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After years of compounded digital transformation, the downsides of the cloud are starting to reveal themselves. As cloud investments increase, benefits remain elusive without also investing in optimization efforts targeted at reducing cloud waste and lowering costs, that’s according to a new study published by CIO.com.

Research reveals that while most companies are investing more in the cloud, 80% of decision makers report cost savings as the biggest issue with existing cloud deployments. In fact, the vast majority (55%) of those respondents say costs are “extremely” challenging.

This key takeaway is being labeled the “cloud cost quandary,” the predicament companies face when they need to invest more in the cloud yet struggle to recognize value on the investments they have already made. But why is capitalizing on the cloud difficult? The research also provides answers.

Data explains why cloud cost savings are problematic

The research report unpacks root causes behind the issues of cost and achieving cost savings in the cloud. The bottom line: it’s hard to follow where the money goes, seeing how, when, and where resources are used and then allocating costs across the organization.

It’s hard to follow the cloud money trail

70% say it’s challenging to account for cloud spending and usage66% of the C-suite cite tracing spend and chargebacks of particular concern

Here’s where the cloud can spur spending surprises that are difficult to chase down.

Cloud infrastructure services generally charge a fee every time data is accessed, as well as when data limits are surpassed during storage and backup. You are also charged by the second for however long a service instance runs. Thus, understanding cloud usage at a very granular level has become a key focal point in putting boundaries around spending.

Tagging capabilities enable granular tracking of service usage, but it’s not always easy to maintain accuracy, spot IaaS instances that are little used or mis-tagged or get a clear view into usage spikes and the reasons for them. Managing tags is essential yet time-consuming when performed manually. Default dashboards from cloud providers don’t offer the speed and data-crunching benefits of advanced analytics nor the cost-cutting insights of cloud expense management platforms.

Deciphering cloud costs on the backend is equally daunting, as invoices can be highly complex in part because of the number of line items for each fee or instance. However, with more investments in cloud, IT finance managers want to ensure resources are used effectively to keep costs to a minimum. Chargebacks and allocating costs are also critical moves for leaders trying to hold departments and lines of business fiscally responsible for digital innovation and the cloud services they use.  

And it’s not just cloud infrastructure fogging the view. The study shows a large majority (70%) of respondents reported Shadow IT as their top challenge with cloud applications. That’s understood after fast-moving changes from the past three years. Most companies today find they have an eye-opening number of unsanctioned tools, multiple redundant SaaS subscriptions, and a significant amount of unused application licenses that need to be identified and reassigned to new owners.

The bottom line: Making time to oversee the cloud—gaining visibility into expansive datasets for deeper investigation and managing accounting details—is an added burden on IT and finance teams.

Cloud waste offers evidence of the difficulties of cloud management.

Waste proves companies are mismanaging cloud resources

When it’s challenging to account for cloud usage and spending, it’s that much harder to optimize cloud resources and reap the benefits of cost savings. Another key takeaway from the study is how many digital transformation dollars are getting washed away in the form of cloud waste. The study shows 29% of cloud resources are wasted with 12% of cloud licenses going entirely unused. 

Those numbers should have any cloud innovator sitting up straight in their chair—not because they should fear exposing how much of the cloud gets squandered, but because they can now see exactly how much a cloud cost optimization program is worth—29% in savings. This is the type of program that could generate meaningful resource reallocations, ROI improvements, departmental recognition, or even personal promotion.

In diving deeper, the research shows the larger the company the larger the problem. This is particularly the case when it comes to cost savings. Roughly 68% of companies with more than $5 billion in revenue faced significant difficulty achieving cost savings with cloud, compared to 36% of smaller companies.

Capitalizing on the cloud: 3 capabilities simplify governance

Few organizations have yet to update their operational processes to handle the cloud effectively. But in the wake of compressed innovation, governance is now necessary in order to fully capitalize on the cloud. Being a good steward of cloud investments requires three cornerstone competencies, which the study respondents prioritized as the top critical capabilities for cloud management:

Cloud optimization and right-sizingMeasuring and tracking total cloud spendMeasuring cloud utilization

These are the most significant factors in maximizing ROI on cloud innovation.

To learn more about cloud expense management services, visit us here.  

Multi Cloud

Posted on Posted in Digital transformation, General topics Tagged with , , , , , , ,

Chief data and analytics officers (CDAOs) are poised to be of increasing strategic importance to their organizations, but many are struggling to make headway, according to data presented last week by Gartner at the Gartner Data & Analytics Summit 2023.

Fewer than half (44%) of data and analytics leaders say their teams are effective in providing value to their organization. That’s from a survey of 566 data and analytics leaders globally that Gartner conducted online from September to November 2022.

“It was kind of an eye-opener that one-third of them felt they were not as effective as they could be,” says Donna Medeiros, senior director analyst at Gartner. “There’s so much going on, so many things they are compelled to do versus what they really want to do, know they need to do, know they need to prioritize. They’re spending a lot of time on things like data quality, data management, things that might be tactical, helping with operational aspects of IT. But that’s not helping move the value of the organization as a business forward.”

The responsibilities of data and analytics leaders are many and varied: Sixty percent of respondents cited defining and implementing data and analytics strategy; 59% said oversight of data and analytics strategy was in their portfolio of responsibilities; 55% pointed to data and analytics governance; and 54% cited managing data-driven culture change.

Organizations are still investing in data and analytics functions. Respondents to the survey reported their organizations are increasing investment in data management (65%), data governance (63%), and advanced analytics (60%). The mean reported budget among respondents was $5.41 million, and 44% said their data and analytics teams increased in size over the past year.

Key obstacles to data success

Despite that increased investment, CDAOs say lack of resources and funding are among their top impediments to delivering results, with 13% citing it as their top obstacle and 29% listing resource constraints among their top three hurdles.

The top impediment? Skills and staff shortages. One in six (17%) survey respondents said talent was their biggest issue, while 39% listed it among their top three. And the tight talent pool isn’t helping, Medeiros says. “CDAOs must have a talent strategy that doesn’t count on hiring data and analytics talent ready-made.”

To counter this, CDAOs need to build a robust talent management strategy that includes education, training, and coaching for data-driven culture and data literacy, Medeiros says. That strategy must apply not only to the core data and analytics team but also the broader business and technology communities in the organization.

Other obstacles to data and analytics success, according to Gartner, include:

Culture challenges to accept change (8%, top impediment; 26%, among top three)Lack of business stakeholder involvement and support (10%, No. 1 impediment; 26%, top three)Not enough authority to execute the CDAO responsibilities (9%, first choice; 24% top three)Poor data literacy (5%, top choice; 23%, top three)

“Their life is very complex,” Medeiros says of the current state of the CDAO role. “They have lots of areas of primary responsibility — implementing data and analytics strategy, oversight of data and analytics initiatives, creating and implementing information systems and data management — and the people side — workforce development, upskilling, making the organization data-driven, artificial intelligence, and centers of excellence. They’ve got a lot of complexity and a lot of people they’re answering to.”

This lack of funding for data initiatives echoes the findings of Foundry/CIO.com’s 2022 Data & Analytics Study, which also found other digital transformation initiatives taking priority and lack of executive advocacy for data initiatives as other key roadblocks to data-driven success.

What it takes to lead data strategy

Strategic missteps in realizing data goals may signal an organizational issue at the C-level, with company leaders recognizing the importance of data and analytics but falling short on making the strategic changes and investments necessary for success. According to a 2022 study from Alation and Wakefield Research, 71% of data leaders said they were “less than very confident” that their company’s leadership sees a link between investing in data and analytics and staying ahead of the competition.

Even in the case where an organization taps a designated IT leader to helm data strategy, whether in a chief data officer or chief analytics officer role, the complexity of the role and how it interfaces with other business leaders needs to be addressed for success.

Medeiros likens the CDAO role to a combination of three personas: an orchestra conductor, a composer, and a performer. The conductor looks across the organization and conducts how data and analytics is done, both across business lines with the help of domain experts, as well as in a centralized function. The composer creates and sells the storyline of the value of data and analytics. And sometimes, data leaders must be performers: helping to implement data management, data quality, data trust, spending time on data governance, compliance, and risk.

“These three personas require juggling soft, people skills and technical savvy,” Medeiros says, adding that “the CDAO serves multiple stakeholders across the organization and cannot operate in isolation. They need to align with organizational strategic priorities, collaborate and sell the overall vision and strategy for data and analytics, and get buy-in for their initiatives.”

The most successful data leaders, according to Gartner’s survey, outperformed their peers by projecting an executive presence while also building an agile and strategic data and analytics function capable of shaping data-driven business performance and operational excellence, Medeiros says. Gartner asked respondents to rate themselves across 17 executive leadership traits. There was a strong correlation between those leaders who said they were effective or very effective across those traits and those who reported high organizational and team performance. For example, 43% of top-performing data and analytics leaders said they were effective in committing time to their own professional development, versus only 19% of low performers.

Prominence matters

How CDAOs are positioned in the organization also impacts data and analytics success. According to Foundry’s 2023 State of the CIO survey, 53% of chief data officers and 45% of chief analytics officers report to the CIO, while just 35% and 38% report to the CEO, respectively. Moreover, only 37% of CDOs and 25% of CAOs report having budgets separate from IT overall.

Foundry / CIO.com

Medeiros concedes that CDAOs who report to the CIO and sit within the IT function can still be effective, but, in general, the higher CDAOs sit in the org chart, the better, she says, as this gives them more visibility and better leverage to work on organizational goals.

“It depends on their roles, responsibilities, and how much time they’re allotted for what we call business enablement — not just enterprise IT but actually helping the organization do what matters,” Medeiros says. “It can be things like cost efficiency, but it’s also new products and services that data and analytics supports and can call out.”

Foundry / CIO.com

Indeed, Rita Sallam, distinguished VP analyst at Gartner, says that by 2026 more than a quarter of Fortune 500 CDAOs will have become responsible for at least one data- and analytics-based product that becomes a top earner for their company.

To get there, though, Medeiros says CDAOs must prioritize strategy over tactics. While tactical elements such as data quality and data security are important, improving effectiveness relies on aligning the data and analytics function with organizational strategic priorities and selling the data and analytics vision to key influencers like the CEO, CIO, and CFO.

“Most CDAOs are delivering on immediate-term business goals, but for around half of CDAOs surveyed, delivery against goals for future-term growth and sustainability is lagging,” Medeiros says.

She notes that the most successful data leaders are focusing on improving decision-making capabilities, monetization of data products, and cost optimization, as well as improving data literacy and fostering a data-driven culture.

Chief Data Officer, Data Management, IT Leadership