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: let’s get started.
Asset Data Integrity is Serious Business discusses physical asset data integrity, a critical aspect of every business. It is 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.
Features
Relies on the authors’ decades of experience and hands-on expertise that cannot be obtained elsewhere.
Includes an assessment tool enabling the reader to easily recognize areas of improvement once a problem is detected.
Features a valuable practical “how to” information.
Focuses on the entire management spectrum, allowing everyone to see the value of data integrity within the context of their own responsibilities.
Robert S. DiStefano, CMRP, previously was Chairman and CEO of Management Resources Group, Inc. Recently, he joined Performance Consulting Associates (PCA), a leading provider of maintenance, inventory, and change management solutions as Chief Operations Officer. He is an accomplished executive manager with more than 35 years of professional engineering, maintenance, reliability, management, and consulting experience.
Steve Thomas has more than 45 years of experience working in the petrochemical industry. He has published six books through Industrial Press, Inc., and Reliabilityweb.com, the most recent being Asset Data Integrity is Serious Business and Measuring Maintenance Workforce Productivity Made Simple.
Contents
Acknowledgements
About the Author
Introduction
1-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
2-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
3-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
4-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
5-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
6-Internal Outcomes and Impacts
Indirect Impacts
Decisions Are Just the Beginning
Indirect Inputs
Indirect Outputs
The Legal Umbrella
Indirect Aspects of the Transform
7-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
8-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
9-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
10-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
11-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
12-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