TECHNOLOGY & DATA
A Smart Building Transformation
Simon Wisdom, VP of Sales and Marketing, SoftBank Robotics EMEA, discusses leveraging data and technology for cleaning operations.
Facilities management (FM) has a somewhat underserved reputation as a technology laggard. While cost pressures and a long-standing short-termism
defined by frequent contract churn create challenges, the industry is beginning to take advantage of smart building and automation-enabling technologies.
This is especially true in cleaning services, an area of facilities that has struggled historically to demonstrate return on investment. Today, the use of sensors and the integration of advanced technology such as collaborative robotics are transforming not only how cleaning services are delivered, but also measured and improved. Let me explain how.
The old days
Traditionally, FM companies have relied on limited metrics such as time and attendance, supervision, experience comparison, P&L and perception-based standards to gauge their cleaning effectiveness. This narrow focus has led to a critical oversight: the failure to measure the cleaner’s performance during their work, leading to inefficiencies and time loss but also negating the ability to provide a verifiable proof of clean. Without a detailed understanding of how cleaners perform their tasks, there is no way to identify inefficiencies or areas where time is being wasted.
What’s more, relying on perception-based standards – i.e. the manager’s watchful eye – is prone to human bias or error. The lack of data makes it nearly impossible to implement demonstrable process improvements.
Making changes
The answer lies in leveraging advanced technology to help cleaning teams and clients gather comprehensive, targeted
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data on cleaning activities. Our approach, in partnership with our customers, focuses on capturing a wealth of information in several ways, including Internet of Things (IoT) sensors. How this can work depends on environmental needs and conditions.
Strategically placing sensors around the building allows cleaning teams to monitor cleaning activities wherever they take place. These sensors can track various aspects, such as the movement of both cleaners and building occupants, time spent cleaning in different areas, and usage of cleaning resources. The data can provide insights, identifying patterns and focusing on both the efficiency and the quality of the service.
From here, cleaning teams can work with their technology partners to make recommendations insights derived from the data. This can include changes in cleaner deployment, improved resource management and optimised cleaning schedules.
Transformative benefits
Conventional frequency-based cleaning schedules are inefficient, relying on estimations rather than actual needs, and this increases the likelihood of either under or over- cleaning. Typically, this results in a standard specification, normally specified by the client based on their experience and requirement to create a benchmark. For example, a schedule that includes daily toilet cleans and five daily floor sweeps is created so that the cleaning is measured in a quantifiable way. As the usage of a building or environment is not static and the estimation is never accurate, this leads to too much cleaning to reduce risk.
Monitoring factors such as footfall allows teams to focus their efforts on high-traffic areas. This not only improves the overall quality of the service but also boosts job satisfaction for cleaning staff as they can see the tangible impact of
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