Introduction
Setting out to improve the way cleaning services use the digital tools available
nowadays, Deloitte has successfully piloted Smart Cleaning with their facility
management service provider and were on top of that able to optimize resources
used and time spent thus leading to cost savings.
Company Info
Deloitte
Deloitte is one of the Big Four global audit and consulting firms. They have implemented Locatee Analytics across their office buildings in Switzerland. Deloitte Switzerland has an office portfolio of 14,000 sqm for their 2,200 members of staff. They are highly invested in testing innovative real estate and facilities management practices and are showcasing them also in their consulting mandates.
Soobr
Soobr is a PropTech company based in Switzerland. Their platform and application allow for optimization and demand-driven planning and execution of cleaning tours based on data and artificial intelligence.
Summary
- Deloitte and their FM service provider set out to improve organization of cleaning
processes and communication with cleaning staff distributing work more
dynamically. - They have successfully piloted a new approach using the Soobr application that is
fed with real-time utilization data from Locatee Analytics. - Their main goal was to improve processes, evidence, and communication.
- At the same time they were able to optimize cleaning routines saving resources
and consequently cost. - All while maintaining a high cleaning standard to keep quality & hygiene
during the pandemic.
How it works?
Smart Cleaning
The Corporate Real Estate and Facility Management industry alike are oftentimes put on the spot for not being at the forefront of digitization and exploiting solutions on the market. Deloitte has proven the opposite with their Smart Cleaning project.
Their FM service provider felt there was a better way to organize cleaning schedules than by paper instructions. Namely, to distribute work more dynamically, setting task priorities based on utilization information and also including a feedback functionality to report on defects.
„Our service provider now has more detailed insight into cleaning performance, and can adapt to building utilization while improving job satisfaction for their staff – a win-win situation for all.”
Early on they had tested a new planning mode by combining Locatee’s utilization heat maps and information from sensor technology in the sanitary areas to count the number of door openings, but there was still a touchpoint missing to make that information easily available to cleaning staff on the ground.
Weekly pattern overview
showing average utilization for each working hour
Floor map view
on Locatee Analytics showing utilization of different zones
That’s how Soobr came into play.
The basic application is set up with space information derived from floor plans or Raumbücher (applicable in the DACH region) and the service-level agreements for cleaning. With that, cleaning routes can be planned and cleaning personnel will get their schedule when they start their shift on a tablet app.
But in order to take it one step further and unlock the full optimization, potential usage data is required. Deloitte was able to take the utilization information for different office zones from Locatee Analytics. For enclosed rooms, utilization information was integrated into the Locatee platform from presence detection sensors that regulate air quality or taken directly from sanitary area door sensors.
off as done once they are finished.
That way, it is also possible to report on the cleaning carried out without having to fill out paper forms. Additionally in the same interface, cleaning personnel can report on necessary maintenance, such as broken light bulbs, stains on the carpet, and anything else they see, with icon buttons, thus avoiding any language barriers.
Soobr App Dashboard
The information is visible for Deloitte at any time on live dashboards. Their FM service provider also shares monthly reports on cleaning tours, duration, number of defects and the washroom usage for instance. This increased the transparency of a service that usually takes place out of office hours.
Benefits Highlights
The Results
Evidence & Reporting
Besides the clear evidence for Deloitte as the customer, their FM service provider benefits from more detailed insights into cleaning performance. When reviewing cleaning routines, it became clear that repetitive, time-consuming tasks, for instance long floor areas, could be better managed by a robot. They can also plan more flexibly, for instance when reassigning tours when a member of staff is unavailable.
Cleaning Staff Satisfaction
A very compelling outcome is that employee satisfaction with cleaning staff has increased as people felt their jobs were appreciated and upgraded by the digitization as well as outcomes clearly measured. Plus, the language barrier has been removed with intuitive visualizations and a selection of supported languages. Consequently, there is very small fluctuations in staff.
„Adding another use case for the utilization data that we’re already
collecting with Locatee was a natural next step and the collaboration with Soobr stepping up our building operations.”
Taking the leap and moving to a smarter approach to cleaning has paid off for all collaboration partners. Deloitte is showcasing the service model and collaboration with peers and clients as a best practice and is also including learnings in their consulting mandates.
Efficiency & Cost Savings
Leaning on utilization data enabled cleaning services to become more efficient with less cleaning products which supports their sustainability goals. With the cost savings from reduction of time spent and materials used the first year, the project was delivered to Deloitte at no additional cost as implementation and licensing fees were effectively paid back.
It is expected that from the second year onwards savings will increase. Soobr has calculated an average saving potential of 15% across their clients depending on flexibility around cleaning schedules and also building configuration. Adding more data sources for demand-based routines will support a stronger business case.
