Contract Throughput Per Legal FTE by ARR & Industry

TL;DR

There is no public dataset that publishes contracts executed per legal FTE segmented by annual recurring revenue and industry. Credible references describe staffing ratios and workload trends, not contract-level throughput. The gap is solvable with internal data. Count executed agreements for a defined period, divide by in-scope legal FTEs, then segment by finance ARR buckets and industry. Use native reporting in systems such as Salesforce, DocuSign CLM, Ironclad, or Concord to extract counts and export to CSV for reproducibility. A blank template is provided: CSV, JSON.

Background and context

Boards and CFOs increasingly ask legal departments to demonstrate output in familiar operating terms. Industry references validate the pressure but stop short of a cross-company “contracts per legal FTE” benchmark. The Association of Corporate Counsel’s 2025 Law Department Management Benchmarking Report summarizes staffing patterns across 395 departments and 23 industries. The CLOC State of the Industry 2025 aggregates operating trends from 186 organizations. The Thomson Reuters Legal Department Operations Index 2024 documents rising demand against flat headcount. None of these sources publishes contract throughput by ARR and industry. That gap is not a barrier. It is a prompt to calculate the metric locally and maintain it under governance.

Definition and measurement

Metric. Contract throughput per legal FTE equals the count of executed agreements in a defined window divided by the number of in-house legal FTEs who materially support contracting during that window.

Scope decisions. Decide whether to include renewals, amendments, and NDAs. Many teams run separate views: new business, renewals, and non-commercial agreements. Document choices so comparisons hold across quarters.

Counting executed agreements.
• In Salesforce, executed agreements can be queried from the Contract object with a filter on signature or activation date, then extracted using the report export feature.
• In DocuSign CLM, counts can be produced from native reporting and filtered by stage or effective date as described in report management.
• In Ironclad, Insights provides workflow counts by type and time; underlying data can be exported for audit.
• In Concord, reporting supports CSV exports from document reports and the inbox, as documented in Export a report and Exporting data from the inbox. Admins can also set up reports via Creating a report and review Analytics & document insights.

Denominator integrity. Count only in-house roles that materially support contracting. Exclude specialists who did not contribute during the window. Record fractional allocations for shared roles.

Segmentation. Apply finance ARR buckets that leadership already uses, then layer an industry classification aligned to external comps. This reduces false comparisons between business models. For example, software vendors with cohort renewals will show larger volumes of standardized agreements than device manufacturers with lengthy supplier negotiations.

Data and evidence

The case for measuring throughput alongside quality and cycle time is supported by recognized bodies. ACC and CLOC describe how staffing lags demand in many departments and how operational maturity correlates with standardization and automation. The Thomson Reuters index shows sustained workload growth. World Commerce & Contracting estimates average value erosion of 8.6 percent from contracting inefficiencies, reinforcing the link between throughput, cycle control, and business impact. See WorldCC’s analysis.

Systems used for contracting also provide practical paths to extract and audit data. Salesforce’s Contract object reference and report export enable reproducible counts. DocuSign CLM’s report management and Ironclad’s Insights overview provide native reports. Concord’s report export and inbox export features support both snapshot views and deeper analysis.

Findings

Public benchmarks are directional only. ACC, CLOC, and the Thomson Reuters Institute supply context on staffing and workload. They do not publish a standardized contracts-per-FTE measure segmented by ARR and industry. Throughput must be computed locally from system data while keeping definitions stable.
ARR and industry drive variance. In SaaS, large volumes of standardized renewals and order forms tend to elevate contracts per FTE. In manufacturing and life sciences, complex supplier terms and regulatory overlay reduce counts per FTE. Segmentation prevents unhelpful averages.
Throughput must be paired with quality controls. A rising throughput figure without cycle-time stability or exception-rate control can signal risk. WorldCC’s 8.6 percent value erosion estimate is a reminder to monitor both speed and safeguards.
Extraction is achievable with current tools. Salesforce reports, CLM analytics, and CSV exports are sufficient to produce quarterly counts, segment them, and store the inputs for audit. Concord, DocuSign CLM, and Ironclad all document export and reporting paths.
Governance matters as volume scales. Published definitions, a quarterly refresh, and simple reconciliations against finance bookings or e-signature totals build trust. Minor data drift is common if signature dates or contract types are not standardized.

Implementation guide

Set definitions. Publish what counts as executed, which contract types are in scope, and how fractional FTE allocations are handled.

Build one extract per system.
• Salesforce: a contracts report filtered by signature date with fields for type, value, and related opportunity; export to CSV.
• CLM: a report or dashboard that totals executed workflows by type; export with signature or effective dates included.

Calculate and segment. Load extracts into a single table with ARR buckets and industry labels. Compute contracts per legal FTE and contracts per 1 million dollars of ARR.

Reconcile. Cross-check counts against e-signature envelopes or bookings for the period. Investigate gaps larger than a low, predefined threshold.

Publish and repeat. Produce a one-page quarterly summary with two visuals: contracts per legal FTE by ARR bucket and by industry. Maintain a living data dictionary.

A blank, reproducible schema is available here: CSV, JSON. The schema includes fields for company, period, ARR, ARR bucket, industry, total contracts executed, legal FTEs, contracts per legal FTE, and contracts per 1 million dollars of ARR.

Methods and limitations

The references cited above establish context for staffing and operating conditions but do not provide a cross-company throughput dataset. The template offered here is intentionally minimal to reduce data wrangling. Actual contract volumes and staffing allocations vary with customer mix, regulatory posture, and approval design. Where teams rely on shared services or alternative legal service providers, note those contributions separately to avoid inflating in-house throughput figures. For context on why cycle segmentation matters for interpreting throughput, see Clause & Current’s modeled analysis of cycle time by agreement type.