Asset data integrity is serious business

If your asset data is not reliable, you need to convince the organization of the enormous potential that is locked away. To accomplish this, you need to understand the breadth of the problem and the value of solving it. A viable business case for action is needed-so let's get started!

Physical asset data integrity is a critical aspect of every business, often the most valuable asset on the balance sheet, yet it is often overlooked. The data that we have about our assets collectively creates information, provides for accurate analysis and facilitates sound business decisions. Without accuracy of asset data there is a strong potential for poor decisions and their negative consequences. This book will not only provide an appreciation of this fact, it will also provide a road map to achieving value out of something most CEOs, managers, and workers often overlook.

Author Notes

Robert S. DiStefano is Chairman of the Board and CEO of Management Resources Group, Inc. He has spent over 30 years working in physical asset management, including over 20 years focused on asset data integrity, spanning 14 industries and across many enterprises.
Stephen J. Thomas has worked in the reliability and maintenance arena for 40 years, and for the past seven he has managed an internal data integrity team at a major company in the petro-chemical industry.

Acknowledgements	p. xi
About the Authors	p. xiii
Introduction	p. xv
1 The Business Case for Data Integrity	p. 1
1.1 Introduction to the Business Case	p. 1
1.2 Information Overload	p. 2
1.3 Searching for Data	p. 3
1.4 Retiring Baby Boomers	p. 4
1.5 The Brain Drain	p. 5
1.6 A Business Case Example	p. 6
1.7 Consistency or Lack Thereof	p. 12
1.8 The Data Integrity Corporate Entitlement	p. 13
1.9 Impact on Shareholder Value	p. 16
Part 1 Understanding the Importance of Asset Data Integrity	p. 19
2 Plant Asset Information - A Keystone for Success	p. 21
2.1 Overview	p. 21
2.2 Who Are The Stakeholders?	p. 24
2.3 Why We Wrote This Book	p. 26
2.4 Who Will Benefit?	p. 27
2.5 What You Will Learn	p. 29
2.6 Chapter Synopsis	p. 30
2.7 Let's Get Started	p. 35
3 What is Data Integrity?	p. 37
3.1 Defining the Terms	p. 37
3.2 Data Elements	p. 39
3.3 Taxonomy and Why Is It Important?	p. 44
3.4 What We Are Looking for in Good Data	p. 45
3.5 The Downside of Poor Data Integrity	p. 49
3.6 A Word About Information Technology	p. 50
3.7 Understanding Data Is Just the Beginning	p. 52
4 The Asset / Data Integrity Life Cycle	p. 53
4.1 About Life Cycles	p. 53
4.2 The Asset Life Cycle	p. 55
4.3 The Asset Data Life Cycle	p. 58
4.4 Why the Data Life Cycle is Important	p. 67
4.5 Roles and Responsibilities Within the Asset Life Cycle	p. 68
4.6 It Is Never To Soon To Start	p. 70
4.7 Life Cycle Links	p. 72
4.8 Life Cycles as a Foundation	p. 74
5 Data Integrity at the Task Level	p. 77
5.1 Task vs. Strategic	p. 77
5.2 The Data Integrity Transform	p. 78
5.3 Data Integrity Tasks	p. 84
5.4 Reactive Data Integrity	p. 85
5.5 Proactive Data Integrity	p. 88
5.6 From Reactive to Proactive	p. 89
6 Internal Outcomes and Impacts	p. 91
6.1 Indirect Impacts	p. 91
6.2 Decisions Are Just the Beginning	p. 94
6.3 Indirect Inputs	p. 97
6.4 Indirect Outputs	p. 101
6.5 The Legal Umbrella	p. 107
6.6 Indirect Aspects of the Transform	p. 111
7 External Outcomes and Impacts	p. 113
7.1 External Issues	p. 113
7.2 Outcomes and Impacts - Partners	p. 115
7.3 Outcomes and Impacts - Suppliers	p. 117
7.4 Outcomes and Impacts -Customers	p. 119
7.5 Outcomes and Impacts -Agencies	p. 120
7.6 Outcomes and Impacts - Public	p. 124
7.7 Outcomes and Impacts - Insurance Carriers	p. 125
7.8 The External Impacts Are Important	p. 126
8 Information Technology (IT) Problems and Solutions	p. 127
8.1 The Implication for IT	p. 127
8.2 Implications to IT of a Modern Asset Data Management Practice	p. 128
8.3 The Advent of ERP Systems	p. 128
8.4 Master Data Management	p. 132
8.5 The Future	p. 133
Part 2 Building a Sound Data Integrity Process	p. 135
9 Building an Enterprise-Level Data Integrity Model	p. 137
9.1 Historical View	p. 137
9.2 What Is an Asset?	p. 139
9.3 Asset Classification	p. 141
9.4 Static Data vs. Dynamic Data	p. 144
9.5 The Differences Among Assets, Functional Locations and Functional Location Hierarchies	p. 148
9.6 Other Asset-Related Master Data	p. 151
9.7 Asset Master Data Structure and Formatting	p. 152
9.8 Ideal Asset Data Repositories	p. 157
9.9 Enterprise-Level vs. Plant-Level Asset Data Integrity	p. 160
10 Building an Enterprise-Level Inventory Catalog Data Integrity Model	p. 165
10.1 The Model For Material	p. 165
10.2 What Is a Spare Part?	p. 167
10.3 Items Classification	p. 168
10.4 Static Data vs. Dynamic Data	p. 173
10.5 Ideal Item Data Repositories	p. 174
10.6 Enterprise-Level vs. Plant-Level Item Data Integrity	p. 175
11 Data Integrity Assessment	p. 177
11.1 Data Quality Dimensions - The Beginning	p. 177
11.2 The Approach to the Assessment	p. 181
11.3 The Initial Steps	p. 182
11.4 They Assessment-General Comments	p. 183
11.5 The Assessment Process	p. 184
11.6 Moving Forward	p. 191
12 Assessment Details-Assets and Material Items	p. 193
12.1 Similar But Different	p. 193
12.2 Assessing Asset Data	p. 194
12.3 Assessing Material Data	p. 196
12.4 Data Strategy Session	p. 197
12.5 To-Be Taxonomy	p. 197
12.6 Primary Data Fields	p. 201
12.7 Class and Subclass	p. 202
12.8 Manufacturer or Supplier Name	p. 208
12.9 Asset-Model Number or Serial Number	p. 210
12.10 Material Items-Manufacturer or Supplier Part Number	p. 213
12.11 Attribute Templates	p. 218
12.12 Other Asset Data Fields	p. 222
12.13 The Goal-Quality Data for the Future	p. 224
13 Asset Data Clean-Up and Repair	p. 225
13.1 After the Assessment	p. 225
13.2 Data Repair is Far from Simple	p. 226
13.3 Repair Problems	p. 226
13.4 Data Repair Strategies	p. 231
13.5 The Big Bang Approach	p. 231
13.6 Fix It As You Go	p. 234
13.7 The Line in the Sand-More on Sustainability	p. 241
13.8 Commitment to Doing the Work	p. 242
Part 3 Sustaining What You Have Created	p. 245
14 Data Governance	p. 247
14.1 Data Governance - Insight to the Problem	p. 247
14.2 Shifting the Burden	p. 249
14.3 The Long Term Solution	p. 251
14.4 The Benefits of Data Governance	p. 257
14.5 The Jobs of Data Governance	p. 261
14.6 It's All About Policy and Controls	p. 263
14.7 Roles and Responsibilities	p. 266
14.8 When Should We Start?	p. 269
15 Sustaining What Has Been Created	p. 271
15.1 The Need to Sustain	p. 271
15.2 Establishing Ownership	p. 272
15.3 Communication	p. 273
15.4 Process and Procedures	p. 274
15.5 Training	p. 275
15.6 Prepare for Data Growth	p. 276
15.7 Walking the Walk	p. 277
15.8 Quality Control and Quality Assurance	p. 278
15.9 Using Key Performance Indicators	p. 281
15.10 The Continuous improvement Cycle	p. 282
15.11 Sustainability Is Not Optional	p. 285
16 Data Integrity Is Serious Business	p. 287
16.1 Getting Started	p. 287
Bibliography	p. 289
Index	p. 293

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Table of Contents