The collection of metric data, either automatically in large quantities or manually at important moments, is a functionality that generates many important conclusions in service processes. Warranticon is equipped with a dedicated module that supports analysis of this data and its proper archiving.
Working with technologically advanced devices is often accompanied by the need to monitor their operation – remotely or ad-hoc. Depending on the type of device, we use the right data analysis methodology to detect irregularities or deviations and, of course, tailor the service to the user’s needs.
Classification of meters
Warranticon allows the system user to initiate the meter collection process and define its type.
- Incremental type – allows the user to control the rate of change of the meter. All devices whose life cycle depends on mileage are protected against the possibility of resetting their meter. It is important to measure cyclically to determine whether the device is used as recommended in order to be able to forecast costs related to maintenance or product replacement.
- printers – in terms of the number of printouts,
- scanners – in terms of the number of scans,
- vehicles – in terms of the number of kilometers driven,
- screens and televisions – in terms of the number of hours the image is displayed.
- Drop type – most often presented in the form of a percentage value allows to determine when wear and tear of a given material occurs, and consequently the necessity of its replacement
- battery level
- fuel tank level
- toner level
- ink level
- Permanent type – particularly important when monitoring the location of products protected against theft. Controlling geographic coordinates allows you to intervene while monitoring the current location of your products.
Analytics of metric data
Through the use of various analytical mechanisms allowing to present metric data in a friendly visual form, we have the opportunity to quickly diagnose the situation. Line or pie charts equipped with mechanisms for viewing values at a given point become an element which attracts the user’s attention – and at the same time provoke interaction in the system.
Automatic algorithms equipped with machnie learning mechanisms are an important feature of the Warranticon system, thanks to which the system “learns” how the device behaves at a given moment of its life cycle. Monitoring the trends associated with one or a group of devices in conjunction with monitored events of a certain criticality priority is often the “trigger” for automatic task creation.
Automation based on metrics means speeding up many operational processes, avoiding situations where a service cannot be performed. If a printer’s toner percentage is dropping at a rate of 4% per day, it should be replaced in as little as 25 days. So plan well in advance to stock the warehouse and ship the product to the intended user.