Review Results
The summary appears here after calculation and stays above the form for quick comparison.
Calculator Inputs
Enter scoped counts, review outcomes, and control coverage values to estimate exposure, readiness, and remediation effort.
Example Data Table
Use this sample review set to verify the calculator logic, export layout, and chart behavior.
| Input Metric | Example Value | Why It Matters |
|---|---|---|
| In-Scope Accounts | 1,250 | Defines the review population baseline. |
| Reviewed Accounts | 980 | Measures completion progress against scope. |
| Privileged Accounts | 86 | Elevated access drives impact and urgency. |
| Dormant Accounts | 73 | Inactive access often becomes hidden risk. |
| Orphan Accounts | 19 | Missing ownership weakens accountability. |
| Overdue Reviews | 145 | Late certifications increase governance exposure. |
| MFA Coverage | 88% | Stronger authentication lowers abuse probability. |
| Monthly Review Capacity | 220 | Helps estimate backlog clearance timing. |
Formula Used
Core Rates
- Coverage Rate = (Reviewed Accounts ÷ In-Scope Accounts) × 100
- Privileged Exposure = (Privileged Accounts ÷ In-Scope Accounts) × 100
- Dormant Ratio = (Dormant Accounts ÷ In-Scope Accounts) × 100
- Orphan Ratio = (Orphan Accounts ÷ In-Scope Accounts) × 100
- Overdue Ratio = (Overdue Reviews ÷ In-Scope Accounts) × 100
- Revocation Rate = (Revoked Accounts ÷ Reviewed Accounts) × 100
- Exception Rate = (Approved Exceptions ÷ Reviewed Accounts) × 100
Risk and Effort Logic
- High-Risk Finding Index = min[100, (High-Risk Findings ÷ Critical Applications) × 25]
- Risk Score = weighted sum of privileged, dormant, orphan, shared, overdue, MFA gap, SoD, leaver, and finding indexes.
- Readiness Score = 0.45×Coverage + 0.20×MFA + 0.15×(100−Overdue%) + 0.10×(100−Orphan%) + 0.10×(100−Dormant%)
- Remediation Hours = dormant×0.25 + orphan×0.5 + shared×0.75 + findings×1.5 + SoD×1.25 + leavers×0.5 + overdue×0.1
- Backlog Clearance Months = Overdue Reviews ÷ Monthly Review Capacity
- Daily Reviews per Reviewer = Remaining Review Gap ÷ Review Window ÷ Reviewers Available
The weighting favors overdue, privileged, orphaned, and authentication gaps because those conditions usually raise both audit concern and abuse potential.
How to Use This Calculator
- Enter the total in-scope population for the application review.
- Add completed reviews, exposure counts, and control gaps.
- Select business criticality and regulatory sensitivity levels.
- Set reviewers, monthly team capacity, and the review window.
- Click Calculate Review Metrics to generate the summary above the form.
- Use the chart to compare positive controls with risk indicators.
- Export the scenario as CSV for records or PDF for sharing.
- Adjust values to test remediation strategies and staffing options.
Frequently Asked Questions
1) What does this calculator measure?
It estimates access review readiness, weighted exposure, backlog pressure, and remediation effort. It combines completion data with risky account conditions and control coverage to help prioritize cleanup and recertification work.
2) Why are orphan and dormant accounts important?
Orphan accounts lack accountable owners, while dormant accounts often escape attention. Both can preserve unnecessary access, complicate audits, and increase the chance of misuse, especially in sensitive applications.
3) How should I interpret the risk score?
Higher scores indicate greater review urgency. The score rises when privileged access, overdue reviews, control gaps, toxic combinations, and ownerless accounts grow relative to the scoped population.
4) What is a good readiness score?
A higher readiness score suggests stronger completion, better MFA coverage, and fewer unresolved review gaps. Many teams target 80 or above for critical systems, but internal policy should define acceptable thresholds.
5) Can I use account records instead of individual users?
Yes. The calculator works with whichever review unit you use consistently, such as identities, application accounts, or entitlements. Keep the same unit across all fields to preserve meaningful ratios.
6) Why does MFA coverage reduce risk?
MFA does not eliminate excessive access, but it lowers the chance of compromise through stolen credentials. That is why the model includes MFA gap as a direct risk contributor.
7) How can this help with staffing decisions?
It estimates remediation hours, clearance months, and daily reviews per reviewer. Those figures help managers decide whether to reassign analysts, extend review windows, or narrow the in-scope population.
8) Should exception approvals always be treated as bad?
Not always. A documented exception can be legitimate, but frequent exceptions may reveal weak access design, recurring business pressure, or missing compensating controls. Trend them carefully across review cycles.