Digital Twin Analytics

By Dave Clifton
Content Strategist
SpaceIQ

As digital twins take their place in smart offices, at the center of the IoT and other networked systems, they’re becoming a source of truth for facility insights. Their ability to contextualize data within a physical model makes digital twin analytics a new standard for decision-making about how to coordinate and operate the workplace.

The chief obstacle companies have with digital twins is establishing them—building them out to create context for IoT data. Instead, many companies are only beginning to explore IoT and currently operate a growing network of sensors and beacons that stream data to various places. An IWMS takes them one step closer to wrangling and using that data, but it’s not until they develop a digital twin does it gain context. Only a digital twin can give data the context it needs to provide analytical insight into potential workplace optimizations.

Here’s a look at why digital twins are so central and important to smart offices—and how to create them within the context of these environments.

What is the digital twin concept?

Digital twin software offers a virtual representation of a physical asset—in this case, the workplace. The purpose of a digital twin is to pair quantifiable information within the context of the physical parameters of the workplace, usually through information sources like user input, IoT sensors, and other intelligent systems.

Digital twin concepts provide insight where it’s not immediately apparent. For example, you might know that a conference room accommodates five people. A motion sensor in this room generates a constant stream of on/off data to determine whether it’s occupied. Moreover, a room booking system provides booking data. All these sources of data feed into the digital twin where they’re juxtaposed and contextualized into actionable insights.

This example is just a small glimpse into the practicality and power of a digital twin. Its power is amplified even more by the fact that digital twin analytics provide insight over time. More than a snapshot of the workplace, digital twins allow you to observe it as an ecosystem.

Where does digital twin data come from?

As mentioned, most digital twins are slow to form because companies are still exploring their foundation: the Internet of Things (IoT). IoT sensors and beacons, and the data they provide, are a primary source of data truth for digital twins. But they’re not the only sources of data. Digital twins benefit from numerous inputs, including:

• IoT sensors and beacons that stream data 24/7
• Manual inputs by facility managers and other stakeholders
• Integrations with other software, which share data with the twin
• Static lookup information that provides context for insights

The more sources of data available to the digital twin, the more context it has in generating its own analytics. Digital twin data itself comes from processing these many sources of data into trends. Typically, that data manifests in a dashboard where it’s more easily understood—such as within an IWMS. Along the way, the digital twin cleans, organizes, and contextualizes data to make it relevant, actionable, and useful.

How digital twin and analytics improve operations

Without digital insights about a workplace, all you see is all there is—meaning you can’t understand when, how, or why people use the workplace fully. Digital twins process raw data about the workplace ecosystem into easy-to-understand insights. They bridge the gap between the parameters you know and the variables you don’t know.

For example, you might know that a conference room’s occupancy is five people, and you might see people in there frequently, which leads you to believe it’s a well-used space. But a digital twin might tell you otherwise. Via aggregated data, it might tell you that it’s most often used by groups of three or fewer. Of the eight hours a day the room is available, it might only achieve a 56% utilization rate—a lower utilization rate than similar spaces in different areas of the building.

These contextual analytics make it possible for facilities managers to improve the workplace based on evidence, rather than intuition. There’s more to workplace operations than meets the eye. Digital twins and the information that contributes to them help you gain a clearer understanding of everything you might be missing. Acting on that information can take the workplace in a new, more efficient, more productive direction, one change at a time.

Apply the insights of a digital twin

Having data and using data are two very different things. A well-orchestrated digital twin is important; using the insights it provides is essential in optimizing the workplace. Companies need to first focus on tying their growing IoT network into a digital twin foundation. Then, they need to deploy an IWMS to glean trend data and insights. From there, it’s a matter of planning and taking action.

Because a digital twin quantifies the physical workplace, it’s instrumental in helping facility managers work backward from a problem. Digital twin analytics provide this same value over time: they show trends and interactions within a static environment. Capitalizing on these insights is the key to making smarter decisions in a smarter workplace—one that is always in flux.

Keep reading: Digital Twins: A Revolution in Workplace Management