The water industry is undergoing profound change. Climate change, increasing urbanisation, growing quality requirements and rising cost pressure are fundamentally changing the operating environment for utilities and operators. At the same time, the digitalisation of infrastructure is advancing. Sensors, automation, AI applications and data-based control systems are increasingly becoming standard
In this environment, it is no longer the technical performance of individual systems alone that determines success, but their ability to make data usable across organisational and system boundaries. Interoperability is thus becoming a key success factor for the water industry in 2026.
Many water suppliers still work with IT structures that have evolved over time, developed in parallel with operational requirements over decades. New systems were often introduced as isolated solutions to solve acute problems without pursuing a comprehensive digital strategy. Process control systems, geoinformation systems, billing solutions, maintenance software and IoT platforms therefore often exist side by side without being systematically integrated. Each application has its own data models, interfaces and logic, which are only coordinated to a limited extent.
In practice, this means that identical information has to be entered and maintained multiple times. Plant identifiers, line data and consumption values are stored separately in different systems, sometimes with different names or update statuses. This results in inconsistencies and redundancies. In order to create operational or strategic evaluations, these data sets must be regularly merged, checked and cleaned up manually. This ties up valuable human resources while increasing the likelihood of errors.
Data is also stored in different formats and interpreted differently. Measurement values from process control technology, geographical information from GIS, commercial data from billing and status data from maintenance systems each follow their own structural and classification logic. Without uniform semantic standards, there is no common understanding of what certain key figures or statuses actually mean. This leads to misunderstandings, incomplete analyses and limited comparability.
Typical consequences of this fragmentation are delayed decision-making processes, as relevant information first has to be gathered from several sources. The effort required for data preparation is constantly increasing because each new analysis requires individual interfaces, exports or manual corrections. At the same time, transparency about network statuses remains limited because no consolidated overview is available in real time. Automation options are also severely restricted because isolated systems can only interact with each other to a limited extent.
This situation may still work during stable operating phases with consistent conditions. As long as networks are subject to few changes and external influences are limited, weaknesses can be compensated for by experience, manual processes and individual expertise. However, with increasing network complexity, rising regulatory requirements, growing cost pressure and more frequent extreme events, this model quickly reaches its limits.
In such situations, fragmented IT landscapes make it difficult to assess the situation quickly and delay necessary measures. Decisions are then based not on an up-to-date, integrated data picture, but on delayed and sometimes incomplete information. This not only increases operational risks, but also reduces the organisation's ability to respond flexibly to new challenges. In the long term, the existing system landscape itself becomes an obstacle to innovation, efficiency and resilience.
Interoperable data is characterised by the fact that it can be understood, used and processed automatically across different systems. This is not just a matter of technical interfaces, but rather a holistic interaction between technology, structure and meaning.
In practice, interoperability encompasses three key levels:
Only when all three levels are fulfilled can data be used consistently without media discontinuity. In this case, a continuous information chain is created, ranging from data collection in the field to processing in central systems to analysis and decision support. Information no longer needs to be transformed multiple times, interpreted manually or transferred to intermediate systems, but is available consistently and up to date.
For operational activities, this means a significant reduction in the workload for specialist departments. Employees can concentrate more on analysis, optimisation and control instead of spending time consolidating and validating data. At the same time, the quality of the basis for decision-making increases, as evaluations are based on complete and harmonised data sets.
At the strategic level, this consistency enables a holistic view of networks, facilities and processes for the first time. Investment decisions, capacity planning and renovation strategies can be based on integrated lifecycle data that links technical, economic and environmental aspects. This not only makes costs more transparent, but also allows long-term risks to be better assessed.
Water management is part of critical infrastructure and bears a special responsibility for public health, economic stability and everyday social life. Disruptions, quality deviations or extreme weather events such as heavy rainfall, droughts or floods require rapid, coordinated and resilient responses. Even minor delays in information processing can have a significant impact on supply security and operational stability in such situations.
This requires the ability to consolidate, contextualise and evaluate operational, measurement and network data from different systems in real time. Only then can an up-to-date and complete picture of the situation be obtained, enabling informed decisions to be made. Control centres, emergency services and management need access to consistent information about pressure conditions, water quality, flow rates and plant status at all times.
Without interoperable systems, information gaps, media breaks and time delays arise at this point. Critical data reaches decision-makers late or in incomplete form, which significantly limits their ability to respond. Measures are then often taken on the basis of assumptions or outdated data rather than on the basis of an integrated real-time picture. In the long term, this not only increases operational risks but also weakens the resilience of the entire supply infrastructure to future stresses.
Modern water utilities are increasingly relying on automated processes and AI-supported applications. These include, among other things:
Early detection of leaks
Predictive maintenance of systems
Dynamic pressure and flow control
Investment planning, network expansions or capacity adjustments require reliable, consistent and long-term data. Given the high investment volumes and long life cycles of infrastructure facilities, wrong decisions can have significant financial and operational risks. Strategic decisions must therefore be based on information that is as complete and reliable as possible.
Only by systematically linking operating data, consumption information, environmental parameters, status assessments and forecasts can a holistic decision-making picture be created. This allows technical, economic and ecological aspects to be evaluated together and different scenarios to be simulated realistically. For example, the effects of climate change, demographic change or changing consumption profiles can be incorporated into planning at an early stage.
Isolated data sources prevent this integrated view. If relevant information remains in separate systems or can only be merged with great effort, the result is incomplete analyses and limited decision-making bases. Strategic planning is then often based on assumptions, individual perspectives or outdated data sets. In the long term, this hinders forward-looking infrastructure development and reduces the ability of companies to respond flexibly and resiliently to future challenges.
Water management is increasingly evolving from isolated operating units to networked, cooperative ecosystems. Utilities are acting less and less as self-sufficient organisations and are instead becoming integrated into regional, national and, increasingly, international data and service networks. They are cooperating with local authorities, energy service providers, technology partners, research institutions and regulatory authorities to jointly overcome complex challenges.
In this context, data is no longer used exclusively for internal purposes, but is shared via platforms, integrated into smart city structures and made available for comprehensive analysis. This creates new opportunities for optimising infrastructure, developing innovative services and improving coordination between different supply areas.
Key areas of application include:
These fields of application require continuous, standardised and secure data exchange between different organisations and technical systems. Not only must technical interfaces be compatible, but data models, definitions of terms and quality standards must also be harmonised.
Without standardised and interoperable data structures, this collaboration remains inefficient and difficult to scale. Projects then become heavily dependent on individual interface solutions, which are costly and difficult to maintain in the long term. Data exchange is delayed, fragmented or only takes place to a limited extent. As a result, innovation potential is lost and cooperation often remains limited to pilot projects instead of being transferred to regular operation on a sustainable basis.
Interoperability thus becomes a fundamental prerequisite for stable, resilient and sustainable digital ecosystems in water management. It enables knowledge, resources and skills to be pooled across organisations and to respond jointly to new challenges.
Parallel to technical developments, regulatory requirements for documentation, traceability and quality assurance are constantly increasing. National and European regulations, environmental requirements and the demands of supervisory authorities oblige operators to record and document operating processes, measured values and interventions in the infrastructure in ever greater detail. Transparency and verifiability are thus becoming central elements of legally compliant and standard-compliant operational management.
Operators must increasingly be able to provide complete documentation of processes and measurement results, from water extraction and treatment to distribution and billing. Maintenance measures, troubleshooting and quality controls must also be documented in a traceable manner. In the long term, these requirements can only be met efficiently with digitally integrated systems.
Interoperable systems enable consistent data chains across all process stages, audit-proof archiving and automated report generation for internal and external bodies. This makes inspections, audits and certifications significantly faster and more reliable. At the same time, the manual effort required to compile evidence is reduced considerably.
Fragmented data sets, on the other hand, make audits and controls considerably more difficult. Information is stored in different systems, formats and versions and must be laboriously collated. This not only increases the administrative burden, but also the risk of incompleteness, contradictions and formal complaints. In the long term, a lack of data integration thus becomes a structural risk for compliance and corporate security.
Building interoperable data landscapes requires a long-term, strategic approach. Key components include:
Uniform functional and technical data models
API-based system architectures
Use of open standards
Clear data governance structures
Centralised, scalable data platforms
Together, these elements form the digital backbone of modern water utilities. Building on this foundation, these building blocks enable the seamless integration of heterogeneous systems, promote data quality and create the basis for data-driven decisions. By consistently implementing such an interoperable data landscape, water utilities can not only make processes more efficient, but also implement new services such as predictive maintenance or intelligent network control. In the long term, this strengthens the resilience of the infrastructure and supports strategic development towards smart, sustainable water management.
Companies that rely on interoperable data structures are already benefiting from measurable improvements. Water losses can be reduced, maintenance costs lowered, energy consumption optimised and faults rectified more quickly. At the same time, organisational resilience to external influences such as climate risks or regulatory changes is increasing.
In contrast, a lack of interoperability leads to rising integration costs, high system complexity and limited innovation capacity. Building on this, these building blocks enable the seamless integration of heterogeneous systems, promote sustainable data quality and create a reliable basis for data-driven decisions at all levels of the company. By consistently implementing such an interoperable data landscape, water utilities can not only make their operational processes more efficient and transparent, but also realise innovative services such as predictive maintenance, intelligent network control and optimised resource planning. In the long term, this strengthens the resilience of the entire infrastructure, increases operational reliability and supports strategic development towards smart, future-proof and sustainable water management.
Interoperable data is not an optional IT project, but a strategic necessity. It forms the basis for efficiency, security, sustainability and innovation. In 2026, the performance of water suppliers will depend largely on how consistently they have integrated and standardised their data landscapes.
Without interoperability, digital potential remains untapped, processes remain fragmented and risks remain high. With it, however, a resilient, transparent and sustainable water management system emerges.