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Total Economic Impact
Cost Savings And Business Benefits Enabled By LaunchDarkly
A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY LAUNCHDARKLY, JANUARY 2026
Total Economic Impact
A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY LAUNCHDARKLY, JANUARY 2026
The increasing pressure on developers to deliver innovation quickly and effectively has highlighted the limitations of traditional software testing and release methods. Feature management and experimentation (FM&E) solutions address these challenges by enabling faster, more successful software deployment with less risk and allowing developers to compare feature variations to enhance customer experience and performance.1 High-scoring solutions in this space offer comprehensive UIs for tracking and managing feature flags, tools for feature A/B testing and experimentation, templated rule sets for best practices, and robust tech debt management, making them valuable tools for development teams.
LaunchDarkly is a runtime control plane for software features designed for engineers, developers, and others in the software development process. Application engineering teams can innovate with new features quickly while maintaining quality, stability and customer trust. Teams can leverage LaunchDarkly AI and automation to release new capabilities and features progressively, remediate issues quickly with feature flags, and track real-time performance. Teams can continuously iterate and improve application feature performance through experimentation and A/B testing. By separating code deployments from feature releases, teams using LaunchDarkly can manage risk in production and make faster, more informed decisions about feature performance, helping reduce risk, save money, and improve business results.
LaunchDarkly commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying LaunchDarkly.2 The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of LaunchDarkly on their organizations.
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed six decision-makers with experience using LaunchDarkly. 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 financial services organization headquartered in the US. It has an annual revenue of $12 billion, 34,000 employees, and 300 developers who now use LaunchDarkly as part of their regular software development processes.
Interviewees said that prior to using LaunchDarkly, their organizations manually coordinated inefficient release processes, which often led to large, stressful release events. Attempts to improve these processes yielded limited success, leaving them with challenges such as the lack of ability to isolate changes, limited flexibility and control, and scalability issues, as well as compliance and governance problems and suboptimal developer productivity during releases. These factors led to time-consuming and buggy releases, difficulty in testing new features, and rigid deployment processes, along with scaling challenges, manual compliance tracking, and delayed feedback on feature performance. Consequently, teams at the interviewees’ organizations struggled with context switching and increased complexity that risked introducing issues that further impacted overall productivity and efficiency.
After the investment in LaunchDarkly, the interviewees reported significant improvements in their release processes. Key results include faster development and more reliable releases resulting in fewer post-deployment issues and enhanced productivity. The interviewees’ organizations moved from large, all-at-once, and complex release events to more frequent, progressive, and easier-to-manage smaller releases. This shift reduced errors and manual intervention, leading to more consistent deployments. Additionally, the ability to deploy features incrementally and target specific user segments enhanced feature management and control, enabling the interviewees’ organizations to deliver the latest tools and features into users’ hands to take advantage of time savings and other benefits. Overall, these changes boosted developer productivity and employee effectiveness, improved work-life balance, increased business opportunities, and enabled greater experimentation and collaboration.
Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits for the composite organization include:
Increased developer testing and deployment efficiencies of 20% worth $2.4 million. Feature flagging capabilities from LaunchDarkly empower development teams at the composite organization to work more efficiently, reduce downtime, and deliver high-quality software more quickly, driving significant productivity gains across the board. The ability to quickly disable flags to shut down problematic features leads to a more reliable software experience, reducing customer-facing issues and enhancing overall performance. The immediate speed and ease of debugging and testing provided by LaunchDarkly eliminates the wait time for pull requests, fostering a culture of innovation and continuous improvement. Additionally, precise flag management enables the composite’s teams to quickly address issues, improving application stability and encouraging faster delivery of minimum viable products (MVPs), ultimately enhancing time-to-market.
Reduced annual deployment remediation costs by up to 90% worth $828,000. Implementing LaunchDarkly results in significant improvements in deployment frequency and simplicity at the composite organization. Deployments used to happen every few weeks and had a higher chance of a code or feature issue since each deployment included many code and feature updates, increasing complexity and leading to high remediation time and costs if there was an issue. With LaunchDarkly, deployments for the composite organization are more frequent — occurring even multiple times a day — and simpler, reducing the risk of issues and making it faster and easier to remediate an issue if anything does happen. With LaunchDarkly, the chance of a deployment issue happening at the composite decreases from 50% to 3%, and the cost to remediate an issue also decreases from $50,000 to $10,000. More frequent and reliable deployments significantly reduce costs associated with rollbacks, hotfixes, and support. The ability to quickly revert changes and deploy software multiple times a day also improves software stability and business performance.
Avoided costs of maintaining homegrown feature management worth $114,000. Before adopting LaunchDarkly, the composite managed homegrown or legacy feature flagging systems. These systems were often hard to scale, lacked real-time control, and couldn’t support granular targeting or safe rollbacks. Implementing LaunchDarkly helps reduce or eliminate costs related to maintaining these systems, including the ongoing engineering effort and maintenance required to support fragmented, homegrown feature flagging solutions.
Improved end-user employee effectiveness worth $102,000 in savings. Implementing LaunchDarkly provides the composite with better deployment management, fewer issues, and faster and more reliable software updates and feature enhancements. LaunchDarkly delivers value to employees across the composite organization, enabling end users to avoid delays and take advantage of improvements more quickly, saving 20% of their time while working with apps now deployed with LaunchDarkly. Before LaunchDarkly, regular deployment calls took hours (or longer if issues needed to be resolved) and involved many high-level IT and business managers. The number of deployment calls is significantly reduced or eliminated with LaunchDarkly by avoiding the bottlenecks of orchestrating coordinated releases. These improvements accelerate time to market, reduce delays, and ensure high-impact features are implemented more quickly to drive business value.
Improved margins attributed to new business opportunities and improved performance due to LaunchDarkly worth $168,000. With efficiencies also come opportunities for the composite. More frequent and reliable deployments result in fewer end-user issues and faster release of tools and features that support employees with direct revenue impact, such as those in sales and marketing teams. Executives and managers at the composite can also benefit from faster releases, leveraging AI-powered automation and data to make more informed decisions that lead to more successful business outcomes, avoiding missteps that can cause lost sales or higher governance and compliance costs. Overall, the composite organization estimates increased sales and other improved outcomes totaling $168,000 in added margin.
Unquantified benefits. Benefits that provide value for the composite organization but are not quantified for this study include:
Improved mobile app deployment. LaunchDarkly allows the composite to quickly address issues, such as crashes on devices, through precise flag management, improving the stability of the composite’s applications and accelerating time to market.
Enhanced developer experience. LaunchDarkly boosts developer motivation and productivity at the composite organization. Developers are now empowered to take ownership of their code, resulting in safer and more reliable software delivery. The ability to test and deploy AI features in real time has improved, enhancing team morale and software quality for the composite.
Improved innovation and stakeholder engagement. LaunchDarkly enhances the composite organization’s ability to innovate and respond to customer needs, leading to better internal and external stakeholder engagement and collaboration. Reduced complexity and costs have increased deployment frequency and reduced failure rates. Better control over feature rollouts and quick rollback capabilities further ensure a smoother deployment process.
Improved work-life balance and operational efficiency. LaunchDarkly helps the composite’s engineering teams experience a better work-life balance. By enhancing their ability to maintain application stability and reduce risk, engineers can avoid stressful remediation work, focus on new development, and avoid late-night and weekend emergencies. A more interesting and positive work environment also helps the composite organization by reducing attrition and avoiding expensive hiring costs.
Enhanced customer or end-user experience. Minimizing website downtime during deployments is critical to retaining customers and reducing churn. By leveraging LaunchDarkly to improve deployment processes, the composite organization can enhance end-user experience, boost customer satisfaction, and drive long-term loyalty.
Costs. Three-year, risk-adjusted PV costs for the composite organization include:
Implementation costs. The composite organization incurs $50,000 in implementation costs. This includes professional services charged by LaunchDarkly as well as internal labor costs of engineers’ time spent on planning and implementation. These costs reflect initial setup and integration efforts required to deploy LaunchDarkly effectively.
Annual software license costs. The composite organization pays $560,000 for LaunchDarkly licenses. This cost is based on typical enterprise pricing and reflects the ongoing expense of maintaining access to LaunchDarkly features and services. Pricing may vary. Contact LaunchDarkly for additional details.
Ongoing LaunchDarkly management costs. The composite organization allocates resources for ongoing management of the LaunchDarkly implementation as well as some incremental time for removing feature flags, totaling a cost of $141,000. These professionals oversee the integration, maintenance, and optimization of LaunchDarkly within the organization, ensuring it meets operational goals.
The financial analysis based on the interviews found that a composite organization experiences benefits of $3.6 million over three years versus costs of $751,000, adding up to a net present value (NPV) of $2.8 million and an ROI of 379%.
Developer testing and deployment productivity improvement
Return on investment (ROI)
Benefits PV
Net present value (NPV)
Payback
| Role | Industry | Region | Revenue | Employees | Engineers |
|---|---|---|---|---|---|
| Vice president of engineering | Human resources technology | United States | $31M | 206 | 35 |
| Head of digital engineering | Retail | Australia | $39B | 120,000 | 75 |
| Senior R&D manager | Data integration, quality, and analytics | Global | $750M | 3,100 | 700 |
| Manager of mobile platform | Financial services | United States | $8.4B | 11,100 | 250 |
| Director of engineering | Financial technology | United States | $2.3B | 7,400 | 275 |
| Director of engineering | Retail | United States | $150B | 400,000 | 125 |
Before implementing LaunchDarkly, the interviewees’ organizations faced several common challenges with their release processes and feature management. Typical prior solutions included manual coordination and monolithic release events, which were slow and prone to errors, resulting in long support and update cycles. These limitations led to various issues that hindered productivity and scalability for these organizations.
Interviewees noted how their organizations struggled with common challenges, including:
Inefficient release processes. Interviewees noted that their teams had to plan large, coordinated release events, often requiring early-morning or late-night efforts from many team members. These events were inconvenient, time-consuming, stressful, and sometimes took several hours to complete. Additionally, releases required significant manual coordination and communication among teams to include all desired code and feature updates, leading to inefficiencies and potential for errors.
Lack of feature isolation. The interviewees said their organization struggled with tightly coupled releases, in which code updates and multiple features were deployed simultaneously. This increased the risk of an issue impacting the entire application. With minimal tools to allow developers to test features independently with feature flags, it was challenging to test new features in production-like environments without exposing them to all users.
Limited flexibility and control. According to interviewees, the lack of feature flags often meant complete rollbacks in the event of application errors that crop up after deployment, leading to longer recovery times. Furthermore, deployment processes were rigid, making it hard to adapt to changing requirements or to deploy features incrementally.
Scalability issues. As interviewees’ organizations grew, existing release processes and tools did not scale well, resulting in increased complexity and risk. Managing releases required coordination across large teams and was resource-intensive, requiring significant time and effort from developers, QA, and operations teams.
Compliance and governance issues. Complicated and error-prone deployments made compliance difficult at the interviewees’ organizations. Internal and external governance requirements were a manual process and prone to errors and inefficiencies. Interviewees also noted that existing tools and processes did not provide adequate audit trails, making it difficult to track and verify compliance.
Lower developer productivity. Developers at the interviewees’ organizations often had to switch contexts between developing new features and managing releases, reducing overall productivity and increasing stress. The lack of immediate feedback on feature performance and issues in production environments delayed the identification and resolution of problems.
The interviewees searched for a solution that could:
Decouple deploy from release. Interviewees wanted a solution that would allow their teams to release features independently without affecting other parts of the application. This was crucial for reducing the risk associated with large, monolithic releases.
Allow feature edits without recompiling. They sought the ability to modify or edit features while it was running without redeploying.
Support incremental rollouts. They needed the ability to gradually roll out features to specific user segments or regions, ensuring stability and minimizing the impact of potential issues.
Enhance testing capabilities. They wanted to facilitate the testing of new features in production-like environments without exposing them to all users, thereby improving the quality and reliability of releases.
After a request for proposal (RFP) and business case process evaluating multiple vendors, the interviewees’ organizations chose LaunchDarkly and began deployment.
Phased deployment approach. Most interviewees’ organizations opted for a phased deployment approach, starting with pilot teams and gradually expanding to other teams and departments.
Broad adoption. LaunchDarkly was deployed to a significant portion of users within the interviewees’ organizations, with some reaching a substantial part of their engineering teams. This broad adoption was essential for maximizing the benefits of feature flagging and incremental rollouts.
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:
Description of composite. The composite organization is a global, multibillion-dollar enterprise operating in the financial services sector, headquartered in the United States. It offers a wide range of banking and financial products, including savings accounts, loans, investment services, and mobile banking solutions. The organization has a strong brand presence, global operations, and a large customer base. It maintains a robust online and offline presence, operating across multiple countries with a significant number of contact centers and agents.
Deployment characteristics. The composite organization begins using LaunchDarkly in Year 1, following a two-month implementation period. Deployment is focused on software engineering teams focused on internal application and tool development, totaling 300 developers. Company growth rates are not included for modeling simplicity, though any organization would be expected to have a growth plan in place that can be applied to a customized business case.
$12 billion in annual revenue
Global geographic focus, US headquarters
34,000 employees
300 software engineers now using LaunchDarkly
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Improved software developer testing and deployment productivity | $960,000 | $960,000 | $960,000 | $2,880,000 | $2,387,378 |
| Btr | Increased deployment remediation cost savings | $249,900 | $308,550 | $459,850 | $1,018,300 | $827,674 |
| Ctr | Avoided costs of maintaining homegrown feature management system | $23,750 | $47,500 | $71,250 | $142,500 | $114,378 |
| Dtr | Improved employee effectiveness | $38,988 | $40,572 | $44,136 | $123,696 | $102,134 |
| Etr | Improved margin attributed to LaunchDarkly | $67,500 | $67,500 | $67,500 | $202,500 | $167,863 |
| Total benefits (risk-adjusted) | $1,340,138 | $1,424,122 | $1,602,736 | $4,366,996 | $3,599,427 |
Evidence and data. Interviewees noted that feature flagging capabilities and less complex deployment processes with LaunchDarkly empowered their development teams to work more efficiently, reduce downtime, and deliver high-quality software at a faster pace, driving significant productivity gains across the board.
The senior R&D manager at a data integration, quality, and analytics company pointed out the immediate speed and ease of debugging and testing LaunchDarkly provided, which eliminated the wait time for pull requests to go through the pipeline. This efficiency broadened their team’s interest in advanced practices like A/B testing and early access, fostering a culture of innovation and continuous improvement. They told Forrester: “The speed is faster, it’s immediate. It’s easier to debug. It’s easier to test. You don’t have to sit and wait for a pull request to go through the pipeline.”
The senior R&D manager added that software engineers were interested in leveraging LaunchDarkly even more, saying: “We have more teams starting to be interested in A/B testing and early access and a lot of these things, which is great. I think we got a lot of value from that.”
Modeling and assumptions. [Based on the interviews, Forrester assumes the following about the composite organization:]
The composite organization has 300 engineers.
Each engineer spends about 24% of their time, or 500 hours annually, on testing and deployment activities before implementing LaunchDarkly.
Engineers save 20% of their time on testing and deployment activities after implementing LaunchDarkly, or 100 hours each year.
Fifty percent of time savings are applied to productive work tasks.
The fully burdened hourly rate for a software engineer in the United States is $80 based on data from the US Bureau of Labor and Statistics.3
Risks. The value of this benefit can vary across organizations due to the following:
Variability in adoption rates. Different teams and organizations may adopt LaunchDarkly at varying rates, impacting the overall productivity gains. Some teams might quickly integrate and leverage the tool effectively, while others may take longer to adapt, reducing the expected time savings. Additionally, some organizations might adopt only basic feature flagging, while others might leverage advanced features such as A/B testing and percentage rollouts.
Complexity of existing systems. Organizations with highly complex or legacy systems may face challenges in integrating LaunchDarkly, which could limit the potential productivity gains. The effort required to adapt and integrate the tool into existing workflows might be higher, affecting the overall benefit.
Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.4 million.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| A1 | Software engineers impacted by LaunchDarkly | Composite | 300 | 300 | 300 | |
| A2 | Time per engineer spent on testing and deployment activities before LaunchDarkly (hours) | Composite | 500 | 500 | 500 | |
| A3 | Time savings on testing and deployment activities with LaunchDarkly | Interviews | 20% | 20% | 20% | |
| A4 | Time per engineer saved with LaunchDarkly (hours) | A2*A3 | 100 | 100 | 100 | |
| A5 | Fully burdened hourly rate for a software engineer | Research data | $80 | $80 | $80 | |
| A6 | Percentage of time savings applied to work tasks | TEI methodology | 50% | 50% | 50% | |
| At | Improved software developer testing and deployment productivity | A1*A4*A5*A6 | $1,200,000 | $1,200,000 | $1,200,000 | |
| Risk adjustment | ↓20% | |||||
| Atr | Improved software developer testing and deployment productivity (risk-adjusted) | $960,000 | $960,000 | $960,000 | ||
| Three-year total: $2,880,000 | Three-year present value: $2,387,378 | |||||
Evidence and data. Several interviewees noted that implementing LaunchDarkly led to significant increases in deployment frequency, along with reduced deployment issues and remediation effort. These enhancements contributed to reduced costs associated with deployment issues and increased overall software reliability.
The vice president of engineering at a human resources technology company noted a substantial decrease in customer-facing issues due to the ability to quickly shut down problematic features, leading to a more reliable software experience so developers could spend less time on remediation. The adoption of LaunchDarkly allowed their company to transition to a rapid delivery model, with features rolled out over a minimum of 4 hours, ensuring stability and performance. They said: “We’ve seen a significant reduction in the number of customer-facing complaints about software errors, unavailability, or glitches that lead to feedback to our CS [customer support] or customer care teams. We moved to a rapid delivery model where every change is tied to a LaunchDarkly workflow that rolls out the feature.”
The head of digital engineering at a retail company said their organization faced challenges with monthly deployments that involved many stakeholders, manual testing, high rate of issues requiring remediation, and significant overhead. With LaunchDarkly, their organization achieved continuous delivery, moving from one deployment per month to multiple deployments per week. They said: “Before LaunchDarkly, we were experiencing a 50% failure rate due to the complexity and frequency of our releases. After implementing LaunchDarkly, our failure rate dropped to 2% to 3%, significantly reducing the costs associated with rollbacks, hotfixes, and customer support.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The chance of a deployment feature or code issue before LaunchDarkly was implemented was 50%.
The average cost of remediating a deployment issue with legacy deployment tools was $50,000. This includes the time and other costs associated with rolling back a complex deployment that includes multiple code and feature updates; investigating the issue amongst multiple code and feature updates; fixing and testing the update; redeploying the fix; and notifying users who may see a delay or outage, along with the opportunity cost of reduced business, such as lost sales during downtime.
The number of deployments before LaunchDarkly increased slightly over time but was never more than one every two weeks. Major coordinated deployments were scheduled 13 times in Year 1, 17 in Year 2, and 26 in Year 3.
The chance of a deployment feature or code issue with LaunchDarkly is 3%.
The average cost to remediate a deployment issue with LaunchDarkly is $10,000, reflecting a significant reduction in time and costs associated with rolling back a simple, focused deployment that includes just one or two code updates or features that can be turned off using feature flags.
LaunchDarkly enables a significant increase in deployment frequency with smaller, incremental releases. Deployments start at two per week in Year 1, then four per week in Year 2 and seven per week by Year 3, totaling 104, 208, and then 364 deployments per year, respectively.
Risks. The value of this benefit can vary across organizations due to the following:
Variability in initial remediation issues or deployment rates before implementing LaunchDarkly. Some organizations may have a lower or higher failure rate than the assumed 63% of deployments facing remediation issues. An organization’s size, industry, and deployment practice maturity can mean the number of deployments before may vary.
Differences in cost per incident. The assumed cost per incident may vary significantly across organizations depending on the nature of incidents, the resources required for resolution, and whether they use deployment flagging tools.
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 $828,000.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| B1 | Software deployments before LaunchDarkly | Composite | 13 | 17 | 26 | |
| B2 | Chance of a deployment feature or code issue before LaunchDarkly | Composite | 50% | 50% | 50% | |
| B3 | Average issues per year before LaunchDarkly | B1*B2 | 6.5 | 8.5 | 13.0 | |
| B4 | Cost per issue before LaunchDarkly | Composite | $50,000 | $50,000 | $50,000 | |
| B5 | Cost of remediating deployment issues before LaunchDarkly | B3*B4 | $325,000 | $425,000 | $650,000 | |
| B6 | Software deployments per year with LaunchDarkly | Composite | 104 | 208 | 364 | |
| B7 | Chance of a deployment feature or code issue with LaunchDarkly | Composite | 3% | 3% | 3% | |
| B8 | Average issues per year with LaunchDarkly | B6*B7 | 3.1 | 6.2 | 10.9 | |
| B9 | Cost per issue with LaunchDarkly | Composite | $10,000 | $10,000 | $10,000 | |
| B10 | Cost of remediating deployment issue before LaunchDarkly | B8*B9 | $31,000 | $62,000 | $109,000 | |
| B11 | Reduction in deployment remediation costs with LaunchDarkly | 1-B10/B5 | 90% | 85% | 83% | |
| Bt | Increased deployment remediation cost savings | B5-B10 | $294,000 | $363,000 | $541,000 | |
| Risk adjustment | ↓15% | |||||
| Btr | Increased deployment remediation cost savings (risk-adjusted) | $249,900 | $308,550 | $459,850 | ||
| Three-year total: $1,018,300 | Three-year present value: $827,674 | |||||
Evidence and data. Interviewees noted that their homegrown feature flag deployment tools lacked scalability and incurred high costs, primarily due to ongoing maintenance costs and continuous engineering effort required to support and update these fragmented solutions.
The director of engineering at a retail organization shared that their homegrown system lacked individual control. They explained, “A bug from one team caused rollbacks for all teams.” After implementing LaunchDarkly, their organization was able to retire its homegrown legacy software systems and the costs associated with them.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Cost savings focus on the ongoing support, maintenance, and engineering efforts required to maintain the system. While the solution may have required significant initial investment, that is not included in this analysis.
The maintenance cost savings associated with legacy systems are $25,000 for Year 1. This savings increases to $50,000 in Year 2 and $75,000 in Year 3, reflecting increased support, maintenance, and technical debt for what would be an increasingly aging solution.
Risks. The amount of this benefit can vary across customers due to differences in the legacy systems and licensing of other software solutions.
Results. To account for these risks, Forrester adjusted this benefit downward by 5%, yielding a three-year, risk-adjusted total PV of $114,000.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| C1 | Avoided costs of maintaining homegrown feature management system | Composite | $25,000 | $50,000 | $75,000 | |
| Ct | Avoided costs of maintaining homegrown feature management system | C1 | $25,000 | $50,000 | $75,000 | |
| Risk adjustment | ↓5% | |||||
| Ctr | Avoided costs of maintaining homegrown feature management system (risk-adjusted) | $23,750 | $47,500 | $71,250 | ||
| Three-year total: $142,500 | Three-year present value: $114,378 | |||||
Evidence and data. Interviewees reported that app and feature deployment issues could lead to outages and infrequent deployments meant that new code and feature updates reached internal teams later, delaying the impact of automation and other time-saving capabilities. They noted delay times ranging from 3 hours to several days when using other legacy and homegrown solutions. Teams often spent hours in large-scale deployment and response meetings, consuming valuable engineering and operations time.
The manager of the mobile platform at a financial services company highlighted significant time savings, saying, “We used to have 4 a.m. release calls with 50–100 people that lasted 4+ hours. Now, it’s a handful of people for 1 to 2 hours. If something goes wrong, we flip the flag and fix it later.”
The director of engineering at a retailer reported that LaunchDarkly improved store activities, saying: “We would produce one big update to deploy to our stores once a month. If any team involved in that update introduced a bug, the whole release would have to roll back, and that was very painful for our retail operations teams. With LaunchDarkly, we have increased our deployment frequency which means we can very quickly turn off a feature that didn’t work as expected and decrease resolution time.”
The director of engineering at a financial technology organization said: “Being able to roll software out, test it, and get feedback fast is huge. It has made the organization faster and more agile.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
3,000 employees now use apps and tools that have been impacted by LaunchDarkly. These employees are from a variety of teams that would use apps and tools developed internally, such as sales, marketing, finance, human resources, and others.
These employees spend an average of 4 hours per week working with apps that are now deployed with LaunchDarkly.
Since implementing LaunchDarkly, employees have seen a 15% improvement in this work time. This is due to more reliable apps, faster access to new features, better tools for accessing data sources, etc., all of which help employees automate or work on tasks more quickly.
The average fully burdened hourly rate for a general business worker is $47 based on data from US Bureau of Labor and Statistics.4
Before LaunchDarkly, a number of developers and managers would gather to meet and discuss each deployment — a meeting that on average took 2 hours, longer if there were issues.
An average of six developers and managers attended each meeting.
The average fully burdened hourly rate for a developer or manager attending these meetings is $110 based on data from US Bureau of Labor and Statistics.5
Seventy-five percent of the total meeting time and cost is now avoided with LaunchDarkly. Deployment meetings still occur but they are shorter, require fewer people, and are not needed nearly as often as every deployment.
For both general employees and deployment meeting participants, 50% of time savings is applied to productive work tasks.
Risks. This benefit may vary across organizations based on the number of employees who use LaunchDarkly-improved apps and how quickly they adopt new apps, as well as the frequency and impact of deployment meetings before LaunchDarkly.
Results. To account for these risks, Forrester adjusted this benefit downward by 20%, yielding a three-year, risk-adjusted total PV of $102,000.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| D1 | Employees using applications and tools now deployed with LaunchDarkly | Composite | 3,000 | 3,000 | 3,000 | |
| D2 | Time per employee per week spent working on tasks using those applications and tools (hours) | Composite | 4 | 4 | 4 | |
| D3 | Improved productivity with apps and tools now deployed with LaunchDarkly | Interviews | 15% | 15% | 15% | |
| D4 | Employee time saved with LaunchDarkly (hours) | D1*D2*D3 | 1,800 | 1,800 | 1,800 | |
| D5 | Average fully burdened hourly rate for a business worker | Research data | $47 | $47 | $47 | |
| D6 | Percentage of time savings applied to work tasks | TEI methodology | 50% | 50% | 50% | |
| D7 | Subtotal: Total employee time savings | D4*D5*D6 | $42,300 | $42,300 | $42,300 | |
| D8 | Deployment meetings per year before LaunchDarkly | B1 | 13 | 17 | 26 | |
| D9 | Time per meeting (hours) | Composite | 2 | 2 | 2 | |
| D10 | Employees per meeting | Composite | 6 | 6 | 6 | |
| D11 | Reduction in deployment meeting time with LaunchDarkly | Interviews | 75% | 75% | 75% | |
| D12 | Deployment meeting hours saved with LaunchDarkly | D8*D9*D10*D11 | 117 | 153 | 234 | |
| D13 | Average fully burdened hourly rate for a developer and manager | Research data | $110 | $110 | $110 | |
| D14 | Percentage of time savings applied to work tasks | TEI methodology | 50% | 50% | 50% | |
| D15 | Subtotal: Total deployment meeting time savings | D12*D13*D14 | $6,435 | $8,415 | $12,870 | |
| Dt | Improved employee effectiveness | D7+D15 | $48,735 | $50,715 | $55,170 | |
| Risk adjustment | ↓20% | |||||
| Dtr | Improved employee effectiveness (risk-adjusted) | $38,988 | $40,572 | $44,136 | ||
| Three-year total: $123,696 | Three-year present value: $102,134 | |||||
Evidence and data. Interviewees highlighted several benefits that impacted their organizations’ bottom line, such as additional cost savings, increased business opportunities, avoided business mistakes, and increased revenue. LaunchDarkly provided employees at the interviewees’ organizations with the most up-to-date tools and apps so they could perform their jobs at a higher level and deliver better services to employees serving customers. These LaunchDarkly-improved tools and apps also allowed these organizations to deliver a better and more useful app experience to their customers and the data and tools needed for managers and executives to take advantage of business opportunities. Examples from interviewees included:
The director of engineering at a retailer highlighted the value of getting apps into the hands of store employees as quickly as possible, saying, “Each one of our new features is worth about $6 million on average.”
The manager of the mobile platform noted that their financial services company also adopted LaunchDarkly for its consumer app development team. They attributed improved customer retention to LaunchDarkly. The mobile platform manager said, “When it comes to customer retention and maintaining our app store reputation, LaunchDarkly is a critical part of our release structure.”
The VP of engineering at a human resources technology organization said that they saved significant hosting costs by consolidating test environments, saying: “We had multiple QA environments. It was super difficult to manage. One of our first goals once we had LaunchDarkly was getting down to a single QA environment.”
The manager of mobile platform at the financial services company also pointed to the ease in tracking changes with LaunchDarkly: “It’s definitely helped us improve audit logs. We have more evidence to show that we’ve done our due diligence for each release.”
The head of digital engineering at a retailer said they could now quickly address and resolve issues with LaunchDarkly. They noted avoiding issues ensured that customer experience and business continuity were maintained, saying, “If a big feature that was going to increase the revenue of the business was delayed, it could be a week to 30 days until the next release window.”
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Some revenue and profit improvement is attributable to LaunchDarkly. This could include new sales, avoided business risks, and other revenue-generating or cost-saving activities.
An amount estimated at one-eighth of total revenue, or $1.5 billion, is impacted by apps and tools delivered to employees and others with LaunchDarkly.
A net revenue gain of 0.10% is attributed to LaunchDarkly. That totals $1.5 million in incremental revenue.
To measure direct value to the organization, operating margin is applied. The composite organization is assumed to have an operating margin of 6% based on the majority of interviewees from financial services and retail industries.
Risks. The value of this benefit can vary across organizations because of differences in operations, sales, cost savings, and other opportunities. This analysis is based on estimates of incremental revenue and margin, as interviewees were unable to share more direct details, such as additional sales and the impact of compliance and audit issues.
Results. To account for these risks, Forrester adjusted this benefit downward by 25%, yielding a three-year, risk-adjusted PV of $168,000.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| E1 | Revenue impacted by apps and tools now deployed with LaunchDarkly | Composite | $1,500,000,000 | $1,500,000,000 | $1,500,000,000 | |
| E2 | Improvement in revenue with LaunchDarkly | Interviews | 0.10% | 0.10% | 0.10% | |
| E3 | Operating margin | Composite | 6% | 6% | 6% | |
| Et | Improved margin attributed to LaunchDarkly | E1*E2*E3 | $90,000 | $90,000 | $90,000 | |
| Risk adjustment | ↓25% | |||||
| Etr | Improved margin attributed to LaunchDarkly (risk-adjusted) | $67,500 | $67,500 | $67,500 | ||
| Three-year total: $202,500 | Three-year present value: $167,863 | |||||
Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify:
Improved mobile app deployment. The manager of mobile platform at a financial services company shared how LaunchDarkly saved their teams considerable time by allowing them to quickly address issues, such as device crashes, through precise flag management. This capability not only improved the stability of their applications but also sped up their time to market. They said: “[LaunchDarkly] saved my teams quite a lot. We had a small exception error causing some crashes. We were able to tightly time the crash logs and turn off the flag. It’s shaped the culture of how we get our apps out the door faster.”
Enhanced developer experience. Interviewees noted that with LaunchDarkly, their developers were empowered to take ownership of their code, resulting in safer and more reliable software delivery. Additionally, the ability to test and deploy AI features improved, allowing for real-time model performance evaluation and ranking. These improvements boosted team morale at the interviewees’ organizations and enhanced the quality and reliability of their software. The vice president of engineering at a human resources technology company said: “Developers are now more motivated and productive. They are empowered to take ownership of their code, resulting in safer and more reliable software delivery.”
Improved innovation and stakeholder engagement. LaunchDarkly enabled better internal and external stakeholder engagement and collaboration at the interviewees’ organizations. With better control over feature rollouts and quick rollback capabilities, developers had more time and opportunities to innovate instead of fixing deployment issues. R&D teams at the interviewees’ organizations were also more involved, fostering a more collaborative and efficient development environment. The head of digital engineering at a retail company said, “Our ability to innovate and respond to customer needs has improved, leading to better internal stakeholder engagement and collaboration.”
Improved work-life balance and operational efficiency. The manager of the mobile platform at a financial services firm said, “Our engineering teams have experienced improvements in work-life balance, enhancing their ability to maintain application stability and reduce risk.” The interviewee also noted their teams gained the ability to decouple releases, which improved new feature speed to market and further reduced risk. Reducing and avoiding deployment meetings — especially those that used to happen outside the normal workday — improved team well-being. Additionally, a better work environment helped the manager’s organization by reducing attrition, avoiding the costs of hiring, recruiting, and training.
Enhanced customer or end-user experience. Interviewees noted that minimizing website downtime — especially for e-commerce sites — during deployments was critical to retaining customers and reducing churn. Even late-night deployments could impact customers. By leveraging LaunchDarkly to enhance deployments, the interviewees’ organizations could eliminate end-user experience issues, boosting customer satisfaction and driving long-term loyalty.
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement LaunchDarkly and later realize additional uses and business opportunities, including:
Enablement of more strategic feature releases. Interviewees said the platform supports beta, private, and public previews, enabling their teams to gather meaningful feedback and fine-tune features before a full rollout. The vice president of engineering at a human resources technology company said, “We can have conversations like, ‘Are we putting it into beta? Are we going to do a private preview? Are we going to do this as a public preview?’”
Facilitation of the transition to micro front ends. This allowed different feature teams at the interviewees’ organizations to release independently, reducing the risk of interdependent failures and enabling more agile development. The manager of the mobile platform at a financial services company said, “We quickly stood up a way that we could federate our micro front end and have the different feature teams released independently of one another.”
Support for organizational growth and scalability. According to interviewees, the platform made it easier to manage a growing number of components and services, enabling their organizations to scale efficiently. The senior R&D manager in data integration, quality, and analytics told Forrester, “LaunchDarkly makes it easier for us to grow and scale so we can add more and more components.”
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Ftr | Implementation costs | $50,400 | $0 | $0 | $0 | $50,400 | $50,400 |
| Gtr | Annual software license costs | $0 | $225,000 | $225,000 | $225,000 | $675,000 | $559,542 |
| Htr | Ongoing LaunchDarkly management costs | $0 | $56,784 | $56,784 | $56,784 | $170,352 | $141,213 |
| Total costs (risk-adjusted) | $50,400 | $281,784 | $281,784 | $281,784 | $895,752 | $751,155 |
Evidence and data. Interviewees noted that their organizations experienced costs around implementation, including the cost of LaunchDarkly’s professional services and internal labor.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The composite organization leverages the initial professional services assistance provided by LaunchDarkly, which costs $10,000.
Additionally, planning and implementation efforts cost $38,000, reflecting the time and engineering resources required over several weeks to integrate the platform effectively.
Risks. The value of this cost can vary across organizations due to the following:
Differences in the duration and complexity of the implementation process, which can lead to varying internal labor costs.
Variability in the number of engineers required and their availability, impacting the overall cost and timeline of the implementation.
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 $50,000.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| F1 | Initial professional services | Composite | $10,000 | |||
| F2 | Planning and implementation | Composite | $38,000 | |||
| Ft | Implementation costs | F1+F2 | $48,000 | $0 | $0 | $0 |
| Risk adjustment | ↑5% | |||||
| Ftr | Implementation costs (risk-adjusted) | $50,400 | $0 | $0 | $0 | |
| Three-year total: $50,400 | Three-year present value: $50,400 | |||||
Evidence and data. Pricing for LaunchDarkly depends on the number of users and scope of deployment. Pricing may vary. Contact LaunchDarkly for additional details.
Modeling and assumptions. Based on the interviews, Forrester assumes the composite organization pays $225,000 annually for LaunchDarkly. LaunchDarkly provided these costs, reflecting standard pricing for a typical enterprise customer like the composite organization.
Risks. While no risk adjustment is applied here, the value of this cost can vary across organizations due to the following:
Variability in the number of users and scope of deployment.
Changes in subscription pricing based on contract negotiations and additional services required.
Results. To account for these risks, Forrester adjusted this cost upward by 0%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $560,000.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| G1 | Annual software license costs | Composite | $225,000 | $225,000 | $225,000 | |
| Gt | Annual software license costs | G1 | $0 | $225,000 | $225,000 | $225,000 |
| Risk adjustment | 0% | |||||
| Gtr | Annual software license costs (risk-adjusted) | $0 | $225,000 | $225,000 | $225,000 | |
| Three-year total: $675,000 | Three-year present value: $559,542 | |||||
Evidence and data. Interviewees told Forrester that they spent time on ongoing management of the LaunchDarkly implementation at their organizations.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The composite spends some incremental time managing the LaunchDarkly solution and relationship as well as the new developer task of periodically removing feature flags.
This time is allocated to software engineers, IT professionals, and managers.
The average fully burdened hourly rate for these employees is $80 based on the US Bureau of Labor and Statistics.6
Risks. The value of this cost can vary across organizations due to the following:
Variability in the number of hours required for management, which can fluctuate based on the complexity of the organization’s use of LaunchDarkly.
Potential changes in the scope of management activities over time, which could increase or decrease the required effort and associated costs.
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 $141,000.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| H1 | Average weekly LaunchDarkly management time (hours) | Composite | 13 | 13 | 13 | |
| H2 | Average fully burdened hourly rate for a professionals managing the LaunchDarkly services and relationship | Research data | $80 | $80 | $80 | |
| Ht | Ongoing LaunchDarkly management costs | H1*H2*52 | $0 | $54,080 | $54,080 | $54,080 |
| Risk adjustment | ↑5% | |||||
| Htr | Ongoing LaunchDarkly management costs (risk-adjusted) | $0 | $56,784 | $56,784 | $56,784 | |
| Three-year total: $170,352 | Three-year present value: $141,213 | |||||
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($50,400) | ($281,784) | ($281,784) | ($281,784) | ($895,752) | ($751,155) |
| Total benefits | $0 | $1,340,138 | $1,424,122 | $1,602,736 | $4,366,996 | $3,599,427 |
| Net benefits | ($50,400) | $1,058,354 | $1,142,338 | $1,320,952 | $3,471,244 | $2,848,272 |
| ROI | 379% | |||||
| Payback | <6 months |
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 LaunchDarkly.
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 LaunchDarkly can have on an organization.
Interviewed LaunchDarkly stakeholders and Forrester analysts to gather data relative to LaunchDarkly.
Interviewed six decision-makers at organizations using LaunchDarkly to obtain data about costs, benefits, and risks.
Designed a composite organization based on characteristics of the interviewees’ organizations.
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.
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.
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 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 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 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.”
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.
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.
A project’s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits less costs) by costs.
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%.
The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs) equal initial investment or cost.
Christopher Condo, Feature Management And Experimentation — An Evolving Market, Forrester Blogs.
The Forrester Tech Tide™: Software Development, Q4 2024, Forrester Research, Inc., October 17, 2024.
The Feature Management And Experimentation Solutions Landscape, Q1 2024, Forrester Research, Inc., March 11, 2024.
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.
1 Source: The Feature Management And Experimentation Solutions Landscape, Q1 2024, Forrester Research, Inc., March 11, 2024.
2 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.
3 Source: US Bureau of Labor Statistics, June 2025.
4 Ibid.
5 Ibid.
6 Ibid.
Readers should be aware of the following:
This study is commissioned by LaunchDarkly 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 LaunchDarkly. 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 LaunchDarkly based on the inputs provided and any assumptions made. Forrester does not endorse LaunchDarkly or its offerings. Although great care has been taken to ensure the accuracy and completeness of this model, LaunchDarkly 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 LaunchDarkly make no warranties of any kind.
LaunchDarkly 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.
LaunchDarkly provided the customer names for the interviews but did not participate in the interviews.
Roger Nauth
Sindhi Ballal
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