Corporate Data Quality

Оглавление

Hubert Osterle. Corporate Data Quality

Foreword

Table of Contents

Table of Abbreviations

About the Authors

1 Data Quality – A Management Task

1.1 Trends in Digitization

1.1.1 Penetration into every Area of Life and Economy

1.1.2 Industry 4.0

1.1.3 Consumerization

1.1.4 Digital Business Models

1.2 Data Quality Drivers

1.2.1 A 360-degree View of the Customers

1.2.2 Corporate Mergers and Acquisitions

1.2.3 Compliance

1.2.4 Reporting Systems

1.2.5 Operational Excellence

1.2.6 Data Protection and Privacy

1.3 Challenges and Requirements of Data Quality Management

1.3.1 Challenges in Handling Data

1.3.2 Requirements on Data Quality Management

1.4 The Framework for Corporate Data Quality Management

1.4.1 An Overview of the Framework

1.4.2 Strategic Level

1.4.3 Organizational Level

1.4.4 Information System Level

1.5 Definition of Terms and Foundations

1.5.1 Data and Information

1.5.2 Master Data

1.5.3 Data Quality

1.5.4 Data Quality Management (DQM)

1.5.5 Business Rules

1.5.6 Data Governance

1.6 The Competence Center Corporate Data Quality

2 Case Studies of Data Quality Management

2.1 Allianz: Data Governance and Data Quality Management in the Insurance Sector. 2.1.1 Overview of the Company

2.1.2 Initial Situation and Rationale for Action

2.1.3 The Solvency II Project

2.1.4 Data Quality Management at AGCS

2.1.5 Insights

2.1.6 Additional Reference Material

2.2 Bayer CropScience: Controlling Data Quality in the Agro-chemical Industry. 2.2.1 Overview of the Company

2.2.2 Initial Situation and Rationale for Action

2.2.3 Development of the Company-wide Data Quality Management

2.2.4 Insights

2.2.5 Additional Reference Material

2.3 Beiersdorf: Product Data Quality in the Consumer Goods Supply Chain. 2.3.1 Overview of the Company

2.3.2 Initial Situation of Data Management and Rationale for Action

2.3.3 The Data Quality Measurement Project

2.3.4 Insights

2.3.5 Additional Reference Material

2.4 Bosch: Management of Data Architecture in a Diversified Technology Company. 2.4.1 Overview of the Company

2.4.2 Initial Situation and Rationale for Action

2.4.3 Data Architecture Patterns at Bosch

2.4.4 Insights

2.4.5 Additional Reference Material

2.5 Festo: Company-wide Product Data Management in the Automation Industry. 2.5.1 Overview of the Company

2.5.2 Initial Situation and Rationale for Action regarding the Management of Product Data

2.5.3 Product Data Management Projects between 1990 and 2009

2.5.4 Current Activities and Prospects

2.5.5 Insights

2.5.6 Additional Reference Material

2.6 Hilti: Universal Management of Customer Data in the Tool and Fastener Industry. 2.6.1 Overview of the Company

2.6.2 Initial Customer Data Management Situation and Rationale for Action

2.6.3 The Customer Data Quality Tool Project

2.6.4 Insights

2.6.5 Additional Reference Material

2.7 Johnson & Johnson: Institutionalization of Master Data Management in the Consumer Goods Industry. 2.7.1 Overview of the Company

2.7.2 Initial Data Management Situation in the Consumer Products Division and Activities up to 2008

2.7.3 Introduction of Data Governance

2.7.4 Current Situation

2.7.5 Insights

2.7.6 Additional Reference Material

2.8 Lanxess: Business Intelligence and Master Data Management at a Specialty Chemicals Manufacturer. 2.8.1 Overview of the Company

2.8.2 Initial Data Management Situation and Business Intelligence 2004 – 2011

2.8.3 Master Data Management at Lanxess since 2011

2.8.4 Structure of the Strategic Reporting System since 2012

2.8.5 Insights

2.8.6 Additional Reference Material

2.9 Shell: Data Quality in the Product Lifecycle in the Mineral Oil Industry. 2.9.1 Overview of the Company

2.9.2 Initial Situation and Rationale for Action

2.9.3 Universal Management of Data in Product Lifecycle

2.9.4 Challenges during Implementation

2.9.5 Using the New Solution

2.9.6 Insights

2.9.7 Additional Reference Material

2.10 Syngenta: Outsourcing Data Management Tasks in the Crop Protection Industry. 2.10.1 Overview of the Company

2.10.2 Initial Situation and Goals of the Master Data Management Initiative

2.10.3 The Transformation Project and the MDM Design Principles

2.10.4 Master Data Management Organizational Structure

2.10.5 The Data Maintenance Process and Decision-making Criteria for the Outsourcing Initiative

2.10.6 Insights

2.10.7 Additional Reference Material

3 Methods and Tools for Data Quality Management

3.1 Method for DQM Strategy Development and Implementation

3.1.1 Structure of the Method

3.1.2 Examples of the Techniques used by the Method

3.2 Maturity Assessment and Benchmarking Platform for Data Quality Management. 3.2.1 Initial Situation

3.2.2 Maturity Model and Benchmarking as Control Instruments

3.2.3 The EFQM Model of Excellence for the Management of Master Data Quality

3.2.4 Corporate Data Excellence: Control Tools for Managers of Data Quality

3.3 The Corporate Data League: One Approach for Cooperative Data Maintenance of Business Partner Data. 3.3.1 Challenges in Maintaining Business Partner Data

3.3.2 The Cooperative Data Management Approach

3.3.3 The Corporate Data League

3.4 Additional Methods and Tools from CC CDQ

4 Factors for Success and Immediate Measures

4.1 Factors for the Success of Data Quality Management

4.2 Immediate Measures on the Path to Successful Data Quality Management

5 Bibliography

6 Glossary

Отрывок из книги

Corporate Data Quality

Corporate Data Quality

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2.5.3 Product Data Management Projects between 1990 and 2009 96

2.5.4 Current Activities and Prospects. 101

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