Information Quality Conference 2004
Miami, FL October 11 - 15, 2004

Information Quality Track 3

Tuesday, October 12:
10:15-11:15 Design for Data Quality at Bank of America
     Bob Bernard, Senior Vice President, Bank of America

1:00-2:00 Transformation to an Information Organization
     Christian Walenta, Manager, ISC Information Management, IBM

2:15-3:15 Data Quality in Practice: an Enterprise Wide Approach
     Manfred Goerk, Global Data Quality Manager, SAP AG, Germany

Wednesday, October 13:
10:00-11:00 Making Data Conversions Less Painful
    Eric Schwartz, Senior Manager, The North Highland Company

11:15-12:15 Improving Data Quality for Risk Management by Eliminating Data Redundancy at Bank of America Using Six Sigma Methodology
    Stuart Roth, Director, Cross Application Business Strategy (Risk Management Technology), Bank of America

Presentation Descriptions

Building it right the first time and sustaining the gain that is what Design for Data Quality (DFDQ) is all about. The Design for Data Quality program focuses on bringing data quality to the forefront of projects and day-to-day business operations. DFDQ was developed using the Total Quality Management Methodology and Six Sigma Practices and focuses on:

• Process integration
• Developing enterprise-wide Data Stewardship programs
• Data quality business assessments
• Data quality metrics design
• Information Quality Consultation services

Learn how IBM's Integrated Supply Chain (ISC), IBM's 5th biggest unit, has transformed to an "information oriented" organization. Mr. Walenta will describe the specifics that ISC faced in its challenging journey to an "information organization" and key steps to success. Given the diverse environment in IBM, this practical approach may be applicable for other complex, heterogeneous businesses as well. The unique implementation approaches include:

• Institutionalizing organizational responsibilities around information
• Establishing Information Management direction and strategies
• Implementing effective Information Management practices
• Making Information Stewardship work

Data Quality got top management visibility and priority at SAP. Based on global assessments, action plans were developed and executed.

In conjunction with CRM implementations, SAP developed a framework of Data Policies, Tools, Processes and People that enabled quick wins and sustained success. Learn how the DQ framework produced a net savings of more than $7.3 million.

• From nothing to global action plans
• Embedding DQ in CRM projects
• Enterprise-wide DQ scope and actions extended to all Lines of Business

Data conversion projects encompass a little bit of everything-requirements gathering to understand the source and target data, some database modeling to better understand the data, data clean-up work and custom development in the form of transformation tools. This presentation covers 10 areas to help project managers make data conversion efforts go more smoothly:

• Build the right team; choose the right tools
• Build the proper infrastructure; control project scope
• Stabilize requirements and target; design a repeatable process
• Build the lookup tables first; decide how to enforce referential integrity
• Document your work; test the process repeatedly

Bank of America leverages its overall Data Warehouse as a strategic resource through projects that significantly increase the use of the central Data Warehouse while at the same time increasing the overall quality of the data by eliminating data redundancy. This presentation focuses on the goals and how we accomplished them and three specific areas of data:

• Availability: Single place, cross product and cross customer views
• Access: High data volume and data reconciliation across disparate data marts; Multiple downstream quality projects in system of record conversions
• Quality: Inconsistent data strategies and inconsistent quality across data marts