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Business area digitalisation analysis

Energy Production and Supply: Digitalisation Opportunities

The integration of asset, operational, field work, customer and compliance data from electricity, heat, gas and other energy resource production, trading and supply into a single managed digital chain.

Digital maturity

Typical digital maturity

Shows the level of technological and process digitalisation at which companies in the sector or business area typically operate today.

A typical market situation is assessed, not the most advanced companies.

The assessment consists of five equally weighted dimensions:

Core system usage
Whether ERP, CRM, WMS, MES, customer portals or other operationally important systems are widespread in companies.
Process digitalisation
How many core processes run in systems and how many are still managed manually.
Systems integration
Whether core systems exchange data between themselves or whether employees transfer information manually.
Data quality and readiness
Whether core data is structured, up-to-date, consistent and suitable for automation and analytics.
Advanced data use
Whether real-time analytics, forecasting, automated alerts, optimisation models or AI are used.

The final score is the average of the five dimensions.

1–5 scale

  • 1 very low maturity
  • 2 low maturity
  • 3 medium maturity
  • 4 high maturity
  • 5 very high maturity

A low maturity score does not necessarily indicate low potential. On the contrary, low maturity and a high level of manual work may indicate significant untapped digitalisation value.

high
Skaitmenizacijos potencialas

Digitalisation potential

Shows how much significant business value a typical sector or business area company can create by systematically digitalising core processes.

The rating is calculated on a 100-point scale across five dimensions:

Process frequency and scale 20 %
An assessment of how frequently the digitalised processes recur and what proportion of operations they represent.
Manual work intensity 20 %
An assessment of the extent to which processes depend on email, telephone, Excel, paper documents and repeated data entry.
Impact on revenue and costs 25 %
An assessment of the potential effect on sales, margin, customer retention, administrative costs, errors, downtime or inventory.
Growth and scale potential 20 %
An assessment of whether digitalisation would enable operational capacity to be increased without expanding headcount and costs at the same rate.
Impact on decisions and risk 15 %
An assessment of the potential effect on data reliability, decision-making speed, customer experience, and the reduction of errors and operational risk.

The final score is calculated according to the assessments and weights of all dimensions.

100-point scale

  • 0–20 very low potential
  • 21–40 low potential
  • 41–60 moderate potential
  • 61–80 high potential
  • 81–100 very high potential

A high score does not mean the solution will be easy to implement. It indicates the size of the potential value, not the implementation complexity.

92/100
Biggest challenge
Production and market signals insufficiently converted into joint actions
Biggest opportunity
Integrated technical and commercial energy portfolio management

Competitiveness will be determined by the ability to align safe equipment operation, market opportunities, balancing risk and customer portfolio margin in one decision chain.

Operating model for energy generation and supply

The business covers the production, trading, balancing, supply, metering and settlement of electricity, heat, gas and other energy resources. The economic result is driven by the ability to simultaneously manage the technical constraints of assets, fuel and emission costs, demand and price forecasts, market positions and customer portfolio margin.

Technical and commercial solutions are inseparable

Production regime must account for equipment constraints, fuel and emission costs, and market value.

Time and data version are critical

Forecast, transaction, actual measurement and correction must be compared based on the information available at that time.

Portfolio margin is driven by exceptions

Balancing, metering, contract and invoice corrections can obscure the true product or customer result.

Market and technology context

In 2026, energy sector digitalisation is driven particularly by variable generation, electrification, storage, demand flexibility and the need to simultaneously optimise technical reliability, market position, balancing and emissions costs.

  • Variable generation and flexibility needsMore frequent forecast updates and storage increase the importance of technical and commercial coordination.
  • Price, fuel and emissions cost fluctuationsProduction regimes must be evaluated against full economic impact, not technical efficiency alone.
  • Smart metering and more flexible customer productsHigher data frequency enables more precise management but increases the need for exception and quality control.

Typical business process

01

Demand, generation and price forecasting

Forecasts are prepared based on weather, customer consumption, asset availability, fuel and market data.

02

Production and market planning

Technical constraints, contractual commitments, market positions and risk limits are aligned.

03

Real-time management and balancing

Deviations, asset condition, network conditions and required corrective actions are monitored.

04

Metering and data quality control

Meter readings, versions, calculated quantities and exceptions are managed.

05

Settlement and customer service

Contract and tariff formulae are applied, invoices are issued and corrections are reviewed.

06

Plan–actual and portfolio margin analysis

Deviations are attributed to technical, forecasting, market, metering or contractual causes.

Digital maturity pathway

0

Separate technical and commercial management

Production is managed via SCADA, trading and forecasting in other systems, and overall performance is reconciled through reports.

1

Digitalised core processes

Production plans, market transactions, metering and billing are managed in systems, but exceptions and root causes are often checked manually.

2

Integrated generation and market plan

Demand, generation, fuel, price, emissions and equipment availability forecasts form a single planning cycle.

3

Closed plan–actual–settlement cycle

Market position, actual generation, balancing outcome, metering and financial impact are linked to a specific portfolio asset or customer.

4

Data-driven generation and supply portfolio Typical current situationSiektina

In key portfolios, forecasts, technical availability, market positions, balancing outcomes, metering and financial impact are linked in a single decision chain, but coverage and model control are not yet uniform across all products.

5

Adaptive real-time energy portfolio

Validated decisions are partially automated, and model quality, risk limits and human intervention are continuously monitored.

Key finding

Energy generation and supply digitalisation must connect technical availability, forecasts, market positions, balancing actions, metering and the final financial result.

The greatest value arises from creating a closed plan–actual–settlement cycle for one portfolio, rather than improving each team's models separately.

Related digitalisation topics

Energy forecasting and balancing analyticsGeneration portfolio optimisationEnergy metering and settlement automation
Next step

Link electricity, heat, gas and other energy resource generation, trading and supply signals, assets and actual operations

Let us assess which gap in forecasting, technical availability, balancing or settlement is currently reducing portfolio margin the most.

Discuss digitalisation direction