For years, technological resilience was measured with two numbers: RTO (how long it takes the company to resume operations) and RPO (how much data can be lost). Today, that metric falls short. Regulatory pressure — and also that of clients, auditors, and cyber insurers — is driving a new standard: recover quickly is no longer enough; you must be able to explain, with traceability and evidence, what happened to the data, what controls acted, and how the service was resumed without “holes” in the logs.
This shift can be called: explainable resilience. It is, in practice, resilience with an embedded “audit mode”: repeatable processes, clean records, automated evidence, and an immutable data trail that can withstand tough questions.
The Trigger: Regulation + Risk + Trust
The change isn’t coming only from Europe. A global pattern is emerging:
- Regulators demanding verifiable controls, third-party risk management, periodic testing, and incident notifications.
- Enterprise clients requiring contractual guarantees (and increasingly, security questionnaires with evidence requirements).
- Insurers seeking fewer promises and more “living proofs”: immutable copies, restoration tests, asset inventories, and documented procedures.
Europe has set the pace with frameworks like DORA, effective from January 17, 2025, which standardize digital resilience obligations in the financial sector and its supply chain.
In parallel, reference frameworks such as NIST Cybersecurity Framework 2.0 (widely used as a common language in audits and security programs) reinforce the idea of governance and evidence, adding the Govern function to the core of the framework.
And in the U.S., even when “resilience” isn’t discussed in the abstract, formal disclosure is required: the SEC mandates reporting material incidents via Form 8-K within 4 business days of determining their materiality.
What exactly is “Explainable Resilience”?
It’s not a product. It’s an approach. It resembles moving from “making copies” to operating a verifiable recovery system. At a minimum, it involves:
- Data lineage: being able to reconstruct the journey: origin → transformations → accesses → storage → backups → restoration.
- Design-by-auditing: coherent, centralized logs with defined retention, integrity, and change control.
- Repeated recoverability: runbooks, automation, and periodic tests with results stored as evidence.
- Demonstrable controls: identity, least privileges, segmentation, encryption, key management, and a clear model of third-party responsibilities.
The key difference from the “classic DR” is that here the question isn’t just “Did we get back online?”, but:
- Which data were affected?
- Which controls prevented (or didn’t) the spread?
- What evidence proves the restoration was complete and unmanipulated?
- How does the business justify, to an auditor, that it returned to a trusted state?
Quick overview of regulations and frameworks: where they apply and what they practically require
| Standard / Framework | Where it Applies | Summary (what it ultimately requires in resilience and evidence) |
|---|---|---|
| DORA (EU) | Financial entities and key parts of their TIC chain in the EU | ICT risk management, incident response & reporting, strong considerations for third parties, and resilience testing with verifiable documentation. |
| NIS2 (EU) | Essential and important sectors (including digital providers like cloud, data centers, etc., per legal development) | Enhances risk management measures and thresholds for “significant” incidents; promotes discipline in controls and reporting. |
| GDPR (EU) | Processing of personal data in the EU | Security of processing, minimization, access control, and accountability (demonstrating compliance). (Amplifies the need for traceability and evidence). |
| NIST CSF 2.0 (US & global) | Widely adopted voluntary framework (businesses, public sector, supply chain) | Common language for cybersecurity programs: now includes Govern, consolidating governance, metrics, and evidence as core elements. |
| SEC Cyber Disclosure (US) | Public companies in the US | Mandates reporting of material incidents and describing governance/risk management: encourages evaluation processes, traceability, and record-keeping. |
| PDPA (Singapore) | Organizations handling personal data in Singapore | Protection obligations and breach notification regimes, requiring processes and evidence for assessment, containment, and communication. |
| Privacy Act + APP (Australia) | Organizations covered by the Privacy Act; APP principles | Principles for handling personal information + practical obligations (including incident responses and notifications). Raises the bar for records and control. |
Practical note: in addition to “the law,” many industries add layers (finance, healthcare, critical infrastructure) with sector-specific guidelines and standards that, in audits, become almost as demanding as formal norms.
The uncomfortable part: evidence becomes a “product”
In a modern audit, or during a serious incident, the company’s competition isn’t only technology. It competes with its ability to demonstrate that it operates with controls.
In practice, teams end up needing a “package” of recurring evidence:
- Live inventory of systems, data, and dependencies (including SaaS and third parties).
- Flow maps: which data travels where and why.
- Restoration tests with records: when they were performed, what was recovered, how long it took, what failed, and how it was fixed.
- True immutability in critical copies (and evidence that they can’t be accidentally deleted).
- Chain of custody during incidents: who accessed, what changed, and when.
- Change control (infrastructure and configuration) with traceability.
The key is that this evidence shouldn’t be “faked” after the scare. It should come automatically from the organization’s operational systems.
Designing a resilience strategy based on compliance
1) Start with the data, not the infrastructure
The initial question isn’t “which backup do we use?”, but:
- Which data are critical, which are personal, which are regulated?
- Which data sets support essential processes (billing, ERP, identity, operations)?
- Which external dependencies could break recovery (DNS, IdP, repositories, licenses, APIs)?
This leads to a useful classification for resilience: criticality + sensitivity + dependency.
2) Define “reliable recovery,” not just “fast recovery”
A restore that resumes service but leaves doubts about integrity, manipulation, or inconsistencies can pose legal and reputational risks.
Three “non-arguable” controls help here:
- Verified restorations (integrity checks, application validations, data reconciliation).
- Quarantine environments to restore without reinfection (ransomware and lateral movement).
- Runbooks with checkpoints (what to validate before declaring the service “OK”).
3) Treat logs as a regulatory asset
If logs are incomplete, scattered, or untrustworthy, the company loses its narrative.
Best practices for explainable resilience include:
- Centralization (SIEM/logging) with defined retention.
- Integrity (sealing, WORM, or equivalent mechanisms).
- Correlation with identity (who did what).
- Evidence of alerts and responses (what was detected, contained, or learned).
4) Treat third parties as part of your perimeter
DORA, NIS2, and real-world practices converge here: if a critical component depends on a provider, their resilience is yours.
This involves:
- Contracts with SLA recovery times and evidence requirements.
- Audit rights / reporting (SOC, ISO, etc.).
- Exit plans (portability, alternative recovery).
5) Turn tests into routine (and keep the “exam” record)
The annual “compliance test” no longer suffices. What works best for serious organizations is:
- Small, frequent tests (per system).
- A periodic “realistic” test (simulating data loss, ransomware, provider failure).
- Storing results as evidence: timing, failures, corrective actions.
Final message: resilience is verifiable trust
The world is moving towards a model where business continuity is audited. It’s not only performed; it’s demonstrated. And that’s the essence of explainable resilience: designing to recover, yes, but above all to prove that recovery was correct, complete, and governed.