This is a perennial challenge for business leaders. There is an opportunity in front of us, but it comes with a cost. Can you afford it? Or, perhaps more pertinently, can you afford not to?
This dilemma has probably never been more acute than it is today. The opportunities presented by emerging technologies such as AI are clear and have the potential to accelerate enterprise cloud platforms and enable organizations to innovate and remain competitive.
However, unlocking this potential requires the use of additional processing power and compute scale to maintain and manage the vast amounts of reference data required for AI, resulting in cloud investments. decision-making is increasingly driven by the need to support AI.
Managing Partner and Global Head of Wipro FullStride Cloud.
Cost management gap
But at what cost? New research from Wipro shows that 54% of organizations cite AI/GenAI as the top driver for cloud investment, while 43% of UK organizations are looking for a coordinated or centralized way to manage cloud costs. I don’t have a good approach. This is significantly higher than the corresponding numbers. France and Germany had 25% and 24% respectively.
There is no doubt that the unique nature of cloud spending is a factor here. In addition to the additional processing and compute scale referenced above, creating a testing sandbox and accommodating new user onboarding are both important requirements. Additionally, unlike fixed cost models such as non-SaaS ERP systems, cloud spending is also based on consumption and therefore always fluctuates. However, like ERP systems, many departments and business functions use the cloud, so a single company can have multiple functions and incur their own cloud costs. This siled management can lead to duplicate spending, inflating cloud costs and diluting business ROI.
Considering all of the above, this cost control gap is a real cause for concern, especially in light of two other important findings in the new study. That means 54% of organizations plan to increase their investments in hybrid cloud, and 56% have plans in place. Increase investment in public cloud. With AI cloud investments expected to continue to dominate enterprise technology budgets, it’s important to quickly close this cost management gap.
But how can businesses control cloud spending as needed without limiting innovation and new technologies that can only truly be realized through the cloud?
Moving from cost to value
The answer lies in cloud economics. Cloud Economics is a collaborative effort to bring clarity to cloud spending by helping organizational leaders (IT, operations, finance, development, business units) define the value of cloud investments and develop strategies accordingly. It’s a practical and practical process. This approach encourages various business units to go beyond cost optimization and make decisions that maximize the business value of the cloud.
To me, this shift in focus from cost to value is the key to a successful cloud program. The reason many first-time cloud migrations yield mediocre results is because businesses primarily focus on migrating to the cloud as a cost-saving measure. While it’s true that moving to the cloud can make some processes more cost-effective, it can also require up-front time and money.
Companies focused solely on cost reduction may view these investments as “mistakes,” but they are not looking at the bigger picture. The key to long-term cost savings is to embed AI and automation across your operations with the knowledge that your investment will be effective. The time and resources you devote to specific areas of cloud development lay the foundation for features and advancements essential to larger business goals.
Cloud economics helps businesses identify their unique cloud goals and the actions needed to achieve them. In doing so, companies learn how to optimize cloud costs and maximize cloud value by aligning different business teams around shared investment goals. This is an organizational change management initiative that requires companies to work together to achieve like-minded goals.
The role of FinOps
As cloud programs progress through evolving investment spending models and changing enterprise needs, other tools such as FinOps can help business managers further optimize cloud spending and business value.
FinOps is a component of cloud economics that focuses on the operational side. Now that your business has moved to the cloud, how can you best manage your cloud spending to achieve your cloud goals? What are the areas of cloud spending that are unrelated? What areas require greater investment? How can your team focus or pivot their cloud investments without disrupting operations?
To answer these questions, FinOps uses a three-step iterative approach: inform, optimize, and operate.
1. Provide information Gain transparency into cloud spending, budgets, benchmarks, forecasts, and more to give teams the information they need to make cloud spending decisions that align with business goals.
2. Optimize Implement changes to optimize cloud usage.
3. Integrate operational analysis and optimization into daily operations to track cloud program progress and adjust as needed.
Through FinOps, companies can identify areas of overspending, take corrective action, and determine how best to reinvest those savings. For example, through FinOps, businesses may learn that they are paying far more for storage space than they need based on average usage. Downsizing storage frees up capital that companies can potentially reinvest in other avenues based on cloud goals outlined through cloud economics.
move forward
As I assess the overall business landscape, the fact that over 50% of organizations see AI as a key driver for cloud investment is really opening up a whole new world of opportunity. However, this new cost control gap must be addressed.
As a cloud leader, we train our employees on Google Cloud’s AI technology to, for example, help enterprise customers around the world better scope, deploy, and manage AI projects that solve their unique business objectives. , plays a role. This significantly powers critical digital transformation projects such as application migration and modernization, increasing productivity by up to 30% with GenAI.
But to collectively unlock the true potential of AI, we must work together to adopt a cloud economics approach that focuses on value, not cost.
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