Digital Transformation in the Energy Sector Training Course

Participants can define governed data foundations for operational energy use cases.

• Data product ownership, domains and stewardship under DAMA-DMBOK principles
• Canonical asset models connecting equipment tags, work orders and sensor streams
• ISO 14224 taxonomy for equipment failure, maintenance and reliability data
• Data quality rules for completeness, timeliness, accuracy and lineage
• Master data governance for asset hierarchies, locations and criticality codes
• Cloud data platform patterns: lakehouse, historian replication and governed access

Participants can select connected-asset architectures appropriate to energy operating requirements.

• Reference architecture from sensors and PLCs to edge and cloud
• OPC UA and MQTT selection for industrial data exchange
• Sensor placement based on failure modes, observability and maintenance access
• Edge analytics for latency-sensitive protection, control and safety use cases
• Historian integration with SCADA, DCS and enterprise asset management systems
• Connectivity trade-offs across private LTE, fibre, satellite and radio networks

Participants can evaluate analytics and AI use cases against operational performance requirements.

• CRISP-DM framing for predictive maintenance and production optimisation cases
• Failure-mode features derived from vibration, temperature, pressure and maintenance history
• Remaining useful life models and confidence intervals for maintenance decisions
• Forecast error metrics: MAE, RMSE and MAPE matched to use cases
• Model drift monitoring, retraining triggers and human review thresholds
• Prescriptive optimisation for dispatch, inventory, crew scheduling and curtailment

Participants can determine where digital twins provide sufficient operational value to justify investment.

• Digital twin types: component, asset, system and process representations
• Physics-based, data-driven and hybrid model selection criteria for assets
• Asset twins connected to condition monitoring, inspections and work management
• Grid and network twins supporting contingency analysis and outage restoration
• Model validation against design data, operating data and observed failures
• Lifecycle costs, fidelity requirements and twin ownership decisions

Participants can identify and address cyber security risks created by digital energy initiatives.

• ISA/IEC 62443 zones and conduits for operational technology segmentation
• Threat modelling using attack trees for connected energy assets
• Remote access controls: multifactor authentication, jump hosts and session recording
• IT/OT incident response roles, escalation paths and recovery priorities
• NIST Cybersecurity Framework 2.0 profiles aligned to transformation initiatives
• Supplier security requirements for cloud platforms, devices and managed services

Participants can create a target-state architecture and make defensible technology sourcing decisions.

• TOGAF architecture domains applied to an integrated energy data platform
• Target-state blueprints covering applications, data, integration, infrastructure and security
• API-led integration between ERP, EAM, GIS, SCADA and customer systems
• Build-buy-partner decisions using total cost, capability and lock-in criteria
• Interoperability requirements expressed through interfaces, data contracts and service levels
• Architecture review boards governing exceptions, technical debt and standards compliance

Participants can govern a digital transformation portfolio from business case through operational handover.

• Benefits cases quantified through avoided downtime, losses, labour and carbon
• Stage-gate governance from discovery through pilot, scale and operational handover
• Prioritisation scoring using value, risk, readiness, dependency and strategic-fit criteria
• Product roadmaps linking releases to measurable operational outcomes
• Agile delivery roles: product owner, scrum team and operational sponsor
• Vendor due diligence covering data rights, service levels and exit provisions

Participants can plan adoption and role changes required by digitally enabled energy operations.

• Stakeholder mapping across operations, maintenance, engineering, IT, unions and regulators
• ADKAR change plans addressing awareness, ability, reinforcement and adoption barriers
• Role redesign for remote operations centres and data-enabled maintenance teams
• Digital skills matrices defining proficiency, learning pathways and workforce gaps
• Frontline adoption measures: active users, workflow compliance and decision cycle time
• Safety management integration for automated decisions and altered work practices

Participants can establish measures, governance and immediate actions for a transformation initiative.

• Use-case charters defining problem statements, owners, data and value metrics
• Transformation scorecards combining financial, operational, safety, customer and carbon measures
• Value realisation tracking from baseline through benefits validation and handover
• Pilot evaluation criteria covering technical performance, adoption, scalability and cyber risk
• Executive communication using investment narratives, milestones, dependencies and decisions
• 90-day application plans with sponsors, actions, measures and review cadence