Adasa and ATL drive the digital transformation from data to decision-making at the Spain Smart Water Summit 2026

2026-10-01

Adasa and ATL drive the digital transformation from data to decision-making at the Spain Smart Water Summit 2026

 

Borja Sanz, Head of the Digital Solutions Division at Adasa, and Antoni Carrasco, Head of Digital Transformation at ATL, presented an approach to digital transformation aimed at turning data and operational knowledge into a shared capability to forecast, simulate and make better decisions.

How can all the information generated by a large water supply infrastructure be transformed into useful operational knowledge?

This was one of the central questions addressed in the presentation by Borja Sanz, Head of the Digital Solutions Division at Adasa, alongside Antoni Carrasco, Head of Digital Transformation at the Ens d’Abastament d’Aigua Ter-Llobregat (ATL), at the Spain Smart Water Summit 2026.

Entitled ‘Digital transformation at ATL: from strategic challenge to cultural change’, the presentation highlighted the work currently underway to lay the foundations for an increasingly integrated, traceable operation capable of anticipating different scenarios.

And the starting point is not to incorporate more technology. It is to ensure that the information and knowledge that already exist can be used in a more coordinated way to inform decision-making.

Organise before integrating
Production, transport, quality, energy, maintenance and planning generate large volumes of data and utilise specialised systems such as SCADA, GIS, CMMS and LIMS, alongside spreadsheets and other working procedures.
 
The challenge is not simply to connect these sources.
 
First, it is necessary to create a common language that allows the information to be contextualised: defining scopes, areas, plants, assets and indicators, and maintaining these relationships as the data moves from one system to another.
 
The approach presented by ATL and Adasa does not aim to replace the specialised tools that already perform their functions correctly, but rather to provide a cross-cutting layer capable of linking information from different environments and offering a coherent view of the same operational reality.
 
This common foundation is essential for taking the next step: being able to trust the data used to make decisions.
 
From available data to reliable data
Data quality was another key focus of the presentation.
 
In processes critical to water management, simply having information is not enough. It is necessary to know whether the data is valid, to detect gaps or anomalies, to apply validation criteria, to reconstruct information where necessary, and to maintain the traceability of the decisions taken.
 
This marks one of the most significant changes in the approach outlined: a shift from systematically reviewing data to managing exceptions.
 
Technology can help to detect problems and suggest solutions, but expert intervention remains essential. Digitalisation is not intended to replace the expertise of professionals, but rather to enable them to focus their time and experience precisely where they add the most value.
 
 

Modelling the network also means gaining a better understanding of it

Hydraulic modelling is another of the project’s cornerstones. Building a coherent model requires linking information from the GIS, assets, sensors, operational data and control rules. During this process, nomenclatures, documentation and operating conditions are cross-checked against the operators’ own knowledge.

For this reason, the value of the model begins even before a simulation is run: modelling also helps to capture, organise and share knowledge of the network.

On this basis, progress is being made in integrating the hydraulic model with AQUADVANCED® Water Networks. In the initial phase, the PTLL–Fontsanta area is being used to validate scenarios and methodology.

The aim is to be able to compare alternatives in situations such as a change in demand, the unavailability of a facility or pipeline, variations in available reserves or different operational strategies.

In short, to start by asking a question before taking action: what might happen if…?

Forecasting, trusting, simulating and deciding
The presentation summarised the capabilities currently being developed around four key questions:
  • Forecasting: how much water will we need?
  • Trusting: which data is reliable enough to make a decision?
  • Simulating: what might happen in a given scenario?
  • Deciding: which alternative best meets operational needs?
Demand forecasting is a good example of this evolution.
 
ATL has established processes that combine historical data, seasonality, real-time information and expert knowledge. Digital transformation therefore does not start from scratch, nor does it seek to replace that knowledge.
 
The aim is to capture it, structure it and turn it into a more collaborative, reproducible and traceable process, in which it is possible to systematically compare forecasts with actual results, analyse deviations and continue to improve the decision-making model.
 
From technological transformation to cultural change
One of the key messages of the presentation was precisely that a transformation of this nature does not depend solely on technology.
 
The project follows a path that begins with understanding the processes through workshops, continues with the configuration and development of use cases, their validation through pilot schemes, and subsequent refinement based on user feedback.

All of this is accompanied by the identification of the teams involved, staff training and change management within the organisation.

The evolution we are seeking can be summarised in several shifts: from information silos to a shared vision; from available data to reliable data; from individual knowledge to a shared capability; and from reacting to events to having better tools to anticipate them.

Along this path, ATL’s operational expertise, the available digital capabilities, and the work on technological integration and hydraulic modelling all converge towards a single objective: that digitalisation should result in better tools for decision-making.