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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.