Applying an asset information maturity model in New Zealand's electricity sector
Asset Dynamics Director Jules Congalton presented a paper at the Electricity Engineers' Association Conference in September 2022 on the application of an asset information maturity model to improve outcomes in New Zealand's electricity distribution sector. This article summarises the framework and its practical application.
Jules presenting at EEA Conference 2022
Why asset information maturity matters
Asset information is the foundation on which responsible asset management rests. Without accurate and complete data, an organisation cannot understand the condition of its network or make sound asset management decisions. Over time, basing decisions on poor data results in diminished reliability, increased costs, and at the most serious level, risk to the safety of workers and the public.
It is not sufficient simply to know that gaps or errors exist in asset data. What matters is understanding the risks those gaps create — whether they are likely to negatively impact customer service, fall short of regulatory obligations, or put lives at risk. Only once the impact is understood can intelligent and prudent decisions about improving asset data be made.
Asset information maturity models provide a structured way to assess an organisation's asset information processes, governance structures, and culture, revealing strengths, risks, and opportunities for improvement.
The EEA Asset Information Maturity Framework
Jules Congalton led the development of the EEA Asset Information Maturity Framework as chair of the EEA's Asset Information Managers' Forum. Published in December 2021, the framework provides maturity models and tools to assess the current state of asset information management across four capability areas, drawn from the IAM Asset Management: An Anatomy and the GFMAM Asset Management Landscape.
Asset Information Strategy covers the alignment of asset information management with corporate business objectives, including the definition of present and future information requirements, data lifecycle management, governance structures, and roles and responsibilities.
Asset Information Standards covers the specification of consistent structure and format for collecting and storing asset information, including data collection standards, information requirements, data quality requirements, and monitoring of non-conformances.
Asset Information Systems covers the hardware, software, and architectural configuration of the systems that store asset information, including governance of system access, security, availability, and integration with operational processes.
Data and Information Management covers the governance, lifecycle management, and continuous improvement of data held within the organisation's asset information systems, including data quality assurance, change management, and data security.
The five maturity levels
The framework uses five maturity levels that apply consistently across all four capability areas.
Level 1, Ad hoc: Data quality problems are treated as an acceptable part of normal business and addressed reactively on a localised, short-term basis.
Level 2, Aware: There is awareness across the organisation that data quality problems are repeated and widespread, triggering at least one business case to address them.
Level 3, Defined: Senior management understands that poor data quality is an enduring, organisation-wide problem. The organisation begins to move from reactive responses to proactive, long-term cultural change.
Level 4, Managed: All employees understand they are personally responsible for ensuring good quality data is supplied to their customers and colleagues.
Level 5, Optimised: There is an understanding that continuous improvement of data quality is essential to the survival of the business, and all staff are engaged in this improvement.
In general, an organisation operating at Level 3 across the four capability areas is meeting the information requirements of ISO 55001:2024 clause 7.6.
Applying the framework
The framework is designed to be used as a self-assessment tool. Organisations assess their current maturity level across each of the four capability areas, identify gaps between current and desired state, and develop an improvement strategy and implementation plan to close those gaps.
A key principle of the framework is that process improvement must precede data improvement. If the processes surrounding the collection of data are broken, cleaning historic data will simply be undone as corrupted data continues to be added. Fixing the process first is essential before investing in data remediation.
The conference paper presents case studies of how the framework has been applied in New Zealand electricity distribution businesses to identify strengths and opportunities for improvement in asset information governance and quality assurance. The full paper is available to download on our Thought Leadership page.
Want to assess your organisation's asset information maturity?Asset Dynamics works with infrastructure organisations to evaluate and improve asset information strategy, governance, and data quality.
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