Mannheimer Insurance GroupGermany

Dr. Wolfgang HofbauerDirector, Head of Finance

Karin NischkPlanning and Controlling

Data Warehouse and Strategic Management

How to Sustain Competitive Advantage

Agenda

1. Overview: The Mannheimer Insurance Group

2. Data Warehouse and Strategic Management

3. Implementing the Warehouse

4. Results

5. Summary

1 The Mannheimer Insurance Group1.1 Mannheimer - Not Like Any Other Insurance

The only listed German insurer without majority shareholding: flexible and short time to marketOur focus:• German market• Growth in life and health insurance• Brand products, innovative offer• Profit oriented underwriting• Professional sales partners• Internet

– Sales support– Optimizing our business processes– Acquisition of our new target group ‘online shopper‘

* As of 31 December 2000

1 The Mannheimer Insurance Group1.2 The Mannheimer Group in Figures*

0.9 € bn gross premiums written• 0.4 € bn casualty, property and accident• 0.5 € bn life and health

About 1,100 employees 1.2 m insurance contracts3.9 € bn assets under management27.9 € m profit for the year3,000 shareholdersMarket value of 685.4 € m

2 Data Warehouse and Strategic Management2.1 Starting point

Various OLTP-systems, data can not be compared without transformationsNo uniform and integrated groupwide data-model for information deliveryNew brand products including several lines of insurance (e.g. p/c + life, life + asset management, p/c + health+ life)

Dramatic changes in the German insurance market

New requirements for planning and controllingNewNew requirements for planning and controllingrequirements for planning and controlling

New requirements for our information delivery systemsNew New requirements forrequirements for our information delivery systemsour information delivery systems

How to sustain competitive advantage ?How How toto sustain competitive advantagesustain competitive advantage ??

2 Data Warehouse and Strategic Management2.2 Problem

Lots of dataNecessary information is hidden and can not efficiently be used for specific business aspects

ButBut:: (as it is often the case in German insurance companies)

Better informationBetter informationQualityEfficiency / QuantityUse of modern statistical analysis (e.g. VaR)Applications for new business explanation-models

2 Data Warehouse and Strategic Management2.3 Objectives

Creation of an uniform uniform groupwide datagroupwide data--modelmodel for information deliverySelecting and organizing data relevant for decicion makingdecicion makingSpecific data for decicion making on all all levels of the companylevels of the company

Improved basis for decicion makingImproved basis for decicion makingImproved basis for decicion making

Key figures available anytime and anyplaceKey figures available anytime and anyplaceKey figures available anytime and anyplace

groupwide integrated datagroupwide integrated data--basisbasis

2 Data Warehouse and Strategic Management2.4 Conceptual Framework

SAP CO/FI

Schaden

Bestand 1

Bestand 2Reuters

Bestand 3

Bestand Leben dereg.

Bestand Leben reg.

• DBR

• Ertrags-barwert

• 5-Jahres-Planung

• Ertrags-barwert

• 5-Jahres-Planung

• DBR

• Ertrags-barwert

• 5-Jahres-Planung

Market surveys

• Kosten-information

• Vertriebs-information

• Kunden-rentabilität

Bestand Kranken

Leistung

group p/c life/health mamax.com Assetmanagement

services

• 5-Jahres-Planung

• Finanz-berichte

• Preis-Kalku-lation

SAP TR-TM

privateequity

• Planung

• Ergebnisse

• ROE

• DCF

Gesellschaft 1 SAP CO

Inkasso

Rückversicherung

Leistung

Bestand

Fondsverwaltung

SAP HR

Statistik Statistik KALCON

Gesellschaft 2

SAP CO-PASAP TR-CM

Key figures(Balanced Scorecard)

RiskRisk--Management Management StrategyStrategy--FormulationFormulation

SAP EC-CS datadata--sourcessources: SAP / : SAP / HostHost / PC/ PCWolfgang Hofbauer, Integriertes Controlling in Versicherungsunternehmen in: Electronic Business und Knowledge Management, hrsg. von A.-W. Scheer, Physica Verlag Heidelberg 1999, pp. 315-333

specific applications for eachspecific applications for eachbusinessbusiness--segmentsegment

groupwidegroupwideapplicationsapplications

drill down

Customers / DistributionCustomers / Distribution

2 Data Warehouse and Strategic Management2.5 Solution / Business Cases

Groupwide sales information systemPattern analysis of our customersStatistical predictions:• Propensity to buy other Mannheimer products

cross selling• Cancellation probability

retention plans• Revenue potential

acquisition of new valuablevaluable customers

Customer lifetime valueOptimizing selling costs / provision system

Underwriting / actuarial controllingUnderwriting / actuarial controlling

RatingRating

Review of tariff structure

Improvement of tariffs

2 Data Warehouse and Strategic Management 2.5 Solution / Business Cases

Contribution accounting information system

Loss prevention

Reduction of loss ratio

Statistical predictions• Claims probability • Fraud probability

Long term planningLong term planning

Internal Accounting for life insuranceInternal Accounting for life insurance

Risk-ManagementRisk-Management

2 Data Warehouse and Strategic Management 2.5 Solution / Business Cases

Early warningBalanced ScorecardApplication of Value at Risk-Models

Strategy reviewStrategy formulation

Actuarial needs

e-Customer Relationship Management mamax.come-Customer Relationship Management mamax.com

Process RedesignProcess Redesign

2 Data Warehouse and Strategic Management 2.5 Solution / Business Cases

Complete reorganization of our information delivery processes

Click-stream-analysis from log-filese-CRM

Organisational LearningOrganisational Learning

Learning in and with the project

2 Data Warehouse and Strategic Management 2.6 Business Cases and Strategic Behaviour

Strategic Behaviour covers five generic managerial patterns

Strategic Enterprise Management

Strategic Capability Management

Strategic Surprise Management

Strategic Issue Management

Strategic Evolution Management

with different focus on

the company`s level (entire company / elements or functions)

the emphasis on fundamental aspects (reduction of complexity /concentration on potentials)

the way to deal with the future (contingency planning / forming the relevant conditions)

Strategic Enterprise Management

Entire companyReduction of complexity

Strategic Capability Management

Entire companyConcentration on potentials

Strategic Surprise Management

Elements/Functions of the companyContingency

Strategic Issue Management

Elements/Functions of the companyForming the relevant conditions

Strategy formulation Balanced ScorecardContribution accounting information systemSales information systemCross selling Acquisition of new valuable customerse-CRMCustomer lifetime valueInternal accounting for life insuranceProcess redesign of information delivery

Early warningValue at Risk

Tariff reviewLoss preventionReduction of loss ratioRetention plansClaims probability

Strategic Evolution Management

Entire CompanyGeneration of varietyForming the relevant conditions

Organizational learning

2 Data Warehouse and Strategic Management 2.6 Business Cases and Strategic Behaviour

sas®

sas®

sas®

sas®

sas®

sas®: started / completed in 2000/2001

sas®

sas®

sas®

3 Implementing the Warehouse3.1 Challenges

Complexity of various OLTP-systemsNo uniform and integrated data-modelInconsistency in data

Data-SourcesData-Sources

ProjectProject

Tight scheduleScarce internal resourcesLack of know-how in data warehousing

TechnicTechnic

Huge volume of dataComplex transformation processes

• purpose-oriented

• composed

• multidimensional

• summarized

K-SchadenK-Bestand

A-Bestand

IS 2000

. . . etc.. . . etc.

• groupwide

• uniform

• single records

• relational

• extracting in ODD• developing interfaces • analysing the OLTP-Systems

• enhancing the Central Warehouse• transforming to Star Scheme

• developing applications• building DataMarts • selecting and summarizing

Meta

data

data flow

design

3 Implementing the Warehouse3.2 Mannheimer Data-Warehousing-Process

describing data and

processes

Entity RelationshipODD

transform infacts and

dimensions

facts

dimen-sion

customer

Star SchemeCentral Warehouse

dimen-sionagent

dimen-sion

product

dimen-sion

region

multidimensional (MDDB)Data Marts

subset, summarise,

compose

selected dimensions

and facts

selected dimensions

and facts

agent

policy

claim

cus-tomer

3 Implementing the Warehouse3.3 Modelling of Data

debit

pay-ment

known in IT (analysis of

existing programs)

known from requests(analysis of

information needs)

?Can be deduced for known requests

but possibly unreliable for future requests!

Think big, start smallThink big, start small

3 Implementing the Warehouse3.4 Proceedings

Analyse all requests according to strategic goalsDraft the framework for the completecomplete warehouse Explain and discuss the solution with users and management Implement the first application a.s.a.p. but continue to broaden the data base according to the defined central warehouse scheme

Avoid redesignAvoid redesignAvoid redesign

Supplementory data easy to includeSupplementory data easy to includeSupplementory data easy to include

Server:IBM AIX S80, 6 proc., 8 GB RAM800 GB ESS RAID5• Developement and operation

SAS/Warehouse Administrator®, SAS/AF®, SAS/EIS®, SAS/MDDB®

• Data-Storage Scalable Performance Data Server®, web-server

40 Clients:NT-PC, 128 KB RAM• Developement

SAS/AF®, SAS/EIS®, SAS/MDDB®, AppDev StudioTM

• Information and Analysing (Specialists)Enterprise Reporter®, Enterprise Guide®, SAS/ASSIST®

60 Web-Clients:NT-PC, 128 KB RAM• Information (Standard-User)

web-browser

3 Implementing the Warehouse3.5 Technical environment

source tables columns records GBcontracts 79 5,805 Replace: 34,500,000

Append: 13,600,00028.4

1.0collections 1 230 Append: 1,300,000 7.5claims 14 441 Replace: 9,700,000 2.7customers 2 59 Replace: 11,000,000 3.7others (agents,costs, planning)

5 73 Replace: 123,000Append: 60,000

0.1

3 Implementing the Warehouse3.6 Quantity structure

ODDODD

Central WarehouseCentral Warehouse

type tables columns records GBfacts 28 1,164 226,600,000 38.5dimensions 42 262 15,100,000 1.5

DataMartsDataMarts

type tables columns records GBp/c 91 4,165 209,500,000 93.9life 10 602 8,200,000 3.3

managers, no specialistsstandard functionality‘thin client‘, web-browser

4 Results4.1 EIS-Application

controller and specialistsenhanced functionality‘fat client‘, sas®

PowerPower--UserUser

StandardStandard--UserUser

EIS-ApplicationEIS-Application

Web-EIS-ApplicationWeb-EIS-Application

4 Results4.1 EIS-Application

Change dimensions (customer, product, sales organisation)

Choose key figures

Explore hierarchies

new: hierarchy for brand products, customer-dimension, explore hierarchies and search for elements

new: hierarchy for brand products, customernew: hierarchy for brand products, customer--dimension, dimension, explore hierarchies and search for elements explore hierarchies and search for elements

4 Results4.1 EIS-Application

Export to PCExport to PC--files files

Show detailsShow details

PrintPrint

new: show single claims and premium-payments to contracts, export to PC-files

new: show singlenew: show single claims and premiumclaims and premium--payments to contracts, payments to contracts, export to PCexport to PC--filesfiles

4 Results4.2 Business benefits

Efficient selection of those of our commercial customers who had already one of our single standard covers and who had a good loss ratio to offer them our new brand product multimulti--riskrisk against loss or damage

Customer/Distibution: Increase cross-sellingCustomer/Distibution: Increase cross-selling

Comprehensive cover for our customers

Higher premium

Expected benefit 2001:Better customer relations and higher customer lifetime valueImprovement of underwriting result by 0.5 € m

Expected benefit 2001:Expected benefit 2001:Better customer relations and higher customer lifetime valueBetter customer relations and higher customer lifetime valueImprovement of underwriting result by Improvement of underwriting result by 00.5 € m.5 € m

4 Results4.2 Business benefits

Underwriting: Reduction of loss ratioUnderwriting: Reduction of loss ratio

After negotiations with customers:

Premium adjustmentLoss prevention measures

Cancellation of contracts

Select automobile liability contracts with high loss ratio and low overall customer value more effective

Expected benefit 2001:Reduction of loss ratio by 5%Improvement of underwriting result by 1.3 € m

Expected benefit 2001:Expected benefit 2001:Reduction of loss ratio by 5%Reduction of loss ratio by 5%Improvement of underwriting result by Improvement of underwriting result by 1.3 € m1.3 € m

5 Summary

Ambitious project with groupwide impact

Intensive efforts have been necessary

Essential basics without tangible benefits

Competitive advantage and measurable ROI can only be

achieved with a clear strategic management focus and

well defined business cases

We have accomplished a lot, but much remains to be doneWe have accomplishedWe have accomplished aa lotlot,, butbut muchmuch remainsremains toto be donebe done

5 Summary

Strategic Management and decicion making without a data warehouse is like navigating without a compass.

StrategicStrategic Management Management and decicion and decicion making withoutmaking without aa data warehouse is data warehouse is like navigating withoutlike navigating without a a compass.compass.

SeUGI 19

Dr. Wolfgang Hofbauer/Karin Nischk, Mannheimer Insurance Group

Data Warehouse and Strategic Management.How to Sustain Competitive Advantage

Abstract

German insurance companies have been facing dramatic changes in their environment. As aresult of this situation, new requirements arose for planning and controlling and consequentlyfor our information delivery systems. In order to meet these demands we have developed anintegrated data warehouse. Our data warehouse and several specific applications providesolutions for defined business cases. As a result we have an improved basis for strategicmanagement and decicion making.

The challenge of implementing the data warehouse lies in the complexity of the variousOLTP-systems and the huge volume of data. Historically, in our company different areas usediffering systems. Therefore, we had to define a logical data model. Then the interfaces tothe OLTP-systems had to be programmed and the transformation rules had to be designedto structure the selected data according to the logical data model. Finally, we set up datamarts for our multidimensional applications. The main advantage of our approach is that wecan easily develop additional applications.

In 2000 we started with our new group-wide, web-based controlling information system andthe first applications for the improvement of our loss ratio and cross selling. In addition theactuarial needs within our life insurance were implemented. In 2001 we will go on withsolutions for the improvement of tariffs, statistics and (e)CRM.

We emphasize that competitive advantage from a data warehouse can only be realized witha clear strategic management focus and well defined business cases.

Description: Mannheimer Insurance Group

Mannheimer (Headquarter: Mannheim, Germany) is a medium-sized insurance groupfocused on the German market.

Mannheimer is a profit-making niche player with various brand products and an innovativeoffer. Mannheimer‘s core businesses are life and health insurance, property and casualtyinsurance, reinsurance and asset management.

Mannheimer is the only listed German insurer without majority shareholding.

Dr. Wolfgang Hofbauer, Mannheimer Insurance GroupDirector, Head of Finance

Biography:

Wolfgang Hofbauer (born 1960) studied business administration in Regensburg, Germany.He then worked as assistent professor at the University of Saarland, Germany, institute oforganisation theory, personnel management, information management and strategicmanagement.

In 1991 after getting his Ph.D. he joined the Mannheimer Insurance Group. He worked inseveral departments and since 1995 he has been Head of Finance.

Dr. Hofbauer has published several books dealing with organizational culture, therelationship between corporate culture and strategy and some papers about such topics ascontrolling, controlling and IT as well as strategic management for insurance companies.

Karin Nischk, Mannheimer Insurance GroupSpecialist Planning and Controlling

Biography:

Karin Nischk (born 1965) studied business administration at the University of Saarland,Germany, with emphasis on computer science for business applications.

In 1990, she joined the Mannheimer Insurance Group as system developer in the IT-department. She was involved in the installation of the first management information systemswithin Mannheimer group.

Since 1994, she has been working in the section planning and controlling, responsible forbusiness management applications and the information-delivery for controlling. Since 1999she leads the Mannheimer Data-Warehouse project with SAS.

SeUGI 19

Dr. Wolfgang Hofbauer/Karin Nischk, Mannheimer Insurance Group

Data Warehouse and Strategic Management.How to Sustain Competitive Advantage

Abstract

German insurance companies have been facing dramatic changes in their environment. As aresult of this situation, new requirements arose for planning and controlling and consequentlyfor our information delivery systems. In order to meet these demands we have developed anintegrated data warehouse. Our data warehouse and several specific applications providesolutions for defined business cases. As a result we have an improved basis for strategicmanagement and decicion making.

The challenge of implementing the data warehouse lies in the complexity of the variousOLTP-systems and the huge volume of data. Historically, in our company different areas usediffering systems. Therefore, we had to define a logical data model. Then the interfaces tothe OLTP-systems had to be programmed and the transformation rules had to be designedto structure the selected data according to the logical data model. Finally, we set up datamarts for our multidimensional applications. The main advantage of our approach is that wecan easily develop additional applications.

In 2000 we started with our new group-wide, web-based controlling information system andthe first applications for the improvement of our loss ratio and cross selling. In addition theactuarial needs within our life insurance were implemented. In 2001 we will go on withsolutions for the improvement of tariffs, statistics and (e)CRM.

We emphasize that competitive advantage from a data warehouse can only be realized witha clear strategic management focus and well defined business cases.

Description: Mannheimer Insurance Group

Mannheimer (Headquarter: Mannheim, Germany) is a medium-sized insurance groupfocused on the German market.

Mannheimer is a profit-making niche player with various brand products and an innovativeoffer. Mannheimer‘s core businesses are life and health insurance, property and casualtyinsurance, reinsurance and asset management.

Mannheimer is the only listed German insurer without majority shareholding.

Dr. Wolfgang Hofbauer, Mannheimer Insurance GroupDirector, Head of Finance

Biography:

Wolfgang Hofbauer (born 1960) studied business administration in Regensburg, Germany.He then worked as assistent professor at the University of Saarland, Germany, institute oforganisation theory, personnel management, information management and strategicmanagement.

In 1991 after getting his Ph.D. he joined the Mannheimer Insurance Group. He worked inseveral departments and since 1995 he has been Head of Finance.

Dr. Hofbauer has published several books dealing with organizational culture, therelationship between corporate culture and strategy and some papers about such topics ascontrolling, controlling and IT as well as strategic management for insurance companies.

Karin Nischk, Mannheimer Insurance GroupSpecialist Planning and Controlling

Biography:

Karin Nischk (born 1965) studied business administration at the University of Saarland,Germany, with emphasis on computer science for business applications.

In 1990, she joined the Mannheimer Insurance Group as system developer in the IT-department. She was involved in the installation of the first management information systemswithin Mannheimer group.

Since 1994, she has been working in the section planning and controlling, responsible forbusiness management applications and the information-delivery for controlling. Since 1999she leads the Mannheimer Data-Warehouse project with SAS.