The Asset Journal

The Asset Journal, Volume 20, Issue 3

The general theme for this edition of “The Asset” is about evidence and how we use information about Assets in our care. There have been many papers and opinion pieces written in the past five years or more relating to data and its importance to Business and particularly to Asset Management. The advent and proliferation of Artificial Intelligence systems have made it very clear how much we depend on correct data and responsible transformation into information that is useful in decision making. AI can only create value when it is built on accurate, trusted and well-managed data.

My experience, which is underpinned by current Industry realisation is, that we still have insufficient understanding of data that is required and consequently cannot fully trust data that is stored in our repositories. Evidence-based asset management depends on treating data as an asset in its own right, supported by a defined management framework, strategic objectives, governance, and lifecycle controls. During a recent assignment to implement an Asset Management system for an overseas mega project, I learned more about the way evidentiary data and information can be built. The key is the treatment of data as an Asset that requires its own interconnected and defined management framework.

When we speak about interconnection, we address interoperability. Asset data must move across functions, departments and systems from a single trusted source, rather than being duplicated and fragmented across isolated repositories. Interoperability is central to this outcome. Building Information Management systems demonstrate the value of this approach, particularly when supported by common data definitions, clear information requirements, and agreed methods for storing, accessing and transforming data into decision-ready information. Some time ago, the International Standards Organisation ISO undertook the development of an interoperability standard for data and documentation (ISO 25964) among others for enterprise interoperability.

A key part is the governance of that data management system, which may require to have a new function in an organisation, a person responsible for this critical governance role at the highest level. Asset Information Strategies and Operational Information Strategies provide the foundation for turning raw data into reliable evidence and maintaining its integrity over time. These are but two of the critical plans and documentation that will underpin the ability to develop data into evidentiary information.

One way of achieving this ideal state is to define attributes for all Assets that exist in an organisation. These attributes can be assigned  to the various end users and form the basis for evidence-based information. Sounds good? It is – but: are we prepared to reform our current data sets and management? Data management and maintenance costs money just as Asset maintenance does.   

If we want to take full advantage of the promise that AI offers, we must make the effort to reconstruct our data and data management. Evidence based Asset Management may otherwise remain a dream for the future and make the investment in AI a failure. Do you agree? What is the status in your organisation? As always, we like to hear from you about your experiences.

This edition of The Asset focuses on evidence: how organisations collect, govern and apply asset information to make better decisions. Over recent years, data has become a central theme in business and asset management. The rapid growth of artificial intelligence has further highlighted a simple reality: AI can only create value when it is built on accurate, trusted and well-managed data.

In practice, many organisations still lack a clear understanding of what data is required, where it resides and whether it can be trusted. Evidence-based asset management depends on treating data as an asset in its own right, supported by a defined management framework, strategic objectives, governance, and lifecycle controls. A recent overseas mega-project reinforced this point: evidentiary information is not created by systems alone; it is built through disciplined data ownership, structure and accountability.

Interoperability is central to this outcome. Asset data must move across functions, departments and systems from a single trusted source, rather than being duplicated and fragmented across isolated repositories. Building Information Management systems demonstrate the value of this approach, particularly when supported by common data definitions, clear information requirements, and agreed methods for storing, accessing and transforming data into decision-ready information.

Strong governance is therefore essential. Asset Information Strategies and Operational Information Strategies provide the foundation for turning raw data into reliable evidence and maintaining its integrity over time. Defining asset attributes, assigning ownership, and aligning data requirements with user needs are practical steps toward this goal. However, this also requires investment: data management carries an ongoing cost, just as asset maintenance does.

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