Are Your Software Dollars Gathering Dust? It's Time to Eliminate the Shelfware and Cloud Waste!
March 24, 2021

Rex McMillan
Ivanti

Share this

Software spend in 2021 and beyond will be a hot button as organizations redirect priorities and spending as a result of the pandemic. Spend that can be linked to clear results — more productivity, more ROI, and better integration of the remote workforce — will be looked upon as worthy. However, wasted spend — particularly software assets that have devolved into "shelfware" or cloud waste — will be a ripe opportunity for CIOs and IT management to direct a laser beam on optimizing software asset usage and its potential drain on budget.

With IT teams now supporting workers who are predominantly in remote environments and the attendant security challenges, a fair question is, "Should worrying about shelfware and uncontrolled cloud usage be added to the list of top concerns?" According to Gartner, "At any point in time IT operations may be running with 25% plus of software going unused." A benchmark study a few years back estimated U.S. wasted software spend to be $30 billion, or an average $259 per desktop. If your organization has 20,000 desktops, for example, that equals $5.2 million in investment bringing in zero return.

So, the answer is yes, tightening control over software asset and cloud spend and use should be on the radar. Inevitably, the C-suite, looking to 2021, will be asking tough questions about any new requested spending. And importantly, IT will be expected to deliver a thorough, cogent report on "spend intelligence" related to software use and whether these assets are contributing to desired business outcomes or are simply a money drain.

Spend intelligence is, among other attributes, a means of getting control of shelfware and cloud consumption. It captures data on all software asset spend and cloud application usage and assesses actual use. It then gives rise to the ability to better manage and retire software and cloud assets, or repurpose them, throughout their usable lifecycle. It is a noble goal. However, gathering data on all software and cloud applications has become far more difficult as IT teams now must look at the universe of those assets residing on-prem, in the cloud, or at the edge where remote workers are using devices and applications to enter the network.

The solution is to incorporate automation, machine learning and data analytics into software spend inquiries. This will accelerate insights into how well an organization is using its current software asset environment, and to put a laser light on all assets that have become shelfware. A few practices to consider include the following:

Eliminate Time-Wasting Tasks

A survey of IT professionals revealed 45% use inventory tools as one of their resources for asset tracking, 43% are still using spreadsheets and 50% are using an endpoint management solution. Introducing automated processes into spend intelligence gathering will eliminate time-consuming manual tasks. Data can be collected and maintained in a single, easily navigated repository, reducing the risk of error.

Automate Data Intelligence

Capturing software asset data across on-prem, cloud and edge environments requires tools that can employ automation to collect data from these diverse environments, then automatically analyze and organize the data into relevant categories like licenses or subscriptions.

By moving this data to a central repository, IT teams can quickly find information they need on a particular license, for example, by just using a search mechanism on the dedicated dashboard.

Speed Up Visibility

Stopping the shelfware and cloud waste budget drain involves not only knowing what unused software assets already exist but also preventing more of those assets from becoming dormant and unused. That takes constant diligence in tracking usage, license types, purchases, subscriptions, renewals and instances, contract expirations and ongoing spend.

Automated processes give IT clear insights into precisely where software spend waste is occurring.

IT also provides an up-to-the-minute picture of which applications are consistently being used, detail that will eventually need to be factored into budget strategy reports to the C-suite.

Dust Off the Shelf

If a software asset is not being used in a reasonable timeframe, it needs to be eliminated, or redeployed where the license cost is valued. That usually means making changes to subscriptions, licenses and contracts, notably those with built-in renewal clauses.

Ivanti's survey of IT professionals found 28% devote hours each week supporting out-of-warranty/out-of-support policy assets, and 20% of them indicate they don't have insights into which assets are out of date. This combination of unused software and those licenses past their expiration date is a weak link in IT's and CIO's charters to spend carefully and strategically post-pandemic. Integrating automated tools that can deliver the needed due diligence in managing vendor relationships has to be a top priority.

Reclaim Dollars

The payoff for incorporating automation into software asset management is clearer insights into asset spend, usage and contractual agreements — both on-prem and in the cloud. IT teams now can reclaim dollars that no longer need to be spent on software assets that have become shelfware or cloud waste, are underutilized or are now out-of-date.

Going into 2021, software asset spending will be a source of more scrutiny as IT executives and CIOs fine tune spending to further stabilize productivity in the remote environment. Spending will occur, but IT departments who have excessive amounts of shelfware, or cloud application licenses that have long stopped contributing to ROI, will be in a weakened position to make a case for new investments. By incorporating automation into data collection and software asset management due diligence, IT can gain the power of knowledge to make a case for new strategic investments, all with an eye to better business outcomes.

Rex McMillan is Principal Product Manager at Ivanti.
Share this

The Latest

September 16, 2021

Achieve more with less. How many of you feel that pressure — or, even worse, hear those words — trickle down from leadership? The reality is that overworked and under-resourced IT departments will only lead to chronic errors, missed deadlines and service assurance failures. After all, we're only human. So what are overburdened IT departments to do? Reduce the human factor. In a word: automate ...

September 15, 2021

On average, data innovators release twice as many products and increase employee productivity at double the rate of organizations with less mature data strategies, according to the State of Data Innovation report from Splunk ...

September 14, 2021

While 90% of respondents believe observability is important and strategic to their business — and 94% believe it to be strategic to their role — just 26% noted mature observability practices within their business, according to the 2021 Observability Forecast ...

September 13, 2021

Let's explore a few of the most prominent app success indicators and how app engineers can shift their development strategy to better meet the needs of today's app users ...

September 09, 2021

Business enterprises aiming at digital transformation or IT companies developing new software applications face challenges in developing eye-catching, robust, fast-loading, mobile-friendly, content-rich, and user-friendly software. However, with increased pressure to reduce costs and save time, business enterprises often give a short shrift to performance testing services ...

September 08, 2021

DevOps, SRE and other operations teams use observability solutions with AIOps to ingest and normalize data to get visibility into tech stacks from a centralized system, reduce noise and understand the data's context for quicker mean time to recovery (MTTR). With AI using these processes to produce actionable insights, teams are free to spend more time innovating and providing superior service assurance. Let's explore AI's role in ingestion and normalization, and then dive into correlation and deduplication too ...

September 07, 2021

As we look into the future direction of observability, we are paying attention to the rise of artificial intelligence, machine learning, security, and more. I asked top industry experts — DevOps Institute Ambassadors — to offer their predictions for the future of observability. The following are 10 predictions ...

September 01, 2021

One thing is certain: The hybrid workplace, a term we helped define in early 2020, with its human-centric work design, is the future. However, this new hybrid work flexibility does not come without its costs. According to Microsoft ... weekly meeting times for MS Teams users increased 148%, between February 2020 and February 2021 they saw a 40 billion increase in the number of emails, weekly per person team chats is up 45% (and climbing), and people working on Office Docs increased by 66%. This speaks to the need to further optimize remote interactions to avoid burnout ...

August 31, 2021

Here's how it happens: You're deploying a new technology, thinking everything's going smoothly, when the alerts start coming in. Your rollout has hit a snag. Whole groups of users are complaining about poor performance on their devices. Some can't access applications at all. You've now blown your service-level agreement (SLA). You might have just introduced a new security vulnerability. In the worst case, your big expensive product launch has missed the mark altogether. "How did this happen?" you're asking yourself. "Didn't we test everything before we deployed?" ...

August 30, 2021

The Fastly outage in June 2021 showed how one inconspicuous coding error can cause worldwide chaos. A single Fastly customer making a legitimate configuration change, triggered a hidden bug that sent half of the internet offline, including web giants like Amazon and Reddit. Ultimately, this incident illustrates why organizations must test their software in production ...