When it comes to high-value technical software, license costs can spiral quickly if IT leaders and portfolio managers don’t have a complete and accurate picture of active usage. But as we discussed in part one, not all usage data is created equally. Often, teams are working with partial or incomplete data, which leads to them committing to bigger and more expensive contracts than their organization needs. Here, we examine the main issues that stem from the limited approach to measuring usage that many IT leaders and portfolio managers employ today.
1. Summary, not depth
Sometimes software products come with in-built metering, but these in-built offerings typically only provide a summary of how many times an application has been opened over a certain period, or the last time it was launched. This data is far too basic to decide what level of license to buy. Especially because technical applications often have complex licensing agreements and models, such as concurrent, term subscriptions and token licensing. For example, overestimating token requirements runs the risk of unused tokens expiring; annual tokens expire after 365 days and contract-based tokens expire at the end of the term. Eliminating the wasted expense of expired tokens, underutilized concurrent users, or simply unused applications, can only be achieved with detailed usage data – summaries just aren’t enough.
2. Easily ‘gamed’ by bad practices
The majority of usage metering tools are too easily ‘gamed’ by bad practices. For example, with concurrent licensing, a pool of licenses are shared across an organization and this maximum number cannot be exceeded. However, it’s possible for employees to ‘license camp,’ whereby they keep an application open to ensure its availability for when they need it, preventing another user from accessing it. A simplistic licensing tool will simply read this as the application being open for an extended period of time, despite it not being in use. This paints an inaccurate picture of usage requirements. IT leaders need to be able to identify practices such as license camping, so they can get a true understanding of license needs.
3. Lack insight into module or function usage
Using certain functionality or modules within an application can cost more since they require access to an additional application or an upgraded version of the software, which is often separately chargeable. One example when using token licensing would be that using base AutoCAD costs 7 tokens a day, but if AutoCAD Mechanical is also run, that’s an additional 7 per day – 14 in total. With other applications it may be that higher cost subscriptions give access to modules or applications that only a handful of users may actually need. The rest could be moved to a cheaper license, saving a considerable amount of budget. Therefore, metering that module individually is important because just monitoring the entire application doesn’t provide a picture of which specific components are genuinely required.
No detail is too small
All of these problems amount to IT leaders and application portfolio managers getting an inaccurate or partial perspective of usage requirements. There is a need for more intelligent metering that can provide minute-by-minute analysis of active usage of all software across the IT estate. Deep analysis is critical to enabling portfolio managers, IT vendor managers, and IT purchasing teams to optimize high-value application costs.
That’s where Scalable’s Asset Vision platform helps, delivering intelligent usage data that helps teams fully understand the extent every high-value application is used, with no blind spots. Asset Vision pinpoints unused and underutilized applications and modules, to enable right-sizing of the software estate and significant savings.
Watch this space for part three of this series, where we will look at the outcomes of not taking an intelligent approach to usage metering.
