Building resilience in the energy sector with data-driven asset intelligence

In light of recent developments such as regulation, threats, and energy disruption, resilience has become a strategic goal for energy companies, transmission system operators and grid operators. In achieving resilience, a data-driven approach to asset management is a central step to take, write experts from OHROS Consulting Group.

From the devastating blackouts in Spain, Portugal, and Chile to escalating geopolitical instability and cyber threats targeting critical infrastructure, the world is witnessing a new era of systemic disruption. In such a volatile context, energy companies, particularly transmission system operators (TSOs) and grid operators face an urgent challenge: how to remain resilient.

Why Resilience Matters Now More Than Ever

The European Union’s 2023 Critical Entities Resilience (CER) Directive has elevated this issue to a regulatory imperative. But compliance is only part of the story. In a survey of executives at TSOs conducted by OHROS Consulting Group, three major threat vectors have emerged as top concerns:

Cybersecurity (rated high/very high by 81% of respondents)
Impact: Network shutdowns, loss of supply, and regulatory exposure.

Operational Efficiency (rated high/very high by 72%)
Impact: Understaffing, overwhelmed resources, and asset performance risks.

Regulatory Compliance (rated high/very high by 45%)
Impact: Health, safety, and reputational risks affecting CAPEX and OPEX decisions.

In all these cases, the consequences extend beyond asset integrity to public safety, customer trust, and business continuity. To counter, mitigate and manage these concerns, building resilience in operations, assets and services is key.

Asset Intelligence as a Pillar of Resilience

At the core of operational resilience lies data, not just volumes of it, but quality, structure, and strategic relevance.

Energy utilities are working on ambitious digital transformation agendas. The shift is toward intelligence-driven asset management, moving away from gut-feeling decisions toward analytics supported strategies. Yet while sensor networks, IoT devices, and AI systems are generating more data than ever, many organizations find themselves drowning in “data lakes” without value.

A recent MIT study revealed that only 13% of companies excel at data management, leaving a vast majority vulnerable to poor decisions stemming from untrustworthy data. The risks are evident – relying on unreliable data cultivates false intelligence, leading to budget overruns and delivery failures.

The need for asset intelligence is amplified by the convergence of a number of megatrends that are impacting the energy sector. These include:

Digitalization
Open data management, real-time monitoring, and predictive maintenance are no longer aspirational, they are minimum requirements.

Energy Transition
From managing variability from renewable energy sources to retiring fossil assets, data governance is central to enabling decarbonization at scale.

Natural disasters
Heatwaves, floods, and storms are degrading asset performance. Resilience now means condition-based maintenance rooted in live performance data.

The Trust Gap in Asset Data

Our research found that executives across asset-intensive sectors are increasingly expressing distrust in the quality of their own asset data. This “trust gap” creates a cascade of challenges:

• Misguided investment strategies
• Flawed maintenance planning
• Regulatory exposure due to reporting inconsistencies
• Unclear pathways to decarbonization goals

In other words, the fallout is not theoretical, it is operational, financial, and reputational.

Closing the Gap: From Raw Data to Resilient Strategy

To address these issues, energy companies must tackle three core pain points:

Fragmented Data Sources
Asset information exists across disconnected Configuration Management Databases, Excel sheets, legacy systems, and unstructured reports.

Lack of Governance Frameworks
Without standards for collection, validation, and usage, even the most advanced systems yield noise instead of intelligence.

Skills Deficit
Technological tools are only as effective as the human insights that guide them. A new class of digital talent-engineers fluent in data science and operational realities is essential.

A Strategic Framework for Resilience

OHROS Consulting Group, in partnership with MetaDino, has developed a strategic approach that blends business and machine data, enabling:

• Confidence in investment decisions
• Greater regulatory readiness
• Improved operational efficiency
• Proactive, condition-based maintenance
• Real-time threat response

By unifying data silos and restoring trust in the data lifecycle, organizations can evolve from reactive risk mitigation to proactive resilience building.

Conclusion

Resilience in the energy sector goes beyond merely hardening infrastructure – it hinges on intelligent decision-making rooted in reliable, high-quality data. While increasing regulatory pressures, such as the EU Critical Entities Resilience Directive, are accelerating the need for action, the true strategic advantage lies in moving beyond mere compliance.

For energy companies seeking long-term viability and competitiveness, investing in digital governance and data capabilities is no longer optional – it is essential.