The Total Economic Impact™ Of Dynatrace

AI-Powered Incident Detection And Resolution Efficiency

Evidence and data. Interviewees reported that Dynatrace’s AI capabilities fundamentally changed how their organizations detect, investigate, and respond to incidents. By leveraging Davis AI -AI-powered observability, automated root cause analysis, and intelligent anomaly detection- teams reduced the manual effort required to identify problems, determine business impact, and coordinate remediation activities. Rather than relying on engineers to correlate data across multiple tools manually, interviewees used Dynatrace to automatically surface probable root causes, prioritize issues based on customer and business impact, and enable teams to act sooner. As a result, organizations reduced MTTR, decreased reliance on large war rooms, and prevented many lower-severity issues from escalating into customer-facing outages.

• The principal site reliability engineer at a telecommunications organization explained that Dynatrace dramatically shortened the time to pinpoint issues: “Understanding the root cause or where to look for an issue has significantly decreased. We now can see it right away.” This immediate visibility eliminated manual guesswork and reduced the time developers and operations teams spent isolating problems. The interviewee added that by removing context switching between multiple monitoring tools, “time to triage and investigate [incidents] is at least 15 to 30 minutes faster per incident” compared to prior practices.

• The CIO at a financial services firm said that Dynatrace’s AI-assisted problem determination reduced the time spent in war rooms for P1 or P2 critical incidents by providing a unified, end-to-end view of system health. They noted, “Problem determination, problem identification, and problem notification is much, much shorter now.” With Dynatrace, their team could immediately determine whether an issue was on the mainframe, an open system, or a failing process, avoiding large cross-vendor meetings. The CIO reported, “The time in the war room has greatly decreased — we spend probably 50% less time there than before.” Average problem identification time for P1 or P2 incidents fell from around 4 hours to around 2 hours, as teams could isolate issues faster and engage the right experts sooner. This decrease in war room duration directly reduced lost productivity for up to 20 people who were often involved in major incident calls, as well as faster service restoration for the business.

• Interviewees also emphasized that Dynatrace’s AI-driven alerts and end-to-end visibility enabled them to address lower-severity issues before they evolved into major outages. One IT leader noted that their teams are now “fixing alerts before they crash and cause outages,” highlighting how Dynatrace helps detect anomalies (e.g., a degrading API or a filling log) early and trigger action to avoid downtime. Another interviewee shared that the profile of incidents fundamentally shifted after Dynatrace, and “the type of incidents we had four years ago, we no longer have now” because they catch and resolve many routine failures at the P3 or P4 level before they impact customers. This proactive approach not only reduced the occurrence of severe P1 outages but also improved efficiency across all incident tiers by containing issues at lower levels where they require less effort to fix.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization experiences 450,000 operational infrastructure, network, and application monitoring alerts in the prior environment across all severity levels.

• Alerts are distributed across severity levels, with a mix of high severity (P1 or P2), moderate (P3), and low severity (P4) incidents.

• The composite organization reduces the time spent resolving P1 incidents by an average of 2 hours per incident, driven by faster root cause identification and reduced coordination effort.

• To address P1 level incidences, the composite convenes war rooms with 20 people.

• The average fully burdened hourly rate for war room personnel is $76.

• With Dynatrace, the composite saves 1 hour resolving each P2 incident and 0.75 hours resolving each P3 incident due to improved visibility and reduced investigation time, which leads to faster triage and resolution.

• For P4 incidents, the composite sees 98% fewer alerts because Davis AI eliminates false positives and multiple alerts caused per core issue. It also enables faster triage and autoresolution, resulting in 0.25 hours saved per incident autoremediated due to improved visibility and reduced investigation time.

• For the remaining 2% of P4 alerts, Davis AI proactively detects and identifies the context of the incident, reducing manual effort and avoiding escalation.

• Of the time saved by deploying Dynatrace, Forrester conservatively estimates that 50% is recaptured for work on other tasks and initiatives, which is therefore included in the benefit calculation. 

Risks. Forrester recognizes that these results may not be representative of all experiences and the value of the benefit will vary depending on:

• The total number of applications being monitored.

• The percentages and severity of alerts being detected and remediated.

• The total number of staff participating in war rooms.

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 $14.4 million.

Improved Developer Productivity For New Features And Applications

Evidence and data. Interviewees reported that Dynatrace significantly reduced the time and effort spent by developers on troubleshooting and operational tasks, thereby freeing them to focus on new development work. For example:

• A principal site reliability engineer at a telecommunications organization explained that diagnosing a production issue previously took 45 minutes of a developer’s time, but the same task now requires 5 minutes with Dynatrace’s AI-assisted root cause analysis. Similarly, gathering logs and metrics for an issue dropped from between 15 and 20 minutes to about 1 minute. These efficiencies translated to nearly 90% less time spent per incident on certain debugging tasks.

• Interviewees shared that their developers no longer need to coordinate with separate monitoring teams for new applications or changes, saving substantial effort. The senior director of IT at a healthcare organization estimated that previously, 10 to 20 hours per project were spent in back and forth dialogue with the monitoring team to set up and validate observability, which Dynatrace’s automation now handles. With roughly 50 new applications onboarded per year, this equates to hundreds of developer hours saved — about one-tenth of an FTE’s effort avoided — according to the interviewee.

• By reducing time on manual tasks and resolving unexpected issues, Dynatrace enabled faster delivery of new features and fixes. The director of the site reliability office at the telecommunications organization observed that major software releases, which used to take 10 to 15 weeks, are now completed in two to four weeks, and minor code fixes that previously required about one week often roll out the same day. The interviewee directly tied this increased velocity to developers spending more time coding and less time troubleshooting.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite has 200 developers using Dynatrace.

• Thirty percent of developers’ time is impacted by Dynatrace.  

• Developers spent an average of 1,248 on new development projects.

• After Dynatrace, developers experienced 30% increased efficiency from reduced troubleshooting and faster debugging in new features and applications.              

• The fully burdened hourly rate for a developer is $76.

• Of the time saved from deploying Dynatrace, Forrester conservatively estimates that 50% is recaptured for work on other tasks and initiatives, which is therefore included in the benefit calculation. 

Risks. Forrester recognizes that these results may not be representative of all experiences and the value of the benefit will vary depending on:

• The frequency and complexity of incidents.

• Teams that already had strong incident management and automation may realize smaller improvements compared to those that had highly manual processes.

• The degree to which saved time is used for additional productive work (versus absorbed by other duties or downtime) can influence the true economic impact for each 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 $2.0 million.

Increased Profit From Dynatrace Business Impact

Evidence and data. Interviewees said that improved application performance, reliability, and business observability translated into tangible top-line benefits. By improving digital customer experiences and reducing downtime, their organizations boosted revenue and protected profit margins.

• Several interviewees said Dynatrace’s proactive monitoring and faster incident resolution helped prevent lost sales during critical periods. The director of the site reliability office at a telecommunications organization noted that their most recent Black Friday — historically prone to performance issues — was a nonevent in terms of incidents. This stability avoided the sizable revenue leakage that previously occurred during peak traffic events. Overall, interviewees indicated 50% or greater reductions in high-severity incidents, thereby minimizing revenue-impacting outages. As the principal site reliability engineer at a telecommunications organization explained, “Because Dynatrace helps us reduce incidents, we’re preventing revenue loss.”

• Dynatrace’s real-user monitoring and business analytics enabled organizations to identify and fix user experience issues that were causing customer drop-off or dissatisfaction. The CIO at a financial services firm shared how Dynatrace exposed performance bottlenecks in their online loan application process that were causing customers to abandon applications. After identifying and fixing bottlenecks in their customer journey, the firm saw a 12-point increase in Net Promoter Score for that digital channel and increased completion of online loan applications from 65% to 95%.² The CIO said: “This was very beneficial for us in terms of subscription rate and success rate of online personal loans. If you consider that we spend about a million euros per month on digital marketing, it means a higher number of successful customer acquisitions.”

• With Dynatrace improving DevOps efficiency and production stability, organizations could introduce new digital services and features more quickly and confidently. The director of the site reliability office at a telecommunications organization described launching new major capabilities with a roughly 70% faster release cycle for key revenue-generating features. This acceleration meant that new products or enhancements started contributing to sales and profit weeks or months sooner than they would have without Dynatrace — effectively pulling revenue forward and improving cash flow for the business.

• Improved service performance and transparency yielded higher customer satisfaction and retention, which in turn safeguarded future revenues. The CIO at the financial services firm used Dynatrace to rapidly resolve performance issues in a customer-facing sales platform, eliminating the complaints that had been jeopardizing partner relationships. The result: They have not lost a major distribution partner due to technology issues in more than four years, after previously facing partner attrition from service disruptions. Keeping key partners and customers engaged helped preserve revenue streams that might otherwise have been at risk from churn or defections due to poor digital experiences.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization is a $7 billion company that has a 10% operating margin.

• The composite experiences 0.2% revenue growth due to faster product releases and improved customer experiences that result in increased sales.

• Of that 0.2% revenue growth, 20% is attributable to Dynatrace.

• The composite avoids 0.2% in revenue losses due to the proactive monitoring and faster remediation of incidences.

• Of the 0.2% of avoided revenue losses, 80% is attributable to Dynatrace.

Risks. Forrester recognizes that these results may not be representative of all experiences and the value of the benefit will vary depending on:

• The overall size of an organization.

• The operating margin of an organization.

• The degree of Dynatrace adoption to innovate or to fix and remediate application issues.

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 $3.1 million.

Operating Cost Containment And Consumption Visibility

Evidence and data. Interviewees described avoiding significant cost growth in IT operations by using Dynatrace’s platform to better govern resource consumption.

• One financial services organization had been paying €5 million annually for mainframe capacity with 5% to 10% year-over-year cost increases due to rising transaction volumes. Using Dynatrace’s insights to optimize inefficient mainframe processes, the firm was able to keep mainframe charges flat for four consecutive years despite sustained workload growth. This equated to hundreds of thousands of euros per year in avoided cost escalation. The CIO at this firm said: “When I arrived here, we had an increase of 5%, 7%, 3%, and 10% in our deal with IBM every year. In the last four years, the volume of personal loans we sell each year has been growing by 5% to 10% year over year, and the cost we pay to IBM has remained stable because we are able to intervene, identify, and optimize our processes on the mainframe.”             

• With Grail, Dynatrace’s unified data lakehouse, and flexible data controls, interviewees reduced log management expenses by up to 50%. For example, one interviewee reported that their organization cut log analytics costs from €150,000 to €75,000 per year after consolidating logs onto Dynatrace’s platform. Interviewees said that Dynatrace’s architecture avoided heavy indexing overhead, and by ingesting only necessary data and eliminating duplicate storage they could contain cloud storage and processing fees that would have otherwise grown with expanding log volumes.

• As organizations expand their use of LLMs and AI services, controlling consumption has become a growing cost-management challenge. The staff technical program manager at a telecommunications organization reported that Dynatrace’s visibility into AI agent activity and token consumption enabled their organization to identify inefficient model usage and adjust which models were used for specific tasks. According to this interviewee, these changes reduced AI token consumption by nearly 20%. Beyond improving operational visibility, interviewees also gained a mechanism for containing AI costs by reducing unnecessary use of higher-cost models and establishing greater control over AI spending as adoption increased.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• Before Dynatrace, the composite spent $5,000,000 on mainframe costs, which increased 8% every year.

• After Dynatrace, mainframe costs no longer increase every year.

• Before Dynatrace, the composite spent $350,000 on AI tokens, with a 30% increase each year.

• By using Dynatrace, the composite conservatively reduces token spend by 20%.

• Before Dynatrace, the composite spent $150,000 on log storage costs each year.

• Dynatrace allows the composite to save 50% in log storage costs each year.

Risks. Forrester recognizes that these results may not be representative of all experiences and the value of the benefit will vary depending on:

• The degree to which an organization previously controlled its costs for data retention policies.

• The AI token visibility benefit assumes a growing use of LLM services; if an organization’s AI use remains minimal, cost savings in this area might be negligible.

• Achieving these savings requires actively leveraging features like metric ingestion controls, retention settings, and AI usage dashboards. Results will vary depending on how comprehensively an organization employs Dynatrace’s FinOps and cost governance capabilities.

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 $1.3 million.

IT Tool Consolidation Cost Savings

Evidence and data. Interviewees described hard-cost savings from retiring or avoiding redundant IT monitoring and analytics tools as they expanded their use of the Dynatrace platform.

• An interviewee from one of the telecommunications organizations said they replaced two major legacy APM products with Dynatrace and saved approximately $1.7 million in annual licensing costs. Their organization also decommissioned its standalone log analytics platform (Logz.io), handling log data via Dynatrace’s unified data lakehouse instead. This change delivered an additional $800,000 per year in avoided log storage and ingestion fees. Overall, this company’s Dynatrace rollout eliminated more than $2.5 million in annual third-party license spend, which the interviewee noted offset a substantial portion of its Dynatrace investment.

• Multiple interviewees reported double-digit percentage reductions in their total monitoring and operations costs post-consolidation. For instance, the managing director at a professional services firm noted that consolidating APM and log management into a single platform reduced overall monitoring costs by approximately 40%. The CIO at a financial services firm said they cut log management costs in half (from €150,000 to €75,000 per year) by migrating from an on-premises stack and using Dynatrace’s Grail for log data. Beyond software license fees, these savings also included avoided hardware, support, and maintenance costs, as Dynatrace’s SaaS platform replaced multiple on-premises tools and their infrastructure requirements.

• The senior director of IT at a healthcare organization said the savings from tool retirements allowed an expanded Dynatrace deployment with little to no net increase in budget — which they said effectively made coverage cost-neutral. Their organization retired its log analytics tools, legacy security and observability, and third-party APM suite and reallocated those budgets to Dynatrace, achieving a  broader monitoring scope without incremental spend.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• Before Dynatrace, the composite paid $1.7 million per year for its legacy APM system and a separate infrastructure solution.

• The composite completely eliminates overlapping legacy APM tools by Year 3.

• The composite previously utilized a standalone log analytics platform, which cost $800,000 per year to support the enterprise’s log volumes.

• The composite completely eliminates overlapping log management tools by Year 3.

Risks. Forrester recognizes that these results may not be representative of all experiences and the value of the benefit will vary depending on:

• The number and cost of legacy applications an organization can eliminate.

• The contract terms for each legacy tool being eliminated.

• The speed at which an organization can reduce or eliminate its IT contracts.

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 $3.0 million.

Regulatory Reporting Efficiency

Evidence and data. Interviewees reported that Dynatrace reduced the time and effort to prepare regulatory and compliance-related incident reports by automatically capturing and correlating the technical, operational, and business context needed to document incidents. Rather than manually assembling information from multiple monitoring tools, log repositories, and stakeholder teams, organizations used Dynatrace to quickly identify the source of an incident, determine affected systems and services, understand customer and business impact, and document remediation activities. This enabled teams to respond more effectively to increasingly stringent regulatory reporting requirements.

An interviewee from a financial services firm highlighted the growing importance of the European Union’s Digital Operational Resilience Act (DORA), which requires regulated organizations to rapidly notify regulators following significant incidents and provide detailed information regarding system impacts, customer impacts, and corrective actions. The interviewee explained that these reports typically require close coordination among technology and business stakeholders under aggressive timelines. By leveraging Dynatrace, their firm was able to automatically populate four of the seven required sections of its DORA incident reports, significantly reducing the manual effort required to gather and validate information.

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization writes incident reports for 450 P1 alerts.

• A cross-functional team of four, including IT operations, DevOps, security, and compliance, participates in report writing.

• Before Dynatrace, the composite required 10 hours of participants’ time. Dynatrace reduced that time commitment by 50% by its AI tools prepopulating information previously gathered manually.

• The fully burdened hourly rate for an IT engineer is $76.

• Of the time saved from deploying Dynatrace, Forrester conservatively estimates that 50% is recaptured for work on other tasks and initiatives, which is therefore included in the benefit calculation. 

Risks. Forrester recognizes that these results may not be representative of all experiences and the value of the benefit will vary depending on:

• Regulatory reporting requirements vary by industry and geography.

• Manual review and compliance approvals may still be required.

• Existing compliance processes may already be mature.

• Benefits depend on an organization’s adoption of business-impact and observability capabilities.

• The number of reportable incidents may be lower than anticipated.

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 $765,000.

Unquantified Benefits

Interviewees mentioned the following additional benefits that their organizations experienced but were not able to quantify:

• Enabling AI-driven automation and lowering barriers to application development. Interviewees described Dynatrace as a foundational platform that enables AI-driven automation and makes advanced observability data accessible to a broader set of users. The principal site reliability engineer from the telecommunications organization said that their engineering teams integrated Dynatrace into an internal AI-powered Slack chatbot that automatically generates diagnostics and answers performance questions, enabling developers to access insights without navigating the platform directly. This capability reduces reliance on specialized expertise and accelerates issue resolution. This interviewee explained: “Using this tool is the great equalizer. We have people trapped in the toil of their day-to-day [work], who, for example, have been incredible ops professionals but haven’t had the dev knowledge to code something themselves and execute on their ideas. That barrier is effectively removed.” By embedding observability data into automation workflows and AI tools, organizations expand who can build, troubleshoot, and improve applications — reducing dependency on highly specialized roles and enabling faster innovation and iteration.

• Risk reduction for mainframe operations amid shrinking specialized skills. Dynatrace improves visibility into mainframe transactions and logs, helping manage operational risk when mainframe expertise is scarce. The head of IT service analytics in financial services said: “Fewer and fewer people know the mainframe, and every tool that helps [organize] the chaos is great. This stabilizes our mainframe operations, which are still important. We have only a few people internally with deep mainframe knowledge, so Dynatrace helps us get a good, decent view of the mainframe as well. If we lost those remaining mainframe skills, we’d have a huge business and compliance problem.”

• Avoided cost to build a regulatory and compliance reporting tool. Interviewees said that Dynatrace’s observability platform significantly eased their regulatory and compliance reporting burdens. By automatically collating critical incident details (e.g., root cause, impacted systems, customer impact) into a single “problem” record, Dynatrace enabled them to prepare mandated reports within hours, meeting regulatory deadlines and avoiding penalties. Interviewees also highlighted built-in AIOps capabilities (e.g., Davis AI) that automatically generated comprehensive evidence and impact analysis, reducing the need for manual data gathering. The CIO in financial services avoided developing a custom reporting solution: “We have this functionality out of the box and didn’t have to spend $800K to build this. I cannot [give] enough thanks to Dynatrace. This is an example of a benefit that you get out of the system out of the box.”

• Improved, consistent visibility across the entire IT ecosystem. Interviewees reported that Dynatrace enabled consistent observability across hybrid environments spanning cloud platforms and legacy systems such as mainframes, improving visibility into end-to-end transactions and dependencies. The CIO at the financial services firm explained, “We extended Dynatrace not only to our open system but also the mainframe, … enabling monitoring of the end-to-end customer experience.” Similarly, a technology leader at a SaaS platform provider described how centralization improved their ability to understand system behavior across environments: “Now it’s one single tool. … I can correlate network data, security data, application data, user data; everything is in one place.” This unified coverage reduces visibility gaps across heterogeneous architectures and supports more consistent enterprisewide monitoring and reliability practices.

• Increasing the value of ITSM and ITOM investments through real-time observability. Interviewees are challenged to manage incidents and outages in complex, distributed systems using ITOM and ITSM. To achieve autonomous operations, they need to see what’s happening in infrastructure and applications in real time and know exactly what’s broken, why it matters, and how to fix it fast. ITSM solutions then can act on it. The staff technical program manager in telecommunications described his vision for this: “There’s a big value add for integration between Dynatrace and [our ITSM solution]. When we talk about observability, if our engineers submit a change request and [our ITSM] says to Dynatrace, ‘Hey Dynatrace, we’re making a change on this application, on this infrastructure piece. Ignore alerting us for 5 minutes because we know we have to reboot XYZ for this code to be installed.’ And then it gives us feedback and we can quickly diagnose a problem because of a change we implemented. In a perfect world, Dynatrace is giving this data to [our ITSM]. We’ve got this robust configuration management database. We’ve got changes going back and forth to Dynatrace. We’ve got autoremediation happening. We’ve got [our ITSM] paging out on problems that we can’t autoremediate on.”

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Dynatrace and later realize additional uses and business opportunities, including:

• Proactive monitoring. By continuously analyzing system behavior and dependencies, Dynatrace can help teams identify potential issues before they escalate into incidents. The principal site reliability engineer in telecommunications noted their organization is evolving from reactive monitoring, enabling earlier intervention based on performance trends rather than failure thresholds. They said: “We’re working with our Dynatrace data on proactive monitoring. Today you get problems after they start. We’re leveraging a third-party agent that we built with Dynatrace data to alert us when problems are about to happen.”

• Scalable platform for new use cases and growth. Dynatrace’s flexible consumption-based licensing and unified “OneAgent” architecture can give organizations the option to expand usage cost-effectively as needs evolve, supporting future initiatives like cloud migration, security monitoring, or tool consolidation.³ One interviewee noted that they could easily extend Dynatrace monitoring to mainframe systems and even trial new features (e.g., application security monitoring) by toggling on modules, without a lengthy procurement or deployment process. This built-in flexibility means enterprises can adopt new capabilities or scale to additional environments quickly — potentially avoiding future costs (e.g., reducing spend on legacy monitoring tools or third-party services) — benefits that are real but treated as optional upside since they depend on an organization’s future strategy.

• Foundation for new business insights and revenue opportunities. Several interviewees said that Dynatrace positions them to pursue innovative business models and data-driven strategies. For example, the staff technical program manager from the telecom firm described the potential to use Dynatrace’s real-time business event data to adjust marketing promotions dynamically by region (e.g., during sales campaigns) and optimize revenue, a capability they are just beginning to explore. By delivering unified observability and business metrics data in real time, Dynatrace opens the door to new revenue-generating and efficiency-driving use cases, such as continuous cloud optimization or AI-informed business decision-making.

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).