Computing potential savings


Computing potential savings


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.

Let us illustrate how to discover possible time and money savings with a couple of examples. If you are interested in these or similar examples, please contact Nexthink Customer Success Services.

Time savings - Startup duration

The startup time of a device is unproductive as well as annoying for the end-user, specially when the waiting time is too long. In Nexthink, the Collector takes two measures that add up to 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 either on the boot time, on the logon time, or on both.

For instance, to compute the total boot time of a device during 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 aggregates 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 holds 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 provides the startup time of each device, let us use metrics to get the sum over all devices. To that end, create a quantity metric that computes daily the startup time score of active devices and aggregate it by the sum over all devices and the whole timeframe.

When displayed in the Portal, the metric may be used to analyze the startup time of devices and help you determine the reason 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 whose startup time is the longest: update the operating system, the system memory, replace old models, etc.


Cost savings - Underutilized software

Software that is installed but never or seldom used incurs in unjustified licensing costs. To help you estimate the cost of licensed software that is not 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 did not execute it during -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 in your corporate infrastructure, create a quantity metric that computes daily the cost score of all devices (you want to include those devices that were not necessarily active the last day) and aggregate the cost by the sum over all devices.

Display this metric in the Portal to know how much money you can potentially save by 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.

Considerations when using scores in metrics

As we have just seen, combining metrics with scores is a powerful mechanism to create dashboards with high business impact. However, there are some combinations of objects (user or device) and aggregation methods that do not make sense when creating a quantity metric that relies on scores. Let us therefore consider the combinations that you should avoid to prevent you from getting misleading results.

  • User (object) and sum (aggregation): As a user may be seen in multiple entities, the addition of their scores may not give the right result.
  • Active devices (object) and average (aggregation): The average of scores is meaningless in this case.