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Edward Lowton
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Tracking cleaning machine performance
12 February 2019
How do you track performance when you have multiple cleaning machines in different locations? John Brill, sales director for Nilfisk outlines a solution.

In days gone by there was simply no way of monitoring how machines were used unless you had a supervisor on the ground. Even then the view was subjective, there was no data, no detail and no easy way to compare similar sites under the same contract.
Digital fleet management systems identified early on that ‘planned’ cleaning was often miles apart from the ‘actual’ cleaning. It is common to see machines under-utilised in some areas whilst, in others, machines are overworked and incurring high service costs.
Importantly data often reveals that cleaning is not performed on all of the days contracted leaving the cleaning company open to dissatisfaction and complaint.
Knowledge sharing
Cleaning teams on the ground often know just how to get the job done and will adapt cleaning plans to improve efficiency and result. This knowledge however is rarely shared between sites. Facility layouts can also differ significantly so what works in one location may need adapting for another.
Data analysis allows you to identify all parameters and use that data to communicate with the cleaning teams. This type of non-subjective information is often better received by individuals on the ground, engaging them in useful dialogue and improving motivation.
So how does it work?
GPS software technology is installed on each machine and automatically transmits equipment operation data and location details to a secure web portal. The intuitive platform can be viewed day or night from a PC, tablet or smart phone. You can schedule reports to be sent directly to email and create alerts when a machine is moved out of a designated area. Tracking assets and avoiding theft has never been easier.
Tracked operational data includes:
Machine ID
Location
Machine working time
Time of day
Operator ID
Battery level
Transport time
Analysis of the data, specifically regarding consumable elements often results in existing equipment being replaced with cost effective machines more suited to the job in hand. Similarly under-utilised equipment can be relocated reducing service costs and prolonging the equipment life.