In our last blog post, we said we were going to look at some of the Use Cases associated with license cost reduction. Reducing license costs assumes there is an overabundance of license availability/capacity relative to the actual need. Different vendors have different licensing approaches, and may have multiple approaches depending on their license or application types. The common elements that enterprises need to understand in order to determine if and how much over-licensing exists are:
- The licensing model (what are the attributes of the license)
- The licensing model constraint (peak use, number of distinct licenses, pay by a unit of measurable quantity, etc.)
- The organization’s current and anticipated future needs for that license
If the best predictor of the future is the past, then most license use analysis starts with historical use patterns. Analysis requires data. In order to measure past use, the organization needs to have been able to accurately measure and record use.Gathering use data depends on the license deployment model and the organization’s application monitoring tool set. If the tools can’t accurately monitor use, the organization typically over-licenses without knowing by how much, and doesn’t have the data to improve efficient use of existing licenses to further drive down licensing costs.
Below are two typical examples of information needed to reduce license costs:
Example 1: Comparing application use between two or more applications
An enterprise wants to identify use of PDF markup and viewing applications to determine the optimal level of licensing for one or more applications. To get this information, the enterprise needs to know:
- Where and how many copies of each application are installed/being using in the enterprise
- Ranking application use by user. Ranking can be defined as how many sessions in a given time period each user used each application, what was the aggregate use time for each application for each user, and which user used multiple applications
- What are the key functions that would direct a user to one or more of the applications
Example 2: Identifying optimal network/concurrent licensing for one application
An enterprise wants to identify peak license use and review several months of data to look for recurring patterns associated with peak use. To get this information, the enterprise needs to know:
- What the entitlement (peak use) for the application is
- When, how often, and for how long peak license use occurs
- Which users/groups are consuming the licenses
- What conditions drive peak use
- Whether the licenses are actively checked out and being used, or if the licenses are check out but are inactive/idle
Without very granular use data, the organization performing the analysis is likely to be paying for more licenses than it actually needs. Users may not know they are “sitting” on licenses that could be used by someone else. Comparing group use can identify needs for training or more active monitoring of some users to help with behavior changes. Business processes, such as rescheduling recurring meetings or shifting customer meetings to different days/times s of the week can have an impact on peak license use.
Cetrus Process Meter provides the most granular application/license use information on the market. Unlike license metering solutions, which report when licenses are checked in and out, Process Meter reports in real time whether or not the checked out licenses are being used. Process Meter reports on standalone, cloud-licensed and server-licensed applications to provide the broadest application use monitoring capability in the industry.