In the world of asset management, assets like machinery, vehicles, and buildings have long been subject to rigorous condition assessments and maintenance schedules. However, when it comes to data assets, organisations often struggle to operate with the same level of scrutiny.
While businesses generally recognise that both physical and data assets degrade over time, a crucial difference emerges: with physical assets, we often understand the problems but lack the resources to fix them. With data assets, we acknowledge issues exist, but don’t know precisely what needs to be resolved.
The condition of physical assets vs. data assets
Physical assets: known problems with limited resources
Physical assets degrade in ways we understand and can manage – even when events are unpredictable, teams have tools and methods to respond effectively. Wear and tear, environmental factors, and regular usage contribute to their declining condition. Industries use established frameworks, like ISO 55000, to align asset management with organisational goals — supporting risk-based decisions, continuous improvement, and value realisation from assets.
- Condition visibility: physical assets can be inspected visually or measured using predefined metrics.
- Predictability: the failure modes of physical assets are well understood, allowing for preventive maintenance planning.
- Resolution challenge: however, even when degradation is known, budget constraints, resource limitations, and operational disruptions often prevent immediate resolution.
Example: a manufacturing firm with 1,000 machines might estimate that 20% are operating at suboptimal efficiency, costing an additional ÂŁ500,000 annually in energy and maintenance costs. Despite knowing the issue, financial and operational constraints might delay repairs or replacements.
Data assets: unknown issues with hidden impacts
Data assets, by contrast, suffer from a lack of visibility into their condition. Organisations often suspect that their data is not in the best shape—missing values, inconsistencies, outdated records—but struggle to pinpoint what specifically needs fixing.
- Condition complexity: unlike physical assets, data condition issues are often intangible. Missing context, ambiguity in business requirements, and a lack of accessibility makes tackling data issues complex.
- Resolution uncertainty: even if businesses allocate resources to data quality improvements, without clear diagnostics, they risk investing in the wrong fixes.
- Lack of predictability: data deterioration can be hard to track systematically, especially without robust governance frameworks.
Example: a financial services company may discover that 30% of its customer records contain incomplete or outdated information, leading to failed credit checks and ÂŁ2 million in lost loan approvals annually. Yet, without a clear assessment framework, they cannot determine where to focus remediation efforts.
Bridging the gap: applying asset management principles to data
To manage data assets effectively, businesses should adopt methodologies from physical asset management:
- Condition assessment frameworks: develop standardised ways to measure data condition, much like how industries use performance indicators for physical assets.
- Clear accountability: assign ownership to data assets just as organisations have facility managers or equipment custodians.
- Investment prioritisation: align data quality initiatives with business objectives to ensure resources are allocated effectively.
- Preventive maintenance for data: establish proactive data governance strategies to prevent degradation before it becomes costly.
Conclusion
Understanding the parallels between physical and data assets helps businesses make informed decisions about managing both effectively. While organisations may not always have the immediate means to fix physical assets, they at least understand the problems. With data, the challenge is different—knowing that issues exist but lacking clarity on what to resolve.
By adopting structured approaches, similar to those used for physical assets, businesses can improve their data condition, ultimately driving greater value from their most overlooked asset.
Get in touch
If your organisation is struggling to assess and improve its data condition, consider implementing a structured data strategy. At Anmut, we specialise in helping businesses uncover hidden data issues and align their data assets with business goals. Get in touch to learn how we can help you maximise the value of your data.