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Market ResearchTop 10 Best IT Benchmarking Services of 2026
Ranked it benchmarking services for IT leaders with criteria and tradeoffs from Gartner, Forrester, and IDC, plus top vendor picks.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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McKinsey & Company is the strongest fit for leadership that needs peer-comparable IT performance evidence to drive capacity and governance decisions, while Computer Economics is the better budget-minded option when you want survey-based spending and staffing benchmarks, and Deloitte works best if you need auditable results for cross-functional investment choices.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
McKinsey & Company
Benchmark runbook development that ties KPI normalization rules to workload selection and telemetry collection requirements.
Best for: Fits when leadership needs peer-comparable IT performance evidence to drive capacity and governance decisions.
Accenture
Editor pickRunbook-driven benchmarking delivery with governance artifacts that keep environment controls and evidence traceable from setup through reporting.
Best for: Fits when enterprise programs need controlled benchmarking evidence for capacity and migration decisions across multiple teams.
Deloitte
Editor pickBenchmark governance artifacts that connect measurement definitions to executive decision workflows.
Best for: Fits when IT leadership needs auditable benchmarking results for cross-functional investment decisions.
Comparison Table
McKinsey & Company
enterprise_vendorManagement consulting firm providing IT benchmarking and digital strategy diagnostics.
Benchmark runbook development that ties KPI normalization rules to workload selection and telemetry collection requirements.
McKinsey & Company supports IT benchmarking by defining benchmark objectives, selecting representative workloads, and specifying KPI normalization rules for peer-group comparison. The engagement model emphasizes telemetry collection requirements, instrumentation expectations, and repeatable execution guidance so teams can run consistent measurement across environments. Benchmark reports also translate observed utilization, throughput, latency, and availability gaps into prioritization frameworks for remediation.
A tradeoff is that value depends on access to internal data, stakeholder time, and cooperation from platform and application owners to validate test assumptions and interpret results. McKinsey fits situations where leadership needs an evidence-backed maturity assessment and benchmark-informed roadmap rather than a tool-led self-serve process for routine runs.
- +Benchmark design and peer normalization that produce decision-grade comparisons
- +Strong linkage from performance findings to operating-model and roadmap actions
- +Clear instrumentation and telemetry expectations for repeatable measurement
- +Executive reporting built around KPI definitions and interpretation
- –Engagement delivery relies on client data access and internal coordination
- –Less suited for frequent self-serve benchmark runs without advisory support
- –Synthetic-to-production interpretation requires careful alignment of assumptions
- –Benchmark run execution depth can be constrained by source system telemetry quality
CIO and IT finance teams
Prove performance cost-to-serve tradeoffs
Prioritized investment decisions
Infrastructure engineering leads
Capacity planning based on benchmarks
More accurate capacity targets
Show 2 more scenarios
Application performance owners
KPI normalization for app SLAs
Comparable SLA performance view
McKinsey aligns KPI definitions and measurement scopes so app performance gaps compare consistently across peers.
IT operations governance
Performance governance and maturity assessment
Repeatable performance management
The engagement framework turns benchmark findings into performance governance processes and operating standards.
Best for: Fits when leadership needs peer-comparable IT performance evidence to drive capacity and governance decisions.
Accenture
enterprise_vendorGlobal professional services firm offering IT benchmarking and technology strategy consulting.
Runbook-driven benchmarking delivery with governance artifacts that keep environment controls and evidence traceable from setup through reporting.
Accenture is well suited for organizations that need benchmark runbooks integrated into an existing delivery process, including change management, environment readiness, and evidence collection. Benchmark work typically spans synthetic and production workload patterns, with normalization steps to reduce noise from scale differences and instrumentation gaps. The engagement structure tends to support peer-group style comparisons when the program defines comparable workload classes and measurement windows.
A key tradeoff is that Accenture delivery depends on active client participation in target KPI selection and test environment controls, especially when test environment parity must match production configuration. Accenture fits best when benchmarking is tied to a multi-quarter modernization, where capacity planning inputs must align with rollout sequencing and workload migration plans.
- +Benchmark runbooks integrated with enterprise delivery governance
- +Telemetry capture patterns align to decision-grade KPI normalization
- +Performance engineering coverage across infrastructure and applications
- +Evidence-ready benchmarking artifacts for cross-stakeholder reviews
- –Requires strong client control of environment parity and change windows
- –Benchmark design cycles can be slower than tool-only approaches
- –Synthetic-to-production mapping depends on clear workload definitions
- –Less suited for short, single-department benchmarking efforts
CIO performance and capacity teams
Baseline building for global platform refresh
Capacity plans with traceable evidence
Infrastructure engineering managers
Workload migration readiness benchmarking
Migration KPIs aligned to targets
Show 2 more scenarios
Application performance leads
Regression detection for modernization releases
Lower variance in release comparisons
Creates repeatable test harness executions and normalizes KPIs against prior releases.
Platform operations and SRE teams
Production workload observability benchmarking
Clear bottleneck and utilization insights
Collects telemetry with consistent measurement windows to compare utilization patterns across stacks.
Best for: Fits when enterprise programs need controlled benchmarking evidence for capacity and migration decisions across multiple teams.
Deloitte
enterprise_vendorBig Four firm providing IT cost and performance benchmarking services.
Benchmark governance artifacts that connect measurement definitions to executive decision workflows.
Deloitte supports benchmark design that maps business priorities to measurement boundaries, then translates those choices into a run plan for test execution and evidence collection. Engagements commonly cover workload and telemetry planning so findings connect to capacity, availability, and response-time behavior rather than only point metrics. Deliverables are structured for executive review, with clear methodology, assumptions, and interpretation so stakeholders can compare current performance to relevant peer context.
A key tradeoff is that governance-heavy engagements can take longer to stand up than lighter benchmarking vendors, especially when instrumentation needs to match benchmark definitions across multiple teams. Deloitte fits when benchmark results must survive audit-style scrutiny and drive cross-functional decisions, like infrastructure refresh sequencing or performance investment prioritization.
- +Benchmark methodology tied to operating model and decision governance
- +Cross-domain benchmarking coverage for infrastructure and application performance
- +Evidence-focused reporting for defensible peer and trend comparisons
- +Implementation support for aligning measurements across teams
- –Benchmark kickoff can be slower due to governance and stakeholder alignment
- –Heavy documentation load can slow rapid, exploratory benchmarking
- –Requires tight input from client teams to keep test boundaries consistent
- –Less suited to one-off quick scans without program orchestration
CIO office and IT governance
Benchmarking for portfolio investment decisions
Priorities aligned to measurable targets
Infrastructure and platform engineering
Capacity and resilience benchmarking program
Capacity plan with risk constraints
Show 2 more scenarios
Enterprise application owners
Application performance benchmarking baseline
Actionable performance improvement backlog
Defines KPI normalization inputs and collects evidence to compare response-time behavior across stacks.
Security and risk leadership
Benchmarking with audit-ready evidence
Findings accepted by oversight teams
Structures methodology documentation and evidence to support scrutiny of assumptions and results.
Best for: Fits when IT leadership needs auditable benchmarking results for cross-functional investment decisions.
EY
enterprise_vendorBig Four firm providing IT benchmarking and technology transformation advisory.
KPI normalization work is paired with advisory governance to align metric definitions across infrastructure and application test results.
EY delivers IT benchmarking services that combine performance assessment with enterprise advisory support across infrastructure and applications. Engagements emphasize benchmark design, KPI normalization, and repeatable testing workflows tied to business and operational objectives.
- +Benchmark design and KPI normalization mapped to operational decision-making
- +Advisory-led governance for test environment parity and configuration drift control
- +Cross-domain benchmarking coverage for infrastructure, platforms, and key applications
- +Peer-group comparison framing tied to actionable maturity and operating-model changes
- –Heavily engagement-led, with limited self-serve automation for in-house teams
- –Integrating internal telemetry into report-ready outputs can extend project timelines
- –Synthetic workload design depth depends on client instrumentation and access
- –Benchmark runbooks may require hands-on coordination with test engineering teams
Best for: Fits when enterprise teams need benchmark design and governance guidance tied to peer comparison and execution priorities.
Computer Economics
specialistIT research firm focused on IT spending, staffing, and budget benchmarking.
Benchmark methodology that normalizes participant data into standardized peer metrics for operational and cost decision-making.
Computer Economics performs IT benchmarking research by collecting organization inputs, normalizing the results, and publishing peer-group comparisons focused on operational and cost performance. It is most distinct for its benchmark-driven advisory workflow that turns survey data into decision-ready metrics and cross-company performance views.
- +Peer-group comparisons built from structured survey inputs
- +Clear KPI normalization approach for cross-organization reporting
- +Benchmark methodology documentation supports consistent annual participation
- +Benchmark outputs map to cost and operations decisions
- –Limited fit for live synthetic benchmark runbook execution
- –Automation and API surface for programmatic submissions is not the focus
- –Benchmark timelines depend on participation cycles and publication cadence
- –Requires internal data collection to match benchmark definitions
Best for: Fits when IT leaders need peer-group performance and cost comparisons using survey-based benchmark methodology.
Capgemini
enterprise_vendorConsulting and technology services firm offering IT benchmarking and optimization.
Benchmark run governance that ties workloads, configuration, and telemetry capture into a repeatable execution record for later comparison.
Capgemini fits IT leaders who need end-to-end benchmark design, lab build, and execution support across enterprise and regulated environments. Its distinct strength is delivery depth that spans workload modeling, performance test engineering, and governance for repeating measurement campaigns across business units.
- +Delivery teams can translate benchmark designs into repeatable test harness runs
- +Telemetry-to-report integration supports traceability from workloads to KPIs
- +Governance around run artifacts helps reduce configuration drift across cycles
- +Cross-domain coverage supports application, infra, and workload benchmark scopes
- –Benchmarks usually require consulting-led scoping rather than plug-and-play setup
- –Automation depth depends on existing tooling integration and data pipeline maturity
- –Benchmark turnaround time can lag when hardware and environment parity are not ready
- –Admin and RBAC controls are constrained by the organization’s internal operating model
Best for: Fits when enterprises need consulting-led benchmark run design, lab parity, and KPI normalization across multiple teams.
Information Services Group
specialistTechnology research and advisory firm specializing in IT outsourcing and benchmarking.
Methodology traceability artifacts that record KPI definitions, assumptions, and run changes for consistent peer-group interpretation.
Information Services Group differentiates in IT benchmarking by tying peer-group performance comparisons to structured measurement programs across enterprise environments.
- +Benchmark design and KPI normalization aligned to repeatable measurement conditions
- +Integration work connects telemetry sources to consistent data collection and reporting
- +Assumptions and change notes improve traceability from run design to results
- +Peer-group comparison framing supports actionable performance interpretation
- –Requires disciplined test-environment parity planning to avoid configuration drift
- –Automation and API surfaces depend more on engagement scope than on a generic self-serve layer
- –Benchmark turnarounds can be constrained by workload availability and client coordination
- –RBAC and audit log granularity is harder to assess without a live governance workshop
Best for: Fits when enterprise IT teams need controlled benchmark methodology and peer-group interpretation across mixed stacks.
The Hackett Group
specialistConsulting firm offering enterprise IT and finance function benchmarking.
Maturity assessment methodology coupled with benchmark design and KPI normalization for auditable peer comparison.
The Hackett Group delivers IT benchmarking and performance benchmarking work built around peer-group comparison and structured maturity assessments. Delivery typically combines benchmark design, target KPI normalization, and cross-company analytics into industry and enterprise performance reports.
- +Peer-group benchmarking model ties KPI definitions to organizational context
- +Measurement governance reduces variation in KPI normalization across datasets
- +Benchmark design documentation supports repeatable benchmark runs
- +Industry benchmarking coverage aligns IT performance to operating models
- –API and automation surface is not positioned as a self-serve benchmark engine
- –Benchmark run timelines depend on data readiness and agreed measurement scope
- –Extensibility for custom workloads is typically project-driven, not product-native
- –Automation for telemetry collection and test harness orchestration requires handoff work
Best for: Fits when enterprise IT leadership needs peer comparison, KPI normalization, and report-ready governance.
Everest Group
specialistResearch and advisory firm providing IT services and outsourcing benchmarking.
KPI alignment and normalization methodology tailored for peer comparisons across suppliers and enterprise contexts.
Everest Group performs IT benchmarking and market intelligence services that translate supplier and enterprise performance signals into peer-group comparisons. Its core work centers on benchmark design, structured performance assessments, and report packages that connect benchmarking outcomes to market and vendor positioning.
- +Benchmark design rigor with KPI normalization for cross-peer comparability
- +Research-led synthesis links benchmarking findings to market and supplier context
- +Structured assessment approach supports governance conversations and executive reporting
- +Well-defined deliverables for benchmarking workstreams and stakeholder updates
- –Less coverage of benchmark run automation and synthetic workload orchestration
- –Heavier reliance on client-provided inputs for telemetry and baselining
- –API and integration surface is limited compared with platform-style benchmarking vendors
- –Benchmark customization depth can require more stakeholder time to finalize scope
Best for: Fits when research-led benchmarking outputs and peer-group interpretation matter more than automated test harness execution.
MetricNet
specialistSpecialist firm providing IT service desk and support benchmarking.
A runbook that ties telemetry collection to KPI normalization for consistent, comparable benchmark reporting across multiple runs.
MetricNet delivers IT benchmarking services that focus on infrastructure and application performance comparisons across peer groups, not just ad hoc test execution. Engagements typically include benchmark design, test workload selection, and KPI normalization so results are comparable across environments.
- +Benchmark design and KPI normalization for cross-environment comparability
- +Runbook-driven workflows that reduce result variability across runs
- +Integration options for pulling observability data into benchmark reporting
- +Peer-group reporting that supports practical capacity and performance planning
- –Requires disciplined configuration control to avoid benchmark drift
- –Automation coverage depends on available telemetry sources
- –Benchmark workload alignment can take time for nonstandard stacks
- –Governance artifacts for audit trails may require extra engagement effort
Best for: Fits when mid-market IT teams need repeatable benchmarking results aligned to peer comparisons and capacity decisions.
Conclusion
After evaluating 10 it benchmarking, McKinsey & Company stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right It Benchmarking
IT benchmarking services translate IT performance measurements into peer-comparable evidence that leadership can use for capacity planning, governance, and migration decisions. This guide focuses on ten providers that deliver benchmark design, KPI normalization, and benchmark run documentation, including McKinsey & Company, Accenture, Deloitte, and EY.
The provider set also includes Computer Economics, Capgemini, Information Services Group, The Hackett Group, Everest Group, and MetricNet. Each entry emphasizes tradeoffs between advisory-led benchmark governance and runbook-driven execution that can keep measurement definitions stable from one run to the next.
IT Benchmarking services that design runbooks, normalize KPIs, and keep benchmark evidence traceable across environments
IT benchmarking services establish benchmark design and measurement definitions so multiple teams and environments produce comparable KPI outputs instead of conflicting results. McKinsey & Company ties KPI normalization rules to workload selection and telemetry collection requirements through benchmark runbook development. Accenture extends that runbook approach with governance artifacts that preserve environment controls and evidence traceability from setup through reporting.
Other providers in this set differentiate by anchoring benchmark work to operating-model decision workflows, cross-domain methodology, or auditable measurement governance. Deloitte connects benchmarking definitions to executive decision workflows, while EY pairs KPI normalization with advisory governance to align metric definitions across infrastructure and application test results. Providers like MetricNet emphasize runbook-driven workflows that reduce result variability across runs, while still requiring disciplined configuration control to prevent benchmark drift.
IT Benchmarking capabilities that determine comparability and governance
Good IT benchmarking services do more than run tests. They lock benchmark design choices into repeatable benchmark run documentation so KPI normalization stays consistent across teams and environments.
These capabilities also decide how evidence survives stakeholder review. The strongest providers connect benchmark definitions to operating-model decision workflows and keep audit trails around what changed between runs.
Benchmark runbooks that tie KPI normalization to telemetry and workload selection
McKinsey & Company builds benchmark runbook development that links KPI normalization rules to workload selection and telemetry collection requirements. MetricNet provides runbook-driven workflows that reduce result variability across multiple runs by tying telemetry collection to KPI normalization.
Governance artifacts that preserve environment controls and evidence traceability
Accenture integrates benchmark runbooks with enterprise delivery governance so environment controls and evidence traceability remain intact from setup through reporting. Deloitte and EY connect measurement definitions to executive decision workflows while adding governance that aligns metric definitions across infrastructure and application test results.
Traceability artifacts for assumptions, KPI definitions, and run changes
Information Services Group focuses on methodology traceability artifacts that record KPI definitions, assumptions, and run changes so peer-group interpretation stays consistent. The Hackett Group adds measurement governance that reduces variation in KPI normalization across datasets while pairing maturity assessment with benchmark design.
Repeatable test harness delivery that can convert benchmark designs into runs
Capgemini supports consulting-led benchmark run design that teams translate into repeatable test harness runs. This repeatability depends on the maturity of telemetry and data pipelines, which Capgemini addresses by tying telemetry-to-report integration to traceability from workloads to KPIs.
Research-led KPI normalization when automation is not the primary requirement
Computer Economics and Everest Group emphasize peer-group comparisons and KPI normalization built from structured inputs and research synthesis. This approach trades off benchmark run automation and synthetic workload orchestration for faster interpretation of peer performance patterns.
Choose by evidence workflow fit, not by benchmark branding
Benchmarking services differ most by how they control the path from benchmark design through evidence reporting. The decision framework below separates runbook-driven delivery that teams can repeat from engagement-led methodology that prioritizes governance and interpretation.
The next steps use branching checks so choices align to delivery constraints like environment parity, data readiness, and desired frequency of runs.
Map the target decision to the provider’s evidence artifact
If the output must feed capacity and governance decisions with measurable workload-to-KPI linkage, McKinsey & Company ties KPI normalization rules to workload selection and telemetry collection requirements. If the output must include setup through reporting evidence that environment controls can defend, Accenture keeps runbooks integrated with enterprise delivery governance.
Pick a delivery philosophy for benchmark repeatability
If repeatability across multiple runs is the priority, MetricNet uses runbook-driven workflows that reduce result variability while still requiring configuration control. If repeatability must be managed through consulting governance and stakeholder alignment, Deloitte and EY anchor measurement definitions to executive decision workflows and may slow kickoff due to governance and alignment steps.
Decide who owns environment parity and change windows
If internal teams can enforce test environment parity and control change windows, Accenture can deliver controlled benchmarking evidence across multiple teams. If parity discipline is not guaranteed, Information Services Group and EY emphasize artifacts for configuration drift control, but both still depend on disciplined test environment parity planning.
Choose benchmark evidence traceability depth versus self-serve automation
If the requirement is auditable governance that records KPI definitions and run changes, Information Services Group records KPI definitions, assumptions, and run changes for consistent peer interpretation. If the requirement is a maturity assessment that pairs benchmark design with governance for auditable peer comparison, The Hackett Group concentrates on measurement governance rather than a self-serve benchmark engine.
Select the benchmark style based on workload orchestration needs
If synthetic workload execution and run harness conversion are needed, Capgemini positions benchmark designs into repeatable test harness runs with telemetry-to-report integration traceability. If the main goal is peer-group interpretation from structured inputs and research synthesis, Computer Economics and Everest Group focus on survey-based or research-led KPI normalization rather than automated synthetic orchestration.
Stress the handoff between benchmark outcomes and the operating model
If benchmarking must connect to operating-model and roadmap actions, McKinsey & Company provides a strong linkage from performance findings to operating-model actions. If benchmarking must align across domains with advisory governance for execution priorities, EY pairs KPI normalization with governance guidance across infrastructure and application test results.
Who should buy IT Benchmarking services from this set
These providers fit buyers who need peer-comparable IT performance evidence with traceable measurement definitions. They also fit enterprises that want governance artifacts tied to how leadership funds capacity and migration decisions.
The profiles below focus on how buyers use benchmarking output in governance, planning, and cross-team alignment rather than on generic benchmarking goals.
CIO and IT leadership teams funding capacity and migration decisions
McKinsey & Company and Deloitte connect benchmarking findings to operating-model and executive decision workflows so leadership can justify investment choices with decision-grade comparisons and governance artifacts.
Enterprise architecture and program governance teams running benchmarking across many environments
Accenture and Capgemini align benchmark run documentation and telemetry integration so multiple teams can keep environment controls consistent from setup through reporting.
IT operations teams that must rerun benchmarks and control benchmark drift
MetricNet and Information Services Group emphasize runbook-driven workflows and methodology traceability so repeated runs remain comparable under controlled configuration and documented run changes.
Procurement and strategy teams using benchmarks to benchmark suppliers or market context
Everest Group and Computer Economics prioritize KPI alignment and normalization tailored for peer comparisons and research synthesis, which supports market and supplier interpretation more than synthetic run orchestration.
Cross-functional stakeholders needing auditable evidence to reduce disagreement across teams
The Hackett Group and EY use measurement governance and advisory governance to reduce variation in KPI normalization, with artifacts that support auditable peer comparison across teams.
Common buying pitfalls that break comparability
Benchmark buyers often lose comparability when they treat benchmark design as a one-time deliverable. The providers in this set repeatedly tie outcomes to runbooks, traceability artifacts, and governance work that must be implemented with disciplined environment control.
The mistakes below map to concrete failure modes seen across advisory-led and runbook-led delivery styles.
Selecting a provider for report quality while underestimating the amount of environment parity work required
Accenture’s controlled evidence depends on client control of environment parity and change windows, so buyers should plan for parity readiness before kickoff. EY and Information Services Group also require test environment parity discipline to avoid configuration drift.
Assuming benchmark results will stay comparable when telemetry definitions and run assumptions are not explicitly recorded
Information Services Group records KPI definitions, assumptions, and run changes, which is needed to keep peer-group interpretation consistent. MetricNet reduces result variability only when configuration control is in place to prevent benchmark drift.
Choosing consulting-led governance when recurring self-serve benchmark runs are the operational requirement
McKinsey & Company and Deloitte focus on engagement-led delivery with advisory support, which is less suited for frequent self-serve benchmark runs. The Hackett Group similarly positions API and automation surface as not the centerpiece for a self-serve benchmark engine.
Expecting automated synthetic workload orchestration from research-led benchmarking approaches
Everest Group and Computer Economics emphasize research-led outputs and KPI normalization from structured inputs rather than benchmark run automation and synthetic workload orchestration. Buyers who need run harness execution should prioritize Capgemini or MetricNet based on runbook-driven execution.
Over-optimizing for a single metric without aligning it to workload selection and telemetry collection requirements
McKinsey & Company ties KPI normalization rules to workload selection and telemetry collection requirements through benchmark runbook development. If buyers separate metric definitions from workload and telemetry assumptions, the normalization artifacts will not prevent run-to-run variation.
How We Selected and Ranked These Providers
We evaluated McKinsey & Company, Accenture, Deloitte, EY, Computer Economics, Capgemini, Information Services Group, The Hackett Group, Everest Group, and MetricNet on benchmarking-specific features, delivery ease, and value for buyers who need comparable IT performance evidence. Features accounted for 40% of the score by weighting benchmark runbook development and governance artifacts that keep KPI normalization traceable to workload and telemetry.
Ease and value each accounted for 30% by rewarding delivery patterns that reduce rework, preserve environment control, and lower the burden of maintaining configuration discipline. McKinsey & Company separated itself by tying KPI normalization rules directly to workload selection and telemetry collection through benchmark runbook development, and by linking performance findings to operating-model and roadmap actions.
Frequently Asked Questions About It Benchmarking
What distinguishes McKinsey versus Deloitte when leadership needs peer-comparable performance evidence?
How does Accenture handle benchmark runbooks inside a change and delivery process compared with Information Services Group?
Which provider is most focused on audit-style defensibility for benchmark methodology and interpretation?
How do Capgemini and MetricNet differ in how they connect telemetry collection to benchmark reporting?
When does Computer Economics fit better than Hackett Group for benchmarking outputs used in operational and cost decisions?
Which services are more likely to support integrations and API-based automation for benchmark workflows?
What tradeoff appears when benchmarking projects require heavy governance artifacts and cross-team instrumentation alignment?
When does governance around benchmark configuration drift matter more: Everest Group or Information Services Group?
What breaks if KPI normalization rules are not aligned with workload selection and telemetry definitions?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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