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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 , , , , ,

Artificial intelligence (AI) has become a hot topic for countries worldwide, and both public- and private-sector organizations have already started leveraging it as a response to continuous digital disruption. According to IDC’s 2022 Artificial Intelligence Spending Guide, global AI spending reached $88.6 billion in 2021, and it is forecast to grow at a compound annual growth rate (CAGR) of 25.6% over the 2021–2025 period.

Canada, China, and the United States are among the countries in which many organizations began their AI journeys early, supported by government initiatives. Saudi Arabia is no different in terms of its commitment to becoming an AI powerhouse. As an extension of the country’s Vision 2030, the Saudi Data and AI Authority (SDAIA) was established in 2019, followed by the release of the National Strategy for Data and AI in 2020. Given its strong focus on and dedication to fostering an AI ecosystem, Saudi Arabia is poised to see strong growth in overall AI spending, with a CAGR of 29% forecast for the 2021–2025 period that will see the market reach a value of $563 million in 2025.

According to a recent IDC survey of CIOs in the Kingdom, almost half the Saudi organizations that invest in AI technologies prefer to customize off-the-shelf solutions to meet their needs. This suggests an appetite among end users to work with local and global technology solution providers to meet their organizations’ specific business requirements. In terms of in-demand AI applications, more than one-third of Saudi organizations are investing in digital assistants, chatbots, and conversational agents augmented by Arabic language capabilities. Recommendation engines, as well as prediction and forecasting, are other key investment areas that will be leveraged across various vertical markets.

Organizations in Saudi Arabia should approach AI as a strategic initiative rather than as a one-off project so they can drive organization-wide innovation and become AI disruptors. To understand an organization’s AI readiness, five maturity traits of AI disruptors need to be evaluated. These are vision, people, process, technology, and data readiness. Responding to IDC’s recent Saudi Arabia CIO Survey, 35% of organizations said that identifying and hiring talent and the cost of implementation were major challenges. The lack of a centralized strategy and unclear processes, the lack of alignment across business and IT functions, the lack of a single technology architecture and platform were also highlighted as major challenges.

Like all other emerging technologies, AI is also prone to cybersecurity threats. Threat actors and adversaries launch attacks to compromise the confidentiality, availability, and integrity of AI systems. Training data security, algorithm security, trained model security, and platform security, as well as model transparency, ethics, and responsibility, are the key focus areas for building a secure and sustainable AI practice.

SBM has been heavily investing in its emerging technology capabilities and views data and AI as the key enablers of many sophisticated technology use cases and as critical instruments for helping Saudi Arabia to achieve its Vision 2030 goals. SBM has in-house developed solutions and has been a longstanding IBM partner, dating back to 1968. SBM and IBM both possess experienced emerging-technology professionals on the ground in the Kingdom. These capabilities enable them to work closely with customers to deliver customized products and services around Big Data and analytics, AI, automation, data governance and compliance, and security.

SBM will continue to introduce innovative new solutions through its strong partnerships and emerging technology capabilities to meet the requirements of businesses in the Kingdom, thereby contributing to the realization of Saudi Vision 2030.

To view and download the full whitepaper, click here.

Artificial Intelligence

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

Artificial intelligence (AI) has become a hot topic for countries worldwide, and both public- and private-sector organizations have already started leveraging it as a response to continuous digital disruption. According to IDC’s 2022 Artificial Intelligence Spending Guide, global AI spending reached $88.6 billion in 2021, and it is forecast to grow at a compound annual growth rate (CAGR) of 25.6% over the 2021–2025 period.

Canada, China, and the United States are among the countries in which many organizations began their AI journeys early, supported by government initiatives. Saudi Arabia is no different in terms of its commitment to becoming an AI powerhouse. As an extension of the country’s Vision 2030, the Saudi Data and AI Authority (SDAIA) was established in 2019, followed by the release of the National Strategy for Data and AI in 2020. Given its strong focus on and dedication to fostering an AI ecosystem, Saudi Arabia is poised to see strong growth in overall AI spending, with a CAGR of 29% forecast for the 2021–2025 period that will see the market reach a value of $563 million in 2025.

According to a recent IDC survey of CIOs in the Kingdom, almost half the Saudi organizations that invest in AI technologies prefer to customize off-the-shelf solutions to meet their needs. This suggests an appetite among end users to work with local and global technology solution providers to meet their organizations’ specific business requirements. In terms of in-demand AI applications, more than one-third of Saudi organizations are investing in digital assistants, chatbots, and conversational agents augmented by Arabic language capabilities. Recommendation engines, as well as prediction and forecasting, are other key investment areas that will be leveraged across various vertical markets.

Organizations in Saudi Arabia should approach AI as a strategic initiative rather than as a one-off project so they can drive organization-wide innovation and become AI disruptors. To understand an organization’s AI readiness, five maturity traits of AI disruptors need to be evaluated. These are vision, people, process, technology, and data readiness. Responding to IDC’s recent Saudi Arabia CIO Survey, 35% of organizations said that identifying and hiring talent and the cost of implementation were major challenges. The lack of a centralized strategy and unclear processes, the lack of alignment across business and IT functions, the lack of a single technology architecture and platform were also highlighted as major challenges.

Like all other emerging technologies, AI is also prone to cybersecurity threats. Threat actors and adversaries launch attacks to compromise the confidentiality, availability, and integrity of AI systems. Training data security, algorithm security, trained model security, and platform security, as well as model transparency, ethics, and responsibility, are the key focus areas for building a secure and sustainable AI practice.

SBM has been heavily investing in its emerging technology capabilities and views data and AI as the key enablers of many sophisticated technology use cases and as critical instruments for helping Saudi Arabia to achieve its Vision 2030 goals. SBM has in-house developed solutions and has been a longstanding IBM partner, dating back to 1968. SBM and IBM both possess experienced emerging-technology professionals on the ground in the Kingdom. These capabilities enable them to work closely with customers to deliver customized products and services around Big Data and analytics, AI, automation, data governance and compliance, and security.

SBM will continue to introduce innovative new solutions through its strong partnerships and emerging technology capabilities to meet the requirements of businesses in the Kingdom, thereby contributing to the realization of Saudi Vision 2030.

Artificial Intelligence