From Operations to Optimisation: The Next Step for Data Centres
As the need for operational efficiency increases, technological advancements are being explored for the data centre industry to offer new ways to model performance, enhance decision-making, and drive improvement to support smarter, more sustainable operations. Among these innovations, Digital Twins (DTs) are quickly gaining attention – offering a way to move from simple monitoring to real-time optimisation.
The journey towards Digital Twins began with technologies like Building Information Modelling (BIM) and the Internet of Things (IoT). When combined, these two technologies set the stage for the development of Digital Twins. While BIM is powerful during design and construction, it lacks real-time feedback once the building is operational. IoT fills this gap, allowing digital models to stay synchronised with their physical counterparts.
What Is a Digital Twin?
Simply put, a Digital Twin connects a physical asset with its virtual representation through a two-way data flow, ensuring that both remain continuously updated. The concept first took off in aerospace and manufacturing, where real-time modelling helped improve performance and predict maintenance needs.
In the data centre industry, a Digital Twin is a 3D virtual replica of the facility that mirrors its real-world conditions in real time. It integrates previously separate systems – space, power, and cooling – into a single, synchronised platform. Any change made in the physical data centre is instantly reflected in the twin, creating a live simulation of operations.
How can Digital Twins be Leveraged for Data Centres
Unlike buildings that operate at full capacity from day one, data centres scale up over time, and this constant evolution means static models fall short. A DT addresses this by monitoring and adapting to every change automatically.
Once developed and calibrated to the actual facility, the twin can run advanced simulations, often using Computational Fluid Dynamics (CFD) to analyse airflow, cooling performance and energy use. This offers a level of insight that goes far beyond traditional monitoring tools like DCIM, helping operators make informed decisions before making physical changes.
Importantly, DTs don’t replace people or existing management systems – they complement them. They act as an intelligent layer on top of operations, offering advisory and optimisation functions that support rather than substitute human expertise.
To integrate a DT effectively, operators first need an accurate digital model created by engineering experts, calibrated with real data from the site. Teams must then be trained to use and interpret the insights, integrating the twin with tools already in place such as DCIM or CMDB. The goal isn’t to overhaul existing operations but to enhance them – providing a platform where decisions can be validated virtually before implementation.
From Design to Daily Operations
In the design and construction stages, a DT can test multiple scenarios to identify the most efficient and resilient layouts. This proactive approach helps reduce risk, optimise cooling design, cut capital costs and support sustainable growth. It also creates a shared workspace for stakeholders, improving communication and reducing lost time.
During operations, the benefits are even more pronounced. Real-time sensor data integrated into CFD simulations allows the twin to display live readings of airflow, power, temperature, humidity and more. This enables operators to detect inefficiencies, reduce hotspots, and optimise cooling, all while maintaining uptime and cutting energy consumption.
Through scenario planning, data centre managers can model potential expansions, simulate power and cooling needs, or test disaster recovery strategies without any physical risk. The twin can even simulate the impact of future IT loads, helping to balance capacity, plan upgrades, and maintain sustainability goals.
DTs provide visibility into how each component interacts – from server racks to cooling systems – allowing for data-driven adjustments that enhance performance and reduce costs. By detecting anomalies early and modelling preventive actions, they support a shift from reactive to predictive maintenance, extending equipment lifespan and reducing downtime risk.
The result is a more cost-efficient, resilient, and sustainable operation. Optimising airflow and temperature distribution alone can cut energy use by 20–30%, directly supporting corporate sustainability targets and reducing carbon footprint.
Challenges Along the Way
Despite their advantages, implementing DTs isn’t without challenges. Data security, privacy, and cybersecurity remain major concerns, given the sensitive information involved.
There’s also the initial and ongoing costs – from installing sensors and IT infrastructure to ongoing software maintenance and computational requirements. Change management is another significant challenge where teams need training and time to adapt to new workflows and tools. Finally, data quality is crucial. Since DTs rely on accurate, real-time inputs, any gaps in data can lead to unreliable outcomes.
That said, these challenges are outweighed by the potential advantages. The technology directly addresses some of the industry’s biggest pain points: downtime, inefficiency, and sustainability.
As adoption grows, one thing becomes clear: the road to optimisation starts with strong operations. Once that foundation is in place, DTs can offer the next step – transforming the way data centres are managed, maintained, and modernised.
Strong operations are the foundation of every high-performing data centre. At VIPA Digital, we help data centres achieve operational excellence through proven processes, ISO-aligned policies, and ready-to-use playbooks, everything needed to run facilities efficiently, safely, and to the highest standards.