Explainability-Driven Data Resilience: The Gold Standard for Compliance

Business resilience depends on data resilience that is compliance-ready.

Take your pick — from DORA (E.U.) and NIST (U.S.) to PDPA (Singapore) and APP (Australia) — regulatory pressure on enterprises the world over is increasing. Regulators, insurers, and customers don’t just want to know that your business is protected; they also want you to show the path of your data, demonstrate the controls, and prove, with clean logs, how you will get your business up and running again!

This is the shift to explainability-driven resilience. Fast and reliable recovery, with traceability and auditability built into every step. Organizations need to map out data resilience strategies through the lens of compliance, ensuring their data management processes' digital footprint withstands scrutiny.

Business case first, compliance always

Data outages and cybersecurity attacks are inevitable business risks that need to be tracked and reported with robust systems in place. The Veeam Data Resilience Maturity Model (DRMM) framework, developed in collaboration with McKinsey and MIT, recommends integrating business strategy, people, process and technology to reduce risk, accelerate recovery, and strengthen long-term resilience.

Explainability-driven data resilience, the glue that binds these elements together, needs to become as standardized as audited financial statements, hitting metrics for key stakeholders that include:

• Investor confidence: Transparent, tested recovery plans reduce perceived operational and financial risk.
• Reputation protection: Recovering quickly and reliably to ensure brand strength.
• Leadership accountability: Evidence-based accountability of resilience posture.
• Reduced fines and insurance costs: Clean, auditable controls lower non-compliance exposure and security premiums.

Regulatory momentum is outpacing compliance readiness

Across Asia Pacific, the regulatory momentum is unmistakable. The Shared Responsibility Framework in Singapore holds financial institutions and telcos accountable for mitigating phishing scams and requires them to compensate scam victims when duties are breached. In Australia, data protection enforcement has intensified with enterprises facing penalties up to AUD50 million (over USD32 million) for data breaches. Elsewhere in India, while implementation rules for the Digital Personal Data Protection Act (DPDP) are still pending, assigned penalties could reach up to INR250 crores (over USD25 million). Meanwhile, businesses in Japan have raised concerns about administrative fines on enterprises that commit grave violations. While regulatory approaches may not be standardized as yet, the long-term message is clear: businesses need to get their data resilience systems in order.

However, here's a reality check: Enterprises are just not prepared. According to the Veeam Data Resilience Maturity Model (DRMM) report, 30% of CIOs overestimate their data resilience, with fewer than 10% above average. 74% of organizations fall into basic and intermediate levels, highlighting significant improvement opportunities. Additionally, 13% of respondents in Veeam's Enterprise Buyer's Guide to Data Protection 2024 did not even have a disaster recovery plan or had never tested it; 28% tested only once a year, and only 27% tested more than twice in the same year.

Embed data resilience with explainability

Imagine data resilience as the foundation of an enterprise structure with explainability as its embedded navigational dashboard. At Veeam, we believe that a four-step approach provides the runway for success:

1. Map, label, and trace data flows

Start with the question most teams avoid: Do we actually know the data we have? The output needs to be an exhaustive inventory of business-critical services, and their data flows across physical, virtual, cloud and backup environments. A standardized data classification policy that involves labelling by sensitivity, associated controls, handling guidelines and recovery sequence must be adopted. Imagine the output to be a multilevel map that is easily understood by humans and automated by machines.

2. Develop a data command center

Once a data classification map is developed, a command center such as that provided by Securiti AI is recommended. Integrating data security posture management with data intelligence platforms such as Veeam Data Platform v13 allows teams to trace lineage and validate policy application across every estate: production, SaaS, cloud, endpoints and backups. Enterprises benefit from full visibility and control over their entire data estate.

3. Test and audit regularly

Testing and auditing data resilience strategies regularly builds enterprise muscle for quick response and recovery in times of crisis. This involves scheduling automated tests several times a year, ensuring offline, air-gapped, and immutable copies. Only then can restoring, developing runbooks for each critical service, and documenting results for an auditable trail become standard protocols.

4. Show the evidence

Make it easy for decision makers with a single dashboard that provides full visibility into key metrics, including asset protection coverage, backup and immutability success rates, drill frequency and pass rate, recovery readiness, and compliance posture, all mapped with evidence links.

According to the DRMM framework, top-performing enterprises score high on a host of business metrics, including 7x faster recovery speed (MTTR), 3x less downtime (RTO), 4x less data loss (RPO) and around 10% higher average revenue growth rate.

Make explainable and compliance-ready data resilience your strategic differentiator

While data protection requirements vary across markets, regulators' demands are converging around similar themes of availability, traceability, and accountability. For multi-regional enterprises, the goal should be a harmonized global explainable system of resilience controls. Build one system, plan for the most stringent regulations, overlay local evidence requirements, and stay audit-ready across markets. As business opportunities shift and emerge, fast restores and broad coverage that are compliance-ready are the scalable strategic differentiators.

Taking it forward

So, ask your team to explain every copy of critical data. Are there offline, air-gapped, and immutable copies for critical business services, and can we prove it? What was the last automated recovery test for each, and how did we fare? If we had to brief the Board or a regulator tomorrow, could we clearly show the data flow, the controls, and the recovery runbook? If the answers don’t flow easily, the explainability gap is a clear signal of compounding risks – operational, business, reputation, and regulatory.

The good news is that Veeam’s suite of data and AI solutions provides the building blocks for integrating business intelligence, data protection, backup, testing, and recovery in enterprises of every size. All that is required is a mindset shift in adopting explainability, data resilience and compliance as a unified baseline capability.

The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/tadamichi