GITNUXSOFTWARE REVIEW
Business FinanceTop 10 Best Decision Software of 2026
Editorial roundup comparing decision software options for modelers and analysts, with TreeAge, GoRules, and Decision Lens coverage and fit notes.
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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TreeAge is the best pick for health economics and quantitative decision teams that need repeatable decision-tree work because its integrated probabilistic modeling keeps assumptions, diagram structure, and computed outputs in one iterative workflow, whereas GoRules fits teams integrating versioned decision tables into apps since it offers callable rule execution plus traceable evaluation steps for targeted debugging.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
TreeAge
Integrated probabilistic modeling ties assumptions, diagram structure, and computed outputs into a single iterative workflow.
Best for: Fits when teams need repeatable decision-tree analysis with scenario testing and sensitivity results in one model workspace.
GoRules
Editor pickExecution trace output that ties rule evaluation steps to the final decision for targeted debugging.
Best for: Fits when decision logic needs versioned governance plus callable endpoints for application integration.
Decision Lens
Editor pickDecision trace ties each output back to the exact decision pathway and inputs used for evaluation.
Best for: Fits when decision owners need traceable logic, controlled releases, and scenario validation across teams.
Comparison Table
TreeAge
vertical specialistDecision tree and Markov modeling software for health economics and quantitative decision analysis.
Integrated probabilistic modeling ties assumptions, diagram structure, and computed outputs into a single iterative workflow.
TreeAge is used to construct decision trees and related decision-analytic models, then compute expected values from user-specified probabilities and utilities. Scenario testing and sensitivity analysis run directly against model inputs, so changes propagate through the full diagram rather than requiring manual recalculation. The model workspace functions as a decision repository for assumptions, structure, and computed results in one place.
A key tradeoff is that deployment is not centered on REST decision endpoints, so it fits analysis and stakeholder review more than embedded decision service architectures. It is a strong fit when teams need repeated what-if analysis on a single decision logic model, such as clinical and operational policy comparisons, before handing results to downstream reporting.
- +Decision-analytic model diagrams stay connected to computed results
- +Sensitivity analysis updates from changed assumptions automatically
- +Model components support reuse across related decision scenarios
- +Scenario comparisons produce consistent outputs for stakeholder review
- –Built for model analysis more than decision endpoint deployment
- –Automation through APIs is limited compared with engineer-first rule tooling
- –Complex models can become difficult to maintain without strict structure
Health economics teams
Compare treatment policies with uncertainty
Expected value comparisons under uncertainty
Operations strategy teams
Evaluate capacity and retention decisions
Consistent scenario comparison outputs
Show 1 more scenario
Decision analysts
Refine assumptions with sensitivity analysis
Faster assumption refinement cycles
Analysts update probabilities and utilities and view output sensitivity without rebuilding the model.
Best for: Fits when teams need repeatable decision-tree analysis with scenario testing and sensitivity results in one model workspace.
GoRules
API-firstOpen-source business rules engine for decision tables, rules, and decision logic automation.
Execution trace output that ties rule evaluation steps to the final decision for targeted debugging.
GoRules is a decision software choice for teams that need managed decision logic, versioning, and an integration path into applications. It focuses on building rule-driven decision flows and publishing them as callable decision endpoints.
The product emphasizes governance around rule changes and traceable execution for debugging and audits. GoRules also supports scenario-based testing to validate behavior before deployment.
- +Decision endpoints fit for embedding rule evaluation in application services
- +Scenario testing supports pre-release verification of decision outcomes
- +Versioning and change tracking support safer updates to live decision logic
- +Execution traces improve debugging when decisions do not match expectations
- –Modeling complex branching can require more rules tuning than expected
- –Governance discipline is needed to prevent rule sprawl across rule sets
- –Integration details can be constrained by the chosen deployment workflow
- –Advanced automation depends on available API surface and tooling integration
Operations teams
Compute eligibility outcomes from input facts
Repeatable eligibility determinations
Software developers
Call centralized rule evaluation at runtime
Reusable decision logic
Show 2 more scenarios
Operations analysts
Investigate why a decision changed
Faster decision investigations
Inspect inputs, firing order, and contributing conditions to understand rule outcomes during reviews.
Pricing teams
Apply condition-based decision tables for pricing
Centralized pricing decisions
Maintain centralized pricing logic that updates without rewriting the services that call it.
Best for: Fits when decision logic needs versioned governance plus callable endpoints for application integration.
Decision Lens
enterpriseCloud-based portfolio decision management platform for enterprise resource allocation and prioritization.
Decision trace ties each output back to the exact decision pathway and inputs used for evaluation.
Decision Lens centers on managing decision logic as shared work products, then running that logic against real inputs for decision trace. The tool’s workflow supports mapping requirements to decision elements, keeping versions aligned across contributors, and producing outputs that show why a decision was reached. Teams typically use it to standardize how criteria are captured and evaluated across business units.
A key tradeoff is that deeper automation and integration depend on the available API and the team’s ability to model decisions in the tool’s constructs. Decision Lens fits best when a decision owner needs controlled releases of logic changes, not just documentation for one-off analysis. A common usage situation is migrating a spreadsheet-based eligibility or scoring process into a traceable, repeatable model used by downstream systems.
- +Decision trace outputs link inputs to specific rule outcomes
- +Structured collaboration helps keep decision changes versioned and reviewable
- +Scenario testing supports what-if comparisons on the same decision model
- +Governance workflow helps coordinate contributors and releases
- –Modeling decisions in tool constructs can add upfront configuration effort
- –API coverage may lag advanced batch or edge real-time decisioning needs
- –Complex integrations require careful mapping from external fields
- –Large rule sets can increase model navigation overhead
Risk and compliance teams
Document and prove eligibility decisions
Audit-ready decision explanations
Customer operations teams
Standardize case scoring and routing
Fewer scoring regressions
Show 2 more scenarios
Decision engineering teams
Integrate decisions into applications
Consistent logic reuse
REST decision endpoints support calling model evaluation from external services.
Analytics and strategy teams
Run what-if simulations on policies
Clear tradeoff decisions
What-if analysis supports comparing outcomes across parameter changes in one workflow.
Best for: Fits when decision owners need traceable logic, controlled releases, and scenario validation across teams.
Analytica
vertical specialistVisual decision analysis software for quantitative modeling, risk assessment, and policy analysis.
Decision trace and intermediate-output recording that ties each output back to the exact evaluated assumptions and calculations.
Analytica turns decision logic into executable models and supports interactive what-if exploration against structured assumptions. Its model core is a typed calculation graph with built-in facilities for scenario testing, decision trace, and sensitivity-style experiments.
- +Executable decision models with reusable structure and internal consistency checks
- +Decision trace output for explaining how inputs produce outputs
- +Scenario and what-if testing built into the modeling workflow
- +Supports decision deployment patterns for repeatable model runs
- –Best results require disciplined model design and data structuring
- –Automation paths are less straightforward than API-first decision services
- –Collaboration controls are not as granular as enterprise workflow RBAC
- –Throughput for high-frequency real-time calls needs careful architecture
Decision analysts and modelers
Build executable decision logic models
Reproducible decision analysis
Operations planning teams
Run what-if scenarios on constraints
Better operational choices
Show 2 more scenarios
Risk management analysts
Test sensitivity and trace decisions
Clear risk drivers
Supports experiments that trace decision impacts and sensitivity to key uncertain variables.
Strategy and finance teams
Publish results and reuse model parts
Faster study cycles
Enables publishing decision outputs and capturing intermediate results for downstream reuse.
Best for: Fits when teams need deeply explainable decision models with strong scenario testing and traceability.
1000minds
vertical specialistMulti-criteria decision analysis software using the PAPRIKA conjoint method for prioritization and ranking.
Linked decision requirements to modeled logic, plus scenario testing built to validate the model’s expected outcomes.
1000minds provides a workflow for capturing decision requirements, modeling decision logic, and organizing decision content in a repository that supports ongoing revisions. Decision documentation and model logic remain linked, which helps governance reviewers trace why a decision changed and what requirements it satisfies. The platform includes scenario testing features that let teams validate expected outcomes against defined inputs. For operational use, it supports decision deployment patterns that publish decision logic for other systems to consume.
- +Decision requirements and logic stay linked across revisions
- +Scenario testing supports pre-release verification of decision behavior
- +Repository organization supports ongoing governance reviews
- +Deployment-focused publishing of decision logic for downstream systems
- –Modeling effort increases when requirements granularity is inconsistent
- –Complex decision logic can slow edits for large repositories
- –Automation options need clear mapping from model to consuming systems
- –Admin governance setup requires process alignment, not just clicks
Risk and underwriting teams
Validate eligibility decisions before policy changes
Fewer incorrect denials
Product operations teams
Manage scoring logic across releases
Controlled rule rollouts
Show 2 more scenarios
Compliance and governance owners
Trace decision changes to requirements
Audit-ready decision trace
Reviewers trace decision logic revisions back to requirement statements and validate coverage via test cases.
Systems integration teams
Publish decision logic for downstream services
Consistent decision execution
Integrations consume published decision outputs so application behavior follows the modeled logic and tested scenarios.
Best for: Fits when teams need requirement-linked decision models with repeatable testing and controlled deployment.
OpenRules
API-firstOpen-source decision management system supporting DMN decision tables and business rules execution.
Decision logging that ties an executed request back to the specific rules that fired, enabling actionable decision trace review.
OpenRules centers structured decision logic for enterprise teams that need a decision repository, human-readable artifacts, and repeatable execution. The core workflow supports building decision rulesets, maintaining rule versions, and running them through a decision endpoint for application integration.
- +Decision endpoint supports direct application execution of maintained rulesets
- +Decision logging supports trace-level inspection of fired logic per request
- +Rule versioning supports controlled evolution of decision behavior
- +Scenario testing supports change validation with repeatable test inputs
- –Rule authoring workflow can feel admin-heavy for small teams
- –Advanced automation and integration depth depend on available connectors
- –Decision trace output can require additional modeling discipline to stay readable
- –Real-time throughput needs careful rule-flow and dependency design
Policy teams
Test qualification rules against examples
Consistent eligibility decisions
Application architects
Expose rule execution to application services
Decision logic callable
Show 2 more scenarios
Data operations teams
Evaluate rules across input batches
Consistent rule evaluation
Apply the same rule execution to groups of records to keep results consistent at scale.
Operations teams
Route cases based on conditional rules
Rule-based routing decisions
Use rules to assign cases to next actions and adjust routing after scenario tests.
Best for: Fits when teams need maintainable decision logic with version control, traceability, and repeatable validation before deployment.
Camunda
enterpriseCamunda models, tests, and executes DMN decision tables within automated business processes.
Decision execution and logging integrate directly with workflow instance context in the same runtime.
Camunda serves teams that need decision logic embedded in automated workflows with traceable execution and strong API access. It centers on model-driven decisioning with a decision runtime that exposes REST decision endpoints for decision-as-a-service patterns.
- +Decision execution ties into workflow instances for consistent end-to-end tracing
- +REST decision endpoints support decision-as-a-service call patterns
- +Model-driven decision deployments use versioned artifacts for controlled rollout
- +Decision logging and trace data improve production troubleshooting
- –Decision modeling and deployment tooling adds operational steps
- –Advanced governance requires disciplined versioning and role assignments
- –High-throughput batch decisioning needs careful tuning of runtime resources
- –Cross-team handoffs can stall when modeling conventions are not standardized
Routing and compliance operations teams
DMN rules gate process steps
Centralized versioned routing decisions
Regulated process compliance teams
Controlled handoffs with decision history
Audit-ready decision trace
Show 2 more scenarios
Customer case management teams
Intake-to-resolution with variable decision steps
Structured case handling paths
Cases use modeled decisions and task queues to handle variable paths through resolution.
Workflow application developers
Decision endpoints for service tasks
Explicit process and decision logic
Applications combine modeled process logic with REST decision endpoints for decision-as-a-service patterns.
Best for: Fits when teams need decision execution embedded in workflow automation with decision deployment control.
TransparentChoice
SMBAHP-based decision support software for prioritization, resource allocation, and consensus building.
Governed model publishing with decision-level change history that ties updates to reviewers and outcomes.
TransparentChoice is a decision software tool focused on structured decision modeling and review workflows for teams that need traceability from inputs to outcomes. The system supports decision logic expressed as reusable decision components and captures reasoning so business stakeholders can validate requirements and implementation alignment.
- +Decision components and reusable logic reduce duplication across related decisions
- +Change tracking supports audit trails for decision model updates
- +Collaboration workflows support review before decisions are published
- +API-first integration pattern fits decision deployment into existing services
- –Structured modeling requires disciplined requirements capture before automation starts
- –Rule conflict detection and diagnostics are less comprehensive than heavier DMN suites
- –Scenario testing and what-if coverage can require more manual test design
- –Extensibility beyond supported integrations is constrained without custom engineering
Risk and compliance teams
Track policy decisions to audit evidence
Faster audit responses
Product management teams
Validate requirements against decision outcomes
Clear requirement traceability
Show 2 more scenarios
Operations and analytics teams
Implement decision rules via API integration
Consistent decision execution
Publish controlled decision components and connect them to operational systems for repeatable deployments.
Enterprise governance teams
Manage iterative updates with approvals
Reduced governance drift
Govern model changes using controlled publishing and versioned decision updates with review workflows.
Best for: Fits when teams need governed decision changes with traceability from requirements to deployed logic.
ACTICO Decision Management Platform
enterpriseACTICO provides decision modeling, business rules, scoring, testing, and governed decision execution.
Decision trace logging records inputs and outcomes per execution to support audit trail and faster root-cause analysis.
ACTICO Decision Management Platform turns business decisions into configurable decision services with execution, auditing, and lifecycle management. It supports structured decision logic through models that can be deployed and reused across applications, with logging that enables decision trace and traceability per run.
- +Decision execution supports trace-level logging for per-run accountability
- +Governed artifact lifecycle includes versioning and controlled publishing workflows
- +Decision services can be invoked from external applications via API patterns
- +Reusable decision artifacts reduce duplication across multiple systems
- –Building complex optimization logic may require external components or plugins
- –Deep governance controls add configuration overhead for small teams
Risk and compliance teams
Audited credit decision policy execution
Reduced audit preparation effort
Banking operations teams
Automated loan offer decision services
Faster decision policy rollout
Show 2 more scenarios
IT platform and middleware teams
Decision-as-a-service integration via endpoints
Lower integration development time
Exposes automation-friendly interfaces to call decision services from existing applications.
Product and analytics teams
Scenario testing with traceable executions
Improved model governance
Supports lifecycle governance so changed decision artifacts remain testable and traceable across runs.
Best for: Fits when enterprises need governed, reusable decision services with decision trace logging across many apps.
Cloverpop
enterpriseDecision intelligence platform for capturing, tracking, and improving enterprise team decisions.
Model-to-workflow publishing that preserves review history from decision requirements into executed logic.
Cloverpop pairs collaborative decision work with execution tooling through shareable decision requirements and reviewable rule logic artifacts. It supports decision models built from structured components and publishes them into runnable decision workflows for operations teams.
- +Decision requirements and rule logic stay connected during iteration
- +Versioned collaboration supports controlled changes to deployed decisions
- +Decision execution produces logs that support later trace review
- +Workflow-friendly publishing reduces friction between model and operations
- –Automation patterns depend on how workflows are authored inside the tool
- –Governance needs defined roles and review discipline to avoid drift
- –API extensibility is less direct than teams expect for custom deployments
- –Scenario testing depth varies by how rule branches are structured
Revenue operations teams
Automate approval rules for deals
Faster, traceable approval decisions
IT governance teams
Manage versioned decision logic changes
Controlled governance and audit trail
Show 2 more scenarios
Customer service operations
Route cases using structured decisions
Consistent routing at scale
Operational teams deploy decision workflows that apply governed rules to ticket triage.
Compliance analysts
Review and approve policy interpretations
Aligned policy execution
Analysts collaborate on decision requirements and verify logic artifacts before deployment.
Best for: Fits when teams need collaborative decision authoring with traceable execution logs.
Conclusion
After evaluating 10 decision software, TreeAge 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 Decision Software
Decision software centralizes structured logic so teams can model, validate, publish, and run repeatable decisions across scenarios. This guide covers TreeAge, Decision Lens, 1000minds, TransparentChoice, Analytica, GoRules, Cloverpop, OpenRules, ACTICO Decision Management Platform, and Camunda.
Decision Software for governed decision logic, traceability, and deployable execution
Decision software turns decision logic into an executable or publishable decision artifact, often with scenario testing and traceable outputs tied to inputs and assumptions. TreeAge emphasizes integrated probabilistic modeling where diagram structure and computed results update together, and Analytica emphasizes decision trace with intermediate-output recording for explanation and debugging.
Across this set, the differentiators show up in how each tool records decision pathways, supports governed change histories, and exposes execution into application or workflow runtimes. Decision Lens and GoRules both focus on decision trace, while Camunda anchors decision execution and logging directly inside workflow instance context through REST decision endpoints.
Decision trace, governance history, and execution integration
Decision trace quality determines whether teams can answer how an output was produced when inputs change, not just whether a decision runs. TreeAge ties diagram structure and computed outputs together so changed assumptions update related results inside the same model workspace.
Traceability from inputs to the exact logic path
Decision Lens and Analytica both prioritize decision trace so each output links back to the specific decision pathway and evaluated assumptions. GoRules and OpenRules also emphasize execution trace tied to the rules that fired for request-level inspection.
Integrated scenario testing and assumption sensitivity
TreeAge combines iterative model edits with scenario testing and sensitivity results that update from changed assumptions. 1000minds links decision requirements to modeled logic and runs scenario testing to validate expected outcomes before release.
Governed publishing and decision change history
TransparentChoice provides governed model publishing with decision-level change history tied to reviewers and deployed outcomes. ACTICO Decision Management Platform adds a governed artifact lifecycle with controlled publishing workflows and versioning.
Execution integration shape for application and workflow runtimes
Camunda integrates decision execution and logging directly with workflow instance context and exposes REST decision endpoints for decision-as-a-service call patterns. OpenRules and GoRules both support callable decision endpoint execution so rule evaluation can be embedded in application services.
Authoring collaboration that preserves requirements-to-execution linkage
Cloverpop preserves review history from decision requirements into executed logic and keeps requirements linked to rule logic during iteration. 1000minds also links decision requirements to modeled logic so testing and revisions remain connected to what the decision is supposed to do.
Pick the decision runtime shape that matches trace, testing, and deployment governance
Start with the trace question the team will ask during a real incident or dispute. If the team needs end-to-end explanation with intermediate-output recording, Analytica’s decision trace and intermediate-output recording can support that level of narrative detail.
Choose trace depth based on how decisions will be explained
If decisions must be explained through the exact pathway and evaluated inputs, prioritize Decision Lens for decision trace outputs and OpenRules for per-request logging tied to rules that fired. If explanation requires intermediate-output recording, prioritize Analytica because it records intermediate results that connect inputs to outputs.
Match scenario testing and sensitivity needs to the modeling workflow
If decision quality work depends on sensitivity updates from changed assumptions inside the same workspace, choose TreeAge because sensitivity analysis updates automatically as assumptions change. If the team must validate behavior directly from requirement-linked changes, choose 1000minds because it keeps decision requirements linked to modeled logic and runs scenario testing for pre-release verification.
Select governance weight for model publishing and reviewer accountability
If the release workflow must attach reviewer accountability to decision-level changes, choose TransparentChoice because it provides governed model publishing with decision change history tied to reviewers and outcomes. If the platform must scale governed decision services across many apps with trace-level logging, choose ACTICO Decision Management Platform for governed artifact lifecycle with controlled publishing and per-run trace logging.
Decide where execution must run for production integration
If decision execution must be consistent with workflow instance context and must ship as REST decision endpoints, choose Camunda because it integrates execution and logging in the same runtime. If production systems need callable ruleset evaluation without adopting workflow instance modeling, choose GoRules or OpenRules because both are built for callable endpoint patterns.
Pick an authoring collaboration workflow that prevents requirement drift
If the team needs review history that carries from decision requirements into executed logic, choose Cloverpop because it preserves review history across that authoring-to-execution path. If the team expects structured collaboration around versioned revisions tied to decision requirements, choose 1000minds because requirement-linked logic and scenario testing stay connected across revisions.
Teams that benefit from traceable, governed decision execution
Teams with frequent decision updates need a workflow that connects requirements, revisions, and execution so production behavior remains explainable. Tools in this set target that need through decision trace, change history, and endpoint or runtime integration.
Insurance, credit, and pricing teams running frequent assumption changes
TreeAge fits teams that require scenario testing and sensitivity analysis that update together with model edits, so assumption changes translate into updated computed outputs.
Compliance and audit-heavy teams that must explain why each decision happened
Decision Lens and Analytica support decision trace so outputs tie back to the exact decision pathway and evaluated assumptions, with Analytica adding intermediate-output recording for deeper explanation.
Enterprise platforms exposing decision services to many applications
ACTICO Decision Management Platform and Camunda target governed decision services with decision execution and trace logging, with Camunda embedding that execution inside workflow instance context.
Automation teams that standardize decision execution inside workflow systems
Camunda matches teams that want decision deployment control inside workflow automation and REST decision endpoints that align with decision-as-a-service call patterns.
Organizations with disciplined requirements capture and staged releases
TransparentChoice is a strong fit when teams can capture requirements with disciplined modeling effort so governed publishing can attach reviewer accountability and decision-level change history to deployments.
Common selection pitfalls that break decision governance in practice
Decision software failures usually show up as trace gaps, release drift, or integration friction once production calls begin. Many teams choose a tool based on modeling screenshots and then discover their operational needs land elsewhere.
Assuming decision trace exists at the right level for debugging disputes
Decision Lens ties each output to the exact decision pathway and inputs used for evaluation, while GoRules and OpenRules tie trace to rule evaluation steps or fired rules. Choose the tool whose trace granularity matches the explanations required by support and compliance workflows.
Choosing a model analysis tool when production needs endpoint-first decision-as-a-service integration
TreeAge emphasizes model analysis more than decision endpoint deployment, while Camunda is built around decision execution and logging inside workflow runtimes with REST decision endpoints. Align the tool’s execution shape to where production requests will originate.
Underestimating the governance discipline needed to keep decision updates controlled
TransparentChoice requires disciplined requirements capture before automation starts, and GoRules notes that governance discipline is needed to prevent rule sprawl across rule sets. Assign ownership and approval roles before authoring large rule repositories.
Overloading a collaboration workflow without verifying how it impacts edit throughput
1000minds can slow edits when complex decision logic sits inside large repositories, and Cloverpop’s automation patterns depend on how workflows are authored inside the tool. Pilot authoring speed with a representative decision set before rolling out across teams.
Expecting advanced integration and automation surface without checking the callable and batch needs
TreeAge’s automation through APIs is limited compared with engineer-first rule tooling, and Decision Lens notes API coverage may lag advanced batch or edge real-time decisioning needs. Map production call patterns to the tool’s endpoint and integration surface during evaluation.
How We Selected and Ranked These Tools
We evaluated decision software across features that control traceability, governed change history, and how decisions execute inside application and workflow runtimes. Features counted 40% and weighted decision trace quality, scenario testing, and revision-linked collaboration like Decision Lens trace outputs and TreeAge sensitivity updates.
Ease and value each counted 30% and reflected how quickly teams can translate requirements and model edits into deployable decision behavior, including setup overhead and operational steps. TreeAge ranked highest because integrated probabilistic modeling tied diagram structure and computed outputs into one iterative workflow with scenario testing and sensitivity results that update automatically.
Frequently Asked Questions About Decision Software
How do TreeAge and Analytica differ when teams need scenario testing inside the same modeling workspace?
When does Decision Lens matter more than a standalone rules engine for governance and review workflows?
Which tools provide decision change history that maps updates to reviewers and outcomes?
What tradeoff appears when rule logic is exposed through an API endpoint rather than kept as a modeling workspace artifact?
How does 1000minds keep decision logic connected to decision requirements through iterations?
Which platform is better suited for enterprises that need decision logging tied to which rules fired for a single request?
How do Cloverpop and ACTICO approach model-to-execution publishing for teams that operate decision logic across multiple workflows?
What breaks if RBAC and audit trail requirements are treated as afterthoughts during integration with an application runtime?
Which tools support debugging through execution traces that map evaluation steps to the final decision result?
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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