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By Matthias Gromann

Infrastructures have become so complex that many organizations fall short when it comes to planning, implementation, and operation. Without the right tools in place, confusion sets in. Where is this cable route? Which ports are occupied? Which infrastructure elements are mission-critical? Are they redundant and is high availability for crucial connections ensured? If you’ve found your team asking these questions, a digital twin can help.

Digital twin
(Source: Adobe Stock by photon_photo)

A digital twin of IT, telecommunications, and data center infrastructure ensures data quality, enables changes to be properly planned and implemented, and allows potential disruptions to be identified quickly. When integrated with a building management system (BMS) for an intelligent overlap and mutual data exchange, an organization can successfully and cost-effectively master the challenges of operating corporate campus structures with multiple buildings — both from the facility management perspective as well as from the complex viewpoint of IT infrastructure and communication network services and lifecycle management. Such an approach allows for overcoming team silo structures by fostering collaboration while at the same time catering for the functional needs of all involved experts. However, there are a few best practices to follow to ensure success. Otherwise, the digital twin can quickly take on a life of its own.

Let’s dive in deeper.

What Is A Digital Twin?

A digital twin is, by definition, a digital replication of “something.” Digital twins can take many forms and replicate different things such as an organization, a building, a city, a product, a process, and of course production machinery in a manufacturing facility. Since IT infrastructure is becoming more and more an essential part of manufacturing products and providing services, data centers, and networks of large corporations, colocators and telecommunications providers are natural candidates for a digital twin.

Although a digital twin is based on data about the infrastructure, usually in the form of documentation, there is still many missing pieces to the puzzle. A table in which all the components in the infrastructure are neatly listed, for example, is far from being “real” documentation — let alone the basis for a digital twin. This is because a table or even a drawing is unable to depict complex logical and functional relationships. If this “what happens if” knowledge regarding object dependencies is missing, simulations cannot be created.

Needless to say, data quality is crucial when working with a digital twin. Typically, professional documentation tools are based on an automatically updating next-generation CMDB (Configuration Management Database) and are capable of mapping all levels of an infrastructure such as buildings and locations, physical components, logical and virtual devices, networks and connections, and applications and services. They allow content from distributed/specialized databases to be consolidated, cross-silo dependencies to be displayed, and data to be merged into a “single point of truth.”

The aim of the digital twin
is to holistically display
the actual condition of the object it is replicating and to make
any need for change or optimization opportunities visible.
It acts as a mirror to simulate and predict the behavior of its
real-world counterpart.


Yet, since infrastructures are dynamic and subject to constant change, documentation quickly becomes outdated. This is where the crux lies. The aim of the digital twin is to holistically display the actual condition of the object it is replicating and to make any need for change or optimization opportunities visible. It acts as a mirror to simulate and predict the behavior of its real-world counterpart. Therefore, the digital twin must reflect reality, in real-time. In order for this to succeed, the so-called closed-loop principle must always be observed. The “closed loop” is a closed cycle from planning to actual execution to return to the digital twin. The cycle is only closed when, for example, the resources that have been put into operation or are in use are compared with the originally planned status and any data discrepancies have been eliminated. This is the only way to confirm that the next planning cycle is based on verified and accurate data, and to ensure that won’t be any surprises awaiting the technician when new components are being installed on site.

Applications Of A Digital Twin

A digital twin replicates and visualizes the documented objects as either georeferenced, schematic, tabular, or graphic 3D representations of all relevant infrastructure and resource details. Certain functionalities are required for this, some of which may already be included in your documentation solution, such as geo maps, 3D animations, analysis, and simulation. Using these functionalities, representations can be created that realistically depict complex infrastructures as well as calculate and depict future scenarios, changes, planning, capacities, etc.

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