Over the last few years, there has been a trend within the SAM and ITAM communities to view inventory as a commodity item – the ugly duckling to swan-like process-driven platforms.
Unfortunately, this attitude puts the fundamental aims of SAM at risk for two critical reasons: First, not all inventory is equal and second, there is no such thing as a one-size-fits-all inventory solution.
While it’s true that inventory alone will not deliver cost savings or compliance, trying to perform SAM without the right inventory data is like trying to build a jigsaw with a bunch of pieces missing.
There are literally hundreds of tools available – some free, some commercial – that claim they will provide you with visibility of the hardware and software assets on your network. That’s great. But are they accurate? Are they easy to deploy? Can they effectively report audit data back across dispersed networks?
Creating an effective inventory solution is harder than you might think. There are a multitude of network vagaries and configuration discrepancies that a tool needs to overcome if it is to successfully collect and return data.
Thinking about the requirements of SAM in particular, it is how this returned audit data is then processed that is of particular importance. Most inventory tools can tell you that they’ve found ‘excel.exe’ installed on a Windows PC (along with another 2,000 or so files!). But how much use is that to a software manager trying to establish if their organisation is compliant with Microsoft licensing?
Far better for the software manager is to be presented with actionable intelligence that tells him what version and edition of Excel is installed on the PC and that it’s part of an Office 2010 Standard installation.
To make the leap from ‘bits and bytes’ audit data to actionable SAM intelligence, the inventory solution needs a software recognition engine, either in-product or as a service. Or perhaps ideally, both.
For those solutions that rely on a static software recognition ‘dictionary’ (sometimes called a ‘library’), there is often little that can be done by the customer when (and not if) an audited file cannot be automatically recognized by the engine. Essentially the file ends up in some form of black hole.
A software recognition service that combines both in-product instant recognition plus the automatic submission of unrecognized files to a team of software experts offers perhaps the best way of truly understanding what commercial software is installed on the network. This is hardly a commodity item.
Another often over-looked data set is software usage – sometimes referred to as metering. Having the ability to track whether installed software is actually used regularly can be extremely beneficial to making informed decisions about re-harvesting software, arguing the case in compliance situations and tracking user behaviour. But sometimes it’s not simply enough to know if a program is executed – you need to know by whom and for how long, or how regularly.
As much as we like to talk about simplification, the fact is that corporate networks have never been more complex, and the chances are they will only get worse in the coming years. Whether the organization is running multiple platforms (how many Windows-only networks are there in organizations with more than 1,000 employees today?), hosting applications in the Cloud or employing multiple hypervisor technologies, it has never been more difficult to track the assets deployed across the network (and beyond).
From a SAM and ITAM perspective, the real problem is that many inventory tools simply aren’t designed for today’s networks. Sure, they can audit a Windows PC (accepting the caveats above regarding software recognition and usage tracking) but what about Mac or Linux machines? What about tracking the use of Cloud-based applications? What about the ability to determine guest/host relationships on multiple hypervisors such as VMware, Hyper-V and Citrix XenServer?
This unfortunately leaves ITAM and SAM managers with an uncomfortable choice. Do they use a single inventory tool and accept that there will be parts of the network missing from the data set (as in the jigsaw analogy I used to open this blog)? Or do they invest in multiple solutions and try to piece together the different data feeds into a coherent picture (perhaps like trying to build the jigsaw in the dark)?
So perhaps there is more to inventory than meets the eye, after all? Selecting the right inventory solution(s) to meet the organization’s SAM and ITAM goals is a critical decision to get right. Here are five questions to help assess if you’ve made the right choice:
With regards to the last question, this is where an effective SAM platform can make all the difference. In fact, a good SAM tool can often make sense of the data collected by an inventory tool, even when the source data seems incomprehensible.
For many organizations – especially those with legacy inventory investments that are not easily replaced – they will have little choice but to use multiple inventory solutions to track different parts of the network. In this scenario, having the ability to consolidate the data from these different tools into a single ‘source of truth’ view on the corporate network is invaluable. Better still, if that SAM platform can apply the same consistent data cleansing and software recognition methodologies to the disparate data sets, then the SAM manager is hopefully left with real actionable intelligence rather than just a lot of raw data.
Is inventory data sexy or exciting? No, even I would struggle to argue the case for that one! But by the same extent, I hope I have shown that it is far from a commodity item. Downplaying the importance of the inventory data potentially puts your entire SAM or ITAM program at risk.
Provide your program with the best quality data – or preferably actionable intelligence – and you will be in a better position to drive the desire cost reductions, asset optimization and compliance.