The role of facilities management is changing, with building owners increasingly expecting facilities management teams to be stakeholders and collaborators for business growth. The focus is shifting to highly efficient operations and an elevated occupant experience, with teams being expected to extend their roles as smart solution providers.
The available technology in the market currently for facilities management is standalone software, but to become value-driven players and stay relevant to changing customer expectations, teams need technology that unifies siloed building automation systems, resolves critical issues, and enables the effective use of existing data.
Buildings today have huge amounts of valuable accrued data on energy, assets and people that can be put to work. With AI and predictive analytics coming into its own, the need of the hour is to use data insights that bring together operations, maintenance and sustainability for smart operations, everyday sustainability performance intelligence, and occupant engagement and productivity.
Today, the built environment requires assembly-line style systems to operate large portfolios of buildings at the highest efficiency level. The Internet of Things and machine learning are at the heart of the technology that will enable efficiencies of scale in facilities management. IoT, as a technology stack, reuses existing siloed investment in buildings like automation systems, fire safety, power systems, security systems etc. Machine learning multiplies the value of data by removing manual work and bringing in data-driven intelligence.
In a high cost, high expenditure and heavy maintenance industry, facilities management teams that use machine learning can switch up their role from service providers to value-added partners and show clear benefits to businesses by delivering sustainable facilities management solutions. Predictive rather than reactive asset management is critical to providing an elevated occupant experience.
Facilities managers spend 30% more on energy costs for a building that is not benchmarked and 15% more per square foot every year on maintenance expenses as a direct result of inefficiencies. An IoT-driven sustainability management solution that derives real-time information about buildings using available data is key to bringing in predictive energy efficiency.