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Software License Optimization Maturity Model: Usage Understood – Level 2

By Randy Littleson

In this four part series, we’re going to break down the Software License Optimization Maturity Model and discuss what you can achieve at each level of maturity.  This is the second in the series on Usage Understood – Level 2.

You can view the rest of the series here:

Level 2 – Usage Understood – What is deployed and how is it being used?

At Level 2 maturity, the organization answers the question “What is deployed and how is it being used?”  Enterprises come to understand which applications they have deployed by processing the evidence collected in Level 1 with an Application Recognition Library, which matches all the data and produces a consistently named (normalized) list of applications.  To make sense of the software inventory without an automated content library, you would need to hire armies of people to analyze software signatures or installation evidence.  It is analogous to trying to determine the titles of books in a library if you only have access to the individual pages. 

 

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Figure 1: The Software License Optimization Maturity Model

Understanding what software is installed and how it is being used sounds simple but has a significant set of challenges, including:

  • Inventory Data from Multiple Sources – Many enterprises have multiple inventory tools covering various platforms across the IT environment—Windows, Windows Server, UNIX, Linux, virtual servers, etc. This data must be aggregated by the license management tool.
  • Product Suites and Bundles – Many vendors offer their software in suites or bundles as well as individual component products. The software asset management tool must be able to determine whether the installed application is part of a suite/bundle, such as Adobe Creative Suite, or is a standalone product.
  • Inconsistent and Incomplete Data – In many cases, the data you collect from inventory is incomplete and/or inconsistent, with the same application going by many different variations on the title and publisher names, for example. One of the jobs performed by the SAM tool is to normalize the data so that you have a standardized, consistent naming convention for all of your software assets.
  • Inventory Data Doesn’t Provide Everything You Need – Some applications, such as Oracle Database products and Microsoft SQL Server, require the collection of additional data. For example, for SQL Server you need to know the edition of the software product. For Oracle databases, it’s important to collect information on options and management packs installed and in use. Standard discovery and inventory tools don’t collect this data. Look for more advanced license management tools that can collect this data.

Basic usage data, typically for desktop applications, can also be collected by the discovery and inventory tools. This information is very useful for doing reharvesting of licenses for unused software and/or for negotiation reductions in maintenance payments.

Once you have an understanding of what software is installed in your environment you need to calculate license consumption based on the metric (user counts, processor counts, core counts with core factors, etc.) used in that license model.  The appropriate metrics for the various license models should be built into the software asset management and license optimization solution and applied automatically.

To learn more about assessing your Software License Optimization maturity, please view our on-demand webinar: Assess Your License Optimization Maturity and Develop a Plan for Improvement. 

 

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