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Every day, the buildings we shop in, work in, or socialise in make a difference in our lives.

It comes as no surprise that we spend 90% of our time indoors. However, the very foundation of how our buildings work is dependent on the safety, security, and well-being of those who use them.

Since the beginning of 2020, the way we use our offices has changed dramatically. We’ve become more adaptable, often only coming into the office when there’s a clear purpose and benefit to doing so. The building itself is not different; however, we must now develop the way our buildings operate to meet our new requirements. However, they are not performing as well as they should.

According to McKinsey Global Institute research, data and analytics could create value worth $9.5 trillion to $15.4 trillion per year if embedded at scale, demonstrating the true impact that silos are holding across industries. As a result, we must begin to value and comprehend our data. Only then will we be able to improve occupant safety and comfort while also saving money and meeting sustainability goals.

The journey to data value

When we have data we can’t understand or contextualise, we may as well have no data at all. Siloed data is dumbing down our smart buildings, but the challenge is that we need to manage the combination of operating technology, bringing together multiple data sources and different systems together to drive value. Right now, the data from each of these point solutions is siloed and disconnected. This is preventing building managers, developers, and owners from seeing the bigger picture, limiting them to small, incremental changes that don’t help realise the full potential of their investment in smart.

From here, it is then possible to move up the data value ladder, unlocking the true benefits of ‘smart’. On the surface level, data can be descriptive, telling us what is happening now. This insight then informs how we move up the levels; diagnostic, predictive, prescriptive and finally, the zenith of cognitive data where AI and automation come into their own.

There needs to be a link between the building and the data, as it provides invaluable insights into how the building is used. You can take a snapshot of the energy in a building and understand its performance, but this won’t help until you have the context of other data, and how that influences the building as well – it’s all interlinked. Understanding siloed data as a connected network means we can approach each building differently, to make recommendations that are more energy efficient and cost saving. By connecting the siloes, we can enrich the data to provide the diagnostic data as well as the descriptive data that will help climb the stairway to value.

What’s more, many buildings house multiple occupants, with various needs and expectations. This is especially true as we are working in a new hybrid world, with flexibility as the focus for many. Needs will vary from building to building, and data averages in the industry aren’t applicable because it’s about the individual building’s requirements. However, some things will remain consistent: the need to drive down energy usage, move towards carbon net zero, improve indoor air quality and provide an impressive and comfortable experience for occupants. All of this is harder to achieve when a building’s data is sitting in siloes, underutilised and unable to provide a 360-degree view of what a building can really offer.

Using technology to increase the potential

To reach this potential, we have to get deep below the surface level of smart technologies to unlock the insights they generate. This happens when we connect smart technology systems together to create an ecosystem or platform for smart solutions, looking at the bigger picture. The data and insights this creates can then be analysed to make vast improvements across a building, and even the whole enterprise.

To make this a reality, the data needs to be connected and easily accessible in the cloud. Then decision makers can analyse the data in its entirety and identify areas of improvement. They can focus this analysis on processes such as maintenance, energy savings and sustainable development – wherever needs attention at that time. Then, they can pinpoint the smart technologies that can make these adjustments autonomously and improve the experience that tenants receive. From these foundations, building and office decision-makers can create something which is truly smart.

Once the building data is embedded and utilises technologies such as Artificial Intelligence (AI) and Machine Learning (ML), we can truly reap the rewards and increase occupant safety and comfort, while saving on costs and achieving sustainability targets.

Data measurement, tracking, and action

Our buildings can make predictions with smart algorithms by utilising technology such as data and tracking software with AI and intuitive dashboards that monitor indoor air quality and energy consumption.

Algorithms predict load profiles as well as plant and equipment-level energy performance under various operating conditions based on historical patterns. Every major piece of equipment, such as chillers, boilers, pumps, cooling towers, and energy storage, has an energy model that predicts how the equipment will perform under various operating conditions. Every 10-15 minutes, the optimisation algorithms run to make ‘dispatch decisions.’ It determines which equipment to turn on or off, as well as which system level setpoints to use, for a wide range of cooling, heating, and power generation systems. This continuously reduces costs and energy consumption.

Historically, analytics and AI solutions have focused on achieving a single goal at a time, whether it is clean air, energy efficiency, safety, or even comfort and experience. Measuring, tracking, and acting on data, on the other hand, gives us control over every single goal we want to achieve.

Democratising data during economic insecurity

Because the UK is experiencing ongoing economic insecurity, businesses are doing everything possible to keep costs low and returns on investment high. However, we must keep in mind that lower costs, energy efficiency, and clean air can all coexist. With AI, machine learning, and democratised data, we can begin to see changes in our buildings that will improve our future.