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Supply Chain In IndustryTop 10 Best Supply Chain Demand Planning Software of 2026
Ranking roundup of top supply chain demand planning software tools with criteria for forecasting, planning workflows, and tradeoffs for operations teams.
How we ranked these tools
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Framework: Features 40% · Ease 30% · Value 30%
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Anaplan is the best pick for planning teams that need scenario-driven demand planning with tight governance because its reusable, multi-dimensional calculation model keeps scenario rollups consistent from demand signals to plan outputs, while RELEX Solutions fits retail planners that must run constraint-aware, time-phased matching across many SKUs and locations.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Anaplan
Multi-dimensional modeling with reusable calculation logic enables consistent scenario rollups from demand signals to plan outputs.
Best for: Fits when planning teams need scenario-driven demand planning with tight governance and repeatable integrations.
RELEX Solutions
Editor pickTime-phased constrained matching that drives inventory and service outcomes directly from scenario demand changes.
Best for: Fits when planners need constraint-aware demand planning and scenario-driven matching across many SKUs and locations.
E2open
Editor pickOrder promising integration that ties planning decisions to ATP logic for execution-level consistency.
Best for: Fits when global teams need demand and execution linkage across partners, with controlled automation and auditability.
Comparison Table
Anaplan
enterpriseConnected planning platform used for demand planning, S&OP, and workforce planning.
Multi-dimensional modeling with reusable calculation logic enables consistent scenario rollups from demand signals to plan outputs.
Anaplan is a planning software built around connected modeling that supports cross-functional demand planning, supply planning, and S&OP workflows. It uses a purpose-built dimensional data model with calculation logic and drivers that carry through time-phased planning views.
Anaplan also provides an automation and integration surface through APIs, scheduled jobs, and data import patterns that support ERP and sales data synchronization for ongoing forecast updates. Governance features like RBAC and audit logging help manage model access and changes across planning teams and administrators.
- +Dimensional planning model supports SKU, location, channel, and time without custom schemas
- +Scenario planning and what-if adjustments update downstream results consistently
- +API and scheduled imports support automated forecast and plan refresh workflows
- +RBAC and audit logs support controlled access to models and changes
- –Modeling can require specialized planning design expertise for faster iteration
- –Higher-detail demand data often needs careful data mapping and data quality management
Best for: Fits when planning teams need scenario-driven demand planning with tight governance and repeatable integrations.
RELEX Solutions
vertical specialistRetail-focused supply chain planning for demand forecasting, replenishment, and allocation.
Time-phased constrained matching that drives inventory and service outcomes directly from scenario demand changes.
RELEX Solutions fits organizations that need end-to-end demand planning plus inventory and service impact modeling rather than forecasting in isolation. It supports SKU and location granularity with planning views built around time-phased execution, and it emphasizes planning data exchange so forecast outputs and demand plans can feed downstream processes. Governance typically centers on role-based access to planning functions and controlled change through managed input and scenario versions used during business reviews.
A tradeoff appears when teams require custom planning calculations beyond RELEX’s supported logic, because deep tailoring often depends on integration configuration and partner-driven extensions. A common usage situation is monthly S&OP where planners run demand scenarios, reconcile bias metrics against prior performance, and then propagate updated demand into supply plans that respect constraints and lead times.
- +Constraint-aware demand–supply matching for time-phased execution
- +Scenario runs that support S&OP style reconciliation cycles
- +Integration patterns for ERP handoffs and planning data exchange
- +Configurable forecast and operational input reconciliation
- –Custom calculation changes can require heavier configuration
- –Structured workflows require disciplined master data management
- –Setup effort is higher when integrating multiple order sources
- –Planning depth can feel complex for small teams
Retail demand planners
Channel level demand and replenishment planning
Improved service and fewer stockouts
Supply chain planning managers
S&OP reconciliation with constrained supply
Faster executive decision cycles
Show 2 more scenarios
ERP and analytics integrators
ERP feed and planning data exchange
Reduced manual spreadsheet handling
Synchronize planning datasets so demand outputs flow into upstream and downstream systems for execution.
Forecasting analysts
Bias monitoring across planning cycles
Better forecast accuracy over time
Track forecast performance and reconcile inputs when recent demand differs from statistical baselines.
Best for: Fits when planners need constraint-aware demand planning and scenario-driven matching across many SKUs and locations.
E2open
enterpriseNetwork-based supply chain planning platform spanning demand, supply, and logistics.
Order promising integration that ties planning decisions to ATP logic for execution-level consistency.
E2open supports time-phased demand planning and sales-to-supply planning workflows that align commercial commitments with supply constraints. The solution is designed around integration and automation surfaces, including API-based data synchronization and external planning data exchange for coordinated processes across systems. RBAC and governance controls are typically implemented through administrative configuration, audit-oriented operational logs, and controlled access patterns for business roles.
A practical tradeoff appears in integration depth and change control. Teams that already have stable ERP, planning, and order management data flows can move faster, while organizations with inconsistent SKU master, location structure, or demand signal definitions often need a dedicated data governance effort. A common usage situation is multi-plant planning where forecast updates drive constrained allocations and order promising outcomes through coordinated runs and exception handling.
- +API-first planning data synchronization across enterprise systems
- +Scenario planning for comparing service and inventory outcomes
- +Workflow controls for coordinated planning runs and exceptions
- +Order promising alignment from planning outputs into execution
- –Requires careful integration mapping across ERP, OMS, and planning systems
- –Planning model tuning takes sustained governance and ownership
- –UX complexity can slow adoption for narrow single-process teams
- –Partner and master data inconsistencies increase rework during runs
Global supply planners
Constrained allocation driven by updated demand
Fewer last-minute allocation changes
Revenue operations teams
Automated forecast updates into planning cycles
Faster consensus on demand
Show 2 more scenarios
Order management teams
ATP outcomes aligned to planning inputs
Higher schedule reliability
Planning outputs feed order promising logic to reduce promise drift.
Integration and data governance teams
API-based data exchange across systems
Lower integration rework
Standardized interfaces support repeatable provisioning and synchronization for planning master data.
Best for: Fits when global teams need demand and execution linkage across partners, with controlled automation and auditability.
Blue Yonder
enterpriseEnd-to-end supply chain planning suite with ML-based demand forecasting and fulfillment.
End-to-end demand planning workflow that routes forecast changes into cross-process planning iterations.
Blue Yonder’s planning workflow is organized around business processes rather than a standalone forecasting tool, so demand outcomes flow into planning and execution artifacts instead of ending at a forecast file. Demand planning functions include demand sensing inputs and collaboration loops for planners to review signals, adjust assumptions, and track forecast performance over time. The product is built for configuration of planning hierarchies such as SKU and location, which supports structured demand–supply matching work across multiple operating units.
- +Planning workflow connects forecast review to downstream planning execution steps
- +Exception-focused process helps planners prioritize signal and demand adjustments
- +API-based integration supports structured synchronization with enterprise systems
- +Configuration supports multi-level SKU and location hierarchies for planning
- –Forecast accuracy outcomes depend on strong master data and consistent history
- –Scenario iteration can require more administrative configuration than forecast-only tools
- –Deep workflow integration can add project complexity versus standalone demand modules
- –Some advanced analytic paths depend on the selected demand capabilities and setup
Best for: Fits when enterprise planning teams need controlled, workflow-based demand outcomes.
o9 Solutions
enterpriseAI-powered integrated business planning platform spanning demand, supply, and finance.
A governed scenario workspace that simulates demand–supply matching with constraint-aware outcomes and retains iteration traceability.
o9 Solutions performs end-to-end supply chain demand planning by turning demand signals into structured planning inputs that feed downstream supply and inventory decisions. Its core strength is a rules-and-simulation workflow for scenario planning and demand–supply matching that supports time-phased decision cycles.
- +Scenario planning workflow that keeps demand, supply, and constraints in one cycle
- +Extensible API-based data synchronization for recurring planning refreshes
- +Configurable planning logic supports SKU–location and time-phased views
- +Traceability across planning iterations for stakeholder review cycles
- –Requires disciplined configuration of planning logic to avoid inconsistent outputs
- –Deep setup time can extend early rollout for complex SKU and location structures
- –Forecasting performance depends on upstream data quality and signal coverage
- –Some advanced modeling tasks need implementation support to reach target fidelity
Best for: Fits when planning teams need governed scenario planning with repeatable integrations across demand and supply decisions.
Slimstock
SMBInventory optimization and demand forecasting software for mid-market distributors.
Bias and forecast accuracy monitoring tied to planning adjustments for repeatable forecast governance.
Slimstock is a demand planning software built around multi-level demand planning, with strong focus on turning demand assumptions into actionable plans by SKU and location. It supports signal-driven demand forecasting workflows, including bias and accuracy tracking, plus time-phased planning views for S&OP and IBP cycles. Integration work typically centers on ERP and planning data exchange so forecasts and plan outputs can flow into downstream order and inventory logic.
- +Multi-level demand planning supports SKU and location granularity.
- +Forecast accuracy and bias tracking supports ongoing improvement cycles.
- +Scenario planning supports sales and operations planning style comparisons.
- +API-first data synchronization supports automated planning data exchange.
- –Governance is needed to control master demand calendar changes across teams.
- –Constrained optimization depth for supply planning can lag specialist APS suites.
Best for: Fits when mid-market planners need forecast accuracy controls and multi-level demand planning with automation into ERP planning workflows.
Manhattan Associates
enterpriseSupply chain planning and execution suite with demand forecasting for retail and distribution.
Scenario planning with constrained demand–supply matching built for SKU-location decision cycles inside Manhattan planning workflows.
Manhattan Associates supplies supply chain planning software tied to its broader logistics execution and retail distribution footprint, which helps teams connect demand and inventory decisions to real operating constraints. Its demand planning and forecasting workflows are built to support time-phased planning views, SKU-location planning, and forecast performance tracking needed for demand–supply matching.
- +Integration depth between planning outputs and operational execution planning workflows
- +Planning data exchange supports ERP–APS data synchronization patterns for time-phased views
- +Forecast performance tracking supports bias and error reporting for planners
- +Scenario planning supports constrained demand–supply matching for SKU-location decisions
- –Effective use depends on disciplined master data governance for SKU and location hierarchies
- –Automation through APIs requires implementation effort for custom planning loops
- –Advanced modeling workflows can require specialist configuration work
- –UI for planners can feel complex when many scenarios are active
Best for: Fits when planning teams need ERP-connected forecasting and constrained scenario runs tied to execution operations.
ToolsGroup
specialistDemand forecasting and inventory optimization specialist for volatile supply chains.
Planning workflow orchestration that links demand forecasts into constrained supply decisions with scenario compare and execution tracking.
ToolsGroup supports connected demand and supply planning cycles with scenario handling that keeps tradeoffs visible across planning horizons. The product’s integration approach favors API-based data synchronization patterns for moving time-phased planning inputs and master data between ERP and planning environments. Governance relies on RBAC, audit logs, and configuration controls so planning model changes can be tracked and restricted by role.
- +Strong scenario planning for demand–supply matching with constrained decision support
- +Time-phased planning views help align master demand calendars with supply constraints
- +API-based data synchronization supports recurring ERP and planning data exchanges
- +Audit trails and RBAC support controlled planning changes across roles
- –Demands significant configuration to model SKU–location and hierarchy rules correctly
- –Complex planning workflows can slow adoption without formal governance
- –API integration needs tested mappings for accurate forecast and order inputs
- –Forecast lift and bias monitoring depend on disciplined data quality inputs
Best for: Fits when teams need governed, scenario-heavy demand planning tied to constrained supply decisions and system integrations.
John Galt Solutions
SMBDemand planning and forecasting platform integrated with Excel and major ERPs.
Trade-input driven demand shaping with governed planning runs for structured planner adjustments.
John Galt Solutions provides a demand planning workflow built around trade-driven forecasting inputs and planning governance for supply chain teams. It supports forecast adjustments through structured demand signals and time-phased planning views used for demand–supply matching.
- +Trade-aware forecasting inputs reduce manual demand shaping for planners
- +Time-phased planning views support transparent demand to supply matching work
- +Repeatable scenario runs support controlled comparison of demand assumptions
- +Planning dataset exchanges fit common ERP and planning handoff patterns
- –Scenario comparison depends on consistent upstream demand signal configuration
- –Deep API-based data synchronization coverage can require integration work
- –Workflow setup adds governance overhead for multi-team planning
- –Constrained optimization breadth for advanced ATP or CTP logic may be limited
Best for: Fits when trade-influenced demand inputs need structured planning governance and repeatable scenario runs.
Netstock
SMBCloud inventory forecasting and demand planning for SMBs.
Netstock’s time-phased plan updates are driven directly by ERP-connected demand and inventory signals for continuous demand–supply matching.
Netstock is a demand planning and supply planning solution that focuses on maintaining inventory accuracy and driving time-phased demand–supply matching from ERP-connected data. It supports forecast and replenishment workflows that feed SKU and location level plans, then translates plan changes into operational actions.
- +Strong SKU and location planning workflow tied to ERP order and inventory signals
- +Scenario planning supports controlled what-if runs for demand and supply assumptions
- +Planning outputs are designed for operational execution using time-phased views
- +Forecast and replenishment processes are linked to measurable forecast errors
- –Planning governance depends on disciplined master data quality in connected systems
- –Limited constrained optimization depth compared with advanced APS suites
- –Extensibility depends on integration and data exchange patterns rather than native modeling
- –Advanced forecasting customization requires careful configuration effort
Best for: Fits when mid-market teams need ERP-connected demand–supply matching with scenario checks at SKU and location level.
Conclusion
After evaluating 10 supply chain demand planning software, Anaplan 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 Supply Chain Demand Planning Software
Supply chain demand planning software coordinates forecast-to-plan workflows that translate changing demand signals into time-phased actions across SKUs, locations, and channels. This buyer’s guide covers Anaplan, Blue Yonder, E2open, John Galt Solutions, Manhattan Associates, Netstock, o9 Solutions, RELEX Solutions, Slimstock, and ToolsGroup.
Planners use these systems to run scenario comparisons, reconcile forecast changes with supply constraints, and keep execution alignment through integration and automation surfaces. The selection choices in this guide focus on integration depth, governed calculation and data handling, and how each platform exposes an API and operational workflow controls for recurring planning refreshes.
Supply Chain Demand Planning Software for forecast-to-plan scenarios, constrained matching, and execution linkage
Supply chain demand planning software turns demand sensing and forecasting outputs into governed planning runs, then pushes time-phased plan results into downstream decisions like inventory position targets and order promising logic. The category commonly includes scenario planning so planners can adjust assumptions and compare impacts across demand, supply, and constraints.
RELEX Solutions centers constrained matching that drives inventory and service outcomes directly from scenario demand changes. E2open connects planning data synchronization with order promising logic so demand and execution stay consistent across enterprise systems and partner flows.
What to verify in Supply Chain Demand Planning Software
Supply chain demand planning software has to move demand changes into governed planning outputs across time-phased views, then keep those outputs aligned to downstream execution logic. The most reliable implementations expose scenario-driven workflows, repeatable calculation logic, and integration surfaces that support recurring refresh cycles.
The feature set also has to support traceability for what changed and why, because planners typically iterate on assumptions and reconcile demand to supply constraints inside shared planning runs. These criteria connect directly to how Anaplan, Blue Yonder, E2open, John Galt Solutions, Manhattan Associates, Netstock, o9 Solutions, RELEX Solutions, Slimstock, and ToolsGroup structure scenario work and data movement.
Scenario modeling that stays consistent from demand inputs to plan outputs
Anaplan supports multi-dimensional modeling with reusable calculation logic so scenario rollups update plan outputs consistently. ToolsGroup also emphasizes scenario compare and execution tracking to keep demand–supply matching decisions aligned across planning iterations.
Time-phased constrained demand–supply matching for SKU and location
RELEX Solutions runs time-phased constrained matching that drives inventory and service outcomes from scenario demand changes. Manhattan Associates focuses on constrained demand–supply matching built for SKU-location decision cycles inside Manhattan planning workflows.
Workflow routing from forecast review into downstream planning execution
Blue Yonder routes forecast changes into cross-process planning iterations through an end-to-end demand planning workflow. ToolsGroup links forecasts into governed scenario-heavy demand planning tied to constrained supply decisions and system integrations.
Integration depth and API-based synchronization across planning and execution systems
E2open provides API-first planning data synchronization across enterprise systems and partner flows to support execution-level consistency. o9 Solutions offers extensible API-based data synchronization so recurring planning refreshes can retain scenario traceability across demand and supply decisions.
Governed planning runs with traceable scenario traceability and constraint handling
o9 Solutions emphasizes a governed scenario workspace that simulates demand–supply matching with constraint-aware outcomes and retains iteration traceability. John Galt Solutions uses trade-input driven demand shaping with governed planning runs that keep planner adjustments structured.
Forecast governance controls and accuracy monitoring tied to planning adjustments
Slimstock ties bias and forecast accuracy monitoring to planning adjustments so forecast governance becomes an input to demand planning iterations. Blue Yonder emphasizes exception-focused process routing so planners prioritize forecast changes that drive downstream planning execution steps.
How to choose based on integration surfaces and planning philosophy
Demand planning tools differ most when the planning philosophy changes from model-first scenario simulation to workflow-first guided execution. Selection should start by mapping how forecast changes become decisions, then check whether the tool keeps those decisions consistent through the required data synchronization and governance controls.
A second fork concerns how constrained matching is executed and how much configuration the planning team can own. Some platforms center calculation model repeatability for scenario rollups while others center workflow orchestration for exception handling and downstream execution linkage.
Choose the planning execution shape: model-first scenario rollups or workflow-first routing
If forecast-to-plan execution needs repeatable calculation logic across scenarios, Anaplan’s multi-dimensional modeling and reusable calculation logic supports consistent scenario rollups. If forecast review needs controlled routing into downstream planning execution steps, Blue Yonder’s end-to-end workflow connects forecast changes to cross-process planning iterations.
Pick the constraint strategy: constrained matching inside the planning loop or execution linkage via order promising logic
If constrained matching must drive time-phased inventory and service outcomes directly from scenario demand changes, RELEX Solutions runs time-phased constrained matching in the scenario loop. If execution-level consistency is critical and order promising logic must stay aligned to planning decisions, E2open ties planning decisions into ATP logic and execution-level outcomes.
Validate integration ownership and API automation surface for recurring refreshes
If enterprise integration requires API-first data synchronization across ERP and execution systems, E2open’s API-first planning data synchronization can reduce manual reconciliation. If recurring planning refreshes must retain scenario traceability across multiple demand and supply decisions, o9 Solutions’ extensible API-based synchronization is built for repeatable refresh cycles.
Confirm how the tool handles trade shaping, master data dependencies, and scenario comparison
If demand shaping depends on governed trade inputs and repeatable planner adjustments, John Galt Solutions structures trade-input driven forecasting inputs and time-phased planning views. If scenario comparisons depend on consistent upstream demand signal configuration, Netstock and Blue Yonder both rely on connected ERP history and master data discipline to produce usable forecast accuracy outcomes.
Assess governance depth for scenario iteration and master data hierarchy rules
If governance requires scenario iteration traceability within a single constraint-aware scenario workspace, o9 Solutions keeps demand, supply, and constraints in one cycle. If the planning workload depends on SKU and location hierarchy governance, Manhattan Associates requires disciplined master data governance for SKU and location hierarchies.
Match expected depth of constrained optimization to implementation capacity
If deeper constrained optimization depth for supply planning is a requirement, RELEX Solutions and ToolsGroup provide time-phased constrained decision support that supports scenario iteration. If the organization prioritizes forecast accuracy controls and bias monitoring while constrained optimization depth can be narrower, Slimstock emphasizes multi-level demand planning with accuracy controls tied to planning adjustments.
Who benefits from these supply chain demand planning platforms
Supply chain demand planning software fits teams that translate forecast changes into time-phased decisions and need those decisions to propagate into constrained matching and execution logic. The best fit depends on whether planning teams own a reusable scenario model or run workflow-guided exception handling for planner throughput.
Organizations also need to match tool governance expectations to internal integration ownership because API-based synchronization and scenario configuration both create ongoing data responsibilities.
Enterprise planning and supply chain teams connecting demand planning to execution systems
E2open supports order promising integration using ATP logic so demand and execution stay consistent across enterprise systems and partner flows. Manhattan Associates ties planning outputs into operational execution planning workflows and supports ERP-connected forecasting with constrained scenario runs.
Scenario-heavy planning groups running repeatable what-if cycles
Anaplan fits teams that need scenario-driven demand planning with tight governance and consistent scenario rollups across multi-dimensional structures. o9 Solutions fits teams that need governed scenario planning with repeatable integrations and constraint-aware outcomes that retain iteration traceability.
Organizations that depend on ERP-connected demand and inventory signals for continuous demand–supply matching
Netstock updates time-phased plans from ERP-connected demand and inventory signals to support continuous demand–supply matching at SKU and location level. RELEX Solutions also drives inventory and service outcomes from scenario demand changes with time-phased constrained matching.
Teams that shape demand using trade inputs and need structured planner adjustments
John Galt Solutions focuses on trade-input driven demand shaping with governed planning runs that support time-phased planning views for transparent demand to supply matching work. ToolsGroup also supports scenario-heavy planning with execution tracking that aligns forecast changes to constrained supply decisions.
Mid-market teams emphasizing forecast accuracy monitoring and forecast governance discipline
Slimstock ties bias and forecast accuracy monitoring to planning adjustments for repeatable forecast governance cycles. Blue Yonder provides exception-focused process routing that helps planners prioritize forecast changes when forecast accuracy outcomes depend on master data discipline.
Common failures when implementing Supply Chain Demand Planning Software
Demand planning implementations often fail when teams underestimate the governance required for scenario comparisons and when they treat integration mapping as a one-time project instead of a recurring responsibility. The most common issues show up as inconsistent scenario outputs, weak auditability for iteration decisions, and slow planner adoption when workflow configuration mismatches real planning practices.
Another frequent failure is choosing a tool that supports constrained matching or API synchronization in concept while the organization does not have the master data discipline needed for SKU, location, and time hierarchy stability.
Configuring scenario comparisons without aligning upstream demand signal history and configuration
Netstock scenario planning outcomes depend on consistent upstream demand signal configuration and disciplined master data quality in connected systems. RELEX Solutions scenario runs also require disciplined master data management because custom calculation changes and structured workflows can surface configuration inconsistencies.
Treating API-based data synchronization as a fixed integration rather than an ongoing governance surface
E2open requires careful integration mapping across ERP, OMS, and planning systems to maintain ATP-linked consistency. o9 Solutions can require extensible setup time for complex SKU and location structures, so integration work must include governance for recurring planning refreshes.
Using workflow-led exception routing without enough master data and history consistency
Blue Yonder forecast accuracy outcomes depend on strong master data and consistent history, which directly affects downstream planning iterations. Manhattan Associates also depends on disciplined master data governance for SKU and location hierarchies to make constrained scenario work effective.
Expecting constrained optimization depth without planning model ownership and configuration capacity
ToolsGroup depends on significant configuration to model SKU-location and hierarchy rules, so teams that lack governance ownership can slow adoption. Slimstock provides constrained optimization depth that can lag specialist APS suites, so requirements for deep constrained supply optimization should be checked against actual execution needs.
How analysts built the shortlist of Supply Chain Demand Planning Software
Analysts gathered information from the original publication pages that discussed each supply chain demand planning software product in this guide and copied every stated figure into internal notes. Analysts then compared those figures with the official documentation and the vendor changelog, and they used an independent review only when it was explicitly cited for the figure being referenced.
Analysts kept only the figures that matched the documentation they reviewed and removed figures that did not reconcile with the vendor sources. The shortlist is the set of products that were covered in the publication pages and still matched the corresponding vendor materials after that reconciliation.
Frequently Asked Questions About Supply Chain Demand Planning Software
How do supply chain demand planning tools handle ERP-to-APS data synchronization for forecast updates?
Which tools provide API-based data synchronization for partner or cross-system planning workflows?
How do RBAC and audit logs work in practice for planners and administrators?
What does data migration typically require when moving from legacy forecasting to scenario-driven demand planning?
How do administrators control scenario versions and change traceability during S&OP or IBP cycles?
When does the demand planning workflow break if master data like SKU or location hierarchy is inconsistent?
Which tools best support demand–supply matching using constrained optimization logic?
How do tools measure forecast accuracy and bias for ongoing demand forecasting governance?
What extensibility options exist when planners need custom calculations beyond the default demand planning logic?
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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