The B2B electricity market is changing faster than most utilities can respond. Commercial and industrial customers are no longer satisfied with fixed-price supply contracts. They want tranche-based models, Power Purchase Agreements (PPAs), spot-price components, and multi-site self-consumption structures – products that reflect the market realities of a renewable-heavy grid. And they are asking for them. Repeatedly.
According to our market research, more than 90% of electricity suppliers regularly receive requests for structured electricity products. Yet only 10–15% are operationally capable of delivering them in a standardized, automated way.
That gap is not a product problem. It is a billing problem.
The challenge begins with data volume. Where a traditional fixed-price contract requires processing a single annual meter reading per metering point, interval metering data (iMSys/RLM) generates more than 35,000 data points per year – per site. For a multi-site corporate customer with tranche, PPA, and spot components, that number multiplies rapidly.
But volume alone is not the issue. The real complexity lies in the dynamic allocation logic that sits at the heart of every structured electricity product.
Consider a corporate group with subsidiaries across four balancing areas. Their electricity supply might consist of:
Every 15 minutes, energy volumes must be allocated across the group's entities – PPA-generated electricity assigned first to the site of the originating subsidiary, then distributed proportionally across remaining entities, with tranche and spot volumes applied last. Long and short positions must be tracked at individual site level. And every component carries its own pricing logic.
This is not a workflow that Excel was designed to handle at scale. Yet for most utilities, Excel remains the central tool.
In conversations with more than 100 electricity suppliers across the past 12 months – ranging from regional municipal utilities (Stadtwerke) to large national energy companies – we observed the same pattern consistently: energy allocation and B2B customer billing are still dominated by manual workflows.
The consequences are measurable. Consider a mid-sized electricity supplier managing 500 GWh across 50 business customers with a mixed tariff portfolio including spot products, tranches, PPAs, and B2B energy sharing. The staffing required for data consolidation, energy allocation calculations, and billing preparation alone – before final invoicing – amounts to approximately 6 FTE. At realistic overhead rates, that translates to roughly €650,000 per year, or 0.13 ct/kWh in operational cost.
Given that margins for structured electricity products rarely exceed 0.3 ct/kWh, manual billing processes consume over 40% of the available margin before a single euro is invested in sales, product development, or risk management.
The scaling problem compounds this. While revenue grows linearly with each new customer, manual effort grows exponentially. Every additional customer means more complex Excel models, more coordination effort, higher operational risk. In this environment, growth does not improve profitability – it erodes it.
Manual formula errors and copy-and-paste workflows also introduce a risk that is difficult to quantify but regularly observed in practice: correction costs of up to €50,000 per month due to incorrect energy allocations or pricing assignments.
The requirements for billing structured electricity products are well understood. What is still missing, for most utilities, is the operational infrastructure to meet them. Any modern billing system serving this market must deliver four capabilities:
Hierarchies and allocation logic. Energy volumes and costs must be allocated flexibly according to customer requirements – at aggregated group level, at subsidiary level, or down to individual delivery points.
Automated data integration. Accurate billing depends on the daily, automated ingestion of interval meter data, consumption forecasts, spot market prices, and generation data. Quarter-hourly allocations cannot be calculated reliably from manual data consolidation.
Complex pricing component management. Billing systems must automatically assign energy volumes from different sources – fixed-price tranches, dynamic tariffs, time-of-use rates, feed-in structures – to the appropriate pricing mechanisms, without manual intervention.
Long and short position management. Particularly for customers with PPA components, generation volumes can differ significantly from forecasts. Billing systems must transparently account for over- and under-coverage situations and their financial impact.
Automated billing is the foundation. But business customers today expect more than an error-free invoice. They want to understand where their electricity came from at any given point in time, how their self-consumption model is performing, and what their PPA and tranche components actually cost.
Utilities that provide this transparency – through modern visualization and intuitive dashboards – create genuine additional value. Energy buyers within business customers gain a detailed view of supply composition across 15-minute intervals. Product managers at utilities gain portfolio-level oversight without manual data consolidation. And the employees of business customers, often an underestimated audience, gain access to sustainability data they can use for internal ESG communication.
Business customers who can fully understand and track their energy supply are more loyal, less likely to switch providers, and more likely to recommend their supplier. Transparency translates directly into stronger Net Promoter Scores and lower support costs.
Replacing manual workflows with a specialized billing engine designed for time-series-based tariffs does not require replacing existing ERP infrastructure. The right approach integrates with systems like SAP S/4HANA or SAP IS-U as an upstream calculation layer, taking over the allocation-intensive pre-billing steps and transferring billing-ready data automatically into the existing billing system via API.
Returning to the earlier example: with automated pre-billing in place, the staffing requirement for the same 500 GWh portfolio drops from 6 FTE to approximately 2 FTE – focused on monitoring and exception handling rather than manual formula maintenance. Total costs fall from €650,000 to around €215,000 per year, reducing the cost-per-kWh from 0.13 ct to 0.043 ct and delivering a margin improvement of 0.087 ct/kWh.
The operational risk picture changes as well. Automation conservatively reduces error-related correction costs by approximately 90%, from up to €50,000 per month to around €5,000.
Critically, the scaling effect reverses. Automated processes scale linearly with portfolio growth. New customers and new products can be onboarded without proportional increases in operational effort – which means every new customer improves contribution margins rather than straining them.
The market is clear. Demand for structured electricity products exists and is growing. The gap is operational, not commercial. For utilities ready to close it, the path is straightforward:
Step 1: Automate billing. Replace fragmented data sources and Excel-based consolidation with an automated data chain – from meter reading to billable item. This immediately reduces process costs and eliminates the error risk embedded in manual workflows.
Step 2: Scale the product portfolio. With automation in place, billing becomes an enabler rather than a bottleneck. Spot-based tariffs, tranche models, PPAs, and multi-site self-consumption solutions can be launched efficiently. Customer requests that previously had to be rejected become revenue opportunities.
Step 3: Differentiate through transparency. Automated billing creates the data foundation for meaningful visualization. Utilities that surface this data through intuitive dashboards – for energy buyers, product managers, and business customer employees alike – build the kind of customer relationships that survive competitive pressure.
This article draws on findings from our new whitepaper, "Scalable Billing: How Complex B2B Electricity Products Become Truly Profitable", authored by Thies Stillahn, Head of Sales DACH at exnaton.
The whitepaper covers:
