“Growing and operating our business in a sustainable way is essential to our long-term success. We are committed to reducing our energy and carbon footprint as we make the transition to a net zero business. Utopi is allowing us to meet our ESG targets.”Bay Downing, Investment Director (Downing and Downing Students)
Our Client.
Known for building extraordinary places for extraordinary student lives, it’s no surprise Downing Students are a brand who truly care about their residents. With PBSA assets across the UK, they are on a mission to build and operate sustainable spaces for this generation, and the next.
The Challenge.
With Downing Students on a mission to reduce their environmental footprint, they tasked Utopi with helping reduce the energy consumption of their UK PBSA portfolio. Starting with two assets that had excessive temperatures, they wanted to test our Smart Temperature Control capabilities, and see if they could vastly reduce their energy waste.
Site teams were aware residents were using external heaters but had no way of monitoring or measuring the outliers or reducing their energy consumption. Using Utopi’s intuitive Smart TRVs solution, the mission was to increase energy controls through the latter end of a heating season Feb – May 2024.
The Utopi Solution.
With Utopi’s dedication to making data acquisition, analysis and action simple, it made sense to work alongside our expert team to see why we’re award winning. Data is simply the beginning, then comes action and positive change.
Our first port of call was ensuring Smart TRVs were installed at the first two PBSA sites, then when installed, heating controls were set via the Utopi Platform to a maximum temperature of 23°C. With automated ESG Explorer reports being sent to site managers weekly for action to be taken, and ongoing monitoring from the Utopi Impact team, Downing would also benefit from proactive Utopi assistance in helping them reduce the energy waste in unoccupied spaces.
Using the Utopi Heatmap and outlier reports, our Impact team could ensure higher than average temperatures were flagged, and data-driven action could be taken to reduce energy waste.
Impact.
Within just one month, energy consumption was reducing and as a result, utility costs were being avoided.