By James Massey, Managing Director of Facilities Management, MRI Software
Bruised and battered coming out of the pandemic, anyone working in the retail sector continues to face severe economic challenges as the cost-of-living crisis and rising energy costs take a devastating toll on disposable income. The upshot is that retailers and commercial landlords cannot afford to make bad decisions – especially when analysing their business on a location-to-location basis.
The good news is that, as many brace for further economic turbulence in 2023, they can use Artificial Intelligence (AI)-driven technologies to better grasp their situations and gain actionable insights. For retailers, landlords and the facilities management teams supporting them, energy management software is a crucial tool for better understanding and controlling costs.
Tools that capture, measure, and analyse energy usage through AI and machine learning make the task of turning sustainability and energy efficiency goals into actual actions much more manageable, compiling millions of data points into a user-friendly application for further analysis and reporting. They can also employ AI-based analytics to more easily make use of complex and voluminous data. Energy management technology helps them to set energy KPIs and track them in real time through dashboards and automated reports.
Having set their KPIs and energy trackers, managers can identify and combat the most common and often unnoticed energy wasters across their properties. These solutions enable them to reduce their carbon footprint, improve efficiency and cut costs around their operational, HVAC, lighting and IT systems. It is a win-win as they not only mitigate spiralling energy costs but emerge as better corporate citizens.
Alongside AI-powered energy management, footfall tracking is another vital predictor of business performance for both landlords and retailers. Technology tools that yield precise footfall data help businesses make faster, more informed decisions that optimise operations across their property portfolios to boost margins.
Footfall tech tools – which can produce real-time data – enable retailers and landlords to understand performance across individual locations by capturing visitor behaviour, such as movement and dwell time. They provide a wealth of information that empowers retailers to boost shopper traffic and engagement while improving capture and conversation rates.
For shopping centre operators and other retail landlords, this type of data allows them to understand the impact of the programming they do at retail centres to attract and retain tenants – like Christmas light festivals, other seasonal activities, or other experiential opportunities linked to annual events such Fashion Week.
Combining footfall and energy use data with sales figures sheds light on the viability of individual stores – helping retailers to decide on actions such as whether they can and should look to use break clauses or renegotiate rents. Tapping into the same data allows landlords to anticipate what retail tenants will do and how they should negotiate with them.
Utilising machine learning and AI throughout this process makes something that was once impossible to do manually now an essential part of retail decision-making. With further economic challenges facing the retail sector in 2023, adopting a range of AI-driven analysis technologies has become increasingly critical to better address the needs of retailers, their landlords and the FM teams tasked with handling major cost contributors such as energy management.
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