This is part one of a two part series on ‘Environment Recognition’. Part two will be published in due course.
Here at ITAMS, it’s been interesting to witness the increased interest in the ITAM market and organizations wishing to gain control of software risk.
As more and more software permeates every area of modern business, we’re finding that organizations are no longer willing to sit in the pockets of software publishers and issue blank cheques – they want to gain control of costs and ensure maximum return for their IT spend.
Over the years there have been a number of market forces affecting the key requirements for managing software licensing:
License metrics have also become increasingly more complex, aligning themselves to the compute power, usage or value of the software being used rather than just it’s existence on a device.
There has always been an overlap between the practices of Hardware Asset Management (HAM) and Software Asset Management (SAM). It has never been possible to manage software without a good handle of hardware – but we’re finding the interdependency is becoming even more significant.
These days, to maintain a trusted and credible license position it is no longer the case of recognizing what software is installed (although this is still critical) – we also need to recognize the environment in which the software is used.
If software recognition is the process of translating technical installation data to meaningful product data ready for reconciliation with purchasing; then environment recognition is identifying the key environmental characteristics critical to manage complex licensing types that go beyond installation. Who is using the software, who’s infrastructure does it sit on? What underlying processing power does it use? Or could it use and so on.
Whilst delivering our SAM Managed Services to customers, we’ve found that in order to stay sane amongst this increasing complexity and growing number of data sources, the Software SKU catalogue is key.
We use the SKU catalogue as a central source of truth, a forge in which to mix multiple data sources from multiple tools, financial records, systems management data and configuration data and compare it with entitlement records and product use rights to create a true picture of effective licensing.
In my next article, we’ll explore some real life examples of Environment Recognition.