This is the third in a series of posts in which we discuss the application use reporting question, “Who is using what application and for how long?” Last post we discussed some of the issues with gathering and reporting on the attributes of identifying “What is the application.” This post we’ll look at data attribute issues around “For how long.” In our next post we’ll look at some of the use cases.
First, some assumptions:
The application is installed on a user’s desktop, and the user launches or starts the application.
Application launch and delivery of the license are essentially instantaneous.
Enterprises want this information for both on-line and off-line application use.
Here are some of the data attributes needed for “How long” reporting:
- When was the application launched
- Is the application actively used
- Is the application not actively used
- How do we know when the application is really not active
- How much time is associated/allocated to activity transition
If you think of application usage as being a timeline, application use measurement can be broken into a start, middle, and an end. The clock “starts” by the triggering element the reporting tool uses – application launch/license released to enable the individual application, a license server log file for concurrent licenses, or log-in for cloud applications.
The middle part of the timeline is where the data source is critical for determining use time accuracy. Users typically start and stop activities when using an application. For instance, I’ve started and stopped working on this blog post at least 5 times, while I’ve had Microsoft Word open for three days. When the administrator wants to know if the application is being actively used, how does she know/get that information? If the definition of use is:
- A license delivered from a license server, I’ve been actively using Word for three days.
- If this application’s window is in the foreground, my use is more likely to have been two to three hours.
- Whether I’m actively typing or moving my mouse in the window, then my use is closer to 45 minutes.
The most accurate depiction of my “use” time in the application is somewhere between actively typing/moving my mouse and having the window open in the foreground. Every time I stop to read and think about what I’ve written, I’m still actively “using” the application, even though the only way to verify this would likely require some way of associating the open window with me sitting at my desk and working with or looking at the application.
A significant issue of identifying the “active” state of an application is determining the time since any activity occurred in the open window. Gathering this information requires the reporting tool having the ability to capture activity information, such as keyboard or mouse movement in the open window from the workstation, the application pushing status information to a database or the license server periodically polling outstanding licenses to gather activity information (however the application gathers activity).
Applications vary in how much “inactive” time might be associated with thinking/data gathering between actively working in the application. In addition, user roles and individuals are likely going to have different typical “inactive” times. Short of having an individual report every activity change, or externally monitoring an individual user, there is no way of capturing the exact activities and duration of application use. The more frequently a use monitoring tool can gather use information increases the accuracy of the use data.
The end of the timeline is easy to capture and report, as the user closes the application and the license is released.
Cetrus Process Meter monitors application use at the desktop allowing it to accurately capture whether the application window is open or in the background, as well as identifying when activity occurred and stopped. The solution also lets administrators set default application-specific times since last actual activity in a window before declaring an application as inactive. In addition, a timeout setting reports how long it’s been since the application was deemed “inactive.” This information lets enterprises have much more accurate visibility into “for how long” applications are being used.
If you’d like to learn more about how Process Meter can help you understand your actual application use, please send us an email at email@example.com, or fill out our contact form.