Computing potential savings (classic)
Last updated
Last updated
Some functionality of Experience Optimization is linked with Finder (classic).
Nexthink Finder is a Windows-only desktop application whose functionality is now available within the Nexthink web interface. Nexthink can now be used directly from a browser and most functions no longer require an additional desktop application.
In combination with metrics, scores help you find out potential money and time savings within your IT infrastructure through the calculation of costs related to software and hardware inventory or through the estimation of the time spent on certain activities.
Through the use of a few select examples, we will illustrate how both saving time and money is possible. If you are interested in these or similar examples, please contact Nexthink Customer Success Services.
The startup time of a device is unproductive and potentially annoying for the end-user, especially when the waiting time is excessive. Nexthink Collector takes two measurements that added together give the total startup time of a device: the boot time and the logon time. A score to find out potential time savings in the startup time of a device may focus on the boot time, on the logon time, or on both.
For instance, to compute the total boot time of a device over the course of one day, create a composite score that multiplies the boot duration of the device by the number of times that it was booted that day. That is, create two leaf scores based on the aggregate Average boot duration and Number of system boots and compose them with the multiply operation to get a composite score that yields the total boot time. Optionally, do the same for the logon time and compose the boot and logon time scores with the sum operation to get a single composite score that contains the total startup time. To combine the score with metrics, it must be computed once every day at midnight in order for the metric to get the value of the score for the full day.
Now that the score has provided the startup time of each device, metrics can be used to get the sum over all devices. To that end, create a quantity metric that computes the daily startup time score of active devices and aggregates it by the sum over all devices and the whole timeframe.
When displayed in the Nexthink web interface, the metric may be used to analyze the startup time of devices and help you determine why some devices have longer startup times. You may use this information to reduce time wasted in the startup process by taking appropriate action over those devices with the longest startup times: update the operating system, the system memory, replace old models, etc.
Software that is installed but never or seldom used, incurs unjustified licensing costs. To help you estimate the cost of licensed software that is not being used, start by creating a score on devices. Use the score to individually assign cost to each device that has a particular software application installed, but that has not executed it over, for instance, the last month. Compute the score every day at midnight to combine it with a metric.
To calculate the total cost of underutilizing a particular software application, create a quantity metric that computes the cost score of all devices daily (you want to include those devices that were not necessarily active the previous day) and aggregate the cost by the sum over all devices.
Display this metric in the Nexthink web interface to see the potential cost savings of removing unused installed programs. As a complement to scores for cost savings, remember that you can create software metering metrics for assessing license use as well.
