Executive Summary
During a time of economic volatility and uncertainty, the management and optimization of cloud spend has become a top priority for organizations. In 2025, average annual IT budgets were $199 million.1 Cloud spending continues to grow as organizations expand their use of modern applications, digital services, and artificial intelligence (AI). As cloud environments become more complex, finance, FinOps, and cloud operations teams face increasing pressure to control costs, improve visibility, optimize cloud infrastructure utilization, and govern emerging AI-related spending.2
Microsoft Cost Management provides organizations with centralized visibility into cloud consumption and spending. Organizations can use it to manage budgets, forecast demand, optimize infrastructure resources, allocate costs, identify anomalies, and track spending across business units. As cloud spending and AI workloads grow, the solution can also be used to monitor costs associated with AI workloads, including token consumption, GPU utilization, model usage, and AI experimentation environments.
Microsoft commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Microsoft Cost Management. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Microsoft Cost Management on their organizations.3
Key Statistics
$6.4M
Benefits PV
$6.3M
Net present value (NPV)
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed four decision-makers with experience using Microsoft Cost Management. For the purposes of this study, Forrester aggregated the experiences of the interviewees and combined the results into a single composite organization, which is a global, multibillion-dollar enterprise with approximately 10,000 employees and $10 million in annual Azure spending.
Interviewees said Microsoft Cost Management is free to active Azure customers and partners. They explained that prior to using it, their organizations relied on a combination of spreadsheets, manually generated reports, decentralized cost-tracking processes, and ad hoc analyses to monitor cloud spending, allocate costs, forecast budgets, and support chargeback activities. As their Azure environments grew, teams struggled to gain consistent visibility into spending across applications, business units, and cloud resources. Prior attempts to manage costs through manual reporting and local optimization efforts yielded limited success, leaving the organizations with fragmented visibility, inconsistent cost allocation, and significant administrative effort. These limitations made it difficult to identify optimization opportunities, forecast future consumption, proactively address cost anomalies, and effectively manage rapidly growing AI-related spending.
Interviewees said Microsoft Cost Management established a centralized source for cloud financial management. This improved visibility into spending and forecasting, automated reporting, provided stronger governance, and led to more effective cost optimization. They also said their organizations gained the ability to monitor infrastructure and AI-related costs, identify underutilized resources, optimize savings plans, and provide self-service access for business stakeholders.
Key Findings
Quantified benefits. Quantified benefits for the composite organization include:
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Twenty-two percent reduction in cloud infrastructure spending through optimization. Using Microsoft Cost Management as a centralized source of data, forecasting capabilities, anomaly detection, and optimization recommendations helps the composite organization reduce unnecessary cloud spending across compute, storage, networking, and other infrastructure services. Over three years, this reduction translates into $5.3 million in savings for the composite organization.
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Twenty percent reduction in AI spend through monitoring and optimization. Microsoft Cost Management provides visibility into the composite organization’s AI spend drivers by enabling it to monitor and optimize AI workloads. It also helps the organization reduce unnecessary AI spending while improving its financial accountability and governance. Over three years, this reduction translates into $757,000 in savings for the composite organization.
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Fifty percent time savings for business unit owners. By centralizing cloud cost visibility and automating reporting, forecasting, allocation, and monitoring activities, Microsoft Cost Management reduces the composite organization’s administrative effort across FinOps, engineering, and business teams while improving access to spending information. Over three years, this translates into $342,000 in savings for the composite organization.
Unquantified benefits. Benefits that provide value for the composite organization but are not quantified for this study include:
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Improved governance, compliance, and audit readiness. Microsoft Cost Management tracks the composite’s spending, supports audits, maintains cost allocation records, and helps it demonstrate compliance with internal and external requirements, which improves its visibility, accountability, and financial controls across cloud environments.
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Improved cloud cost forecasting. Improved forecasting helps the composite organization budget more accurately, enhance procurement decisions, and improve reservation planning and savings plan utilization.
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Foundation for AI governance. The composite organization improves its visibility into token consumption, GPU utilization, model usage, AI agents, and AI experimentation environments while helping it establish governance processes, accountability structures, and reporting capabilities for future AI initiatives.
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Reduced financial reporting risk. Automated reporting and having a central source of financial information improves the composite organization’s accuracy and confidence in cloud spending data used for budgeting, forecasting, and management decisions.
Quantified costs. Quantified costs for the composite organization include:
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Internal labor costs of $185,000 for implementation, management, and support. The composite organization incurs labor costs associated with implementation, training and maintenance of Microsoft Cost Management.
The financial analysis that is based on the interviews found that a composite organization experiences benefits of $6.4 million over three years versus costs of $185,000, adding up to a net present value (NPV) of $6.3 million.
20%
Reduction in AI spend
Benefits (Three-Year)
The Microsoft Cost Management Customer Journey
Drivers leading to the Microsoft Cost Management investment
Interviews
| Role | Industry | Region | Revenue | Users | Annual Azure Spend |
|---|---|---|---|---|---|
| Head of digital transformation and insights strategy | Food and beverage | Global | $90B | 500 | $100M + |
| CIO | Public sector | US | N/A | 250 | $100M |
| CISO | Information technology | Global | $60B | 400 | $8M – $10M |
| CISO | Information technology and services | Global | $300M – $500M | 100 | $7.2M |
Key Challenges
Interviewees said that prior to adopting Microsoft Cost Management, their organizations faced growing challenges around managing cloud expenditures across increasingly complex Azure environments. Cloud usage was expanding across business units, applications, development teams, and geographies, while financial oversight processes often relied on a combination of spreadsheets, manually generated reports, ad hoc analyses, and decentralized governance processes.
As their Azure consumption increased, the organizations struggled to consistently allocate costs, identify optimization opportunities, forecast future spending, and hold business units accountable for cloud consumption. Several interviewees noted that visibility into cloud spending was fragmented across teams, making it difficult to establish a common view of costs and resource utilization. Budget owners and business leaders frequently depended on finance or IT teams to provide cost reports and spending analyses, which created delays and increased administrative burden.
The interviewees also reported that it was challenging to detect cost anomalies, identify underutilized resources, and optimize commitments (e.g., reserved instances, savings plans). They said that without centralized visibility and automated reporting, their cloud operations, finance, and engineering teams spent significant time manually gathering data, reconciling charges, performing chargeback activities, and preparing budget forecasts.
In addition, several interviewees said their organizations were experiencing rapid growth in AI-related spending, citing increasing use of AI-enabled applications, copilots, foundation models, GPU-intensive workloads, and AI-assisted software development. However, some said their companies lacked the tools and governance processes needed to effectively monitor token consumption, GPU utilization, AI experimentation environments, and AI-specific costs. As a result, leadership teams sought greater visibility and control over both traditional cloud infrastructure spending and emerging AI expenses.
Interviewees noted how their organizations struggled with common challenges prior to investing in Microsoft Cost Management, including:
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Limited visibility into cloud and AI spending. As cloud environments grew and spending became distributed across teams, applications, and business units, the organizations struggled to gain a clear understanding of where cloud resources were being consumed and who was accountable for those costs. This challenge became more significant as AI-related spending increased and the organizations sought visibility into token consumption, GPU utilization, and model usage. The CISO at an information technology and services company said, “[Engineers] don't even need to really ask the finance person [about spending] anymore because everything is already tagged and pre-allocated.”
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Manual reporting, forecasting, and cost management processes. The organizations’ finance and cloud operations teams spent substantial time manually compiling reports, allocating costs, reconciling spending, supporting chargeback processes, and answering questions from budget owners and business stakeholders. This reduced their productivity and delayed decision-making. The CISO at the information technology and services company said, “People were having to do all of this stuff manually and making mistakes.”
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Difficulty managing rapidly growing AI spend. Interviewees reported increasing use of AI-enabled applications, AI-assisted development tools, and AI experimentation environments, but a lack of effective processes and governance controls to monitor token usage, GPU consumption, model selection, and AI-related spending. The CISO at the information technology and services company explained, “The budgets for AI are exploding, and they’re exploding in an unexpected way.”
Composite Organization
Based on the interviews, Forrester constructed a TEI framework, a composite company, and an ROI analysis that illustrates the areas financially affected. The composite organization is representative of the interviewees’ organizations, and it is used to present the aggregate financial analysis in the next section. The composite organization has the following characteristics:
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Description of composite. The composite organization is a global, multibillion-dollar enterprise with approximately 10,000 employees and $10 million in annual Azure spending.
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Deployment characteristics. The composite organization deploys Microsoft Cost Management to 287 users, including two FinOps resources, 10 cloud engineers, 75 business unit managers, and 200 business users with self-service access. AI workloads represent approximately 13% of the organization’s Azure spending in Year 1, equivalent to $1.3 million annually. A five-person cross-functional team consisting of FinOps, finance, cloud engineering, and reporting resources configures governance policies, establishes tagging and allocation structures, builds dashboards, and enables business users. The implementation takes two weeks.
KEY ASSUMPTIONS
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Global enterprise
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Multibillion-dollar company
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10,000 employees
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$10 million annual Azure spend
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13% AI spend in Year 1
Analysis Of Benefits
Quantified benefit data as applied to the composite
Total Benefits
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Cloud infrastructure cost savings | $2,007,000 | $2,163,150 | $2,314,125 | $6,484,275 | $5,350,909 |
| Btr | AI spend optimization | $221,000 | $299,200 | $411,400 | $931,600 | $757,273 |
| Ctr | Labor cost savings | $137,700 | $137,700 | $137,700 | $413,100 | $342,440 |
| Total benefits (risk-adjusted) | $2,365,700 | $2,600,050 | $2,863,225 | $7,828,975 | $6,450,622 |
Cloud Infrastructure Cost Savings
Evidence and data. Interviewees reported that their organizations’ cloud spending continued to increase as they expanded Azure usage across applications, business units, and development teams. They said that prior to adopting Microsoft Cost Management, their organizations lacked consistent visibility into resource utilization and frequently struggled to identify underutilized infrastructure, optimize reservations, forecast demand, and allocate costs effectively.
They explained Microsoft Cost Management provided a centralized source of data, forecasting capabilities, anomaly detection, and optimization recommendations, which helped their organizations reduce unnecessary cloud spending across compute, storage, networking, and other infrastructure services. Interviewees also reported that they receive recommendations about cost optimization, utilization insights, and other aspects of managing infrastructure through Microsoft Azure Advisor, which is included within Microsoft Cost Management. Interviewees cited this feature as key to reducing cloud costs.
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The head of digital transformation and insights strategy at a food and beverage company said: “Approximately 15% to 25% is the cloud optimization impact. Suppose I spin up a VM (virtual machine), and the utilization is only 50%. Then the other 50% is not getting utilized. That’s a cost. So, optimizing the resources is very important. We want to allocate the resources, put guardrails in place, optimize the resources, and buy the right savings plans.”
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The CISO at an information technology company said: “We are able to rightsize the clusters, CPU, and network bandwidth, and allocate the resources. Anywhere from 20% to 25% is a decent number with Microsoft Cost Management versus without it.”
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Each interviewee spoke about the importance of forecasting and said Microsoft Cost Management enables more accurate budgeting, capacity planning, and procurement decisions. The head of digital transformation and insights strategy at a food and beverage company said, “Forecasting is important because I can commit that much volume and get heavier discounts on the savings plan.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
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The composite organization spends $10 million on Azure in Year 1. These costs increase by 10% in both Year 2 and Year 3, totaling $11 million in Year 2 and $12.1 million in Year 3.
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The organization’s VM spend as a percentage of total is 45%.
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Microsoft Cost Management reduces the organization’s VM spend by 30%.
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The organization’s storage spend as a percentage of total is 25%.
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Microsoft Cost Management reduces the organization’s storage spend by 25%.
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The organization’s other Azure services spend as a percentage of total is 17% in Year 1, 14% in Year 2, and 10% in Year 3.
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Microsoft Cost Management reduces the organization’s other Azure spend by 15%.
Risks. The scale of this benefit may vary from organization to organization based on:
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The extent to which leadership mandates use of Microsoft Cost Management and enforces accountability for Azure costs.
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The pace of change in the organization’s cloud environment.
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The accuracy of initial cloud service sizing.
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The extent of tagging across the organization.
Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $5.4 million.
22%
Cloud infrastructure cost savings
Cloud Infrastructure Cost Savings
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| A1 | Azure spend | Composite | $10,000,000 | $11,000,000 | $12,100,000 | |
| A2 | VM spend as a percentage of total | Interviews | 45% | 45% | 45% | |
| A3 | Reduction in VM spend | Interviews | 30% | 30% | 30% | |
| A4 | Azure VM cost savings | A1*A2*A3 | $1,350,000 | $1,485,000 | $1,633,500 | |
| A5 | Storage spend as a percentage of total | Interviews | 25% | 25% | 25% | |
| A6 | Percentage reduction in storage spend | Interviews | 25% | 25% | 25% | |
| A7 | Azure storage cost savings | A1*A5*A6 | $625,000 | $687,500 | $756,250 | |
| A8 | Other Azure spend as a percentage of total | Interviews | 17% | 14% | 10% | |
| A9 | Percentage reduction in other Azure spend | Interviews | 15% | 15% | 15% | |
| A10 | Other Azure cost savings | A1*A8*A9 | $255,000 | $231,000 | $181,500 | |
| At | Cloud infrastructure cost savings | A4+A7+A10 | $2,230,000 | $2,403,500 | $2,571,250 | |
| Risk adjustment | ↓10% | |||||
| Atr | Cloud infrastructure cost savings (risk-adjusted) | $2,007,000 | $2,163,150 | $2,314,125 | ||
| Three-year total: $6,484,275 | Three-year present value: $5,350,909 | |||||
AI Spend Optimization
Evidence and data. Interviewees said AI is one of the fastest-growing areas of cloud spend. They explained that as their organizations accelerated their adoption of AI-enabled applications, copilots, foundation models, AI-assisted development tools, and AI agents, they faced increasing pressure to monitor and control token consumption, GPU utilization, model usage, and AI experimentation costs.
They also reported their companies had limited visibility into AI-related spending and a lack of standardized governance processes. As AI usage expanded across the organizations, leadership sought better mechanisms to monitor consumption, identify anomalies, forecast spending, and allocate costs to business units and budget owners.
Interviewees explained that Microsoft Cost Management provided visibility into AI spend drivers and enabled their organizations to monitor and optimize AI workloads and reduce unnecessary AI spending while improving financial accountability and governance.
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Interviewees reported that improved visibility into token consumption, model selection, inference costs, and AI utilization enabled meaningful reductions in AI-related spending. One estimated that optimizing token usage and selecting appropriately sized models reduced AI costs by 20% to 30%, while another estimated saving approximately 25% on AI spend through improved governance and monitoring. A CIO in the public sector noted: “You need cost management ... to understand token [usage], inference [costs], utilization rates, and interactions. [Reducing token usage or using] smaller models ... [can save] 20% to 30%.”
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The head of digital transformation and insights strategy at the food and beverage company: “We manage [AI spend] in a much closer and much more optimized way. [AI costs] can balloon very fast.”
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The CISO at the information technology and services company said, “The budgets for AI are exploding, and they’re exploding in an unexpected way.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
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The composite organization spends $10 million on Azure in Year 1. These costs increase by 10% in both Years 2 and Year 3, totaling $11 million in Year 2 and $12.1 million in Year 3.
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The organization’s AI spend as a percentage of total is 13% in Year 1, 16% in Year 2, and 20% in Year 3.
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Microsoft Cost Management reduces the organization’s AI spend by 20%.
Risks. The scale of this benefit may vary from organization to organization based on:
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The extent of AI usage.
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The extent that the organization uses Microsoft Cost Management to manage AI costs.
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Visibility into AI spend.
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Growth of AI spend.
Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $757,000.
20%
Reduction in AI spend
AI Spend Optimization
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| B1 | Azure spend | A1 | $10,000,000 | $11,000,000 | $12,100,000 | |
| B2 | AI spend as a percentage of total | Interviews | 13% | 16% | 20% | |
| B3 | Percentage reduction in AI spend | Interviews | 20% | 20% | 20% | |
| Bt | AI Spend Optimization | B1*B2*B3 | $260,000 | $352,000 | $484,000 | |
| Risk adjustment | ↓15% | |||||
| Btr | AI Spend Optimization (risk-adjusted) | $221,000 | $299,200 | $411,400 | ||
| Three-year total: $931,600 | Three-year present value: $757,273 | |||||
Labor Cost Savings
Evidence and data. Interviewees said that prior to using Microsoft Cost Management, their organizations relied on manual processes to monitor cloud spending, allocate costs, prepare forecasts, investigate anomalies, support chargeback activities, and respond to requests from budget owners and business stakeholders. FinOps and cloud operations teams spent significant time gathering data, reconciling reports, preparing dashboards, and answering questions about cloud consumption.
Interviewees explained that Microsoft Cost Management centralized cloud cost visibility and automated reporting, forecasting, allocation, and monitoring activities, which reduced administrative effort across FinOps, engineering, and business teams while improving access to spending information. They also reported that self-service dashboards, automated reporting, anomaly detection, and cost-allocation capabilities significantly reduced the amount of time spent creating reports, investigating spending patterns, and responding to budget inquiries.
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The head of digital transformation and insights strategy at the food and beverage organization noted, “People’s time has been saved a lot where everyone had to do bottoms-up cost calculation, optimization, and forecasting.”
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The CISO at the information technology organization reported: “[Engineering teams] are able to save … 10% to 15% of their time because of superior dashboard and deeper analytics.”
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The CISO at the information technology and services organization noted that business stakeholders gained the ability to access spending information directly: “They really don’t even need to ask the finance person anymore because everything is already tagged and pre-allocated.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
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The composite organization has two FinOps team members.
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The average fully burdened annual salary for a FinOps team member is $135,000.
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Microsoft Cost Management saves the organization’s FinOps team members 30% of their time.
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The organization has 10 cloud engineers who spend 25% of their time on cloud cost/resource management.
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The average fully burdened annual salary for a cloud engineer is $150,000.
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Microsoft Cost Management saves the organization’s cloud engineers 10% of their time.
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The organization has 75 business unit managers who spend 1 hour each week on cloud cost/resource management.
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The average fully burdened annual salary for a business unit manager is $200,000.
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Microsoft Cost Management saves the organization’s business unit managers 50% of their time.
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Forrester applied a 50% productivity recapture rate to account for the portion of time savings that can be converted into incremental productive output.
Risks. The scale of this benefit may vary from organization to organization based on:
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Time spent using Microsoft Cost Management.
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Differences in compensation levels, which can vary based on industry, geography, experience, and skill sets.
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Organizational structure and team sizes.
Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $342,000.
50%
Time saved by business unit owners
Labor Cost Savings
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| C1 | FinOps team members | Composite | 2 | 2 | 2 | |
| C2 | Average fully burdened annual salary for a FinOps team member | Composite | $135,000 | $135,000 | $135,000 | |
| C3 | Percentage of time saved by FinOps team members | Interviews | 30% | 30% | 30% | |
| C4 | FinOps team savings | C1*C2*C3 | $81,000 | $81,000 | $81,000 | |
| C5 | Cloud engineers | Composite | 10 | 10 | 10 | |
| C6 | Average fully burdened annual salary for a cloud engineer | Composite | $150,000 | $150,000 | $150,000 | |
| C7 | Percentage of time cloud engineers spend on cloud cost/resource management | Interviews | 25% | 25% | 25% | |
| C8 | Percentage of time saved by cloud engineers | Interviews | 10% | 10% | 10% | |
| C9 | Cloud engineers team savings | C5*C6*C7*C8 | $37,500 | $37,500 | $37,500 | |
| C10 | Business unit managers | Composite | 75 | 75 | 75 | |
| C11 | Average fully burdened annual salary for a business unit manager | Composite | $200,000 | $200,000 | $200,000 | |
| C12 | Time business unit managers spend on cloud cost/resource management (hours) | Interviews | 52 | 52 | 52 | |
| C13 | Percentage of time saved | Interviews | 50% | 50% | 50% | |
| C14 | Business unit managers savings | C10*C11/2,080*C12*C13 | $187,500 | $187,500 | $187,500 | |
| C15 | Productivity recapture rate | TEI methodology | 50% | 50% | 50% | |
| Ct | Labor cost savings | (C4+C9+C14)*C15 | $153,000 | $153,000 | $153,000 | |
| Risk adjustment | ↓10% | |||||
| Ctr | Labor cost savings (risk-adjusted) | $137,700 | $137,700 | $137,700 | ||
| Three-year total: $413,100 | Three-year present value: $342,440 | |||||
Unquantified Benefits
Benefits that provide value for the composite organization but are not quantified for this study include:
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Improved governance, compliance, and audit readiness. Interviewees reported that Microsoft Cost Management improved visibility, accountability, and financial controls across cloud environments. They said their organizations improved the ability to track spending, support audits, maintain cost allocation records, and demonstrate compliance with internal and external requirements. The head of digital transformation and insights strategy at the food and beverage company noted, “Everything is getting under a single control tower.”
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Improved cloud cost forecasting. Interviewees cited improved forecasting of cloud costs as one of the most valuable capabilities of Microsoft Cost Management and noted that it enabled more accurate budgeting, better reservation planning, improved savings plan utilization, and enhanced procurement decisions. The head of digital transformation and insights strategy at the food and beverage company said, “Forecasting is important because then I [know I] can commit that much volume, and I can get heavier discounts on the savings plan.”
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Foundation for AI governance. Interviewees identified AI cost management as an emerging area of focus and said Microsoft Cost Management provided their organizations with visibility into token consumption, GPU utilization, model usage, AI agents, and AI experimentation environments that are increasingly required as AI adoption expands.
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Reduced financial reporting risk. Interviewees reported that centralizing cloud cost information reduced the risk of errors associated with manual reporting, reconciliation, and spreadsheet-based processes. They explained that using Microsoft Cost Management as a central source of financial information that automates reporting improved their organizations’ accuracy and confidence in cloud spending data used for budgeting, forecasting, and management decisions.
Flexibility
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Microsoft Cost Management and later realize additional uses and business opportunities, including:
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Scaling FinOps and cloud operations. Interviewees expressed interest in emerging agentic operations capabilities that extend beyond visibility and reporting into automated optimization and cost governance. They described a future state where intelligent agents monitor cloud consumption, identify optimization opportunities, explain recommendations, and autonomously take corrective actions (e.g., rightsizing resources, shutting down unused capacity, responding to spending anomalies). As cloud and AI environments continue to grow in complexity, interviewees expect Microsoft Cost Management to provide a foundation for agentic capabilities to help scale governance and optimization efforts without requiring proportional increases in FinOps or cloud operations staffing.
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Expanding governance across additional Microsoft services. Interviewees said their organizations may extend cost-allocation, chargeback, forecasting, and governance practices to additional Microsoft cloud services as usage grows and financial management requirements become more sophisticated.
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Establishing enterprisewide AI chargeback models and cost accountability frameworks. Interviewees said that as their organizations’ AI investments increase, they may leverage Microsoft Cost Management to establish AI-specific chargeback models and spending accountability frameworks in an effort to help business leaders understand the financial impact of AI initiatives and drive more efficient consumption behavior.
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).
Analysis Of Costs
Quantified cost data as applied to the composite
Total Costs
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Dtr | Implementation and ongoing maintenance | $80,771 | $42,001 | $42,001 | $42,001 | $206,774 | $185,222 |
| Total costs (risk-adjusted) | $80,771 | $42,001 | $42,001 | $42,001 | $206,774 | $185,222 |
Implementation And Ongoing Maintenance
Evidence and data. Interviewees described deployment of Microsoft Cost Management as straightforward due to its native integration with Azure and minimal infrastructure requirements. Implementation activities included configuring governance policies, establishing cost-allocation structures, creating dashboards, and enabling users. After deployment, the organizations maintained a small team responsible for cloud financial management activities (e.g., forecasting, chargeback administration, anomaly detection, reporting maintenance, governance reviews, dashboard management).
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
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The composite organization’s initial implementation requires a cross-functional team of five employees.
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The organization’s initial setup takes two weeks.
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The average fully burdened weekly salary for a team member is $3,077.
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The organization trains 75 users.
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Each user spends 8 hours in training during the initial period.
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The organization requires 0.25 FTE to provide ongoing maintenance in Years 1 to 3.
Risks. The impact of this cost may vary by organization depending on the following:
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The size of the organization’s cross-functional team.
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Team member salaries.
Results. To account for these risks, Forrester adjusted this cost upward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $185,000.
Implementation And Ongoing Maintenance
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| D1 | Cross-functional team members involved in implementation | Composite | 5 | |||
| D2 | Implementation time (weeks) | Interviews | 2 | |||
| D3 | Blended fully burdened weekly salary for an implementation team member | Composite | $3,077 | $3,077 | $3,077 | $3,077 |
| D4 | Implementation costs | D1*D2*D3 | $30,770 | |||
| D5 | Users trained | Composite | 75 | |||
| D6 | Training time (hours) | Interviews | 8 | |||
| D7 | Training costs | D5*D6*D3/40 | $46,155 | |||
| D8 | FTEs required for ongoing maintenance | Interviews | 0 | 0.25 | 0.25 | 0.25 |
| D9 | Ongoing maintenance costs | D8*D3*52 | $0 | $40,000 | $40,000 | $40,000 |
| Dt | Implementation and ongoing maintenance | D4+D7+D9 | $76,925 | $40,000 | $40,000 | $40,000 |
| Risk adjustment | ↑5% | |||||
| Dtr | Implementation and ongoing maintenance (risk-adjusted) | $80,771 | $42,001 | $42,001 | $42,001 | |
| Three-year total: $206,774 | Three-year present value: $185,222 | |||||
Financial Summary
Consolidated Three-Year, Risk-Adjusted Metrics
Cash Flow Chart (Risk-Adjusted)
Cash Flow Analysis (Risk-Adjusted)
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($80,771) | ($42,001) | ($42,001) | ($42,001) | ($206,774) | ($185,222) |
| Total benefits | $0 | $2,365,700 | $2,600,050 | $2,863,225 | $7,828,975 | $6,450,622 |
| Net benefits | ($80,771) | $2,323,699 | $2,558,049 | $2,821,224 | $7,622,201 | $6,265,400 |
| Payback | <6 months |
Please Note
The financial results calculated in the Benefits and Costs sections can be used to determine the ROI, NPV, and payback period for the composite organization’s investment. Forrester assumes a yearly discount rate of 10% for this analysis.
These risk-adjusted ROI, NPV, and payback period values are determined by applying risk-adjustment factors to the unadjusted results in each Benefit and Cost section.
The initial investment column contains costs incurred at “time 0” or at the beginning of Year 1 that are not discounted. All other cash flows are discounted using the discount rate at the end of the year. PV calculations are calculated for each total cost and benefit estimate. NPV calculations in the summary tables are the sum of the initial investment and the discounted cash flows in each year. Sums and present value calculations of the Total Benefits, Total Costs, and Cash Flow tables may not exactly add up, as some rounding may occur.
From the information provided in the interviews, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in Microsoft Cost Management.
The objective of the framework is to identify the cost, benefit, flexibility, and risk factors that affect the investment decision. Forrester took a multistep approach to evaluate the impact that Microsoft Cost Management can have on an organization.
Due Diligence
Interviewed Microsoft stakeholders and Forrester analysts to gather data relative to Microsoft Cost Management.
Interviews
Interviewed four decision-makers at organizations using Microsoft Cost Management to obtain data about costs, benefits, and risks.
Composite Organization
Designed a composite organization based on characteristics of the interviewees’ organizations.
Financial Model Framework
Constructed a financial model representative of the interviews using the TEI methodology and risk-adjusted the financial model based on issues and concerns of the interviewees.
Case Study
Employed four fundamental elements of TEI in modeling the investment impact: benefits, costs, flexibility, and risks. Given the increasing sophistication of ROI analyses related to IT investments, Forrester’s TEI methodology provides a complete picture of the total economic impact of purchase decisions. Please see Appendix A for additional information on the TEI methodology.
Total Economic Impact Approach
Benefits
Benefits represent the value the solution delivers to the business. The TEI methodology places equal weight on the measure of benefits and costs, allowing for a full examination of the solution’s effect on the entire organization.
Costs
Costs comprise all expenses necessary to deliver the proposed value, or benefits, of the solution. The methodology captures implementation and ongoing costs associated with the solution.
Flexibility
Flexibility represents the strategic value that can be obtained for some future additional investment building on top of the initial investment already made. The ability to capture that benefit has a PV that can be estimated.
Risks
Risks measure the uncertainty of benefit and cost estimates given: 1) the likelihood that estimates will meet original projections and 2) the likelihood that estimates will be tracked over time. TEI risk factors are based on “triangular distribution.”
Financial Terminology
Present value (PV)
The present or current value of (discounted) cost and benefit estimates given at an interest rate (the discount rate). The PVs of costs and benefits feed into the total NPV of cash flows.
Net present value (NPV)
The present or current value of (discounted) future net cash flows given an interest rate (the discount rate). A positive project NPV normally indicates that the investment should be made unless other projects have higher NPVs.
Return on investment (ROI)
A project’s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits less costs) by costs.
Discount rate
The interest rate used in cash flow analysis to take into account the time value of money. Organizations typically use discount rates between 8% and 16%.
Payback
The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs) equal initial investment or cost.
Appendix A
Total Economic Impact
Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.
Appendix B
Endnotes
1 Source: The Cloud Cost Management And Optimization Solutions Landscape, Q3 2025, Forrester Research, Inc., August 28, 2025.
2 Forrester defines FinOps as a practice dedicated to maximizing cloud value through technology-powered cloud optimization, process change, operational excellence, and cultural transformation to ensure IT financial responsibility around cloud investments.
3 Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.
Disclosures
Readers should be aware of the following:
This study is commissioned by Microsoft and delivered by Forrester Consulting. It is not meant to be used as a competitive analysis.
Forrester makes no assumptions as to the potential ROI that other organizations will receive. Forrester strongly advises that readers use their own estimates within the framework provided in the study to determine the appropriateness of an investment in Microsoft Cost Management. For any interactive functionality, the intent is for the questions to solicit inputs specific to a prospect's business. Forrester believes that this analysis is representative of what companies may achieve with Microsoft Cost Management based on the inputs provided and any assumptions made. Forrester does not endorse Microsoft or its offerings. Although great care has been taken to ensure the accuracy and completeness of this model, Microsoft and Forrester Research are unable to accept any legal responsibility for any actions taken on the basis of the information contained herein. The interactive tool is provided ‘AS IS,’ and Forrester and Microsoft make no warranties of any kind.
Microsoft reviewed and provided feedback to Forrester, but Forrester maintains editorial control over the study and its findings and does not accept changes to the study that contradict Forrester’s findings or obscure the meaning of the study.
Microsoft provided the customer names for the interviews but did not participate in the interviews.
Consulting Team:
Maria Kulikova
Published
October 2026
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