Overview
Poor information quality costs organizations10-20% of operating revenue in process failure and "information scrap and rework" in direct costs with missed opportunity costs often greater.

This seminar describes quality principles applied to business and systems processes to achieve effective business performance. It provides guidelines for implementing an effective IQ environment.

Learning Objectives

• Define information quality and its three components
• Describe categories of information quality tools and how to use them
• Describe how to measure information definition and content quality
• Describe how to measure costs of nonquality information
• Describe how to reengineer and correct data and implement audits and control for data movement
• Conduct an information quality process improvement initiative
• Describe how to organize and manage an information quality environment

Seminar and Workshop Outline

     Defining Information Quality (IQ)

• Quality and information quality
• Customer satisfaction as business driver
• Dispelling myths about IQ

     Applying Quality Principles to Information

• The information product
• Kaizen, TQM and business excellence principles
• Identifying information "customers"
• Customer "expectations" of their information product

     Information Quality Tools and Processes

• Categories of IQ tools
• TIQM® Quality System Overview
• Architecture of IQ tools in the TIQM process

     Assessing Data Definition and Information Quality

• Data definition quality characteristics
• Three categories of data definition quality assessment
• QFD: Designing quality in data models
• Metrics for data definition quality

     Assessing Information Quality

• Information quality characteristics
• Applying statistical quality control (SQC) to information

     Measuring the Costs of Poor Quality Information and the ROI of Information Process

• Calculating information costs
• Calculating poor quality information cost
• Calculating lifetime value as a measure of information value

     Improving Information Process Quality: Data Defect Prevention

• The Plan-Do-Check-Act cycle for information process improvement
• Root cause analysis using cause and effect diagrams
• From quality assurance to continuous quality

     Improving Information Product Quality: Data Reengineering & Correction (Cleansing)

• Principles of data correction
• Audits and Controls for ETL processes
• Discovering "business rules" in legacy data

     Implementing and Sustaining an Information Quality Improvement Environment

• Deming's fourteen points of quality applied to information
• Organizing and facilitating culture change for information quality

Audience

• Information Quality Personnel
• Quality Management Personnel
• Data Management & Warehouse Personnel
• IT Management
• Systems Analyst
• Business Analyst
• IT Consultant
• Information Stewards
• Internal and EDP Auditors
• Business Personnel who require quality information

Special Features

• Lecture with exercises and interchange to reinforce the concepts
• Free copy of "IQ Applied: Best Practices for Improving Business Information, Processes, and Systems" book