David Nollet on ISO 14224 for Master Data

When it comes to structuring industrial master data, few voices are as respected as David Nollet’s, a Mechanical Engineer and Reliability Consultant at Laurentide Controls with years of field experience.

Nollet has worked extensively with standards and frameworks that shape how organizations manage equipment information for multiple years. Among these, ISO 14224 stands out, and Nollet has clear views on its value, its limitations, and why reliability professionals should pay attention.

Master data forms the backbone of business operations by defining core data entities such as, products, suppliers, and assets. These entities are grouped into data domains, which represent the essential categories that support key business processes and data governance strategies.

Effective master data management (MDM) ensures that this critical information is accurate, consistent, and up-to-date across multiple systems, eliminating data silos and reducing the risk of errors.

Data consolidation plays a key role in this process by integrating information from disparate systems, supporting operational efficiency and informed decision-making. Departments such as finance, customer service, and operations rely on high-quality master data.

For manufacturing and asset-intensive organizations, master data governance is also essential for optimizing inventory management, reducing downtime, and improving overall operational efficiency.

Data Governance

Data governance is the framework that ensures an organization’s data assets are managed responsibly, securely, and effectively. It involves setting clear policies, procedures, and standards for data management, as well as defining the roles of data owners and data stewards who are accountable for maintaining data quality and integrity.

Strong data governance is essential for achieving regulatory compliance, minimizing data risks, and maximizing operational efficiency. By leveraging data governance tools and establishing a comprehensive data governance framework, organizations can enforce governance policies, monitor data quality, and ensure that customer master data, product data, and supplier data are managed consistently across the enterprise.

Master data governance is a specialized area within data governance that focuses on the stewardship and control of master data entities. It ensures that critical data is accurate, secure, and aligned with business objectives. Effective data governance not only protects valuable data assets but also empowers organizations to make informed decisions, improve data quality management, and drive business success.

Data Integrity

Data integrity is the cornerstone of trustworthy and reliable master data. It refers to the accuracy, completeness, and consistency of data assets throughout their lifecycle. Maintaining data integrity is vital for supporting effective business processes, ensuring regulatory compliance, and enabling confident decision-making.

Common data integrity challenges, such as duplicate records, inaccurate data, and inconsistencies, can lead to operational inefficiencies, poor customer experiences, and increased risk of non-compliance. To address these issues, organizations must implement robust data validation rules, conduct regular data quality checks, and invest in data cleansing processes that remove errors and standardize information.

Governance policies and master data management solutions, including platforms like SAP Master Data Governance, or ISO 14224 provide the structure and tools needed to safeguard data integrity. By embedding data quality management practices into daily operations, organizations can ensure that their master data remains reliable, supports business objectives, and delivers value across all areas of the enterprise.

Why ISO 14224 Matters for Asset Data

Because reliability is non-negotiable in these industries, they have historically been at the forefront of maintenance and reliability practices. David Nollet points out that this context is critical: if a standard can help these industries manage risk, it naturally provides a strong foundation for others.

Broader Relevance Across Industries

While ISO 14224’s roots are in oil and gas, David Nollet emphasizes that its insights are far-reaching. Manufacturers, utilities, and other asset-intensive sectors can benefit from the standard’s approach to data collection, taxonomy, and reliability definitions. In these industries, the quality and consistency of asset data and operational data are crucial for supporting maintenance, reliability, and overall business performance. The challenges of equipment failure, data inconsistency, and unclear terminology exist everywhere, not just offshore rigs or refineries.

What ISO 14224 Provides for Data Quality

Data Requirements and Formats

At its core, ISO 14224 does two things.

• First, it specifies which data organizations should record for maintenance, reliability, and regulatory purposes.
• Second, it defines the formats in which that data should be captured.

This standardization is what makes information easier to compare, analyze, and apply across different assets and operations.

A Common Language for Maintenance & Reliability

For Nollet, an aspects of ISO 14224 is its role as a dictionary for the field. It defines fundamental terms (failure, failure mode, failure cause, component, risk matrix, etc.) and standardizes their use.

This shared language reduces ambiguity and ensures that everyone, from engineers to managers, speaks about reliability in the same way. Taxonomies and classification lists not only support consistent categorization but also facilitate the management of different master data domains within maintenance and reliability.

Practical Tools and Guides

The richness of ISO 14224 lies in its annexes, which make up a large portion of the document. These are not just appendices, they are practical resources that reliability professionals can use directly in their work. They include:

• Templates for data collection that show exactly how information should be structured, along with data quality rules to enforce consistency, standardization, and accuracy.
• Taxonomies and classification lists that help categorize equipment consistently, from common assets like pumps to more specialized components.
• Failure mode libraries that associate likely failure mechanisms with different classes of equipment, saving organizations from reinventing the wheel.
• Examples and case structures that demonstrate how to apply definitions in practice.
• Suggested asset hierarchies that give organizations a starting point for structuring their data.

Managing the data lifecycle is essential, and the annexes support data lifecycle management practices by providing guidance for overseeing data from creation through ongoing use to archiving or deletion, ensuring data accuracy and compliance throughout its existence.

Nollet emphasizes that these resources are particularly valuable for those new to maintenance and reliability. Instead of struggling with vague concepts, professionals can reference ready-made examples that show how to put theory into action.

When applying these standards, organizations may encounter limitations or unique requirements. Flexibility is important, and effective change management plays a key role in adapting standards and processes to fit evolving organizational needs while maintaining data quality and governance.

David Nollet’s Perspective on ISO 14224

A Solid Foundation, But Not Absolute

Nollet stresses that ISO 14224 is one of the most useful resources available for structuring master data. It helps improve data quality, brings order to asset information, and creates a common ground for decision-making across teams. In his view, it can make the difference between an organization struggling with scattered, inconsistent data and one that uses information as a strategic asset.

Yet Nollet add a word of caution: the standard should not be treated as the only source of truth. Blindly applying ISO 14224 without considering the specific realities of an organization can backfire. Every company has unique processes, constraints, and operational contexts, including how and where data is stored across different platforms.

On Equipment Boundaries and Classifications

One of the strengths of ISO 14224 is its guidance on how to define equipment boundaries. By clearly stating what is included in a piece of equipment, and what is not, organizations can avoid confusion when recording failures, assigning maintenance tasks, or analyzing performance data.

Nollet highlights that this clarity is especially useful in complex plants, where misunderstandings about “where the pump ends and the motor begins” can easily lead to inconsistent data.

In addition, the standard offers a detailed list of equipment classes and characteristics, covering a wide range of common industrial assets. For widely used equipment such as pumps, compressors, and valves, these classifications give organizations a ready-made structure to record information in a consistent way.

Yet Nollet points out that the guidance does not always go far enough. In real operations, equipment often exists in configurations that are more complex than the examples presented in the standard. Boundaries may overlap and site-specific modifications may blur the lines.

Flexibility in Asset Taxonomy

ISO 14224 gives guidance on asset taxonomy particularly with a suggested pyramid hierarchy for organizing equipment. This structure lays out levels that move from systems down to components, offering a logical way to break down complex plants into manageable units. For many organizations, especially those starting from scratch, it provides a clear framework for building an equipment hierarchy without guesswork.

Every organization has its own context, from how assets are maintained, to the way operations are structured, to the constraints of their CMMS. Applying the pyramid without adjustment can lead to friction, unnecessary complexity, or data structures that do not reflect how work is actually done. Defining and managing data processes is essential to ensure consistency between workflows and the realities of daily operations.

Limits in CMMS Integration

While ISO 14224 offers robust guidance on data and taxonomy, it was never designed with specific Computerized Maintenance Management Systems (CMMS) in mind. This creates a natural tension: organizations may find that some of the standard’s recommendations do not map neatly onto the fields, structures, or workflows available in their chosen system.

Nollet notes that this mismatch can cause frustration. For example, a CMMS may not support the same depth of equipment classifications, or it may use terminology that differs from ISO definitions. Similarly, the way the system structures locations, systems, and components may not perfectly align with the hierarchy suggested by the standard. Legacy systems, in particular, can pose significant challenges, as their outdated and inflexible platforms often do not support modern data governance or integration needs.

This does not mean that ISO 14224 should be set aside. On the contrary, Nollet sees the gap as a reminder that standards and tools must be reconciled thoughtfully, not forced together. Managing master data is an ongoing effort that requires continuous attention to data quality, integration, and alignment with evolving business needs.

Why Reliability Professionals Should Care

A Learning Tool for Beginners

For those just entering the world of maintenance and reliability, Nollet strongly recommends ISO 14224 as a starting point. It provides a comprehensive overview of how data should be managed and what reliability really means in practice.

A Data Quality Enabler

For more seasoned professionals, its biggest value lies in data quality. By standardizing definitions and formats, ISO 14224 makes master data more reliable, more comparable, and ultimately more actionable. Data stewardship and the role of the data owner are essential for maintaining quality data and addressing data quality issues within this framework.

Governed master data and reliable data support better decision-making by ensuring consistency and trustworthiness across systems. Inconsistent data can lead to poor data quality, so strong data policies and a focus on data consistency are necessary to prevent errors and inefficiencies.

Adhering to data privacy regulations is also critical for compliance and protecting sensitive information. Data teams play a collaborative role in supporting master data quality and helping business users adopt governance practices. This is why master data governance important for achieving organizational success.

Final Thoughts from David Nollet

For David Nollet, ISO 14224 is far more than a technical document, it is a cornerstone for anyone serious about building reliable, high-quality master data. Its definitions, taxonomies, and practical tools give professionals a common framework to collect, structure, and interpret information in a consistent way. Yet Nollet is equally clear: no standard should ever replace professional judgment.

The strength of ISO 14224 lies in how it equips organizations to think more clearly about reliability and data quality. But its true value emerges only when professionals adapt its recommendations to their own context, balancing structure with flexibility.

For reliability professionals at every level, from beginners seeking clarity to experts striving for consistency, Nollet’s message is simple: ISO 14224 is a foundation worth building on, but the blueprint is yours to complete.