DR Readiness Index Calculator

Use these example values to validate setup and compare your environment baseline.

The calculator converts each recovery control into a 0–100 subscore, applies a weighted model, then sums weighted points into a final readiness index.

• Weights: Restore and recovery alignment are weighted higher because they represent direct recoverability, not only policy coverage.
• Clamping: Scores are limited to 100 so overperformance does not hide weak controls elsewhere.
• Freshness: Old runbooks reduce readiness because execution quality drops when procedures drift from production.

1. Enter target RTO and RPO values from your recovery policy or service-level commitments.
2. Provide actual performance from the latest DR test, failover exercise, or validated incident evidence.
3. Fill coverage metrics using percentages for backups, replication, automation, monitoring, training, mapping, and security parity.
4. Add operational values for downtime and data-loss costs to estimate business exposure alongside readiness score.
5. Press Submit. The result appears above the form, directly under the page header.
6. Review the weighted breakdown and top priorities, then export results to CSV or PDF for audits or planning meetings.

Recovery Objectives and Evidence Quality

The DR Readiness Index works best when inputs come from evidence, not estimates. Teams should source RTO and RPO values from test reports, failover timelines, backup logs, and incident reviews. When actual recovery time exceeds the stated target, the score declines and signals execution risk. This design stops optimistic policy documents from masking weak recovery performance and keeps leadership discussions anchored in recovery behavior. Audit traceability improves when evidence links to each input value.

Weighted Scoring and Priority Interpretation

Weighted scoring helps cloud teams avoid treating controls as equally important. In this model, recovery alignment and restore testing carry more weight because they directly prove recoverability. A weak score in one high weight control can reduce the final index more than several minor gaps. The lost points view is valuable because it shows where remediation creates the biggest score gain and strongest operational improvement, which supports efficient budgeting and faster remediation cycles.

Coverage Metrics Across Modern Cloud Environments

Replication coverage, automation coverage, monitoring coverage, dependency mapping, and security parity show how complete the recovery design is across production services. Strong backup success alone is not enough if application dependencies or security controls are missing in the recovery environment. Teams should measure these percentages against critical workloads first, then expand to tier two services. This sequence improves business continuity earlier while building a practical roadmap for broader resilience coverage.

Operational Cadence, Drills, and Runbook Freshness

The calculator rewards consistent drills and current runbooks because readiness decays when teams do not practice. Quarterly exercises usually create a reliable baseline, but high change environments may require monthly partial failover tests. Runbook freshness should be managed as a measurable KPI with owners, review dates, and triggers tied to infrastructure releases. Organizations that track documentation age and drill cadence together usually recover faster because procedures match real production states.

Exposure Estimation and Governance Decisions

The estimated exposure output translates technical readiness into business language by combining downtime cost and projected data loss cost. This value does not replace a business impact analysis, but it supports prioritization during planning cycles. For example, a moderate readiness score with very high exposure may justify replication upgrades or restore automation. When reported monthly, the index and exposure trend help executives approve investments, set thresholds, and track resilience improvements across business units.