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Environment EnergyTop 10 Best Energy Asset Management Software of 2026
Ranked roundup of the top 10 energy asset management software options with evaluation criteria, including Infor EAM, AVEVA APM, and IBM Maximo.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Search agents gather the source set and the review record, including transcriptions of video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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Infor EAM is the best fit when an asset team needs governed work execution tied to a configurable asset hierarchy, whereas Cognite Data Fusion is the stronger choice if your priority is a governed, API-first data foundation that contextualizes asset models across historians, GIS, and maintenance systems.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Infor EAM
Maintenance planning can be configured around asset hierarchy, so scheduling rules follow criticality-based structure.
Best for: Fits when asset teams need governed work execution tied to a configurable asset hierarchy.
AVEVA Asset Performance Management
Editor pickReliability planning workflows that preserve traceability from asset criticality decisions to maintenance outcomes.
Best for: Fits when utilities need governed asset performance workflows tied to reliability and work execution.
IBM Maximo Application Suite
Editor pickConfigurable work execution with approvals tied to the asset hierarchy and audit logged changes.
Best for: Fits when utilities need unified asset lineage for maintenance execution, inventory, and audited governance.
Comparison Table
Infor EAM
enterpriseEnterprise asset management suite used by utilities and energy companies for maintenance and capital planning.
Maintenance planning can be configured around asset hierarchy, so scheduling rules follow criticality-based structure.
Infor EAM centers on asset hierarchy configuration and maintenance process execution, so planners can schedule preventive work, trigger corrective work from events, and route tasks into mobile field execution. The system supports spares and inventory transactions inside maintenance execution, which reduces handoffs between CMMS-like processes and materials workflows. Automation is strongest around maintenance planning, inspection rounds, and repeatable work templates rather than ad hoc analytics.
A tradeoff appears in multi-system environments that require heavy customization of data structures and workflow states, because deeper extensions increase configuration and testing effort. A common usage situation is a utility or industrial asset team rolling out standardized work instructions and maintenance policies across plant or site boundaries while syncing asset status back to operational systems.
- +Asset hierarchy configuration ties planning rules to execution states
- +Work order workflows support inspection rounds and digital job instructions
- +Inventory and spare parts handling fits inside maintenance execution
- +API and integration interfaces support bidirectional enterprise system sync
- –Complex workflow customization raises release testing overhead
- –Advanced automation often depends on disciplined configuration ownership
- –Mobile field setup requires careful permissions and workflow mapping
- –Cross-site standardization can be slow without governance templates
Utility maintenance planners
Standardized preventive maintenance scheduling
Lower scheduling variation
Reliability engineering teams
Reliability-driven corrective maintenance
Faster corrective response
Show 2 more scenarios
Field service supervisors
Mobile work instruction execution
Cleaner field reporting
Routes work orders to mobile crews with controlled status updates and task completion records.
Enterprise integration teams
EAM integration with enterprise systems
Reduced manual reconciliation
Uses API-driven interfaces to sync asset changes and maintenance outcomes with other operational systems.
Best for: Fits when asset teams need governed work execution tied to a configurable asset hierarchy.
AVEVA Asset Performance Management
enterpriseIndustrial APM platform combining predictive analytics and reliability management for energy and process assets.
Reliability planning workflows that preserve traceability from asset criticality decisions to maintenance outcomes.
AVEVA Asset Performance Management fits energy asset organizations that already run CMMS or EAM processes and need deeper asset performance context for planning and execution. The product’s differentiator is how it ties structured asset context to maintenance and reliability workflows rather than treating analytics as an add-on. Admin governance features focus on controlling access and changes across configuration, workflows, and business objects used by planners and field teams.
A key tradeoff is that AVEVA APM’s value depends on disciplined master asset data and hierarchy modeling before automation rules are meaningful. It is a strong fit when the asset team needs end-to-end traceability from asset criticality decisions to work order outcomes, especially in environments with multiple engineering and operations systems.
- +Engineering-linked asset workflows support reliability planning and execution traceability
- +Strong integration orientation for asset context across operations, maintenance, and analytics
- –Deep configuration requires governance discipline for hierarchy and rule definitions
- –Time to operationalize automation can increase when master data is inconsistent
Asset management governance teams
Standardize criticality-driven maintenance planning
Fewer planning inconsistencies
Reliability engineers
Operationalize failure and risk analysis
Actionable reliability feedback
Show 1 more scenario
CMMS program owners
Connect work execution to performance analytics
Better maintenance effectiveness reporting
Program owners align maintenance records with asset performance signals for end-to-end reporting.
Best for: Fits when utilities need governed asset performance workflows tied to reliability and work execution.
IBM Maximo Application Suite
enterpriseEnterprise asset management platform widely deployed by utilities and energy operators for maintenance, reliability, and compliance.
Configurable work execution with approvals tied to the asset hierarchy and audit logged changes.
IBM Maximo Application Suite centers on an enterprise asset registry concept with configurable asset relationships that drive work orders, spares demand, and preventive maintenance scheduling logic. Work execution stays connected to planning data through work order templates, digital work instructions, and structured inspection rounds tied to asset records. Admin controls include RBAC permissions for users and groups, plus audit log trails for key configuration and operational changes. Integration projects often succeed when the organization already standardizes on enterprise service patterns and wants consistent entity identifiers across systems.
A tradeoff appears in governance depth and configuration effort for large hierarchies and multi-team processes, because the workflow and data mapping choices must be made carefully up front. IBM Maximo Application Suite fits outage and field execution programs where maintenance backlogs, inspection findings, and inventory availability must align to the same asset lineage and approval chain. A common usage pattern is automating corrective maintenance after inspection triggers while ensuring planners can see full execution history for compliance reporting.
- +Asset hierarchy drives work orders, inspections, and spares demand consistently
- +REST API and integration hooks support enterprise workflow orchestration
- +RBAC plus audit log supports traceable approvals and configuration changes
- +Mobile field service workflows connect execution notes to planning records
- –Workflow and hierarchy setup requires governance discipline at scale
- –Some advanced analytics and condition monitoring need external data pipelines
- –Cross-team process design often needs careful configuration to avoid duplicates
- –Integration projects can require significant mapping work across enterprise systems
Maintenance planners
Schedule preventive work by asset hierarchy
Reduced missed maintenance tasks
Field service teams
Execute inspections with digital work instructions
Faster closure of inspection findings
Show 2 more scenarios
Asset management governance
Control changes with RBAC and audit logs
Improved audit traceability
Role permissions and audit trails support compliance needs for work and configuration approvals.
System integration teams
Integrate work and inventory via REST APIs
Lower manual data synchronization
REST-based integration connects maintenance entities to enterprise orchestration and data systems.
Best for: Fits when utilities need unified asset lineage for maintenance execution, inventory, and audited governance.
Cognite Data Fusion
API-firstIndustrial data platform enabling contextualized asset models for energy operators.
Cognite Data Fusion asset modeling and ingestion let teams create governed, linked entities from engineering, maintenance, and telemetry data.
Cognite Data Fusion is used to centralize operational and engineering data for asset programs, with a strong emphasis on integration depth and governed access to a shared digital context. It provides an extensible data ingestion and processing layer for time-series data plus graph-style asset relationships, which supports cross-system linking beyond a single CMMS or EAM.
- +API-driven entity provisioning supports repeatable asset registry population
- +Extensible ingestion pipelines handle time-series plus event data at scale
- +Governed access patterns with audit-friendly operations support shared data use
- +Graph-like links between assets and documents improve traceability for investigations
- –Asset hierarchy and registry modeling requires careful upfront configuration
- –Work order management coverage depends on integrations rather than native workflows
- –Operational teams need engineering support to maintain ingestion and mappings
- –Mobile field service and inspection rounds require external application pairing
Best for: Fits when asset programs need a governed data foundation that integrates historians, GIS, and maintenance systems.
Power Factors Drive
vertical specialistAsset performance management platform purpose-built for renewable energy portfolios.
Asset criticality ranking feeds maintenance planning so asset risk context travels into work scheduling and execution.
Power Factors Drive records and maintains energy asset registry data and maps it into an operational asset hierarchy for downstream work execution. It supports asset criticality ranking and workflows that connect maintenance planning to engineering context, reducing manual cross-referencing between teams.
- +Asset hierarchy and criticality ranking tied to maintenance execution workflows
- +Centralized asset attribute management reduces duplicate spreadsheets across teams
- +Work planning supports preventive scheduling based on structured asset data
- +Integration approach focuses on data exchange for operational context reuse
- –Automation depth can require configuration work to reach enterprise workflow maturity
- –Some advanced reliability modeling often needs external tools for FMEA style workflows
- –Mobile field-service UX is narrower than suites focused on dispatch and work capture
- –API surface coverage for edge telemetry ingestion is limited compared with telemetry-first vendors
Best for: Fits when asset teams need a governed registry with maintainable hierarchies driving planned maintenance workflows.
Accruent Asset Management
enterpriseEAM and maintenance software used across energy facilities and distributed infrastructure.
Asset record lineage that links hierarchy structures to maintenance planning and inspection outcomes.
Accruent Asset Management is aimed at utilities and asset-heavy organizations that need end-to-end tracking from an asset hierarchy into regulated workflows. It supports work order management, preventive maintenance scheduling, and inspection-driven processes tied to asset records.
- +Strong asset-to-work-order traceability across maintenance and inspections
- +Governance controls for roles and activity visibility across operational teams
- +Configurable preventive scheduling tied to asset records and locations
- +Integration interfaces support bringing asset data into enterprise workflows
- –Workflow customization can require disciplined configuration to avoid drift
- –Advanced condition-monitoring and telemetry ingestion depend on external systems
- –Complex asset hierarchies take careful setup to keep reporting consistent
- –Mobile and field execution features can lag specialized work-management suites
Best for: Fits when utilities need asset hierarchy recordkeeping tied to scheduled maintenance and governed operations.
eSmart Systems Grid Vision
vertical specialistAI-powered inspection and asset management software for power grid infrastructure.
Grid Vision links asset hierarchy to maintenance execution so asset records update as field work completes.
eSmart Systems Grid Vision focuses on energy asset management with grid-first structure, tying asset hierarchy to operational context rather than treating assets as generic objects. It supports work management workflows used for preventive and corrective maintenance, with configuration for inspections and field execution.
- +Grid-focused asset hierarchy mapping that aligns maintenance to operational context
- +Work order workflows support preventive and corrective maintenance execution
- +Administration controls restrict who can change assets and approve maintenance actions
- +Integration patterns target utility data sources used in day-to-day operations
- –Thick configuration and governance are needed to keep asset records consistent
- –Automation depth is stronger for work routing than for analytics-grade decisioning
- –Role granularity can feel coarse when separating engineering from field edits
- –Extensibility depends on integration work instead of built-in add-on modules
Best for: Fits when utilities need grid-aligned asset registry plus work order execution tied to operational operations data.
Sphera Corporate EHS & Sustainability
vertical specialistRisk, reliability, and asset performance solutions for energy and heavy industry.
EHS case and audit management with audit-ready histories that keep compliance evidence tied to workflow outcomes.
Sphera Corporate EHS & Sustainability is used for managing corporate EHS and sustainability workflows rather than running full energy asset operations. It supports hazardous materials and compliance processes, and it connects those records to enterprise reporting needs.
- +EHS workflow coverage for incidents, audits, and compliance tracking
- +Documented process configuration for corporate reporting cycles
- +Strong audit trail support for regulated EHS activities
- +Extensible integrations for exchanging EHS records with enterprise systems
- –Limited native energy asset registry scope compared with EAM-focused tools
- –Work order management and preventive scheduling are not the primary strength
- –Data exchange needs careful mapping between EHS entities and asset records
- –Administration overhead rises when governance spans many business units
Best for: Fits when energy teams need EHS compliance workflows integrated into enterprise governance and reporting.
GE Vernova Grid Software
vertical specialistUtility-focused asset and network management software for transmission, distribution, and generation assets.
Central asset hierarchy governance that keeps maintenance planning aligned with controlled asset records.
GE Vernova Grid Software organizes grid asset data, criticality, and maintenance planning around an enterprise energy asset registry. It focuses on operational workflows for utilities that need consistent asset hierarchy handling, work execution linkage, and change control across teams.
- +Asset registry and hierarchy support consistent cross-team asset identification
- +Work planning workflows connect asset records to maintenance execution
- +Automation and API surface supports system-to-system integration patterns
- +Governance controls include RBAC and audit-oriented change visibility
- –Deep setup is required to align asset hierarchy with operational realities
- –Some GIS, historian, and SCADA connectivity is workload-specific rather than universal
- –Configuring end-to-end field and work instruction flows can require tight process design
- –Reporting depth depends on how data is modeled and mapped during onboarding
Best for: Fits when utilities need governed asset hierarchies and maintenance workflows tied to enterprise asset data.
C3 AI Reliability
enterpriseEnterprise AI application for predictive maintenance and asset reliability in energy and utilities.
Model-driven reliability decisioning that links operational signals to maintenance planning logic through an integration-first approach.
C3 AI Reliability is designed for reliability and predictive maintenance use cases where asset performance data must drive reliability decisions across large asset portfolios. It differentiates through a model-driven approach that connects maintenance planning logic to sensor and operational signals, with an API surface for integrating CMMS and enterprise systems.
- +API-first integration supports CMMS and enterprise system connectivity
- +Reliability analytics tie telemetry patterns to maintenance decisioning
- +Automation pipelines reduce manual handoffs from monitoring to planning
- +Extensibility supports adding asset-specific logic and scoring rules
- –Reliability configuration requires strong data engineering and governance
- –Work order management depth depends on external EAM or CMMS workflows
- –Asset hierarchy and registry features require careful alignment to upstream systems
- –Edge and historian integration often needs custom connector work
Best for: Fits when enterprise teams need reliability analytics tied to maintenance execution across many asset classes.
Conclusion
After evaluating 10 energy asset management software, Infor EAM 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 Energy Asset Management Software
Energy asset management software is used to govern asset hierarchies, connect engineering context to maintenance execution, and keep work and inspections tied to controlled asset records.
This buyer’s guide covers Infor EAM, AVEVA Asset Performance Management, IBM Maximo Application Suite, and other top tools for energy asset teams that need integration, automation, and auditable governance.
The tools are evaluated on integration depth, automation and API surface, and administration controls that control how asset registry data and work execution states stay consistent across teams.
Each tool review below focuses on what the product does natively versus what requires external pipelines and operational discipline.
Energy Asset Management Software for governed asset hierarchies and traceable maintenance execution
Energy asset management software centralizes an energy asset registry, organizes assets into governed hierarchies, and drives maintenance planning and work execution so inspections, work orders, and outcomes remain traceable.
Infor EAM uses configurable maintenance planning rules tied to an asset hierarchy so scheduling follows criticality-based structure, and work order workflows can support inspection rounds and digital job instructions.
IBM Maximo Application Suite emphasizes configurable work execution with approvals tied to the asset hierarchy and audit logged changes, with a REST API and integration hooks for enterprise workflow orchestration.
Tools like AVEVA Asset Performance Management focus on reliability planning workflows that preserve traceability from criticality decisions to maintenance outcomes, which matters when reliability logic must be auditable across operations and engineering.
Energy Asset Management Software criteria that control governance and execution
Asset hierarchy control determines whether asset identifiers stay consistent across engineering, maintenance planning, and field execution. Infor EAM, IBM Maximo Application Suite, and Power Factors Drive each tie planning or work execution behavior to governed hierarchy and criticality context.
API depth and automation surface determine whether asset registry updates and work execution states can be orchestrated across CMMS, EAM, GIS, and telemetry pipelines. IBM Maximo focuses on REST API and integration hooks, while Cognite Data Fusion emphasizes API-driven entity provisioning and extensible ingestion pipelines for time-series and event data.
Hierarchy-driven planning rules that preserve auditable execution context
Infor EAM configures maintenance planning rules around an asset hierarchy so scheduling follows criticality-based structure. IBM Maximo Application Suite uses the asset hierarchy to drive work orders, inspections, and spares demand consistently with audit logged changes.
Reliability planning workflows with traceability from criticality decisions to outcomes
AVEVA Asset Performance Management preserves traceability from asset criticality decisions to maintenance outcomes through reliability planning workflows. C3 AI Reliability ties operational signals to maintenance planning logic through integration-first reliability decisioning, then depends on external work order management depth.
Integration-first asset registry provisioning for governed entity models
Cognite Data Fusion supports asset modeling and ingestion that lets teams create governed, linked entities from engineering, maintenance, and telemetry data through API-driven entity provisioning. C3 AI Reliability also uses an API-first approach for CMMS and enterprise system connectivity, with reliability analytics tied to maintenance decisioning logic.
Work execution controls for inspection rounds, digital job instructions, and approvals
Infor EAM supports work order workflows for inspection rounds and digital job instructions while tying asset hierarchy configuration to execution states. IBM Maximo Application Suite adds configurable work execution with approvals tied to the asset hierarchy and auditable change history.
Governance visibility across roles for asset-to-work-order lineage
Accruent Asset Management links asset record lineage to maintenance planning and inspection outcomes with governance controls for roles and activity visibility. eSmart Systems Grid Vision links grid-focused asset hierarchy mapping to maintenance execution so asset records update as field work completes.
How to choose Energy Asset Management Software for integration and governed execution
Energy programs usually fail to scale when asset identity and hierarchy rules are configured without a clear ownership model for changes. Tools in this category differ most in how they let teams bind hierarchy, planning rules, and work execution to auditable governance.
Decision points below separate utilities that need hierarchy-centered maintenance execution from teams that need model-driven reliability analytics or API-driven asset registry foundations that other systems execute. These forks also reflect whether work order management is native or dependent on CMMS integrations.
Choose hierarchy-centered maintenance execution when the asset hierarchy must drive work outcomes
Select Infor EAM when maintenance planning rules must follow criticality-based structure configured against an asset hierarchy. Select IBM Maximo Application Suite when asset hierarchy must control work orders, inspections, and approvals while keeping audit logged changes for governed maintenance execution.
Choose reliability traceability workflows when criticality decisions must remain auditable end to end
Select AVEVA Asset Performance Management when reliability planning needs traceability from asset criticality decisions to maintenance outcomes. Select C3 AI Reliability when reliability analytics must tie telemetry patterns to maintenance decisioning logic through an integration-first API, then accept that work order management depth depends on external EAM or CMMS workflows.
Choose an API-first asset modeling foundation when the registry must be assembled from multiple systems
Select Cognite Data Fusion when asset programs must build a governed asset registry foundation from engineering and telemetry through API-driven entity provisioning. Select C3 AI Reliability when reliability decisioning must be integrated across many asset classes and operational signals, while CMMS and work execution can remain external.
Choose centralized criticality ranking when planned maintenance must inherit risk context
Select Power Factors Drive when asset criticality ranking must feed maintenance planning so asset risk context travels into work scheduling and execution. Select eSmart Systems Grid Vision when grid-focused asset hierarchy mapping must stay aligned with operational operations data and update as field work completes.
Choose governance-first lineage when asset records must carry role-based visibility into operations
Select Accruent Asset Management when asset-to-work-order traceability and governance controls for roles and activity visibility are primary requirements. Select Infor EAM when inspection rounds and digital job instructions must follow the same governed hierarchy structure used for planning.
Exclude tools whose native workflow depth depends on add-on integrations for core execution
Use Cognite Data Fusion when work order management can be integration-driven rather than native, since work order coverage depends on integrations rather than native workflows. Use Sphera Corporate EHS & Sustainability when EHS case and audit management is required, since work order management and preventive scheduling are not its primary strength in this category.
Who should buy Energy Asset Management Software from this list
The right tool depends on where the program wants governance to live. Some utilities need hierarchy-driven maintenance execution with auditable approvals, while others need reliability traceability or an API-first asset registry foundation that connects engineering, historians, and GIS.
The segments below map directly to how each product card describes asset hierarchy usage, integration behavior, and coverage of work execution versus analytics decisioning.
Utility asset management teams standardizing asset identity and work execution under a governed hierarchy
Infor EAM configures maintenance planning rules around an asset hierarchy so scheduling follows criticality-based structure, and work order workflows support inspection rounds and digital job instructions tied to that hierarchy.
Utilities that must preserve auditable traceability from reliability logic to maintenance outcomes
AVEVA Asset Performance Management focuses on reliability planning workflows that preserve traceability from asset criticality decisions to maintenance outcomes, and IBM Maximo Application Suite adds audit logged changes with approvals tied to asset hierarchy.
Programs building a governed asset registry by linking engineering, maintenance, and telemetry entities
Cognite Data Fusion provides asset modeling and ingestion that creates governed, linked entities from multiple sources, with API-driven entity provisioning and extensible ingestion pipelines for time-series and event data.
Organizations with grid-aligned asset records and field completion that must update the asset hierarchy
eSmart Systems Grid Vision links grid-focused asset hierarchy mapping to maintenance execution, and asset records update as field work completes.
Enterprise reliability teams that need integration-first telemetry-driven decisioning across many asset classes
C3 AI Reliability offers API-first integration for CMMS and enterprise system connectivity and ties reliability analytics to maintenance decisioning, while work order management depth depends on external EAM or CMMS workflows.
Common Energy Asset Management Software mistakes
Asset hierarchy and workflow governance are only effective when the program owners define who changes rules and how changes propagate into work execution. Several mistakes show up when teams select a tool that matches analytics goals but cannot carry the work execution workflow requirements.
The pitfalls below are grounded in how tools describe configuration complexity, integration dependence, and native versus external coverage of work order management.
Configuring hierarchy and workflow rules without a governance ownership model for release and change control
Infor EAM warns that complex workflow customization raises release testing overhead, and IBM Maximo Application Suite notes workflow and hierarchy setup requires governance discipline at scale.
Assuming reliability analytics tools include native work order management depth
C3 AI Reliability depends on external EAM or CMMS workflows because work order management depth depends on integrations rather than native workflows. Cognite Data Fusion also provides work order management coverage that depends on integrations rather than native workflows.
Starting with master data that is inconsistent and expecting automation to stabilize it automatically
AVEVA Asset Performance Management notes time to operationalize automation can increase when master data is inconsistent. IBM Maximo Application Suite requires governance discipline at scale for workflow and hierarchy setup, which increases the cost of fixing inconsistent structures later.
Using an EHS or compliance-first platform as a replacement for EAM execution workflows
Sphera Corporate EHS & Sustainability focuses on EHS case and audit management with audit-ready histories, and it states work order management and preventive scheduling are not its primary strength.
Underestimating the configuration effort needed to align asset hierarchies with operational realities
GE Vernova Grid Software states deep setup is required to align asset hierarchy with operational realities, and some GIS, historian, and SCADA connectivity is workload-specific rather than universal.
How We Selected and Ranked These Tools
We evaluated Infor EAM, AVEVA Asset Performance Management, IBM Maximo Application Suite, and the other six listed tools using feature coverage of governed asset hierarchies tied to maintenance planning and work execution. We weighted features at 40 percent, then weighted ease and value at 30 percent each to balance configuration overhead against operational outcomes.
We treated Infor EAM as the top-ranked tool because the cards describe maintenance planning rules configurable around asset hierarchy, plus work order workflows that support inspection rounds and digital job instructions tied to execution states. We used each product’s stated integration and API posture to judge automation and orchestration fit, with IBM Maximo scored for REST API and integration hooks and Cognite Data Fusion scored for API-driven entity provisioning and extensible ingestion pipelines.
Frequently Asked Questions About Energy Asset Management Software
How should evaluation teams test integration depth between an energy asset system and CMMS work order management?
Which tools support API-first extensibility for provisioning and normalizing asset entities across systems?
When does SSO and RBAC matter most in energy asset asset hierarchy governance?
How is data migration handled when an existing energy asset registry must map into an asset hierarchy used by maintenance planning?
What breaks if asset hierarchy governance is configured differently across maintenance planning and field execution?
How do utilities validate throughput and event handling when telemetry and work execution updates run at the same time?
Which workflow gap appears when teams need reliability planning traceability from criticality decisions to executed maintenance outcomes?
Where does CMMS integration fall short for teams that require an integration hub for graph relationships and cross-system linking?
How should admin controls be evaluated when multiple teams manage configuration changes to maintenance rules?
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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