Problem and value definition
Define the operational, planning, asset, data, model, integration, regulatory, resilience, and customer-service problems the digital twin must solve.
TwinGrid Services
Services built from the utility digital twin workflow
TwinGrid Services follow the complete implementation sequence: from problem definition and use-case value to data/model readiness, architecture, sourcing, RFP support, governance, validation, cybersecurity, adoption, and sustainment.
Service catalogue
TwinGrid service modules
Each module can be delivered independently, but the strongest value comes from linking them into one decision trail from business need to implementation and long-term ownership.
Use-case prioritization
Convert pain points into digital twin use cases and score them against value, readiness, model dependency, integration complexity, cybersecurity, adoption, and time-to-value.
Data and model readiness
Inventory existing data sources and network models across GIS, SCADA, ADMS, EMS, OMS, AMI, DERMS, historian, planning, asset, and protection environments.
System integration definition
Classify the required interfaces across OT, IT, engineering, planning, enterprise, external, and analytics systems by criticality and exchange pattern.
Target architecture blueprint
Define the logical, physical, data, model, integration, cybersecurity, deployment, simulation, application, and workflow architecture for the selected digital twin scope.
First-build roadmap
Select the first implementation phase based on business priority, dependencies, data readiness, model maturity, cybersecurity effort, and adoption probability.
Buy-build-integrate strategy
Decide which capabilities should be bought, built, configured, integrated, or deferred based on strategic importance, market maturity, internal capability, cost, and risk.
RFP and vendor evaluation
Translate the digital twin scope into procurement requirements, vendor response templates, demonstration scenarios, scoring models, and acceptance criteria.
Implementation governance
Set decision rights, steering structure, workstreams, RACI, risk/issue control, change control, and executive reporting before delivery begins.
Validation, cybersecurity, and acceptance
Define model accuracy criteria, test scenarios, data quality thresholds, security zones, access control, approval gates, go-live criteria, and rollback.
Adoption and sustainment
Prepare users, support teams, model owners, data stewards, vendor managers, and enhancement governance for long-term ownership after go-live.
Engagement options
How utilities can start
Executive readiness scan
A short diagnostic to assess business drivers, leadership alignment, use-case clarity, data/model gaps, architecture risk, and procurement readiness.
Pre-RFP strategy package
A targeted engagement to prepare the use-case scope, architecture requirements, procurement structure, vendor evaluation logic, and acceptance criteria.
Implementation governance support
A delivery support model for utilities after vendor selection, covering workstreams, RACI, risk, model validation, cybersecurity approval, training, and go-live.