There is intense competition in the cleaning sector.
Price is the deciding factor and the cheapest service provider usually wins the contract.
The result: poorly trained cleaners who often barely understand the local language and only clean superficially, if at all, under great time pressure.
The problem: cleaning is complex and therefore labour-intensive. This leads to a high level of administrative and organisational tasks that tie up additional staff capacity and cause high ancillary costs.
Because cleaning is cognitively and motorically demanding, even the latest technologies cannot replace cleaning staff, but they can take care of the expensive and time-consuming ancillary tasks.
They can also guide cleaning staff autonomously, provide targeted support, monitor quality in real time and avoid downtime.
This would save considerable resources and costs and the money saved could be used to pay cleaners better and enable efficient cleaning.
This would also make the cleaning profession more attractive for many people and counteract the chronic staff shortage that is severely affecting many companies - a win-win situation.
To summarise, we want to solve the following problems:
- Make cleaning cost-efficient
- automation - Improve quality
- Create jobs
