Data is an increasingly important business asset and enabler for organisational activities. With growth in data sets and data volumes, it's becoming ever harder to manage. Data quality - the fitness for purpose of data - is a key aspect of data management and failure to understand it increases organisational risk and decreases efficiency and profitability. This book explains data quality management in practical terms, focusing on three key areas - the nature of data in enterprises, the purpose and scope of data quality management, and implementing a data quality management system, in line with ISO 8000-61. Cover 1 Copyright Page 6 CONTENTS 7 LIST OF FIGURES AND TABLES 10 AUTHORS 11 ACKNOWLEDGEMENTS 13 ABBREVIATIONS 14 GLOSSARY 15 PREFACE 17 PART I THE CHALLENGE OF ENTERPRISE DATA 21 1 THE DATA ASSET 23 WHAT ARE DATA? 23 WHAT ARE DATA QUALITY? 31 WHAT IS DATA QUALITY MANAGEMENT? 34 SUMMARY 34 2 CHALLENGES WHEN EXPLOITING AND MANAGING DATA 35 THE COMPLEX DATA LANDSCAPE 35 COMPLEX DECISIONS 36 VIRTUOUS CIRCLE OR DOWNWARD SPIRAL? 36 UNCLEAR DATA OWNERSHIP 37 BACKUPS AND DATA QUALITY 37 DATA QUALITY AND LACK OF TRANSPARENCY IN BUSINESS CASES 38 THE DATA TRIANGLE 39 DATA AS A RAW MATERIAL 40 THE DATA MACHINE: EXPECTATIONS VS REALITY 40 DO YOUR DATA TRUST YOU? 41 THE CHALLENGE OF MANAGING ENTERPRISE DATA QUALITY 43 SUMMARY 44 3 THE IMPACT OF PEOPLE ON DATA QUALITY 45 COMPARISONS BETWEEN DATA QUALITY AND HEALTH AND SAFETY 45 PEOPLE AND DATA 46 THE DATA ZOO 48 HOW DATA BEHAVIOURS INTERACT 60 INDIVIDUALS AS PART OF A TEAM 60 TEAMS WITHIN THE ORGANISATION 61 DATA DEMOTIVATORS 62 SUMMARY 63 4 CASE STUDIES AND EXAMPLES 64 REAL-WORLD EXAMPLES OF THE IMPACTS OF POOR DATA 64 CASE STUDY – MARS CLIMATE ORBITER 65 CASE STUDY – MAINTENANCE PRODUCTIVITY TARGETS DEGRADING DATA QUALITY 66 CASE STUDY – RAILTRACK 67 CASE STUDY – STATUTORY REPORTING 67 CASE STUDY – OVERSIZED TRAINS 68 CASE STUDY – RETAIL FAIL 68 CASE STUDY – INAPPROPRIATE CONTROLS AND HASTE DEGRADED DATA QUALITY 69 SUMMARY 69 PART II A FRAMEWORK FOR DATA QUALITY MANAGEMENT 71 5 THE PURPOSE AND SCOPE OF DATA QUALITY MANAGEMENT 73 THE DIFFERENCE BETWEEN DATA MANAGEMENT AND DATA QUALITY MANAGEMENT 73 KEY PRINCIPLES FOR DATA QUALITY MANAGEMENT 75 SUMMARY 76 6 THE ISO 8000‐61 APPROACH 77 THE SCOPE OF ISO 8000-61 77 THE PROCESSES IN ISO 8000-61 77 SUMMARY 80 7 DATA QUALITY MANAGEMENT CAPABILITY LEVELS 81 CAPABILITY LEVEL 1 81 CAPABILITY LEVEL 2 83 CAPABILITY LEVEL 3 84 CAPABILITY LEVEL 4 86 CAPABILITY LEVEL 5 87 OVERALL CAPABILITY MODEL 87 SUMMARY 88 8 ISO 8000‐61 PROCESSES 89 DATA PROCESSING 89 PROVISION OF DATA SPECIFICATIONS AND WORK INSTRUCTIONS 91 DATA QUALITY MONITORING AND CONTROL 93 DATA QUALITY PLANNING 94 DATA‐RELATED SUPPORT 97 RESOURCE PROVISION 103 DATA QUALITY ASSURANCE 105 DATA QUALITY IMPROVEMENT 109 SUMMARY 113 9 THE MATURITY JOURNEY 114 PLANNING THE JOURNEY 114 ASSESSING MATURITY 115 SUMMARY 116 PART III IMPLEMENTING DATA QUALITY MANAGEMENT 117 10 PREPARING THE ORGANISATION FOR DATA QUALITY MANAGEMENT 119 WHAT DOES A DATA‐ENABLED ORGANISATION LOOK LIKE? 119 IMPROVEMENT OPPORTUNITIES IN TYPICAL ORGANISATIONS 121 THE DATA QUALITY MANAGEMENT JOURNEY 124 THE CASE FOR CHANGE 125 THE CHANGING ORGANISATION 128 THE ROLE OF THE CHIEF DATA OFFICER 129 PREPARING THE ORGANISATION 130 SUMMARY 131 11 IMPLEMENTING DATA QUALITY MANAGEMENT 132 OVERALL APPROACH TO DATA QUALITY MANAGEMENT IMPLEMENTATION 132 SENIOR‐LEVEL SPONSORSHIP 133 UNDERSTAND THE CONTEXT 134 IDENTIFY SYNERGIES 135 CHOOSE AN IMPLEMENTATION APPROACH 136 AGREE THE ‘FOOTPRINT’ 136 CHANGE MANAGEMENT 137 ETHICAL USE OF DATA 139 DEALING WITH CHALLENGES AND ISSUES 139 DE‐RISK EXISTING PROJECTS 140 SECURING BUDGET AND RESOURCES 141 STARTING IMPLEMENTATION 142 SUMMARY 143 12 THE HUMAN FACTOR – ENSURING PEOPLE SUPPORT DATA QUALITY MANAGEMENT 144 PEOPLE ARE THE SOLUTION 144 BEHAVIOURS AND CULTURE 145 THE EMPLOYEE DATA AGREEMENT 146 STRATEGIES FOR CHANGING DATA BEHAVIOURS 147 ORGANISATIONAL INFLUENCES ON BEHAVIOURS 149 SUMMARY 151 CONCLUSIONS 152 BIBLIOGRAPHY 154 INDEX 156 Back Cover 161
