McGilvray Executing Data Quality Projects

Ten Steps to Quality Data and Trusted InformationTM
1. Auflage 2008
ISBN: 978-0-08-055839-4
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 352 Seiten

Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her 'Ten Steps” approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approach-in which she has trained Fortune 500 clients and hundreds of workshop attendees-applies to all types of data and to all types of organizations.
* Includes numerous templates, detailed examples, and practical advice for executing every step of the 'Ten Steps” approach.
* Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.
* A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.

Danette McGilvray is president and principle of Granite Falls Consulting, Inc., a firm specializing in information and data quality management to support key business processes around customer satisfaction, decision support, supply chain management, and operational excellence.

Autoren/Hrsg.

McGilvray, Danette

Inhaltsverzeichnis

1;Front Cover;1
2;Executing Data Quality Projects;4
3;Copyright Page;5
4;Contents;8
5;Acknowledgments;12
6;Introduction;14
6.1;The Reason for This Book;14
6.2;Intended Audiences;15
6.3;Structure of This Book;16
6.4;How to Use This Book;18
7;Chapter 1. Overview;21
7.1;The Impact of Information and Data Quality;23
7.2;About the Methodology: Concepts and Steps;25
7.3;Approaches to Data Quality in Projects;28
7.4;Engaging Management;31
8;Chapter 2. Key Concepts;33
8.1;Introduction;35
8.2;The Framework for Information Quality;35
8.3;The Information Life Cycle;42
8.4;Data Quality Dimensions;49
8.5;Business Impact Techniques;54
8.6;Data Categories;58
8.7;Data Specifications;64
8.8;Data Governance and Data Stewardship;71
8.9;The Information and Data Quality Improvement Cycle;73
8.10;The Ten Steps Process;76
8.11;Best Practices and Guidelines;78
9;Chapter 3. The Ten Steps Process;81
9.1;Introduction;83
9.2;Step 1 Define Business Need and Approach;85
9.2.1;Introduction;85
9.3;Step 1.1 Prioritize the Business Issue;88
9.4;Step 1.2 Plan the Project;91
9.5;Step 2 Analyze Information Environment;95
9.5.1;Introduction;95
9.6;Step 2.1 Understand Relevant Requirements;101
9.7;Step 2.2 Understand Relevant Data and Specifi cations;103
9.8;Step 2.3 Understand Relevant Technology;109
9.9;Step 2.4 Understand Relevant Processes;112
9.10;Step 2.5 Understand Relevant People/Organizations;117
9.11;Step 2.6 Define the Information Life Cycle;121
9.12;Step 2.7 Design Data Capture and Assessment Plan;124
9.13;Step 3 Assess Data Quality;127
9.14;Step 3.1 Data Specifi cations;133
9.15;Step 3.2 Data Integrity Fundamentals;137
9.16;Step 3.3 Duplication;147
9.17;Step 3.4 Accuracy;153
9.18;Step 3.5 Consistency and Synchronization;159
9.19;Step 3.6 Timeliness and Availability;162
9.20;Step 3.7 Ease of Use and Maintainability;166
9.21;Step 3.8 Data Coverage;168
9.22;Step 3.9 Presentation Quality;170
9.23;Step 3.10 Perception, Relevance, and Trust;174
9.24;Step 3.11 Data Decay;178
9.25;Step 3.12 Transactability;180
9.26;Step 4 Assess Business Impact;182
9.27;Step 4.1 Anecdotes;186
9.28;Step 4.2 Usage;192
9.29;Step 4.3 Five “Whys” for Business Impact;194
9.30;Step 4.4 Benefit versus Cost Matrix;196
9.31;Step 4.5 Ranking and Prioritization;200
9.32;Step 4.6 Process Impact;205
9.33;Step 4.7 Cost of Low-Quality Data;208
9.34;Step 4.8 Cost–Benefit Analysis;214
9.35;Step 5 Identify Root Causes;217
9.36;Step 5.1 Five “Whys” for Root Cause;220
9.37;Step 5.2 Track and Trace;222
9.38;Step 5.3 Cause-and-Effect/Fishbone Diagram;223
9.39;Step 6 Develop Improvement Plans;227
9.40;Step 7 Prevent Future Data Errors;232
9.41;Step 8 Correct Current Data Errors;237
9.42;Step 9 Implement Controls;241
9.43;Step 10 Communicate Actions and Results;246
9.44;The Ten Steps Process Summary;252
10;Chapter 4. Structuring Your Project;257
10.1;Projects and The Ten Steps;259
10.2;Data Quality Project Roles;271
10.3;Project Timing;272
11;Chapter 5. Other Techniques and Tools;275
11.1;Introduction;277
11.2;Information Life Cycle Approaches;277
11.3;Capture Data;282
11.4;Analyze and Document Results;282
11.5;Metrics;288
11.6;Data Quality Tools;290
11.7;The Ten Steps and Six Sigma;296
12;Chapter 6. A Few Final Words;297
13;Appendix: Quick References;301
13.1;The Framework for Information Quality;303
13.2;The POSMAD Interaction Matrix in Detail;305
13.3;POSMAD Phases and Activities;307
13.4;Data Quality Dimensions;308
13.5;Business Impact Techniques;309
13.6;Overview of The Ten Steps Process;310
13.7;Definitions of Data Categories;312
14;Glossary;314
15;Bibliography;322
16;List of Figures, Tables, and Templates;326
17;Index;330
18;About the Author;353

Leseproben

Chapter 1 Overview If the state of quality of your company’s products and services was the same level of quality as the data in your databases, would your company survive or go out of business?

–Larry English

A corollary: If the state of quality of your company’s data was the same level of quality as your company’s products and services, how much more profitable would your company be?

– Mehmet Orun In This Chapter The Impact of Information and Data Quality About the Methodology: Concepts and Steps Approaches to Data Quality in Projects Engaging Management The Impact of Information and Data Quality
Information quality problems and their impact are all around us: A customer does not receive an order because of incorrect shipping information; products are sold below cost because of wrong discount rates; a manufacturing line is stopped because parts were not ordered—the result of inaccurate inventory information; a well-known U.S. senator is stopped at an airport (twice) because his name is on a government “Do not fly” list; many communities cannot run an election with results that people trust; financial reform has created new legislation such as Sarbanes–Oxley.1 Information is not simply data, strings of numbers, lists of addresses, or test results stored in a computer. Information is the product of business processes and is continuously used and reused by them. However, it takes human beings to bring information to its real-world context and give it meaning. Every day human beings use information to make decisions, complete transactions, and carry out all the other activities that make a business run. Applications come and applications go, but the information in those applications lives on. That’s where information quality comes into play. Effective business decisions and actions can only be made when based on high-quality information—the key here being effective. Yes, business decisions are based all the time on poor-quality data, but effective business decisions cannot be made with flawed, incomplete, or misleading data. People need information they can trust to be correct and current if they are to do the work that furthers business goals and objectives. A firm’s basis for competition … has changed from tangible products to intangible information. A firm’s information represents the firm’s collective knowledge used to produce and deliver products and services to consumers. Quality information is increasingly recognized as the most valuable asset of the firm. Firms are grappling with how to capitalize on information and knowledge. Companies are striving, more often silently, to remedy business impacts rooted in poor quality information and knowledge. – Kuan-Tsae Huang, Yang W. Lee,
and Richard Y. Wang2 Tom Redman says it well: The costs of poor quality are enormous. Some costs, such as added expense and lost customers, are relatively easy to spot, if the organization looks. We suggest (based on a small number of careful, but proprietary studies), as a working figure, that these costs are roughly 10 percent of revenue for a typical organization…. This figure does not include other costs, such as bad decisions and low morale, that are harder to measure but even more important.3 What is the cost to a company of the sales rep, publicly announced to have won the top sales award for the year along with the trip to Hawaii, only to have it rescinded a few days later because the sales data were wrong? Does the resulting embarrassment and low morale influence that sales rep’s productivity and therefore sales, or even his decision to stay with the company? What is the cost to the embassy whose name was splashed across the front pages of a major U.S. city’s newspaper when its visa applications containing sensitive personal and business information, such as Social Security numbers and strategic business plans, were found thrown in an open dumpster instead of being properly disposed of? Does the resulting lack of trust in the management of that information influence another company’s decision to do business in that country? What Is Information Quality?
Information quality is the degree to which information and data4 can be a trusted source for any and/or all required uses. Simply put, it is having the right information, at the right time and place, for the right people to use to run the business, serve customers, and achieve company goals. Quality information is also fit for its purpose—the level of quality supports all of its uses. Definition Information quality is the degree to which information and data can be a trusted source for any and/or all required uses. It is having the right set of correct information, at the right time, in the right place, for the right people to use to make decisions, to run the business, to serve customers, and to achieve company goals. Where Do Information Quality Problems Come From?
Information quality problems may be caused by human, process, or system issues. They are not restricted to older or particular types of systems. Although everyone is aware that data cause problems from time to time, it may be difficult to perceive the extent to which these problems affect the business. Some normal business activities are indicative of data quality problems5: Correction activities Rework Reprocessing orders Handling returns Dealing with customer complaints Many of these activities do not appear to be associated with information quality, when in fact they are. Since processes and functions are distributed across an organization and many people, the cost and scope of data quality problems are often not visible. Business processes create, update, and delete data in addition to applying information in many ways. Information technology (IT) teams are responsible for the quality of the systems that store and move the data, but they cannot be held completely responsible for the content. Both IT and the business must share in insisting on clearly articulated requirements, strict testing of systems, and the development of quality processes for data management. The Information Quality Challenge
I believe that two major trends have created an environment where information quality is getting more of the attention it deserves. One is the increasing number of legal and regulatory data quality requirements. The need for and benefits from information quality have always been there and ready for any organization who invests in it. But human nature being what it is, the threat of bad publicity and high fines and the risk of a CEO going to jail have created the motivation to actually do something about data quality. The second reason is based on the need for business to see information brought together in new ways. Examples include the need to see what top customers are doing across the enterprise through CRM (Customer Relationship Management), to have data available for decision support through business intelligence and data warehousing, to streamline business processes and information through ERP (Enterprise Resource Planning), and to deal with the high rate of mergers and acquisitions, which require the integration of data from different companies. All these initiatives require data integration—bringing together data from two or more different sources and combining them in such a way that new and better uses can be made of the resulting information. Data that previously fulfilled the needs of one particular functional area in the business are now being combined with data from other functional areas—often with very poor results. We have different business uses for the same information; different platforms, systems, databases, and applications; different types of data (customer, vendor, manufacturing, finance, etc.); different data structures, definitions, and standards; and data, processes, and technology customized to fit the business, geography, or application. These are the challenges of the current environment. What we need is the ability to share information with our customers and with each other across the company. We need the ability to find what we need, when we need it, and to be able to trust it when we get it. What is required for that to happen? We must consciously manage information as a resource (a source of help) and as an asset (a source drawn on by a company for making profit). We must have information that is real (an accurate reflection of the real world), recent (up to date), and relevant (that our business and customers need and care about). This book is here to help. About the Methodology: Concepts and Steps
“Doctor, my left arm hurts!” The doctor puts your arm in a sling, gives you an aspirin, and tells you to go home. But what if you were having a heart attack? You would expect the doctor to diagnose your condition and take emergency measures to save your life. After you were stabilized you would expect the doctor to run tests, get to the root cause of the heart attack, and recommend measures to correct any damage done (if possible) and prevent another attack from occurring. The doctor would...