For Business Process Professionals

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	April 24, 2006 Next-Generation Enterprise Asset Management Moving From A Reactive To Predictive State Of Maintenance by Patrick M. Connaughton with Noha Tohamy, Elisse Gaynor	Average: 8  (2 ratings)

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Executive Summary

Enterprise Asset Management (EAM) solutions have been on the market for more than two decades and range in sophistication from basic work order generation to predictive analysis of future asset performance. As of late, emerging technologies have sparked a renewed interest in EAM, but, overall, user adoption continues to suffer. This is due in part to ongoing challenges like inconsistent data quality and poor usability. While EAM vendors are providing incremental product enhancements to address these immediate issues, they typically fall short when it comes to enabling the next level of asset optimization: Predictive Maintenance (PdM). To achieve a predictive state, firms not only need the technology solution but also a strong foundation of supporting processes. To get there, firms need to conduct a thorough assessment to gauge the strengths and weaknesses of the current processes, especially before taking on system upgrades or new installs. While this is often a daunting task, well-defined frameworks like the Reliability Centered Maintenance (RCM) methodology are available to help streamline the project. For those looking to jumpstart these initiatives, Forrester recommends running the business case for employing a full-service outsourcing company to manage the operations.

TABLE OF CONTENTS

• New Technologies Reenergize Enterprise Asset Management
• Solution Providers Seek To Meet Clients' Evolving EAM Needs
• Reactive Culture Hinders Wide EAM Adoption
• EAM Solution Providers Focus On Adoption Challenges
• To Achieve PDM, EAM Solutions Need To Move Upstream

RECOMMENDATIONS

• Reliability-Centered Maintenance: The First Step In EAM Transformation

WHAT IT MEANS

• Maintenance Outsourcing Can Expedite The Asset Management Transformation
• Related Research Documents

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