the Enterprise Data Warehouse presented at the Carnegie Mellon Auditorium in Washington D.C – June 2007

BI Award - Best Practices in Business Intelligence in the category “Creating an Agile BI Infrastructure” presented in Las Vegas, NV – September 2007

Showcase AgendaShowcase Agenda Background/Business Case Background/Business Case

20 minutes Sandy Wagner20 minutes Sandy Wagner

Data Warehouse – AIIM Data Warehouse – AIIM 20 minutes Latha Subramanian20 minutes Latha Subramanian

Data Model – AIIM Data Model – AIIM 20 minutes Duke Ganote20 minutes Duke Ganote

Information Management – AIIMInformation Management – AIIM20 minutes Dan Daly20 minutes Dan Daly

Q& A – Duke/Sandy/Latha/Dan Q& A – Duke/Sandy/Latha/Dan 20 minutes20 minutes

Enterprise Data WarehouseEnterprise Data Warehouse

Create an implementation roadmapCreate an implementation roadmap Content scope – January 1998 thru presentContent scope – January 1998 thru present All products loaded over 5 yearsAll products loaded over 5 years

Implement “value” after each iterationImplement “value” after each iteration Loss Cost, Retention, Loss TrianglesLoss Cost, Retention, Loss Triangles

Establish Data Stewardship - 2004Establish Data Stewardship - 2004

Enterprise Data WarehouseEnterprise Data WarehouseThe data warehouse will support:

Loss Cost Analysis

RetentionAnalysis

modernLINK Reporting

ProfitabilityAnalysis

DataWarehouse

UnderwritingAnalysis

ProductPricingAnalysis

FinancialAnalysis

Data Warehouse ValueData Warehouse Value

MH

Loss Cost

SB

Loss Cost

MC

Loss CostRetention

UVRC Pricing / GLMLoss

TrianglesmodernLINK

MH PIFmLINK

vs. Legacy

Retro

StudiesMapping

Renewal

Reporting FID MSB

CAT Analysis

Cancellation

Reporting

Address

Data

Agency

Profile

Analysis

Claims

Liability

Partner

Experience

Reporting

Data Warehouse StatisticsData Warehouse Statistics

1997 policies used to seed warehouse: ~700,000

Total policies Jan 1998 thru Jun 2007

Total units Jan 1998 thru Jun 2007

Average Number of Coverages per policy: 5

Average number of policies in-force per month: 800,000

Average number of claims per month: 8,000

Data Warehouse BenefitsData Warehouse Benefits Single version of the truthSingle version of the truth

Data integrated at the lowest levelData integrated at the lowest level

High-end hardware platformHigh-end hardware platform

Codes translated to “English” termsCodes translated to “English” terms

Resolve source system problemsResolve source system problems

Data quality review and correctionData quality review and correction

Integration of external informationIntegration of external information

Data Mart ThemesData Mart Themes

modernLINK quote modernLINK quote ExposureExposure RetentionRetention ExperienceExperience Loss CostLoss Cost ClaimsClaims UnderwritingUnderwriting

Technology Enablers….Technology Enablers…. IBM RS6000 AIX processorsIBM RS6000 AIX processors

EMC data storageEMC data storage

Oracle DBMSOracle DBMS

COGNOS for reporting utilizing query, report, COGNOS for reporting utilizing query, report, mapping and analytical tools mapping and analytical tools

Websphere PortalWebsphere Portal

LDAP for single sign-onLDAP for single sign-on

Data Model Data Model Provides a common, integrated way for the Provides a common, integrated way for the

corporation to view and to communicate corporation to view and to communicate about its businessabout its business

Allows the business to drive the systemAllows the business to drive the system

Creates standard definitions/documentationCreates standard definitions/documentation

Provides structure to new development Provides structure to new development projectsprojects

Enterprise Data ModelEnterprise Data ModelPeoplePeople PlacesPlaces ThingsThings

InsuredsInsureds

OperatorsOperators

LienholderLienholderss

ClaimantsClaimants

GeographyGeography

AddressAddressQuotes/PoliciesQuotes/Policies

ClaimsClaims

Coverages Coverages

Accidents/ViolationsAccidents/Violations

Homes/VehiclesHomes/Vehicles

UW rulesUW rules

Makes/ModelsMakes/Models

Jump Start Enterprise Data ModelJump Start Enterprise Data Model

Acord Standards

Generic Model based on Insurance Industry Practices

AMIG Enterprise Data Model

TransformAMIG Specific Requirements

Integrated View: Common Data DefinitionsAcross business

Manufactured HomeSite BuiltMotorcycleMotor HomeTravel TrailerClassic AutoFIDCommercial

Data Model BenefitsData Model Benefits Foundation for:Foundation for:

modernLINK rate & quote applicationsmodernLINK rate & quote applications Data warehouse/data mart/analytic designData warehouse/data mart/analytic design mLP3 Operational Data Store (ODS) mLP3 Operational Data Store (ODS)

designdesign New projects simply add to the modelNew projects simply add to the model

Insurance scoreInsurance score Claims liabilityClaims liability

Development of data standards and a Development of data standards and a common “language”common “language”

Inmon, InitiallyInmon, Initially

Data warehouse built using Inmon Data warehouse built using Inmon approach:approach:

Source (non-

relational)

Data Warehouse(normalized)

DataMart(star)

End of month

End of month

“Corporate Information Factory Components”, W. H. Inmon http://www.inmoncif.com/view/26

ConformanceConformance

Conformed Dimensions:Conformed Dimensions:

Data Warehouse(normalized)

Loss CostDataMart

(star)

Conformed Dimensions

PricingDataMart

(star)

RetentionMart(star)

“The 38 Subsystems of ETL”, Ralph Kimball http://www.intelligententerprise.com/showArticle.jhtml?articleID=54200319

ChallengesChallenges

Multiple sourcesMultiple sources LatencyLatency StewardshipStewardship

Multiple SourcesMultiple SourcesOPPORTUNITIESOPPORTUNITIES::

Daily claims/catastrophe feedsDaily claims/catastrophe feeds

3rd party Claim data (claims cost 3rd party Claim data (claims cost standards)standards)

Huon (an new Insurance ERP)Huon (an new Insurance ERP)

Munich RE (pending merger with Munich RE (pending merger with reinsurer)reinsurer)

Multiple SourcesMultiple Sources

RESPONSESRESPONSES:: Pull dataPull data: generally from relational : generally from relational

DBMS, e.g. DB2, Informix, SQL DBMS, e.g. DB2, Informix, SQL ServerServer

Push dataPush data: generally from non-: generally from non-relational DBMS: DMS II (Unisys)relational DBMS: DMS II (Unisys)

Latency ChangesLatency Changes

OPPORTUNITYOPPORTUNITY: Daily information: Daily information

Catastrophe reporting; e.g. Hurricane Catastrophe reporting; e.g. Hurricane Katrina 2005, “Fab Four” of 2004Katrina 2005, “Fab Four” of 2004

Financial Institutions requesting daily Financial Institutions requesting daily account information on insureds.account information on insureds.


Source (OLTP)

CATastropheDataMart

(star)StagingArea

daily daily

Daily Conformed Dimensions

dailydaily

RESPONSERESPONSE: Kimball architecture: Kimball architecture

“Kimball Design Tip #34: You Don’t Need an EDW”, Ralph Kimball http://www.kimballgroup.com/html/designtipsPDF/DesignTips2002/KimballDT34YouDontNeed.pdf


Kimball ArchitectureKimball Architecture““The staging area is exactly like the kitchen in a The staging area is exactly like the kitchen in a

restaurant. The kitchen is a busy, even dangerous, restaurant. The kitchen is a busy, even dangerous, place filled with sharp knives and hot liquids. The place filled with sharp knives and hot liquids. The cooks are busy, focused on the task of preparing the cooks are busy, focused on the task of preparing the food. It just isn't appropriate to allow diners into a food. It just isn't appropriate to allow diners into a professional kitchen or allow the cooks to be professional kitchen or allow the cooks to be distracted with the very separate issues of the fine distracted with the very separate issues of the fine dining experience. ”dining experience. ”

Two Powerful Ideas: foundations for modern data warehousing, Ralph Kimball Sept 17, 2002: http://www.intelligententerprise.com/020917/515warehouse1_1.jhtml

Data StewardshipData Stewardship

OPPORTUNITYOPPORTUNITY: : Daily instead of monthly reference data Daily instead of monthly reference data needed. However, for example, no needed. However, for example, no dailydaily system of recordsystem of record automated for: automated for:

Claims AdjustersClaims Adjusters

Catastrophe name/detailsCatastrophe name/details

Data StewardshipData Stewardship

RESPONSERESPONSE::

Data stewards maintain master data / Data stewards maintain master data / system of record.system of record.

Over night ETL uses master data for Over night ETL uses master data for building dimension.building dimension.

Referential integrity always enforced with Referential integrity always enforced with fact table, so data stewards cannot fact table, so data stewards cannot “delete” required for integrity.“delete” required for integrity.

Information Management BenefitsInformation Management Benefits

Single BI ArchitectureSingle BI Architecture Provides a consistent view of our Corporate DataProvides a consistent view of our Corporate Data Allows for common product training & supportAllows for common product training & support Volume license pricing provides flexibility and Volume license pricing provides flexibility and

cost savingscost savings

Converting Data Collectors to Information Converting Data Collectors to Information ConsumersConsumers

Corporate Portal IntegrationCorporate Portal Integration Delivering specific information to specific Delivering specific information to specific

business usersbusiness users Providing pre-emptive alerts to users based on Providing pre-emptive alerts to users based on

specific (data) eventsspecific (data) events

Single BI ArchitectureSingle BI Architecture (Consistent View, Common Training & Support & Volume Pricing)(Consistent View, Common Training & Support & Volume Pricing)

Using Cognos 8.2 for our Enterprise Using Cognos 8.2 for our Enterprise Reporting PortalReporting Portal Report Studio, Analysis Studio, Query Studio, Report Studio, Analysis Studio, Query Studio,

Event Studio, Metric StudioEvent Studio, Metric Studio

All Cognos Content Provided in ThemesAll Cognos Content Provided in Themes modernLINK quote modernLINK quote ExposureExposure RetentionRetention ExperienceExperience Loss CostLoss Cost ClaimsClaims UnderwritingUnderwriting

Single BI ArchitectureSingle BI Architecture (Consistent View, Common Training & Support & Volume Pricing)(Consistent View, Common Training & Support & Volume Pricing)

Converting Data Collectors Converting Data Collectors to Information Consumersto Information Consumers

Corporate Portal IntegrationCorporate Portal Integration

Converting Data Collectors Converting Data Collectors to Information Consumersto Information Consumers

Delivering specific content to specific usersDelivering specific content to specific users ‘‘Bursting’ Experience & Exposure information Bursting’ Experience & Exposure information

directly to our Business Partners (Agents)directly to our Business Partners (Agents)

Converting Data Collectors Converting Data Collectors to Information Consumersto Information Consumers Providing pre-emptive alerts to users Providing pre-emptive alerts to users

based on specific (data) eventsbased on specific (data) events

So What’s Next?So What’s Next?

Spend more time Spend more time executing strategy executing strategy & less time & less time gathering datagathering data

Manage to Manage to Corporate Corporate Scorecards / Scorecards / Performance Performance MetricsMetrics

Q & A sessionQ & A session

Wrap UpWrap Up Enterprise Data Warehouse now in its 7th year

Business units embrace the DW

Holistic view of information in one place

Next phase: deliver similar functionality to our external business partners

Our case study has been placed in National Archives

The copy of the case study can be found on the following web page: http://www.cwhonors.org/viewCaseStudy.asp?NominationID=54

SWOC DAMA 2008 Showcase atSWOC DAMA 2008 Showcase at American Modern Insurance American Modern Insurance

February 21, 2008