ISBN-10:
0831134224
ISBN-13:
9780831134228
Pub. Date:
10/15/2010
Publisher:
Industrial Press, Inc.
Asset Data Integrity Is Serious Business

Asset Data Integrity Is Serious Business

by Robert S. DiStefano, Stephen ThomasRobert S. DiStefano

Hardcover

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Overview

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.

The Business Case for Data Integrity

  • Introduction to the Business Case
  • Information Overload
  • Searching for Data
  • Retiring Baby Boomers
  • The Brain Drain
  • A Business Case Example
  • Consistency or Lack Thereof
  • The Data Integrity Corporate Entitlement
  • Impact on Shareholder Value

PART 1: UNDERSTANDING THE IMPORTANCE OF ASSET DATA INTEGRITY
Plant Asset Information - A Keystone for Success
  • Overview
  • Who Are The Stakeholders?
  • Why We Wrote This Book
  • Who Will Benefit?
  • What You Will Learn
  • Chapter Synopsis
  • Let's Get Started

What is Data Integrity?
  • Defining the Terms
  • Data Elements
  • Taxonomy and Why Is It Important?
  • What We Are Looking for in Good Data
  • The Downside of Poor Data Integrity
  • A Word About Information Technology
  • Understanding Data Is Just the Beginning

The Asset / Data Integrity Life Cycle
  • About Life Cycles
  • The Asset Life Cycle
  • The Asset Data Life Cycle
  • Why the Data Life Cycle is Important
  • Roles and Responsibilities Within the Asset Life Cycle
  • It Is Never To Soon To Start
  • Life Cycle Links
  • Life Cycles as a Foundation

Data Integrity at the Task Level
  • Task vs. Strategic
  • The Data Integrity Transform
  • Data Integrity Tasks
  • Reactive Data Integrity
  • Proactive Data Integrity
  • From Reactive to Proactive

Internal Outcomes and Impacts
  • Indirect Impacts
  • Decisions Are Just the Beginning
  • Indirect Inputs
  • Indirect Outputs
  • The Legal Umbrella
  • Indirect Aspects of the Transform

External Outcomes and Impacts
  • External Issues
  • Outcomes and Impacts - Partners
  • Outcomes and Impacts - Suppliers
  • Outcomes and Impacts -Customers
  • Outcomes and Impacts -Agencies
  • Outcomes and Impacts - Public
  • Outcomes and Impacts - Insurance Carriers
  • The External Impacts Are Important

Information Technology (IT) Problems and Solutions
  • The Implication for IT
  • Implications to IT of a Modern Asset Data Management Practice
  • The Advent of ERP Systems
  • Master Data Management
  • The Future

PART 2: BUILDING A SOUND DATA INTEGRITY PROCESS
Building an Enterprise-Level Data Integrity Model
  • Historical View
  • What Is an Asset?
  • Asset Classification
  • Static Data vs. Dynamic Data
  • The Differences Among Assets, Functional
  • Locations and Functional Location Hierarchies
  • Other Asset-Related Master Data
  • Asset Master Data Structure and Formatting
  • Ideal Asset Data Repositories
  • Enterprise-Level vs. Plant-Level Asset Data Integrity

Building an Enterprise-Level Inventory Catalog Data Integrity Model
  • The Model For Material
  • What Is a Spare Part?
  • Items Classification
  • Static Data vs. Dynamic Data
  • Ideal Item Data Repositories
  • Enterprise-Level vs. Plant-Level Item Data Integrity

Data Integrity Assessment
  • Data Quality Dimensions - The Beginning
  • The Approach to the Assessment
  • The Initial Steps
  • The Assessment-General Comments
  • The Assessment Process
  • Moving Forward

Assessment Details-Assets and Material Items
  • Similar But Different
  • Assessing Asset Data
  • Assessing Material Data
  • Data Strategy Session
  • To-Be Taxonomy
  • Primary Data Fields
  • Class and Subclass
  • Manufacturer or Supplier Name
  • Asset-Model Number or Serial Number
  • Material Items-Manufacturer or Supplier Part Number
  • Attribute Templates
  • Other Asset Data Fields
  • The Goal-Quality Data for the Future

Asset Data Clean-Up and Repair
  • After the Assessment
  • Data Repair is Far from Simple
  • Repair Problems
  • Data Repair Strategies
  • The Big Bang Approach
  • Fix It As You Go
  • The Line in the Sand-More on Sustainability
  • Commitment to Doing the Work

  • PART 3: SUSTAINING WHAT YOU HAVE CREATED
    Data Governance
    • Data Governance - Insight to the Problem
    • Shifting the Burden
    • The Long Term Solution
    • The Benefits of Data Governance
    • The Jobs of Data Governance
    • It's All About Policy and Controls
    • Roles and Responsibilities
    • When Should We Start?

    Sustaining What Has Been Created
  • The Need to Sustain
  • Establishing Ownership
  • Communication
  • Process and Procedures
  • Training
  • Prepare for Data Growth
  • Walking the Walk
  • Quality Control and Quality Assurance
  • Using Key Performance Indicators
  • The Continuous Improvement Cycle
  • Sustainability Is Not Optional

Data Integrity Is Serious Business
  • Getting Started

Bibliography
Index


 

Product Details

ISBN-13: 9780831134228
Publisher: Industrial Press, Inc.
Publication date: 10/15/2010
Pages: 224
Product dimensions: 6.20(w) x 9.10(h) x 0.90(d)

Table of Contents

Acknowledgements xi

About the Authors xiii

Introduction xv

1 The Business Case for Data Integrity 1

1.1 Introduction to the Business Case 1

1.2 Information Overload 2

1.3 Searching for Data 3

1.4 Retiring Baby Boomers 4

1.5 The Brain Drain 5

1.6 A Business Case Example 6

1.7 Consistency or Lack Thereof 12

1.8 The Data Integrity Corporate Entitlement 13

1.9 Impact on Shareholder Value 16

Part 1 Understanding the Importance of Asset Data Integrity 19

2 Plant Asset Information - A Keystone for Success 21

2.1 Overview 21

2.2 Who Are The Stakeholders? 24

2.3 Why We Wrote This Book 26

2.4 Who Will Benefit? 27

2.5 What You Will Learn 29

2.6 Chapter Synopsis 30

2.7 Let's Get Started 35

3 What is Data Integrity? 37

3.1 Defining the Terms 37

3.2 Data Elements 39

3.3 Taxonomy and Why Is It Important? 44

3.4 What We Are Looking for in Good Data 45

3.5 The Downside of Poor Data Integrity 49

3.6 A Word About Information Technology 50

3.7 Understanding Data Is Just the Beginning 52

4 The Asset / Data Integrity Life Cycle 53

4.1 About Life Cycles 53

4.2 The Asset Life Cycle 55

4.3 The Asset Data Life Cycle 58

4.4 Why the Data Life Cycle is Important 67

4.5 Roles and Responsibilities Within the Asset Life Cycle 68

4.6 It Is Never To Soon To Start 70

4.7 Life Cycle Links 72

4.8 Life Cycles as a Foundation 74

5 Data Integrity at the Task Level 77

5.1 Task vs. Strategic 77

5.2 The Data Integrity Transform 78

5.3 Data Integrity Tasks 84

5.4 Reactive Data Integrity 85

5.5 Proactive Data Integrity 88

5.6 From Reactive to Proactive 89

6 Internal Outcomes and Impacts 91

6.1 Indirect Impacts 91

6.2 Decisions Are Just the Beginning 94

6.3 Indirect Inputs 97

6.4 Indirect Outputs 101

6.5 The Legal Umbrella 107

6.6 Indirect Aspects of the Transform 111

7 External Outcomes and Impacts 113

7.1 External Issues 113

7.2 Outcomes and Impacts - Partners 115

7.3 Outcomes and Impacts - Suppliers 117

7.4 Outcomes and Impacts -Customers 119

7.5 Outcomes and Impacts -Agencies 120

7.6 Outcomes and Impacts - Public 124

7.7 Outcomes and Impacts - Insurance Carriers 125

7.8 The External Impacts Are Important 126

8 Information Technology (IT) Problems and Solutions 127

8.1 The Implication for IT 127

8.2 Implications to IT of a Modern Asset Data Management Practice 128

8.3 The Advent of ERP Systems 128

8.4 Master Data Management 132

8.5 The Future 133

Part 2 Building a Sound Data Integrity Process 135

9 Building an Enterprise-Level Data Integrity Model 137

9.1 Historical View 137

9.2 What Is an Asset? 139

9.3 Asset Classification 141

9.4 Static Data vs. Dynamic Data 144

9.5 The Differences Among Assets, Functional Locations and Functional Location Hierarchies 148

9.6 Other Asset-Related Master Data 151

9.7 Asset Master Data Structure and Formatting 152

9.8 Ideal Asset Data Repositories 157

9.9 Enterprise-Level vs. Plant-Level Asset Data Integrity 160

10 Building an Enterprise-Level Inventory Catalog Data Integrity Model 165

10.1 The Model For Material 165

10.2 What Is a Spare Part? 167

10.3 Items Classification 168

10.4 Static Data vs. Dynamic Data 173

10.5 Ideal Item Data Repositories 174

10.6 Enterprise-Level vs. Plant-Level Item Data Integrity 175

11 Data Integrity Assessment 177

11.1 Data Quality Dimensions - The Beginning 177

11.2 The Approach to the Assessment 181

11.3 The Initial Steps 182

11.4 They Assessment-General Comments 183

11.5 The Assessment Process 184

11.6 Moving Forward 191

12 Assessment Details-Assets and Material Items 193

12.1 Similar But Different 193

12.2 Assessing Asset Data 194

12.3 Assessing Material Data 196

12.4 Data Strategy Session 197

12.5 To-Be Taxonomy 197

12.6 Primary Data Fields 201

12.7 Class and Subclass 202

12.8 Manufacturer or Supplier Name 208

12.9 Asset-Model Number or Serial Number 210

12.10 Material Items-Manufacturer or Supplier Part Number 213

12.11 Attribute Templates 218

12.12 Other Asset Data Fields 222

12.13 The Goal-Quality Data for the Future 224

13 Asset Data Clean-Up and Repair 225

13.1 After the Assessment 225

13.2 Data Repair is Far from Simple 226

13.3 Repair Problems 226

13.4 Data Repair Strategies 231

13.5 The Big Bang Approach 231

13.6 Fix It As You Go 234

13.7 The Line in the Sand-More on Sustainability 241

13.8 Commitment to Doing the Work 242

Part 3 Sustaining What You Have Created 245

14 Data Governance 247

14.1 Data Governance - Insight to the Problem 247

14.2 Shifting the Burden 249

14.3 The Long Term Solution 251

14.4 The Benefits of Data Governance 257

14.5 The Jobs of Data Governance 261

14.6 It's All About Policy and Controls 263

14.7 Roles and Responsibilities 266

14.8 When Should We Start? 269

15 Sustaining What Has Been Created 271

15.1 The Need to Sustain 271

15.2 Establishing Ownership 272

15.3 Communication 273

15.4 Process and Procedures 274

15.5 Training 275

15.6 Prepare for Data Growth 276

15.7 Walking the Walk 277

15.8 Quality Control and Quality Assurance 278

15.9 Using Key Performance Indicators 281

15.10 The Continuous improvement Cycle 282

15.11 Sustainability Is Not Optional 285

16 Data Integrity Is Serious Business 287

16.1 Getting Started 287

Bibliography 289

Index 293

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