Cleaning companies are increasingly adapting data-driven practices, not just to follow a trend but as a necessity to increase their operational efficiency, reduce their costs, and improve their service quality.
Protecting the indoor environment and human health is critical to the cleaning industry’s effectiveness. We no longer simply sell labor or spend the bulk of our time emphasizing appearance and creating an illusion of cleanliness. We focus on extracting and removing contaminants, and on using data to measure and improve cleaning systems and processes.
Quality assurance is a critical aspect of any cleaning operation. Traditional methods of inspection and feedback can be subjective and inconsistent. Data analytics can provide a more objective and reliable approach to verifying cleanliness.
Data-driven cleaning involves collecting, analyzing, and using data to make informed decisions about cleaning activities. By tracking cleaning metrics such as frequency, duration, and
available resources, cleaning professionals can optimize their processes.
Understanding performance through measurement
Performance is integral to success and the only way to document effective performance is to measure it.
Measurement is the first step that leads to consistency and improvement. If you can’t measure something, you can’t understand it. If you can’t understand it, then you can’t control it. If
you can’t control it, you can’t improve it.
Identifying measurable factors will maximize your ability to protect people, their property, and the indoor environment. Cleaning operations are dirty, mechanical, and can temporarily create
conditions that are hazardous for those who use the indoor environment and for those who clean it. Measuring the effectiveness of your equipment, the amount of cleaning chemicals you use, and
whether you use these chemicals properly will assist you in reaching your cleaning goals.
Cleaning professionals at a university with 88,000 students and 17,000 staff, participating in the ISSA Making Safer Choices program—a partnership that increases the knowledge, demand, and use of the U.S. Environmental Protection Agency’s Safer Choice labeled products—implemented a data-driven approach to measure their water and cleaning chemical usage. By analyzing data on water consumption, chemical usage, and cleaning outcomes, they identified opportunities to optimize cleaning procedures. The university also introduced microfiber cloths to its cleaning routine and installed low-flow water fixtures in its facilities, resulting in a 30% reduction in water usage and a 20% decrease in chemical consumption. This data-driven sustainability initiative not only
reduced environmental impact but also saved the university substantial costs.
Setting up benchmarks for comparison
After determining which factors to measure, be sure to identify key performance indicators (KPIs) that are relevant to your cleaning activities. Next, you need to implement tools for data collection
and establish a routine for analyzing the data. Fortunately, help is available for those tasks.
The effective utilization of equipment, tools, and technology can help increase your cleaning productivity. The eighth edition of ISSA’s Cleaning Times & Tasks focuses on five components: task,
tool, time, total units, and training. You can use these components as a benchmark to compare how you clean to an industry standard; their purpose is to act as a guide for estimating labor
costs and cleaning expenses.
By calculating cleaning times, you can identify how long it will take your staff to finish specific tasks, such as how many minutes it would take to mop 2,700 square feet of vinyl flooring with a
14-inch flat mop and dual-chamber bucket.
Data collection tools are another helpful resource. They provide real-time data to help facility managers and cleaning professionals pinpoint the specific cleaning needs in their facilities, enabling your crew to work smarter.
Examining real-life success stories
The GBAC STARTM program, which offers facilities comprehensive training in cleaning, disinfection, and infectious disease prevention strategies, recommends the use of data-collecting
technology. Several GBAC STAR-accredited facilities have reported success in using data to improve their cleaning results.
For example, a large office building in New York City with 470 toilets to clean daily implemented sensors to track restroom usage and cleanliness. The data revealed patterns of high- and low-traffic periods, allowing the cleaning staff to adjust their schedules for more frequent cleaning during high-traffic periods. This adjustment created a noticeable improvement in restroom cleanliness and increased satisfaction from building occupants.
A leading international hotel chain with 1,350 hotels created a data-driven quality assurance program using handheld devices to record cleaning performance metrics such as time spent cleaning each room, adherence to cleaning protocols, and guest satisfaction scores. After analyzing this data, the hotel chain identified areas where staff were not meeting cleaning standards. The chain set up targeted training programs in these problem areas, resulted in improved cleaning quality and guest satisfaction ratings.
An international airport with five terminals and 130 boarding gates that handles 62 million passengers a year used data analytics to optimize its cleaning schedule. By analyzing data on passenger movement and floor space usage, the cleaning staff could ensure that areas with the highest traffic were prioritized in the cleaning schedule. This not only improved the airport’s cleanliness but also enhanced passenger satisfaction and safety.
Optimizing data-driven cleaning through education
Data-driven cleaning is transforming the industry. ISSA has merged elements of the GBAC STAR Service accreditation criteria into the ISSA Cleaning Industry Management Standard (CIMS). The
result—ISSA CIMS advanced by GBAC—outlines the primary characteristics of a successful, quality cleaning organization, with a renewed emphasis on maintaining hygienic environments through
cleaning, disinfection, and infection prevention protocols. CIMS Advanced by GBAC, describes the procedures and principles to consider in designing and implementing quality management programs for cleaning, including:
- Ensuring all stakeholders understand and agree on the expectations and deliverables for each site.
- Developing and documenting a quality plan that includes processes for monitoring performance, taking corrective actions, and ensuring continuous improvement.
- Using tools and methods to measure the quality of cleaning services. Examples of monitoring tools can be found within ISSA’s Clean Standard and GBAC’s Process Verification and Auditing Tools for the Cleaning Industry Guide.
- Committing to continuous improvement by regularly reviewing performance data, implementing corrective actions, and updating processes to meet evolving customer needs and industry standards.
