Contract cleaning is an under-appreciated service. Without it, your workplace – whether it’s a corporate high-rise, a hospital or even a hotel — would be uninhabitable. Yet cleaners have long struggled to demonstrate the positive difference they make.
The reason for this is an inability to measure, quantify and, ultimately, prove how valuable the service is, both for the hygiene and effectiveness of a space and the bottom line.
Historically, cleaning has been labour-intensive and driven by unsophisticated specifications. Input-based contracts, the standard bearer for contract cleaning, measure only what goes into the service, such as the volume of labour used to complete tasks, the amount of time spent, and the quantity of the cleaning supplies. There is no consideration for challenges and outcomes unique to each site. This keeps everything static. It leaves little room to understand how effective cleaning services are, how they can be improved, and how they might be aligned to a business’s commercial, operational or strategic business goals.
The emergence of smart technology is changing all this. By capturing data from different sensors, measuring factors such as occupancy, cleanliness, and customer satisfaction, and putting these insights through AI-powered analytics platforms, cleaning teams can provide a site-specific and more efficient service. This represents a transformation into output-based cleaning, where businesses can work toward specific outcomes they desire, such as the level of cleanliness, passing inspections or even occupier satisfaction, and then identifying the steps and solutions needed to achieve these.
Application of this technology allows cleaning teams to focus work on necessary timings and optimise their specifications to avoid under or over-servicing. Traditional cleaning methods have set times and frequencies based on biases and guesswork. Often, this leads cleaning teams to clean with the same man-hours regardless of the number of facility users.
Imagine a washroom in a busy shopping centre which has thousands of people using the facilities throughout the week. The challenge is that occupancy will change day to day and even hour to hour. Weekends will be busy. Weekends before Christmas will be even busier. Then there’s the school holiday period to consider. There are other factors too. Is the washroom near the food court? Is there a busier washroom on the other end of the shopping centre near the entrance? Whatever the situation, sensors can help quantify when the washroom is busiest, allowing cleaning teams to go in more frequently during busy periods. It’s a waste of resources if cleaners are cleaning the washroom if nobody has used it.
What’s more, customers (often employees) have visibility of the cleaning operation’s effectiveness, providing them with peace of mind, an especially emotive factor following on from the safety concerns of the Covid-19 pandemic. On-demand is a powerful motivator for cleaning teams as it automates repetitive tasks, allowing cleaning team members to focus on more challenging and rewarding aspects of their job. Providing them with advanced tools and technology, such as robotics and AI-driven systems, not only enhances their efficiency and effectiveness but also gives them a sense of accomplishment and pride in their work.
This concept allows cleaning teams to focus work on necessary timings and optimise their specifications to avoid under or over-servicing. The model enables a dynamic, on-demand service based on factors such as the level of cleanliness, the number of users, and the satisfaction scores. The combination of historic and live data allows cleaning teams to change the frequency and depth of cleaning based on the latter factors. If a washroom is less busy, the cleaning scheduled can be adjusted, resulting in a reduced cost without compromising hygiene.
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