It’s not always easy being green, but it is becoming increasingly essential for businesses.
Environmental sustainability has emerged as a vital corporate imperative as businesses seek to do their part in moving towards zero carbon goals and saving the planet. What’s more, cutting gas and electricity consumption has become a critical business objective too, as soaring energy costs have hit bottom lines. The question is how.
Many large organisations operating across a significant number of properties struggle to gather the information they need to fully understand when, where, and how they are using energy – and where wastage is occurring. Capturing and then being able to analyse the vast volumes of data involved can be a complex endeavour. In fact, over half of the companies we have worked with to help better manage their energy consumption initially say they don’t have easy access to all the information they need.
The reason for most is the scale and complexity of the task facing them. For example, an organisation operating 100 buildings with, on average, 10 energy metres per site could create over 17.5 million records per year. It would then have to process all that data to get a complete and accurate picture of its energy use and spending. And an even larger global enterprise might operate, for example, 55,000 properties worldwide, making the scope of processing and absorbing the data exponentially more complex.
There is, however, a way to get at these sorts of volumes of data today. Deploying Artificial Intelligence (AI)-driven software tools that capture, measure, and analyse massive amounts of energy data makes generating actionable insights that enable businesses to significantly boost energy efficiency very achievable. Utilising machine learning capabilities, these tools make it possible for organisations to make sustainability and cost-reduction goals a reality.
Getting the full picture
To harness the necessary energy consumption data generated across a broad corporate property portfolio, a company needs to first identify how to capture the information. In any retail store, office block, hotel, shopping centre, medical facility, or any other commercial building, sensors can be – and in many cases already have been – deployed to track and manage footfall, air quality, desk occupancy, meeting room use, system logins, and other everyday aspects of the building use.
To then get a grip on its energy usage, an organisation needs to bring its data all together in one place. The solution for many businesses is to automate the collection of all the applicable building data through an AI-powered application that then enables analysis and reporting.
AI technology is essential to making sense of the massive amounts of complex data that needs to be processed in a timely way. The result is organisations gain complete visibility of power consumption. They can then identify common, often unnoticed areas of energy wastage across their property portfolios and take action on those.
Achieving real results
It has become clear that organisations of all types simply cannot afford to ignore energy wastage, and their management boards are taking notice – both for the cost and the corporate reasonability implications.
An increasing number of UK organisations see managing their energy consumption as a major concern. Nearly two-thirds of British businesses (64%) say energy is now their top business risk, with 91% saying their board is concerned about how they are dealing with this issue, according to the npower Business Energy Tracker 2023.
Working to help organisations tackle energy inefficiency across a broad range of property portfolios, we are able to help them see the less obvious ways to boost energy efficiency – and sometimes even those staring them in the face. In one instance, analysis by a retailer identified that, in one of its stores, the escalators connecting four floors had not been turned off at any time for five years – not even overnight.
In another example, energy management technology-enabled Carlsberg UK to reduce power use in its brewing process by 10% – plus, it was able to cut its water consumption by 10% and its effluent costs by 16%. In a further instance, a leading European real estate and facilities management company, Apleona, deployed a centralised system to report on carbon emissions while identifying energy conservation measures – reducing, in a typical project, consumption by 25%.
The fact is, in all sorts of cases, AI-enabled energy management systems use data to uncover ways in which incremental improvements add up to major cost reductions. The average outcome is a 30% reduction in energy consumption.
Using AI to score green progress
AI is also increasingly playing a critical role in helping organisations to better position themselves to comply with sustainability standards across their lease and property portfolios.
Companies operating across large property portfolios know that manual ‘lease abstraction’ – extracting and making sense of immense data volumes from multiple, sometimes hundreds or even thousands of leases – can be an expensive process. Undertaking manual lease abstraction to access details on sustainability compliance for individual properties simply takes too many staff hours and takes too long to do to get the information companies need when they need it.
AI-driven contract intelligence solutions, however, make quick work of this sort of process by scanning and organising data from leases and other documents – which means it takes days, or even just hours, depending on the size of a company’s operation, to do what otherwise would take weeks or months.
For example, one managing agent handling over 2,000 leases was able to build a picture of environmental practice and compliance across all the properties it manages using an AI-powered contact intelligence solution. The company was able to benchmark its properties in areas such as energy rating and performance, waste handling and facilities, the use of sustainable materials, and other elements relating to environmentally friendly
The result of this sort of analysis is that organisations can quickly gather and evaluate information from hundreds or even thousands of contracts – each often hundreds of pages long – and use that information to create a ‘green scorecard’ for every property it manages. Having this information at its fingertips enables an organisation to address environmental sustainability standards as and when new lease negotiations come up to help it prepare to meet future environmental requirements.
A new strategic necessity
Energy management has emerged as a strategic issue for companies of all types and sizes – and if it is not a concern, it should be. Tapping AI capabilities and analytics tools just makes good business sense. Gaining a clearer picture of energy usage not only empowers an organisation to make smarter decisions but positions it to be a better corporate citizen.
About the Author
Richard Smith is Senior Director Energy Management Solutions at MRI Software. MRI Software is a leading provider of real estate software solutions that transform the way communities live, work and play. MRI’s comprehensive, flexible, open and connected platform empowers owners, operators and occupiers in commercial and residential property organizations to innovate in rapidly changing markets. MRI has been a trailblazer in the PropTech industry for over five decades, serving more than two million users worldwide.
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