When Grosvenor Group needed to optimize energy consumption and improve sustainability in their London estates, they turned to Demand Logic to help. The solution was to deploy tiny sensors to measure the temperature at critical points in each building to get detailed insights on how to lower energy consumption across their portfolio.
Grosvenor Group Limited, an international property company focused on the management and investments of real estate, has a large number of properties in London’s West End. Although they were already working with Demand Logic to receive operational data from their larger commercial buildings, their smaller buildings didn't have the equipment or Building Management System (BMS) software to report data from meters and hot water boilers.
The west side of London is among the most expensive areas of London, and renters have high expectations when it comes to comfort. Even though the buildings are from the Edwardian period, tenants expect high energy efficiency and comfortable temperatures inside. The Grosvenor Group was experiencing challenges with both thermal comfort and energy data collection in certain buildings: these smaller, existing stock buildings present a challenge for many real estate companies when it comes to meeting net-zero and ESG objectives, where the expensive retro-fits with 'trophy assets' are not an option.
Grosvenor Group wanted to get more data from these buildings and implement a more condition-based maintenance approach, so they asked Demand Logic to extend their existing data insight across their wider portfolio. If property managers could access energy usage and ambient temperature levels across the estate, they could pinpoint sites requiring attention from their Facilities Management and Maintenance teams. They decided to implement this new system in all of their commercial buildings, even those with no BMS or existing data sets.
Demand Logic is a software company focused on making the management of buildings easier by providing actionable intelligence to property managers and building contractors. They offer companies a Performance Scorecard, which provides a helicopter view of performance across a real-estate portfolio and assesses overall performance when it comes to energy efficiency, occupier comfort, and mechanical effectiveness. Grosvenor Group was already using this platform to gather data from its larger buildings and to present the analytics to maintenance teams, facilities managers, and sustainability managers. The next step was to start collecting data from smaller properties as well (buildings as small as 2,000 square feet / 186 square meters).
Demand Logic uses wireless temperature sensors from Disruptive Technologies to get data from hot water boilers and radiators, and to monitor the temperature of the office spaces. They then provide Grosvenor Group with an overview of energy usage and identify problematic areas and potential challenges a contractor can follow up on. They are currently collecting actionable data from around 40 buildings using 250 wireless temperature sensors from Disruptive Technologies.
Grosvenor Group now has a simple way to collect insights from all building types using the same methodology, enabling like-for-like analysis and portfolio benchmarking. Both maintenance engineers and portfolio managers use the platform, and the analytics are adjusted to their needs.
Demand Logic focuses on providing insights into three different areas:
The Grosvenor Group is committed to addressing their social, commercial, and environmental impact, and they were able to use the insights captured in their sustainability reporting. Understanding their building portfolio's energy usage is crucial to achieving their sustainability goals and an important topic for their tenants.
This project's primary, long-term aim is to enhance operational efficiency across Grosvenor Group's entire real estate portfolio. They recognize the vital role of continuous, data-driven maintenance planning and see that having a unified platform providing actionable insights supports their sustainability initiatives and broader ESG objectives.
Demand Logic started to install the Disruptive Technologies sensors at Grosvenor Group in November 2022. They have seen over 400 Building Performance Actions raised since then, providing valuable suggestions for how to improve energy efficiency, occupier comfort, and mechanical effectiveness. The maintenance teams can then proactively address them in line with their condition-based maintenance goals. The group has reduced energy consumption by 15-20% so far, making the project highly profitable, in addition to addressing tenant needs and sustainability.
Demand Logic could only succeed with this project by using a temperature sensor that fulfilled all their requirements:
Tiny and discrete – Sensors installed on office walls need to be unobtrusive and discrete.
Easy to integrate – Simple API integration and insights made available to several user groups are essential.
Wireless and easy-to-install – Wireless, peel-and-stick sensors that don't need pairing are very easy to install, keeping the deployment cost down to a minimum.
Scalable – The ability to collect reliable data from many rooms across multiple floors in several buildings, and make it available via one platform is important.
Long-Lasting – Battery-powered sensors that last for up to 15 years require no maintenance, which is necessary for a low cost of ownership.
The Disruptive Technologies sensors enabled them to deliver their solution into buildings where it was previously too difficult or uneconomical to capture insights on operational performance. Here's what Nick Smith, the Chief Operating Officer at Demand Logic had to say:
Founded in 2013, Disruptive Technologies (DT) is the Norwegian developer of the world’s smallest wireless sensors and an award-winning innovator in the IoT market. Our small, efficient, powerful, and adaptable wireless sensors are the best in the world and designed to reach an ever greater number of operational components, making buildings intelligent and sustainable in minutes.
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