Calculator Methodology
Redux ROT Impact Score — transparent, citable, versioned.
This document explains every number the calculator produces: the formulas, the benchmarks behind the defaults, the assumptions we make, and what the model deliberately excludes. It is designed to be shared with analysts, executives, and procurement teams evaluating the results.
01How Every Number Is Computed
Step 1 — Total Data Estate
The calculator sums storage volumes across three environments: on-premises (primary SAN/NAS + archive/tape, excluding backup infrastructure), public cloud (hot, cool, and archive tiers across AWS, Azure, GCP, and OCI), and Microsoft 365 / SaaS (mailbox, OneDrive, SharePoint, Teams, other SaaS). M365 volumes are derived from user count × per-user averages you supply.
Step 2 — Annual Storage Cost
Each environment uses tiered cost-per-TB rates:
- On-prem primary: default $3,000/TB/yr (SAN/NAS fully loaded: controllers, networking, power, floor space, admin)
- On-prem backup: default $600/TB/yr (purpose-built backup appliance), divided by your deduplication ratio
- On-prem archive: default $80/TB/yr (LTO-9 tape or cold object)
- Cloud: per-region pricing refreshed weekly from each vendor's pricing API (AWS, Azure, and Oracle live; Google Cloud activates once its API key is configured), with the published static rate card as the fallback whenever a feed is unavailable ($/GB/month × 1,024 × 12 = $/TB/yr)
- M365: mailbox storage valued at the Office 365 Extra File Storage add-on rate ($0.20/GB/mo) plus the storage-attributed share (40%) of non-mail license spend. Mailbox figures are a storage-equivalent value — what that storage would cost at add-on rates — not necessarily a line item you can delete from an invoice
cloudCost = Σ provider (hotTB × hotRate + coolTB × coolRate + archiveTB × archiveRate)
m365Cost = mailboxStorageCost + nonMailStorageCost
Step 3 — ROT Percentage Estimation
We report three tiers so you see a conservative-to-aggressive range rather than a single false-precision number. The tier anchors — 25% / 33% / 45% — are built around the cited ~33% cross-industry benchmark: the mid (default) tier is that published figure, with a modeled ± band for the low and high tiers. We label them P25 / P50 / P75 as a familiar low/mid/high convention; the low and high bounds are Redux modeling assumptions, not measured survey percentiles.
Each tier — Low (25%), Mid (33%, the cited cross-industry figure), and High (45%) — is then adjusted by two factors:
- Hygiene adjustment: up to ±10 pp based on your classification maturity, lifecycle policies, duplication rate, stale-data %, and temp-file %.
- Industry retention floor: Redux’s estimate of the fraction of data typically subject to regulatory retention (e.g., Healthcare ~25%, Financial Services ~30%, Government ~35% — modeling assumptions informed by HIPAA, SEC 17a-4, and NARA, not exact legal quantities). This floor is subtracted from the base ROT %, so regulated industries show lower recoverable ROT.
rotPct = clamp(adjustedROT, 10%, 80%)
Within the total ROT, we split into Redundant (30–40%), Obsolete (35–40%), and Trivial (25–30%) using tier-specific ratios derived from industry literature.
Step 4 — ROT Cost Attribution
Each environment's ROT cost is the recoverable ROT percentage applied directly to that environment's own annual cost. An environment's cost is already proportional to its volume, so no additional share factor is applied — the result is partition-invariant: the same estate produces the same total waste whether it is entered as one environment or split across several. On-premises attribution uses the primary + archive cost; backup is handled separately in Step 5 so it is never counted twice.
totalAnnualWaste = totalAnnualCost × rotPct (the sanity check a CFO can do on a napkin)
Step 5 — Backup Amplification
On-premises backup infrastructure amplifies ROT cost: every redundant file that lives on primary also exists across your backup copies, reduced only by deduplication.
backupAmplificationCost = backupAnnualSpend × rotPct
This is the ROT share of your actual backup bill — by construction it can never exceed your backup spend, and it is exactly zero if you report no backup.
Cloud and M365 manage their own backup/versioning and are not amplified through on-prem backup infrastructure.
Step 6 — FinOps Cloud Cost Modeling
For each active cloud provider, we compute a detailed FinOps breakdown:
- Savings Plans: blended rate = covered % × (1 − discount %) + uncovered %. Default: 30% coverage, 30% discount.
- Egress cost: monthly egress TB × per-GB rate × 12, with free-allowance offsets (e.g., OCI 10 TB/mo free).
- Early-deletion penalty: pro-rated penalty if archive-tier ROT is younger than the minimum storage duration (e.g., S3 Glacier 90-day, Azure Archive 180-day).
- Retrieval cost: estimated cost to read archive ROT for classification/deletion, using the provider's highest deep-tier retrieval fee.
Step 7 — Multi-Year Projection
The total annual waste is compounded by your stated annual data growth rate to produce 3-year and 5-year projections.
Quick Wins
The calculator identifies up to 7 non-overlapping remediation opportunities. Each quick win claims an explicit TB slice from the total ROT pool. A running total ensures no TB is double-counted and total savings never exceed annual waste.
02Benchmark Sources
Every external number used in the calculator is cited below with publication year and link. Cloud storage rates are refreshed weekly from each vendor's pricing API (with the static rate card as fallback); the remaining benchmarks are reviewed at least annually.
| Benchmark | Value Used | Source | Year |
|---|---|---|---|
| Average breach cost | $4.44 M (global avg) | IBM Cost of a Data Breach Report 2025 | 2025 |
| Enterprise ROT % (industry benchmark) | 33% of stored data is ROT | Veritas Databerg Report (original 33% figure); corroborated by Komprise 2025 | 2016 / 2025 |
| Fully-loaded storage cost | $3,000–3,300/TB/yr (blended) | Redux 2026 modeling estimate (fully-loaded SAN/NAS incl. hardware, power, cooling, management). User-overridable. | 2026 |
| Productivity waste from ROT | $5.7 M/yr per 1,000 knowledge workers (time spent searching for information) | IDC, “The Hidden Costs of Information Work” | IDC |
| Enterprise ROT % (P50 anchor) | 40–50% of enterprise data is ROT | IDC Global DataSphere (unstructured data analysis, 2023); corroborated by Veritas Data Genomics Index (40–50% range) | 2023 |
| Unstructured data share | 80% of enterprise data is unstructured | Komprise 2025 / IDC | 2025 |
| Cloud storage pricing | Per-region, per-tier (hot/cool/archive) — live API + static fallback | Vendor pricing APIs (weekly refresh): AWS S3, Azure Blob, GCP, OCI | Live (weekly) |
| M365 storage attribution | 40% of per-user license cost | Gartner "Microsoft 365 License Optimization" (2025) + Microsoft 365 E3/E5 SKU pricing analysis | 2025 |
| Office 365 Extra File Storage | $0.20/GB/month ($2,458/TB/yr) | Microsoft 365 Admin Center — Office 365 Extra File Storage (SharePoint/OneDrive) pricing | 2025–26 |
03Assumption Table
Every default value the calculator ships with is listed below, along with the rationale and its sensitivity — how much the final annual-waste figure moves if you change the default.
| Parameter | Default | Why This Default | Sensitivity |
|---|---|---|---|
| Data growth rate | 25%/yr | IDC Global DataSphere midpoint for enterprise data growth | High — 5-year projection scales exponentially; ±5 pp shifts 5-yr cost ~18% |
| On-prem primary $/TB/yr | $3,000 | 2026 fully-loaded SAN/NAS (controllers, networking, power, floor space, admin FTE) | High — directly scales on-prem ROT cost; ±$500 shifts annual waste ~8–12% |
| On-prem backup $/TB/yr | $600 | Purpose-built backup appliance (e.g., Dell PowerProtect, Cohesity) | Medium — affects backup amplification cost |
| On-prem archive $/TB/yr | $80 | LTO-9 tape or cold object storage (media + library + admin) | Low — archive is already cheap; moving ±$40 has minimal overall impact |
| Backup copies | 3 | 3-2-1 backup rule (3 copies, 2 media types, 1 offsite) | High — each additional copy linearly increases backup amplification |
| Dedup ratio | 2:1 | Conservative default; many orgs without inline dedup achieve 1:1–2:1 | Medium — higher ratios reduce backup amplification cost proportionally |
| M365 license cost/user/mo | $22 | Blended E3/E5 midpoint ($36 E3 list, weighted by common E3-heavy deployments) | Medium — scales M365 storage attribution (40% of total license) |
| M365 storage attribution ratio | 40% | Gartner 2025 analysis: storage infrastructure = 35–45% of M365 per-user cost | Medium — ±10 pp shifts M365 ROT cost ~25% |
| Avg mailbox size | 5 GB | Typical enterprise with basic retention; ranges 2–25 GB | Low — small per-user; matters at scale (10k+ users) |
| Avg OneDrive/user | 15 GB | Midpoint of observed enterprise usage (quota often 1 TB, actual 5–50 GB) | Low — similar scale effect as mailbox |
| % data untouched 12+ months | 60% | Komprise 2025: 74% of orgs manage 5+ PB; majority untouched. Veritas Data Genomics: 40%+ untouched 3+ years | High — primary driver of hygiene adjustment (±3 pp ROT) |
| Known duplication rate | 30% | Enterprise average for unmanaged file shares (range 20–60%) | Medium — above 40% adds +3 pp to hygiene adjustment |
| Temp/personal files | 12% | Veritas Databerg: avg 26.5% store personal files; 12% is the mid-range for enterprises with BYOD policies | Low — above 20% adds +2 pp to hygiene adjustment |
| Savings Plan coverage | 30% | Typical enterprise starting FinOps maturity; range 0–80% | Low — only affects FinOps breakdown, not headline ROT cost |
| Savings Plan discount | 30% | AWS/Azure typically 20–40% for 1-year commitments | Low — only affects FinOps breakdown |
| Archive data age | 180 days | Beyond most early-deletion minimums (90–180 days), so penalties are usually zero | Low — only triggers penalty if below provider's minimum |
Industry Retention Floors
These floors are Redux estimates of the fraction typically subject to regulatory retention in each industry (modeling assumptions, not exact legal quantities). They reduce the recoverable ROT ceiling.
| Industry | Floor | Regulatory Basis |
|---|---|---|
| Government | 35% | NARA, FOIA, state sunshine laws |
| Financial Services | 30% | SEC Rule 17a-4, SOX, MiFID II |
| Healthcare | 25% | HIPAA (7-year medical records) |
| Energy | 20% | NERC CIP, EPA record-keeping |
| Manufacturing | 15% | ISO 9001 quality records, OSHA |
| Education | 15% | FERPA student records |
| Retail | 10% | PCI DSS (limited retention) |
| Technology | 10% | Minimal regulatory burden |
| Media & Entertainment | 10% | Minimal regulatory burden |
| Other / Unregulated | 10% | General business record-keeping |
04What We Don't Model
Honesty about model boundaries is essential for credibility. The following costs and effects are deliberately excluded from the calculator.
Egress Costs on ROT Deletion
The FinOps panel shows your current egress spend, but we do not model the one-time egress cost of migrating or deleting ROT across regions. The actual cost depends on whether data is deleted in-place (zero egress) or migrated before deletion.
Reserved Instances & Committed Use Discounts (Compute)
Our savings-plan modeling covers storage commitments only. Compute-attached storage (e.g., EBS volumes on reserved EC2 instances) is not broken out separately. If your ROT lives on compute-attached volumes, the true savings from deletion may be lower than shown.
Scope 3 Carbon Emissions
Storing ROT data consumes energy — powering disks, cooling data centers, manufacturing replacement drives. We do not quantify the CO₂ impact. Estimates range from 2–7 kg CO₂/TB/year for cloud and 10–30 kg CO₂/TB/year for on-prem, but methodology varies widely.
Indirect Productivity Loss
IDC (“The Hidden Costs of Information Work”) estimates ~$5.7M/year per 1,000 knowledge workers lost to time spent searching for information. The executive report scales this to your workforce as a directional benchmark; it is NOT included in the annual storage-waste figure, because productivity impact varies widely by organisation and is hard to attribute directly to storage.
Compliance Fine Exposure
The dashboard shows potential GDPR, CCPA, and HIPAA fine ranges as context, but these are not summed into the headline cost. Fine risk depends on breach probability, data sensitivity, and regulatory jurisdiction — factors outside this model's scope.
Data-in-Transit & Network Costs
Replication traffic, cross-region sync, and VPN/Direct Connect costs associated with ROT data are not modeled. These are highly architecture-dependent.
Software Licensing for Data Management Tools
The cost of classification, DLP, backup, and archival software licenses is not included. We model infrastructure cost, not the tools used to manage it.
Human Cost of Remediation
Cleaning up ROT requires project management, change management, and engineering time. This implementation cost is not deducted from the projected savings shown in Quick Wins.
05Changelog
We use semantic versioning. Major = new calculation model, Minor = new data source or input field, Patch = bug fix or cosmetic.
- •Presentation — generalized public-facing source attribution. Marketing and report surfaces (homepage, dashboard, executive report, insights) now describe the ~33% ROT figure as a widely-cited cross-industry benchmark rather than headlining a single vendor report. Full provenance — including the original figure and its corroborating sources — remains documented in the Benchmark Sources table below. No change to any value or calculation.
- •Tier anchors re-centered on the cited cross-industry benchmark. The mid (default) ROT tier is now the published ~33% cross-industry benchmark, with a modeled ± band for the low and high tiers. The tier bases moved from 29% / 45% / 58% to 25% / 33% / 45%, so the headline number you see by default is the one Redux can cite directly. Hygiene adjustment and the industry retention floor are unchanged. This lowers most scores relative to v1.2.0.
- •Quick-win recommendations no longer vanish at lower ROT%. The forward-looking “lifecycle policies” and “data classification” recommendations are prevention/enablement actions, so they now carry their own savings budget instead of competing for the same recoverable-ROT pool as the concrete deletion wins. The total quick-win savings remain capped at your total annual ROT waste.
- •Citation review — validated-and-cited figures only. Every published number was re-checked against its source. Removed unverifiable/uncited claims (a “+2–3% breach probability per TB” figure; a per-organization breach-cost figure derived by apportioning the industry average; a “$34M Securiti” benchmark). The average breach cost is now shown only as the cited IBM 2025 industry average, for context.
- •Corrected the productivity benchmark. The $5.7M figure is IDC’s estimate per 1,000 knowledge workers (“The Hidden Costs of Information Work”), not a whole-enterprise figure; labels and source corrected.
- •Honest sourcing of estimates. The $3,000–3,300/TB storage cost and per-industry retention floors are now labeled as Redux modeling estimates (user-overridable), not external citations. Tier anchors (29/45/58%) are described as Redux’s modeled spread around the ~33% Veritas benchmark, not measured survey percentiles.
- •Corrected the Microsoft 365 add-on storage rate attribution ($0.20/GB/mo = Office 365 Extra File Storage). Reworded the homepage headline to the cited Veritas figure (~a third of data is ROT).
- •ROT Impact Score — Dollar Exposure lane refined. The 60-point Dollar Exposure lane now combines intensity (ROT waste as a share of spend, 0–40) with magnitude (the absolute annual dollars wasted, log-scaled 0–20). Previously the lane was waste ÷ spend, which — because waste is defined as ROT% × spend — reduced to a pure function of ROT% and carried no information about the size of the dollar exposure. Two estates at the same ROT% but very different absolute waste now score differently, and the lane no longer saturates at high ROT%. Individual scores change (generally lower for small-dollar estates, preserved for large ones); the underlying waste, ROT%, and dollar figures are unchanged.
- •On-premises $/TB rate now honored. Fixed a defect where a custom on-prem storage cost entered in the wizard was ignored and the $3,000/TB default was used regardless. On-prem cost, ROT waste, projections, and the score now reflect the entered rate.
- •Tightened the waste identity for the “no backup” edge case so backup spend and its ROT share are always counted together (waste = ROT% × total spend holds exactly).
- •Corrected citation for the 33% ROT figure: the original source is the Veritas Databerg Report 2016, not Komprise 2025. Komprise 2025 is now listed as a corroborating source. No change to the value used in calculations.
- •Replaced the P50 anchor attribution from “Valora 2024” (unverifiable) to IDC Global DataSphere (2023) + Veritas Data Genomics Index (40–50% range). No change to the value used in calculations.
- •Removed the “Exonar Dark Data Research” attribution for the 58% figure: the source is unverifiable and has been removed from the benchmark table. The 58% value continues in use as the Industry P75 arithmetic ceiling (upper bound of industry observations), now without a named source. It is retained as a conservative upper bound consistent with Veritas/IDC published ranges.
- •Documented the retention-floor model: recoverable ROT excludes the industry compliance-retention floor — data under regulatory hold is treated as non-recoverable regardless of its ROT status (a deliberately conservative assumption). No engine changes.
- •Resolved Fixture C test discrepancy: the original ≤33% assertion was internally inconsistent with the additive floor model. Corrected to assert the actual engine output (46% for Healthcare aggressive with poor hygiene).
- •Added direction-guard test: higher retention floor ⇒ lower recoverable ROT% (Government < Energy < Technology across all tiers).
- •Corrected the v1.0.1 rename: “ROT Impact Score” is now used for an individual user's score (the 0-100 hero metric). “ROT Impact Benchmark” is reserved for the quarterly published aggregate report. This split makes the brand match what the methodology actually computes per user vs. what gets published quarterly.
- •Removed “Conservative / Moderate / Aggressive” tier labels in favor of “Industry P25 / P50 / P75” as the sole tier framing. The percentile labels are honest to the methodology; the qualitative labels implied a risk-judgment the math doesn't make.
- •Updated homepage and OG metadata to lead with the “Redux — ROT Impact Score” brand.
- •Renamed tier labels: Conservative/Moderate/Aggressive → Industry P25/P50/P75.
- •Renamed "Data Trust Index" → "ROT Impact Benchmark" across all user-facing text.
- •Synced all 9 non-English locale files with 33 missing translation keys.
- •Initial public release of the methodology document.
- •7-step calculation pipeline: estate inventory → cost → ROT % → attribution → backup amplification → FinOps → projection.
- •3 estimate tiers: Industry P25 (29%), Industry P50 (45%), Industry P75 (58%).
- •Industry-aware retention floors for 10 industries (Healthcare through Other).
- •Tiered on-prem costing: $3,000 / $600 / $80 per TB/yr (primary / backup / archive).
- •FinOps cloud modeling: savings plans, egress, early-deletion penalties, retrieval costs.
- •M365 cost model: Exchange add-on pricing ($0.20/GB/mo) + 40% storage license attribution (Gartner 2025).
- •Benchmarks updated: IBM 2025 ($4.44M breach), Komprise 2025 (unstructured data), Gartner 2025 ($3,300/TB), IDC 2024, Securiti 2024.
- •Replaced 2015 Veritas Databerg figure with 2024/2025 multi-source corroboration (Komprise 2025, IDC 2023).
- •Non-overlapping Quick Wins engine with explicit TB-slice claiming and savings cap.
Questions about the methodology? privacy@rotimpact.com
Last updated July 2026 · Methodology v1.3.1