Mike Chen | Content Strategist | October 25, 2023
For business leaders, cloud migration may seem like the obvious IT choice in today’s data-centric world. However, it doesn’t come with a simple one-size-fits-all strategy. The benefits of the cloud compared with on-premises data centers vary from organization to organization. Thus, when deciding to migrate to the cloud, businesses must consider a complex range of practical and technical variables, and determining the long-term organizational impact requires thoughtful analysis and foresight.
Cloud economics studies the financial impact of cloud computing, including elements such as legacy hardware investments, monthly cloud service budgeting, and projected savings due to better collaboration and technical innovations, to help an organization better assess its situation. While nearly every organization can benefit from cloud computing, individual circumstances dictate the how and why of getting there, making cloud economics a crucial step in the decision-making process.
Cloud economics is the process of examining the financial and functional impact of cloud computing on an organization. Leaders assess the critical elements involved in a potential cloud migration. A cloud economics analysis weighs financial factors such as return on investment (ROI), legacy hardware investment, and the total cost of ownership (TCO) for the cloud versus on-premises data centers.
In addition to expected financial and technology considerations, a cloud economics analysis should factor in the following cultural elements:
When considering cloud computing, organizations must understand that the scope of analysis goes beyond hardware investments or monthly fees. Cloud migration can completely change operations and development, depending on functional, data, and budgetary realities. In some cases, organizations may have a simpler IT setup, and cloud migration may focus on improving reliability and availability, with other features making less of an impact.
A common cloud economics approach involves breaking the analysis down across the following four pillars:
Total cost of ownership: A data center TCO analysis includes infrastructure costs, such as the purchase or lease of the physical building, power and cooling systems, and networking. Additionally, there are costs associated with hardware and software; personnel, including salaries and benefits for IT staff; maintenance and support, including software updates; and energy given that data centers require a substantial amount of power to operate.
In a cloud model, the TCO shifts to monthly usage costs for compute and storage, and outlines how a shift in staffing needs will affect payroll. A cloud economics analysis breaks these details down, providing cost/benefit insights across the organization.
Operational resilience: Local data centers face a constant risk of real-world issues affecting availability. Natural disasters, power outages, and even local politics regarding infrastructure can all cause unexpected downtime for on-premises equipment. Cloud providers build uptime guarantees into service level agreements and design their business models around redundancy, giving customers greater resilience.
Operational agility: Many different factors can change the volume of network traffic, including app updates and remote access. To absorb these spikes, on-premises data centers need the physical resources to handle peak loads. In a cloud environment, scalability becomes as simple as upgrading to a higher service tier. This creates organizational agility, whether spikes are temporary, such as with holiday sales, or the start of significant and lasting growth.
Cloud economics is important because a cloud migration affects both tangible budgets and theoretical shifts in operations and IT. No one-size-fits-all strategy applies; each organization has different internal and customer demands and unique network and hardware configurations. In addition, some organizations may still have networks built for business circa 2000, with connectivity limited to email and uploaded files.
For IT departments, cloud economics provides a deeper understanding of what organizations must prepare for in both the short and long term. A cloud economics analysis should answer the following questions:
Consider these two examples. In each, the organization must weigh different variables to properly gauge its cloud economics situation.
A small regional healthcare group: A healthcare network’s IT department must support electronic health records, incoming data from Internet of Things (IoT) devices, telehealth access, and general operations. Because of privacy concerns, certain governance and security issues also apply. The network faces a generally steady rhythm of data queries and traffic but must be prepared for emergency situations.
A software company launching an app version of a video game: Prior to the app’s launch, the needs of development and operations teams drive internal IT. Tasks include facilitating codebase collaboration and supporting remote contractors across the globe. However, the app launch shifts focus. Now we need servers capable of managing expected user volumes—and if the app becomes a viral overnight sensation, the infrastructure must be elastic enough to withstand massive spikes in usage.
While both of these organizations can benefit from the cloud, their situations demand different strategies and different implementation plans. Without proper consideration of cloud economics, organizations waste resources, waste money, or remain woefully unprepared. In some cases, perhaps all of the above.
Beyond cost savings (see the next section for more on that), cloud migration comes with a wide range of functional benefits to increase efficiency across the entire organization. These benefits include the following:
Scalability: In a data center, resource growth, be it processing power or storage capacity, is dependent on purchasing and integrating new hardware. Thus, when demand spikes, scaling to meet that demand can be a costly and slow process. In a cloud environment, resource usage scales as needed based on configurations and SLAs, making it easier to maintain stability and functionality as your needs expand.
Improved collaboration: Cloud infrastructure better supports cloud applications, data integration, remote access, and other methods of flexibly syncing users. By granting easier access to tools, data, and lines of communication, cloud computing can significantly increase staff collaboration and accelerate data sharing among departments.
Flexibility: The cloud’s scalability makes it easy to deal with sudden demand spikes. For example, if an app faces an enormous number of download requests after an unexpected viral event, hardware in a local data center can’t be upgraded in time to accommodate the new users, who may not come back. Because clouds operate on a pay-as-you-use model, sudden spikes can be absorbed without long-term investments or maintenance.
IT productivity: With the cloud, day-to-day server maintenance becomes the cloud provider’s responsibility. Thus, cloud migration reduces the burden of tedious yet vital IT tasks and frees up staff to concentrate on more-critical projects that benefit the entire organization, such as governance or new product development.
Increased security: Cloud infrastructure offers many data security improvements. From a practical perspective, public cloud providers focus their entire business models on ensuring security for their customers, so their investments in and efforts to maintain security will generally outdo those of individual IT departments. Big cloud providers have more tiers of defense, larger investments in the latest security innovations, a better ability to hire scarce security talent, and faster compliance with the latest regulatory rules. In addition, centralized administration executes all patching and security updates for infrastructure and applications quickly and with minimal or no downtime.
Better disaster recovery: Similar to security implementation, cloud providers often offer more options and faster execution when it comes to disaster recovery because their business models are built around data availability. Greater levels of redundancy, fast failover, and anywhere, anytime access ensure users can recover data, even in the event of a natural disaster.
The total economic benefit of cloud migration includes the immediate cost savings and the financial impact of its many functional benefits across an organization. The following are a few ways organizations reduce costs with the cloud:
Reduced TCO: With an on-premises configuration, an organization must budget for all stages of a hardware cycle, from initial acquisition to maintenance costs and configuration time. In a cloud environment, the provider handles data center needs. The provider’s staff takes care of replacements and repairs, relieving cloud customers of the need for capital investments and ongoing licensing and maintenance costs.
Save on intangibles: If your IT staff aren’t burdened by maintenance tasks, such as troubleshooting a problematic server, where could they spend that time and effort? Moving to the cloud frees them up so they can further IT innovation for the organization and drive improvements that create efficiencies and stability.
OpEx instead of CapEx: By moving to the cloud, organizational budgets shift from a mainly CapEx model to an OpEx model. This creates a more efficient spending strategy as cloud-based OpEx budgeting doesn’t require the long-term up-front investments in compute, storage, and capacity—all resources that may never be fully utilized.
Scale as needed: When working with an on-premises data center, hardware plans must account for the maximum possible resource usage. For example, if an upcoming launch is expected to drive traffic, then IT must scale to that volume with additional safety-net coverage. However, if the app’s launch drives less than the anticipated traffic, all that overhead will be wasted. Cloud providers scale on demand with a pay-as-you-go pricing model.
There’s no single ideal cloud strategy—each organization must develop its own based on an evaluation of its needs and budget. The following use cases can help. They capture some of the different areas organizations may emphasize when crafting a cloud strategy. In addition, a sound cloud strategy should consider an organization’s specific challenges; key considerations are listed below.
Cost optimization: For organizations with varied functions that create a range of workload requirements, a cloud provider delivers the flexibility to adapt compute, storage, and other technical resources without the need to invest in hardware that may not be fully utilized.
Scalability: For organizations such as startup companies, where workloads grow in step with an increasing customer base, cloud platforms allow for scalability so allocated costs track with business needs.
Disaster recovery and business continuity: For on-premises environments, disaster recovery comes with inherent challenges. Failover protocols rely on redundant infrastructure and physical circumstances, such as local utilities and accessibility. Both downtime and data loss lead to lost revenue, in addition to the cost of repair or replacement. Cloud providers offer stability and availability guaranteed by service level agreements.
Digital initiatives: The cloud creates a more efficient development cycle thanks to the availability of capacity on demand. For both software and microservice releases, developers can focus on the application rather than resource usage, storage space, or compute capabilities. All of this leads to faster time to market, which promotes healthier revenue.
Remote work and collaboration: In a cloud environment, employees can access applications and databases remotely to better support hybrid work. Not only does this provide greater flexibility for employees, but collaboration becomes easier through shared applications and synced data sources.
TCO: While the cloud frees organizations from many data center expenses, they should evaluate migration costs, including potential downtime. To calculate the ongoing TCO, organizations should couple projected monthly technology fees with ongoing costs for management and security.
Security and compliance: While cloud providers handle the underlying infrastructure, organizations maintain responsibility for their data and the devices used to access cloud services, whether PCs, IoT endpoints, or smartphones. Ensuring data security and regulatory compliance and managing data integration fall under the purview of IT teams.
Vendor lock-in: Migrating from on-premises to the cloud can be straightforward as many vendors use standard strategies and processes. However, moving from, say, AWS to Google Cloud or Oracle Cloud Infrastructure is a different story. Vendor lock-in often stems from limitations such as proprietary data formats, applications locking into workflows, and business processes becoming dependent on specific applications.
Skills and training: For IT teams that have built their tasks around local data center maintenance and management, cloud management creates new challenges that require training. Organizations must invest in providing their IT teams with appropriate learning resources and set expectations for transition periods.
Data governance: Organizations must keep an ongoing governance strategy in place to ensure workloads meet necessary governmental compliance standards while managing user access via identities and roles. Because both internal and governmental rules evolve, governance requires a continuous investment of time and budget to keep data safe.
To get approval for the cloud migration process, organizations must make a business case that addresses their specific needs. A government office will have different needs than a small tech startup or an established corporation with legacy databases. A cloud environment will likely provide more flexibility while reducing costs in nearly any circumstance—but realizing the benefits depends on the execution.
To make a sound business case for cloud economics, organizations should consider the following questions:
What are our existing data center costs? To get started, organizations must evaluate their existing data center hardware, software, maintenance, and operational spend. Technical resources, licenses, regular repair and maintenance, and human labor costs all add up to a number that acts as a benchmark for a cloud economics analysis.
How difficult will migration be? The initial migration to the cloud will create a number of expenses unique to each organization. An organization that has an existing configuration with databases and internal networking is likely to have a more straightforward migration than a company that bases revenue on a larger customer base querying database records via an app. Migration can be gradual, completed in stages, or done in one fell swoop with planned downtime and a backup strategy in place. Organizations must project the one-time costs of migration, including time for testing apps on the new infrastructure. Do you have a lot of custom or homegrown applications that will need to be moved to the cloud?
What will monthly cloud costs be? Once migration is complete, organizations can begin to examine projected monthly costs based on a combination of historical usage and upcoming activity. In addition to provider estimates for monthly fees, budget projections should include related costs such as management time, training, and governance.
How will this improve processes? If cloud migration will reduce monthly costs, then that offers a strong business case for transitioning. However, decision makers should look beyond the numbers to fully understand the scope of change. Enhanced collaboration, machine learning capabilities, improved processes, and increased levels of security are just the start. For developers and engineers, the cloud can accelerate rollouts while allowing for micro-updates rather than huge milestone releases. For operations teams, the cloud offers easier ways to unify and share data, allowing different groups to gain insights on demand. When making the business case for cloud economics, organizations must factor in the financial impact of these improvements as part of their long-term projections.
While it’s true that a cloud migration delivers many benefits, the nuances of cloud economics require forethought, smart decision-making, and continual monitoring. Otherwise, common mistakes can occur, including the following:
Assuming financials don’t evolve: The savings accrued during the first week, month, or even year don’t necessarily reflect longer-term financial projections. Big-picture cloud economics takes many different variables into account, including accelerated development time and new cloud-based features. By limiting the scope of cloud economics to immediate hardware benefits, organizations create inaccurate projections that skew the business case for the cloud while missing further opportunities.
Basing projections on historical usage: Cloud budgeting is based on a pay-as-you-go model, but organizations that rely only on historical usage patterns may find themselves unprepared to handle a spike in activity. Historical usage should be only one of the data points considered in projecting budgets. Seasonality, the frequency of releases and upgrades, publicity and marketing campaigns, and other factors also require consideration for proper cloud resource planning.
Treating all cloud elements the same: Compute, storage, and other infrastructure elements will likely hold different priorities for each organization. IT teams should identify their priorities and the scope of their resources to understand which elements benefit most from the scalability and elasticity of a cloud environment.
Putting all data in the cloud: Some applications won’t benefit from being in the cloud. In these situations, migrating the app creates additional work and costs when it might be simpler and more cost-effective to keep the status quo. Organizations should evaluate all their potential workloads to identify any that can, and should, remain as is for cost and resource efficiency.
If your organization has defined a cloud budget, examined operational benefits, and considered potential innovations, then the next step is to evaluate cloud providers. Oracle Cloud Infrastructure (OCI) makes cloud migration simple, then delivers higher performance, lower costs, and stronger integrations across data and security systems.
OCI provides a flexible and scalable foundation that reduces data egress fees and eliminates billing surprises, all with a suite of ready-to-use applications that accelerate development cycles, generate deeper business insights, and improve operations.
What are the 4 pillars of a cloud value framework?
These are the four pillars of a cloud value framework.
What is a cloud economist?
A cloud economist is someone in an organization that looks at the tangible and theoretical benefits of cloud infrastructure. Their scope of examination ranges from practical cost savings via hardware reduction to projected savings from accelerated workflows and increased collaboration.
Which cloud model is most economical?
Cloud providers typically offer public and private models. Between these two, public is the easiest to implement, both in terms of functionality and cost. Private clouds require more management and initial setup. However, organizations can use hybrid models to connect public and private systems. The economics of hybrid clouds vary and often fall somewhere in between the public and private cloud in terms of cost.
What is the difference between FinOps and cloud economics?
These two terms are sometimes used interchangeably, but there is a difference between FinOps and cloud economics. FinOps commonly references finance cloud operations but is sometimes used to refer to organizational financial operations more broadly. In the context of the cloud, FinOps refers to the management of cloud integration and usage across an organization, including the cultural impact. On the other hand, cloud economics examines only the financial aspect, including the TCO and the financial impact of improved processes.