This is the fourth blog in our five-part series on how intelligent usage metering brings value to teams seeking to optimize high-value application costs.
In our last blog, we discussed how not taking an intelligent approach to usage metering can have serious impacts on your business – from unnecessary expense to disrupting users’ workflows. So how do you actually go about intelligently measuring high-value application usage? Here, we unpack seven critical areas of best practice to consider when optimizing high-value engineering application license costs.
1. Minute -by-minute usage data
In our second blog, we discussed how in-built usage metering tools don’t give enough detail on active usage, key information that’s needed to build an accurate picture of usage requirements. Best practice is to employ granular active usage analytics that can provide deep-dive keystroke and mouse click data to give minute-by-minute insight into your organization’s true application usage.
2. Read/Write detection
IT leaders must determine whether use of an application is read-only or read/write, so they don’t identify license requirements that simply do not exist. It’s important to have visibility into whether users only ever read documents or web pages in certain applications to determine which users to move to read-only/viewer/report-only licenses. These are both cheaper and provide a better solution for those users.
3. ‘License camping’ detection
In our second blog, we covered how common practices like license camping (when a user keeps an application open to ensure its availability for when they need it, preventing another user from accessing it) can trick simplistic licensing tools into believing usage requirements are higher than they are. In tests conducted by Scalable, actual usage is almost always less than IT leaders imagine; we’ve seen real usage of an application over a 90-day period as low as five percent of the total community of users. It’s essential to identify instances of license camping and exclude them from usage measurements to right-size accurately.
4. Web application usage
It’s not just offline high-value applications that need to be considered – web application usage also racks up significant costs if licensed incorrectly. Non-intelligent usage metering methods typically only monitor page loads. However, to get a usable picture of ongoing requirements for web applications, IT leaders need to meter the amount of time spent interacting with identifiable elements of the application.
5. Plug-in usage
Sometimes, plug-ins and add-ons have licensing cost implications that are as significant as the cost of the underlying application itself. Best practice is for software usage metering to identify whether individual plug-ins are loaded and used in your environment. Otherwise, an organization will be totally unprepared for software audits that may cover the plug-ins.
6. Sub-function usage
Many high-end data feed applications or large ERP suites have modules defined by some set of functions a user may exploit. These sub-functions may be separately chargeable, so it is important that application usage metering can be configured to monitor and report on sub-function use to avoid a hefty charge down the line, and to better align contracts to true usage.
7. Primary user identification
Often, user identification starts and ends with the last logged in user, but for organizations that hot-desk or share resources in other ways, this information is of little use. It’s much more valuable to identify the primary user of a workstation or actual user of an application, so IT leaders have intelligence on which individuals, departments, or even locations require usage of an application, and how often. These insights can be used to right-size more effectively and optimize costs in the process.
Scalable addresses all seven factors
Watch this space for the final part in this blog series, where we will look at how Scalable’s Asset Vision helps unravel license complexity and incorporates all seven of these critical best practices. Asset Vision enables organizations to understand true usage requirements of their high-value engineering applications, so IT leaders and application portfolio managers can accurately right-size contracts and optimize costs.
