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Supply Chain In IndustryTop 10 Best Distribution Planning Software of 2026
Top 10 ranking of distribution planning software for supply chain teams, with comparisons across Anaplan Supply Chain Planning, Maestro, and Infor.
How we ranked these tools
Gitnux editors write the brief first: the topic, the inclusion rules, and the frame for what belongs.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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If you’re aiming for repeatable scenario-based distribution planning across many sites, Anaplan Supply Chain Planning is the most reliable pick, whereas ToolsGroup SO99+ is a better fit when you want governed multi-echelon what-if planning with repeatable allocation rules.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Anaplan Supply Chain Planning
Scenario modeling runs against a shared calculation model to compare allocations and inventory positions across versions.
Best for: Fits when planners need repeatable, scenario-based distribution planning with controlled assumptions across many sites.
Kinaxis Maestro
Editor pickConstraint-aware scenario modeling that produces allocation and replenishment decisions tied to publish-ready outputs.
Best for: Fits when planners need repeatable, governed what-if planning across many nodes and constraints.
Infor Supply Planning
Editor pickConstraint-aware allocation and replenishment outputs tied to network planning scenarios.
Best for: Fits when distribution planners need constraint-aware scenario modeling across warehouses.
Comparison Table
Anaplan Supply Chain Planning
enterpriseModels demand, supply, inventory, and network scenarios through connected planning models.
Scenario modeling runs against a shared calculation model to compare allocations and inventory positions across versions.
Anaplan Supply Chain Planning is built around model-driven planning where distribution data, sourcing rules, and allocation logic live inside connected model layers. Scenario work is organized through calculation and workflow steps, which helps teams compare plan versions without rebuilding spreadsheets. Automation is typically implemented through scheduled calculations and model mappings, and integration is handled through Anaplan APIs and connector patterns used for upstream demand and downstream execution feeds.
A key tradeoff is that the quality of outputs depends on the governance of the shared assumptions and the completeness of network inputs. Teams get the most benefit when they need repeatable multi-site planning runs with controlled versioning, like monthly replenishment planning or exception-driven re-planning after demand shifts.
- +Model-driven scenarios keep assumptions consistent across plan versions
- +Allocation and replenishment logic can be encoded as reusable model rules
- +Extensible calculation workflows support repeated planning cycles
- +API-driven integration helps connect demand, inventory, and execution systems
- –Network modeling effort can be high for complex multi-echelon structures
- –Advanced planning governance requires disciplined model administration
Distribution planning teams
Monthly replenishment with allocation constraints
Fewer manual rework cycles
Operations planning analysts
Exception-driven re-planning after shocks
Faster plan stabilization
Show 1 more scenario
Supply chain systems integrators
API integrations with upstream and downstream
Cleaner data handoffs
Connects forecast, inventory, and execution inputs through structured API data exchange.
Best for: Fits when planners need repeatable, scenario-based distribution planning with controlled assumptions across many sites.
Kinaxis Maestro
enterpriseCoordinates concurrent supply, inventory, demand, and distribution planning.
Constraint-aware scenario modeling that produces allocation and replenishment decisions tied to publish-ready outputs.
Kinaxis Maestro fits organizations running multi-site and multi-stage networks where planners must coordinate supply, inventory positioning, and allocation rules under lead-time variability. The planning workflow is designed to run frequent scenario iterations, then publish decisions to downstream execution partners, which matters when demand signals change faster than manual planning cycles. The data handling emphasis is on keeping planning logic consistent across scenarios, so teams can compare outcomes on service and inventory impact rather than rework assumptions each run.
A key tradeoff is that Maestro’s planning logic and network configuration require deliberate setup to reflect the business structure, including sourcing options, transportation constraints, and exception handling rules. Maestro works best when planning teams need repeatable automation with clear governance around which assumptions were used for each published plan. Organizations with one-off planning needs or highly bespoke modeling that changes daily may find the configuration overhead heavier than simple forecasting tools.
- +Scenario runs support constraint-aware allocation and replenishment decisions
- +Workflows connect planning assumptions to published decisions for execution handoff
- +Integration patterns cover ERP, WMS, and TMS connectivity requirements
- +Governed scenario management supports repeatable planning iterations
- –Network and rules setup takes sustained governance effort
- –Exception workflows can feel heavy for small planning teams
- –Users may need training to interpret scenario drivers and tradeoffs
- –Deep configuration can slow down frequent assumption changes
Distribution planning teams
Coordinating constrained replenishment across sites
Fewer stockouts and transfers
Supply chain operations planners
Managing allocation rule changes under pressure
Faster decision cycles
Show 2 more scenarios
Enterprise planners in S&OP
Aligning demand, supply, and capacity assumptions
More accurate commitments
Iterate plans using consistent assumptions across scenarios to evaluate service and inventory impact.
Systems and integration teams
Connecting planning with WMS and TMS
Lower manual reconciliation
Integrate planning outputs and inputs so operational systems reflect updated availability and movement assumptions.
Best for: Fits when planners need repeatable, governed what-if planning across many nodes and constraints.
Infor Supply Planning
enterpriseProvides demand-driven supply planning, replenishment, and inventory management for enterprises.
Constraint-aware allocation and replenishment outputs tied to network planning scenarios.
Infor Supply Planning targets distribution organizations that run frequent planning cycles across warehouses and inventory positions, then translate outputs into actionable replenishment and allocation decisions. Scenario modeling supports what-if runs for changing demand, supply, and constraints so planners can compare alternative plans before committing. Planning results connect into execution workflows that align inventory movement decisions to service expectations. The scope fits teams that already standardize planning data and want those processes reflected across the network.
A tradeoff is that deeper constraint coverage depends on clean upstream master data and consistent rule configuration, because allocation and replenishment logic uses those inputs directly. In practice, the strongest usage situation is a multi-warehouse environment where lead-time variability and distribution constraints affect available inventory and service-level outcomes. Another common fit is a planning organization coordinating sales plans with network capacity limits to drive deployment-like decisions across sites.
- +Scenario modeling supports constraint-aware distribution plan comparisons
- +Allocation and replenishment workflows translate network plans into actions
- +Planning cycle outputs integrate with Infor supply and execution processes
- +Rules-based planning supports repeatable decisions across facilities
- –Constraint outcomes depend heavily on disciplined master data governance
- –Advanced configuration can slow time-to-first reliable plan
- –Execution alignment may require tighter setup with downstream systems
- –Planner usability can be harder for teams needing lighter planning scopes
Supply chain planning teams
Run network what-if distribution scenarios
Fewer plan surprises
Distribution operations leaders
Operationalize allocation and replenishment
More consistent availability
Show 1 more scenario
S&OP coordinators
Coordinate network plans with business forecasts
Better forecast-to-plan fit
Scenario outputs support aligning sales plans with feasible distribution decisions across facilities.
Best for: Fits when distribution planners need constraint-aware scenario modeling across warehouses.
Blue Yonder Supply Chain Planning
enterprisePlans demand, inventory, replenishment, and distribution across complex supply networks.
Scenario modeling for distribution decision cycles that enables controlled what-if analysis over replenishment assumptions.
Blue Yonder Supply Chain Planning targets distribution networks with constraint-aware planning for replenishment and allocation decisions across nodes and lanes. It is built around scenario modeling and what-if runs that planners can repeat with controlled changes to demand, supply, and lead-time assumptions.
- +Scenario modeling supports controlled what-if runs for distribution planning assumptions
- +Strong distribution focus for allocation and replenishment decision cycles across network nodes
- +Integration workflows align planned inventory positions with execution systems
- +Planning configuration supports repeating governance over planning logic
- –Advanced configuration depth can slow initial onboarding for distribution planners
- –Multi-echelon network scope can increase run times for large SKU and node sets
- –Workflow usability depends on tight setup of master data, rules, and constraints
- –API coverage is dependent on integration design with adjacent execution systems
Best for: Fits when distribution teams need repeatable, constraint-aware replenishment and allocation planning across many nodes.
SAP Integrated Business Planning
enterpriseConnects demand, supply, inventory, and response planning in a cloud planning suite.
Tightly governed planning across SAP structures with audit-traceable scenario changes and workflow-controlled distribution allocation.
SAP Integrated Business Planning is built around SAP planning objects, so distribution plans can stay aligned with SAP master data and logistics hierarchies.
- +Strong integration with SAP master data and planning objects for consistent item-location planning
- +Scenario modeling supports controlled what-if analysis for network and allocation changes
- +Workflow-driven automation helps reduce manual reconciliation across planning steps
- +RBAC and audit log coverage track planning actions by user and change context
- –Distribution planning depth depends on configuration and on linked SAP components
- –High governance and master-data discipline is required to keep scenarios comparable
- –Real-time updates are limited compared with systems built for fast event-driven replanning
- –APIs and extensibility typically require SAP integration patterns and developer effort
Best for: Fits when teams run end-to-end planning inside SAP and need governed scenario-based distribution allocation.
Oracle Fusion Cloud Supply Chain Planning
enterpriseProvides demand, supply, replenishment, and inventory planning across connected operations.
Orchestrated planning runs that connect network decisions to allocation and replenishment outputs inside the Oracle Fusion process context.
Oracle Fusion Cloud Supply Chain Planning is a cloud planning suite built for end-to-end supply chain use cases that center on network-wide decisions. It supports demand-to-supply planning workflows that feed allocation, replenishment, and distribution execution with scenario management for what-if comparisons.
- +Tight alignment between planning outputs and downstream order and inventory processes
- +Scenario planning supports controlled what-if runs for network and constraint changes
- +Use of automation hooks and API integrations for data movement into planning and execution
- +Governed configuration helps standardize planning logic across business units
- –Effective DRP-style distribution planning needs substantial master data readiness
- –Advanced scenario maintenance can feel heavy without dedicated planning operations ownership
- –API and integration setup depth raises time-to-first-accurate-plans for new networks
- –Some distribution-specific workflows require careful mapping to underlying processes
Best for: Fits when global distribution networks need governed planning logic with scenario control and strong system integration.
o9 Digital Brain
enterpriseCombines demand, supply, inventory, and network planning on a connected planning platform.
Rules-first distribution planning workflow that ties allocation and constraint logic into repeatable scenario executions.
o9 Digital Brain brings distribution planning into a rules-driven optimization workflow that connects network, inventory, and allocation decisions. The solution focuses on scenario modeling so planners can compare service-level outcomes under different constraints and lead-time variability.
- +Scenario modeling supports constraint-heavy what-if runs for allocation and replenishment
- +Rules-based optimization links network constraints to inventory placement decisions
- +API-oriented integration supports automated refresh from planning and order data
- +Governed configuration and permissions help control who can publish planning outputs
- –Strong setup governance is needed to keep allocation rules consistent across runs
- –User experience is less direct for planners who only need simple spreadsheet DRP
Best for: Fits when planners need scenario automation across a constrained distribution network with governed rule changes.
ToolsGroup SO99+
specialistAutomates demand forecasting, inventory optimization, replenishment, and supply planning.
Constraint-rich scenario planning that recalculates distribution outcomes while preserving allocation rules across complex network structures.
ToolsGroup SO99+ is a distribution planning suite that focuses on scenario-driven network and operational planning rather than spreadsheets. It supports multi-echelon inventory optimization workflows with supply allocation logic, replenishment decisions, and performance targets tied to service objectives.
- +Scenario modeling supports repeated planning iterations with consistent constraints
- +Allocation and replenishment logic covers network flows across multiple echelons
- +Strong integration patterns for connecting planning inputs to upstream systems
- +Planning configuration reduces manual spreadsheet reconciliation during what-if cycles
- –Setup for network, lead times, and constraint coverage requires disciplined configuration
- –Complex planning models can increase cycle-time during large scenario batches
- –Advanced optimization needs careful governance of rules and exception handling
- –Data mapping effort can be significant when integrating heterogeneous source systems
Best for: Fits when distribution planners need governed what-if planning across a multi-echelon network with repeatable allocation rules.
Flowlity
specialistUses probabilistic inventory planning to improve replenishment and supply decisions.
Workflow-driven allocation planning that ties sourcing rules directly to scenario outputs across network nodes.
Flowlity is a distribution planning software that builds allocation and replenishment workflows around a configurable supply network. It focuses on scenario modeling for demand-supply balancing, including lead-time variability and constraint-aware stock movements.
- +Rule-based allocation workflows with repeatable what-if scenario runs
- +Constraint-aware stock movement planning for multi-node networks
- +Scenario comparisons that keep decisions tied to network inputs
- +Workflow automation supports plan execution after input refreshes
- –Requires careful configuration of sourcing and allocation rules
- –Limited evidence of deep WMS and TMS native integration coverage
- –Scenario throughput can lag when running many network variants
- –Governance controls like RBAC and audit trails are not clearly documented
Best for: Fits when distribution planners need scenario-driven allocation and replenishment logic across a constrained network.
RELEX Solutions
vertical specialistPlans retail demand, inventory, replenishment, allocation, and supply chain execution.
Forecast-driven supply allocation workflow built to produce replenishment plans across store and network nodes from shared planning inputs.
RELEX Solutions is a distribution planning software choice for retailers and CPG organizations that need tight linkages between supply planning, inventory positioning, and store or node replenishment decisions. Its core strength is forecast-to-allocation workflow support that drives replenishment plans across a multi-node network and adjusts to demand and supply variability.
- +Strong end-to-end planning workflow from forecasting signals to allocation decisions
- +Scenario comparison supports faster what-if iteration for network and service tradeoffs
- +Planning outputs align well to store and node replenishment rhythms
- +Integration focus reduces friction between planning data and operational execution
- –Modeling effort is substantial for complex networks with frequent rule changes
- –Iterative planning depends on clean input master data and consistent identifiers
- –Advanced governance and automation typically require IT and integration support
- –Deep customization can take longer than planners expect for smaller teams
Best for: Fits when planners need forecast-driven supply allocation and multi-node replenishment plans with reliable scenario iteration.
Conclusion
After evaluating 10 distribution planning software, Anaplan Supply Chain Planning 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 Distribution Planning Software
Distribution planning software is used to run repeatable network scenarios that translate assumptions into allocation and replenishment decisions across multiple nodes. This guide covers Anaplan Supply Chain Planning, Kinaxis Maestro, and SAP Integrated Business Planning alongside infor Supply Planning, Oracle Fusion Cloud Supply Chain Planning, and Blue Yonder Supply Chain Planning.
It also evaluates o9 Digital Brain, ToolsGroup SO99+, Flowlity, and RELEX Solutions for rules-based or workflow-driven planning execution. The comparison prioritizes scenario modeling behavior, constraint handling, and how planning outputs connect to downstream actions.
Distribution Planning Software for scenario-based allocation and replenishment across network nodes
Distribution planning software supports controlled what-if analysis where planners run scenario iterations to compare allocation outcomes and inventory positioning across warehouses and echelons. Anaplan Supply Chain Planning is built around scenario modeling runs against a shared calculation model so allocation and inventory positions remain comparable across plan versions.
Kinaxis Maestro emphasizes constraint-aware scenario modeling that ties allocation and replenishment decisions to publish-ready outputs for execution handoff. Tools in this category typically translate network rules into decisions such as sourcing and replenishment quantities, then preserve those decision drivers so scenario results can be governed during planning cycles.
Distribution Planning Software capabilities that control scenario accuracy and allocation consistency
Scenario modeling behavior determines whether allocation and inventory positions stay comparable across planning iterations. The tools listed here separate scenario assumptions from decision outcomes so teams can trace why replenishment changes while still enforcing consistent rules.
Constraint handling then governs whether the decisions remain feasible under real network limitations. These platforms differ in how they keep constraints tied to allocation logic and how they translate scenario results into publish-ready outputs for handoff.
Shared calculation model for scenario comparability
Anaplan Supply Chain Planning runs scenario modeling against a shared calculation model so allocation and inventory positions remain comparable across plan versions. This design targets repeatable distribution scenarios where planners must keep assumptions aligned across many sites.
Constraint-aware publish-ready decision outputs
Kinaxis Maestro produces allocation and replenishment decisions that stay tied to constraint-aware scenario runs. This focus connects what-if planning to publish-ready outputs for execution handoff.
Network planning scenarios that translate into distribution actions
Infor Supply Planning ties constraint-aware scenario modeling to allocation and replenishment workflows that translate network plans into actions. Advanced configuration still depends on disciplined master data governance to keep constraint outcomes stable.
Distribution decision cycle what-if analysis with controlled replenishment assumptions
Blue Yonder Supply Chain Planning supports controlled what-if runs for replenishment assumptions across many nodes. The platform emphasizes repeatable distribution planning decision cycles where scenario depth can affect runtime on large SKU and node sets.
Workflow-controlled allocation inside SAP planning structures
SAP Integrated Business Planning supports tightly governed planning inside SAP structures so scenario changes remain audit-traceable. Allocation decisions follow SAP planning objects that require configuration depth and linked SAP components for distribution planning coverage.
Orchestrated planning runs aligned to downstream order and inventory processes
Oracle Fusion Cloud Supply Chain Planning connects network decisions to allocation and replenishment outputs inside the Oracle Fusion process context. This tight alignment supports governed planning but depends on master data readiness and ongoing scenario maintenance ownership.
Choose Distribution Planning Software by scenario governance and how decisions get executed
Distribution planning success depends on whether scenario executions preserve decision drivers across iterations. The tools in this list diverge on whether they center a model-driven scenario engine or a workflow-first rule execution approach.
The second deciding axis is how much governance effort the organization can sustain during setup and ongoing operations. Some platforms can keep assumptions consistent through a shared model, while others trade speed of onboarding for deeper constraint or rule coverage.
Select the scenario engine style that matches the team’s governance workflow
Choose Anaplan Supply Chain Planning when scenario comparability must stay consistent through a shared calculation model across plan versions. Choose Kinaxis Maestro when constraint-aware scenario runs must produce publish-ready outputs through workflows that support execution handoff.
Verify constraint-to-decision traceability for allocation and replenishment
Choose Infor Supply Planning when constraint-aware scenario comparisons must drive allocation and replenishment workflows that translate network plans into actions across warehouses. Choose Blue Yonder Supply Chain Planning when controlled what-if analysis over replenishment assumptions must stay repeatable across many distribution nodes.
Match the platform to the system-of-record planning objects in the enterprise
Choose SAP Integrated Business Planning when planning must remain inside SAP structures with audit-traceable scenario changes and workflow-controlled distribution allocation. Choose Oracle Fusion Cloud Supply Chain Planning when global distribution networks require governed planning logic aligned to downstream order and inventory processes inside Oracle Fusion.
Decide whether rule-first automation outweighs direct planner usability
Choose o9 Digital Brain when scenario automation needs rule-first distribution planning where allocation and constraint logic become repeatable scenario executions. Choose ToolsGroup SO99+ when governed what-if planning across a multi-echelon network must preserve allocation rules during recalculation batches.
Assess runtime and configuration load for large networks and frequent changes
Choose Blue Yonder Supply Chain Planning carefully when multi-echelon network scope increases run times for large SKU and node sets. Choose Oracle Fusion Cloud Supply Chain Planning when advanced scenario maintenance can feel heavy without dedicated planning operations ownership.
Confirm the network depth needed versus the depth of workflow integration coverage
Choose o9 Digital Brain when a rules-based workflow that ties constraints to inventory placement decisions is required across constrained networks. Choose Flowlity only when workflow-driven allocation and replenishment logic is the priority and the organization can handle sourcing and allocation rule configuration with limited evidence of deep WMS and TMS native integration coverage.
Who Distribution Planning Software is built for
Organizations need distribution planning software when allocation and replenishment decisions must be repeatable under changing assumptions. This category fits teams that run scenario iterations and then use scenario outputs as controlled inputs to downstream planning or execution.
The tools here differ in how much governance discipline they require from planners and admins. Some platforms emphasize shared model consistency, while others emphasize constraint-aware workflows tied to publication and handoff.
Supply planning teams running repeatable multi-site scenario iterations
Anaplan Supply Chain Planning fits teams that need repeatable, scenario-based distribution planning with controlled assumptions across many sites using a shared calculation model.
Network planners managing constraint-heavy allocations with publish-ready outputs
Kinaxis Maestro fits teams that need constraint-aware scenario modeling tied to publish-ready allocation and replenishment decisions for execution handoff.
Enterprises standardizing planning execution inside SAP or Oracle Fusion objects
SAP Integrated Business Planning fits teams that run end-to-end planning inside SAP and need audit-traceable scenario changes tied to SAP planning objects. Oracle Fusion Cloud Supply Chain Planning fits teams that need governed planning logic inside Oracle Fusion with orchestration aligned to downstream order and inventory processes.
Planners who want rules-first automation for constrained networks
o9 Digital Brain fits planners that need scenario automation where allocation and constraint logic become repeatable rule executions. ToolsGroup SO99+ fits multi-echelon planning groups that must recalculate distribution outcomes while preserving allocation rules.
Common mistakes when buying Distribution Planning Software
A frequent failure pattern is assuming scenario outputs will remain comparable without validating the scenario engine and calculation model behavior. Tools that compare allocation outcomes across versions depend on consistent assumptions and disciplined setup across network nodes and master data.
Another mistake is underestimating governance effort during network modeling and rules setup. Several platforms require ongoing admin discipline to keep scenario maintenance stable and constraint outcomes trustworthy during repeated planning cycles.
Buying for scenario iterations but not validating how comparability is preserved across plan versions
Teams should confirm whether scenario modeling uses a shared calculation model or requires other mechanisms to keep assumptions consistent across versions, since Anaplan Supply Chain Planning explicitly targets scenario comparability through a shared calculation model.
Treating constraint outcomes as automatic without confirming master data governance requirements
Infor Supply Planning highlights that constraint outcomes depend heavily on disciplined master data governance, so incomplete item-location data will reduce trust in allocation and replenishment results.
Ignoring the governance workload implied by network and rules setup
Kinaxis Maestro and ToolsGroup SO99+ both require sustained governance effort for network and rules setup, so procurement teams should validate admin capacity for ongoing scenario and constraint maintenance.
Under-scoping initial configuration time for advanced scenario maintenance ownership
Oracle Fusion Cloud Supply Chain Planning can feel heavy for scenario maintenance without dedicated planning operations ownership, so buyers should budget internal ownership for ongoing scenario updates.
How We Selected and Ranked These Tools
We evaluated Anaplan Supply Chain Planning, Kinaxis Maestro, SAP Integrated Business Planning, and the other listed tools by scoring features at 40%, ease at 30%, and value at 30%. Features scoring prioritized scenario modeling behavior that keeps allocation and inventory positions consistent across scenario versions, plus constraint handling that supports publish-ready or workflow-controlled distribution decisions.
Ease scoring weighted how quickly teams can reach reliable plan outputs after network and rules setup. Value scoring reflected how effectively each tool turns scenario outputs into allocation and replenishment decisions that teams can iterate on without breaking comparability, with Anaplan Supply Chain Planning earning separation by running scenario modeling against a shared calculation model to keep allocation and inventory positions comparable across plan versions.
Frequently Asked Questions About Distribution Planning Software
How do Kinaxis Maestro and SAP Integrated Business Planning handle scenario modeling for distribution allocation with different constraints?
What workflow difference affects supply planners when moving from Anaplan Supply Chain Planning to Oracle Fusion Cloud Supply Chain Planning?
Which tool is better suited for multi-echelon inventory optimization across many nodes, ToolsGroup SO99+ or Blue Yonder Supply Chain Planning?
How do o9 Digital Brain and RELEX Solutions structure scenario iteration when forecast-to-allocation tradeoffs must stay consistent?
What breaks if admin teams cannot align data schema and master data when integrating planning with WMS and TMS systems in Oracle Fusion Cloud Supply Chain Planning?
How do RBAC and audit logs differ between SAP Integrated Business Planning and Kinaxis Maestro for controlled change management?
How should data migration be approached when moving distribution planning inputs from existing planning tools into Infor Supply Planning?
What integration pattern changes the most when deploying Flowlity instead of Anaplan Supply Chain Planning for distribution planning execution?
Which tool provides the most direct path from scenario outputs to API-oriented downstream exchange, o9 Digital Brain or RELEX Solutions?
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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