Guidance on the Management of Data Assets

As asset management has evolved, it has become clear that ensuring the performance of physical assets also requires effective management of other asset types throughout their lifecycle. This has led to the development of ISO 55013:2024 – Asset management – Guidance on the management of data assets. According to its introduction, this standard “provides guidelines for the management of data when applying asset management principles or requirements for an asset management system.”

It is no surprise that data assets were prioritised by TC251, the technical committee behind the development of the ISO 55000 series of standards. Data and information play a critical role in all aspects of asset management, from decision-making and planning to asset lifecycle management and performance evaluation. Without reliable, high-quality data, achieving asset management objectives becomes unlikely.

In this article, we explore ISO 55013:2024 and discuss its implications for enhancing how organisations manage data and information in support of asset management.

What is a Data Asset?

ISO 55000:2024 defines an asset as an “item, thing or entity that has potential or actual value to an organisation.” Data, on the other hand, is defined simply as “facts about an object,” with “object” referring to “anything perceivable or conceivable.” Based on this language, we might conclude that a data asset is “any fact that has potential or actual value to an organisation,” which is indeed a broad category.

However, ISO 55013 narrows this definition. It describes a data asset as a “collection of asset data that has the properties of an asset,” where asset data refers to “data that lists and describes an asset.” Additionally, ISO 55013 clarifies that “data supporting asset management decision-making can be considered as asset data.”

From this, we arrive at a more specific working definition: a data asset is a “collection of data that lists and describes an asset, as well as data that supports asset management decision-making.”

This definition includes data that may be stored within an asset management information system or within documented information.

Data Requirements and Quality Requirements

In alignment with Clause 7.6 of ISO 55001, ISO 55013 identifies the need for organisations to determine their data requirements and the associated quality requirements. The standard points out the need for a balance of cost, risk and performance when determining quality requirements, and that data quality may be considered as analogous to asset health and assessed using similar schemas.

Data Lifecycle Stages

ISO 55013 provides a helpful specification of typical data lifecycle stages and their interrelationships:

Define: activities to provide guidance of asset data required by the organisation.
Collect: data acquisition, gathering and creation.
Store: Locating the data where it can be retrieved.
Reporting: extraction and analysis of data for use in decision-making, distribution or disposal.
Decide: making a decision based upon reports.
Distribute: extraction or copying of data for a purpose other than decision-making.
Dispose: permanently removing data that is no longer required.

These lifecycle stages may be used as a basis for establishing, formalising and integrating asset management data and information management processes.

Identifying Data Assets

Clause 6.2 of ISO 55013 “Factors identifying data assets” provides a practical list of factors that may point to the existence of a data asset. While the factors are diverse, they are underpinned by a consideration of risk to the organisation (whether the impact is a downside, or an opportunity foregone) if the asset data set is unavailable or not fit for purpose.

Guidance for Managing Data Assets

The standard sets out six areas of guidance for managing data assets.

Benefits provided by management of data assets
Identify data related to each organisational objective and strategy
Assess data availability
Applying asset management to data assets
Interoperability of the data asset
Digital preservation

The first three of these areas are discussed in more detail below.

Strategic Alignment of Asset Data Management

ISO 55013 notes that data assets may be required to support achievement of business objectives. This means that strategic plans for data assets should be aligned with organisational strategies and objectives and the strategic asset management plan. The alignment should consider both the interdependence of activities and their timing. Ensuring that data sets are ready to be used to support strategic initiatives is often a significant undertaking and requires appropriate lead-time to avoid project delays or an inability to realise benefits of the work.

Linking Data to Objectives, Strategies and Processes

The standard encourages organisations to identify data related to each organisational objective and strategy, as well as planning and decision-making processes. This enables the costs of managing the data through its lifecycle to be assessed against the risks incurred by not having the data.

As for data health, the concept of data criticality is another area where physical asset management concepts can be applied in the asset management data and information management domain. By creating linkages between data held in information systems and the impact if that data is not available, better resource allocation decisions can be made.

Data Asset Availability

Although the organisation may hold required data, it may not be available to those who need it when it is required. The availability of data assets should therefore be assessed. ISO 55013 provides a four-point scale to judge data asset availability:

Readily available, either internally or externally.
Available after internal development, for example after data has been processed or combined.
Available after procurement or data gathering activities.
Not available, which includes the situation where the data is held by the organisation but not available to asset management stakeholders.

Governance

ISO 55013 highlights the importance of good governance for both asset data and data assets. The standard recognises that governance is likely to be required from both an asset management and a data governance perspective. From the asset management perspective, the key priority is ensuring that asset data meets the needs of asset management. From the data governance perspective, the focus is on ensuring that the management of asset data aligns with the organisation’s broader data management requirements. While these perspectives often overlap, without a strong influence from the asset management function, data governance risks becoming purely a technical exercise with little connection to the ultimate goal of realising value from assets.

ISO 55013 suggests that the “evaluate, direct, monitor” (EDM) model for governance may be suitable for ensuring effective governance of asset data and data assets. In this model, "evaluate" involves the governance function assessing potential data asset management activities to meet asset management objectives. "Direct" refers to the governance function developing data strategies and policies for data governance. Finally, "monitor" involves overseeing the performance and compliance of asset data and data asset management activities.

Conclusion

Asset management requires a whole-of-organisation approach to ensure value is realised from physical assets. However, the importance of asset data in achieving this goal is not always fully understood. Even when it is, many organisations lack the necessary data literacy to implement effective governance and management processes. ISO 55013 advances the asset management data and information field by clearly stating that asset data can be recognised as organisational assets. It also provides guidance to help organisations enhance their capabilities and performance in this area.

Furthermore, this standard opens the door for other intangible assets, typically managed within the asset management system, to be acknowledged for the value they generate. These include knowledge (both documented and tacit), as well as asset management capability and knowhow, which manifest in processes, ways of working, and relationships between teams.

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