How data improves planning and reduces systemic costs in Utilities

From static planning to data-driven planning

Traditionally, planning in the Utilities sector has been based on forecasting models built on aggregated data updated at low frequency. Whilst this approach is effective in relatively stable contexts, it is now revealing its limitations in an increasingly variable energy system, where supply and demand are influenced by factors such as renewable generation, consumer behaviour and weather conditions.

The introduction of smart metering data makes it possible to overcome this rigidity. Planning is gradually becoming data-driven, fuelled by near real-time information that allows forecasts to be continuously updated and operational strategies to be adapted. In the electricity sector, this means better management of loads and demand peaks; in the water sector, a greater ability to detect leaks and optimise distribution; in the gas sector, more accurate forecasting of seasonal demand.

This change is not merely technological, but cultural. Decisions are no longer based solely on theoretical models or consolidated historical data, but on a combination of advanced analytics, simulations and dynamic scenarios.

Reduction in systemic costs: where the value of data lies

The most significant impact of this approach is seen in the reduction of systemic costs – that is, those costs that do not depend on a single activity, but on the overall efficiency of the system. One of the key areas concerns network management. Data makes it possible to identify widespread inefficiencies, such as water losses, energy wastage or sub-optimal use of infrastructure. Targeted action to address these issues helps to reduce operating costs, improve service quality and minimise the waste of resources.

Another crucial area is investment planning. Thanks to a more accurate picture of the condition of assets and their utilisation levels, utilities can allocate resources more effectively, avoiding both over-investment and critical delays. This is particularly relevant in regulated environments, where investment efficiency is directly linked to the economic sustainability of the system. Demand management also benefits from the use of data. Through predictive modelling, it is possible to anticipate consumption peaks and adopt strategies to spread them over time, reducing the need for additional capacity and limiting the costs associated with emergency management.

The contribution of Terranova’s solutions to data-driven planning

In this context, software platforms play a crucial role in transforming data into value. The smart metering solutions developed by Terranova sit precisely at this intersection between data collection, management and utilisation.

Through advanced Meter Data Management systems, Terranova enables utilities to integrate data from heterogeneous, multi-commodity meters, ensuring high levels of quality, consistency and availability of information. This is a fundamental prerequisite for building reliable planning models, in which data provides a solid foundation for operational and strategic decisions.

A key distinguishing feature is the ability to transform large volumes of data into actionable insights. The platforms enable continuous monitoring of grids performance, the identification of anomalies and support for predictive models that improve the planning of maintenance work and investments. In this way, utilities can move from reactive to proactive management, reducing inefficiencies and systemic costs.

Furthermore, integration with existing business systems enables the value of data to be extended throughout the entire operational chain, from planning to customer management, contributing to a unified and consistent view of the system.

Towards predictive and integrated planning

The natural evolution of data-driven planning lies in its integration with predictive models based on artificial intelligence. In this context, smart metering data becomes the fuel for algorithms capable of anticipating behaviour, identifying anomalies and simulating future scenarios. This predictive capability enables utilities to move from a post-event optimisation approach to proactive management, where decisions are made based on what is likely to happen, not just on what has already happened. The result is a further reduction in systemic costs, accompanied by improved resilience and sustainability of the networks.

In the Utilities sector, data is playing an increasingly central role in shaping operational and investment strategies. Smart metering, in particular, represents one of the richest and most relevant sources of information, capable of enabling more accurate, flexible and efficiency-oriented planning.

The reduction in systemic costs is therefore not the result of individual measures, but the effect of an integrated approach, in which data, technology and expertise converge to improve the overall functioning of the system. Those utilities that are able to fully exploit this potential will be best placed to tackle the challenges of the energy and digital transitions, transforming complexity into a competitive advantage.