The Total Economic Impact™ Of Confluent, An IBM Company

Data Streaming Delivery Efficiency

Evidence and data. Interviewees said that managed services and more repeatable platform patterns reduced infrastructure setup and bespoke engineering work, contributing to shorter delivery cycles for production data streaming use cases.

• The senior fellow, software engineering and platforms, at a manufacturing organization described the delivery of a major change supporting the organization’s order-to-cash process: “Before, any change would have led to at least a nine-month lead time. Right now, it is 65 days.”

• According to the senior director, data streaming platform, the hospitality organization reduced standard producer-to-consumer onboarding from roughly 4 to 5 months to a best case of 2 sprints and a worst case of 1 program increment.

• Interviewees said production delivery still required coordination across application, platform, security, architecture, governance, and business teams.

Modeling and assumptions. Based on the customer-reported ranges, Forrester models the following for the composite organization:

• For this analysis, a production data streaming use case is a new streaming workflow or a material change to an existing workflow that requires coordinated design, build, testing, and deployment before release to production. Routine maintenance and minor configuration changes are not counted as separate use cases.

• The composite launches three new or materially updated production data streaming use cases in Year 1, five in Year 2, and seven in Year 3. Each use case involves five engineers. Forrester selects an elapsed cycle of 20 weeks in the prior state and 8 weeks in the expanded state, then translates those elapsed cycles into 120 active hours per engineer in the prior state and 48 active hours in the expanded state, equivalent to 6 active hours per engineer per week in each state. The difference across five engineers is 360 active delivery hours avoided per use case.

• For modeling purposes, the five engineers represent the broader technical delivery group, and Forrester values their combined time using one consistent data engineer-equivalent hourly rate. This does not assume that every use case involves five people with identical job titles.

• Forrester applies a fully burdened rate of $111 per data engineer hour and a 75% productivity recapture. Forrester values 75% of the avoided delivery time as productive capacity and leaves the remainder unquantified. The benefit includes active design, build, test, coordination, and deployment effort. It excludes platform operations and enablement, formal governance review, high-severity incident response, technology costs, revenue acceleration, and business value from faster decisions.

Risks. The scale of this benefit may vary from organization to organization based on:

• The organization’s ability to identify and prioritize additional production data streaming use cases.

• The complexity and configuration of the prior environment.

• The maturity of reusable delivery, platform, and governance standards.

• The skills and experience of the technical teams involved.

• The organization’s ability to redirect avoided delivery time to productive work.

Results. Forrester applied a 10% downward adjustment to reflect differences in use case complexity, active engineering effort, team mix, and the ability to redirect time. This yields a three-year, risk-adjusted total PV (discounted at 10%) of $327,000.

Platform Engineering Efficiency

Evidence and data. By moving eligible workloads to Confluent Cloud and standardizing support patterns, interviewees’ organizations reduced the internal effort required to operate and support their streaming platforms. Interviewees said this released platform operations and enablement capacity for other work.

• The senior fellow, software engineering and platforms, at a manufacturing organization described support moving from approximately 13 to 14 people managing self-managed Apache Kafka before the cloud move to about two people supporting Confluent Cloud and about three people supporting retained, self-managed Apache Kafka clusters on-premises.

• The senior director, data streaming platform, at a hospitality organization described reallocating platform capacity after Confluent assumed much of the operating work: “One pod is about seven to eight people. We reduced one pod because now, Confluent is running it for us.”

• Interviewees also described greater self-service, fewer routine infrastructure-related questions, and at one organization, an approximately 50% decline in infrastructure-related support tickets.

Modeling and assumptions. Based on the interviews, Forrester models the following for the composite organization:

• The composite requires platform operations and enablement capacity equivalent to 10.5 FTEs in the prior state and 3.5 FTEs in the expanded state. The recaptured annual capacity of seven FTEs comprises the equivalent of five platform operations FTEs and two enablement FTEs. The expanded state retains 3.5 FTEs for internal platform ownership, architecture, monitoring, vendor coordination, workload oversight, and continued user enablement.

• For modeling purposes, platform operations and platform enablement professionals are role-equivalent labor categories representing the technical work performed rather than formal job titles.

• Forrester applies a fully burdened rate of $98 per hour and 2,080 annual work hours per FTE. No separate partial productivity recapture is applied because the seven-FTE difference is defined as net annual capacity that can be reassigned or avoided, not gross task-hour efficiency. This treatment does not assume layoffs or direct payroll reductions. It excludes application delivery, formal governance review, high-severity incident response, and technology costs.

Risks. The scale of this benefit may vary from organization to organization based on:

• The scale and complexity of the streaming environment, including hybrid and retained on-premises workloads.

• The maturity of platform automation and self-service before the investment.

• The skills and experience of internal platform personnel.

• The division of operating responsibility across Confluent, customer teams, and service providers.

• Growth in platform use and the organization’s ability to redirect released capacity or avoid future hiring.

Results. Platform scale, retained hybrid infrastructure, support demand, responsibility boundaries, and capacity reassignment can differ across organizations. To account for these risks, Forrester applied a 20% downward adjustment, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.8 million.

Avoided Infrastructure And Platform Technology Costs

Evidence and data. Interviewees did not provide sufficiently comparable organization-specific nonlabor cost data to model this benefit directly. They described retiring infrastructure and consolidating portions of their platform technology footprint after moving eligible workloads to managed services, while retaining some on-premises and hybrid costs. Forrester used this qualitative evidence to develop rounded composite cost assumptions and phased realization rates.

Modeling and assumptions. Forrester models the following for the composite organization:

• The composite incurs $500,000 in annual nonlabor platform costs in the prior state and $300,000 in the expanded state while supporting the same projected workload and use case demand. The $200,000 difference includes eligible compute, storage, networking, monitoring, backup and disaster recovery, non-Confluent software and support, and duplicate capacity. The values are intentionally rounded composite assumptions, not customer-reported budgets.

• To reflect the phased retirement of prior-state costs, the composite realizes 75% of the eligible difference in Year 1, 90% in Year 2, and 100% in Year 3 as workloads move, contracts expire, and parallel run requirements end. The benefit excludes labor, Confluent fees, implementation, downtime losses, and any cost that continues in both states.

Risks. The scale of this benefit may vary from organization to organization based on:

• The prior-state technology inventory and eligible nonlabor cost base.

• The share of infrastructure retained for hybrid workloads.

• The timing of contract, lease, and support renewals.

• The expanded-state consumption profile.

• The amount of duplicate capacity that can be retired while meeting the same demand.

Results. Because the eligible cost base, retained hybrid footprint, contract timing, and retirable duplicate capacity can vary materially, Forrester adjusted this benefit downward by 25%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $327,000.

Incident Response Efficiency

Evidence and data. Confluent Cloud provided a managed operating environment for eligible streaming workloads, reducing the infrastructure that customer teams had to administer directly. Following the migration and related platform changes, interviewees reported fewer high-severity incidents, shorter recovery times, fewer people involved in response, and lower on-call burden.

• The senior director, data streaming platform, at a hospitality organization said streaming platform incidents fell from approximately 1 per month to 1 per quarter and estimated an 80% reduction in on-call work.

• The senior fellow, software engineering and platforms, at a manufacturing organization reported no outages during the cited post-migration period.

• The vice president of product at a retail technology organization reported that mean time to resolution improved from 8 or more hours to 1 to 4 hours and that typical incident involvement fell from six to 10 people to three to five.

• The senior vice president, architecture, and senior lead analyst at a financial services organization described how, in some cases, 6-hour overnight troubleshooting calls became shorter diagnostic events.

Modeling and assumptions. Based on the ranges described in the interviews, Forrester models the following for the composite organization:

• The composite experiences 12 high-severity production incidents per year in the prior state and four in the expanded state. Each prior-state incident requires eight responders working 8 active hours each; each expanded state incident requires four responders working 2.5 active hours each. Annual active response effort therefore falls from 768 hours to 40 hours, avoiding 728 hours per year.

• In this analysis, “incident response engineer” refers to the technical employees directly involved in diagnosing and resolving high-severity incidents, regardless of their formal titles.

• Forrester applies a fully burdened rate of $71 per hour of incident response engineer time and a 75% productivity recapture. The model leaves 25% of the avoided active response time unvalued because responders may not be able to redirect every saved hour to productive work. The benefit includes active triage, war-room coordination, troubleshooting, and recovery. It excludes routine support, planned maintenance, passive on-call availability, business downtime, lost revenue, service-level penalties, and customer experience effects.

Risks. The scale of this benefit may vary from organization to organization based on:

• The organization’s incident history and definition of high severity.

• The criticality and dependency footprint of the streaming environment.

• The maturity of monitoring, observability, and diagnostic practices.

• The number and role mix of incident responders.

• The organization’s ability to redirect avoided response time to productive work.

Results. Differences in incident frequency, severity, responder mix, and active response time led Forrester to apply a 15% downward adjustment. The three-year, risk-adjusted total PV (discounted at 10%) is $82,000.

Governance Standardization Efficiency

Evidence and data. Confluent supported more consistent message, schema, access, and review patterns as interviewees’ organizations expanded production streaming. Interviewees said that greater standardization reduced custom translation work and the governance, architecture, and coordination effort required for new or updated use cases.

• The senior vice president, architecture, and senior lead analyst at a financial services organization said earlier projects defined messages differently and often required brokers or translation layers between formats. The organization later established enterprise messaging and governance standards to support its streaming architecture. The evidence indicated 10% to 25% less custom translation or broker work and 10 to 20 fewer governance, architecture, and coordination hours per use case after stronger standardization.

• The senior fellow, software engineering and platforms, at a manufacturing organization described automated access provisioning, while other interviewees described more repeatable governance patterns. Standardization reduced governance and coordination effort but did not eliminate the underlying governance, security, architecture, or compliance work. Forrester therefore modeled only the review and coordination time avoided.

Modeling and assumptions. Based on the interviews, Forrester models the following for the composite organization:

• The composite launches three new or materially updated production data streaming use cases in Year 1, five in Year 2, and seven in Year 3. Forrester applies an assumption of 15 hours of formal governance review and coordination avoided per use case. This is the total time saved across reviewers, not 15 hours per person.

• The “data governance analyst” category covers architecture, security, access, review, and coordination work performed across roles, regardless of title.

• Forrester applies a fully burdened rate of $98 per data governance analyst hour and a 75% productivity recapture rate. Forrester values 75% of the avoided governance and coordination time as productive capacity and leaves the remainder unquantified. The benefit excludes design, build, test, and deployment work; platform operations and enablement; incident response; custom translation labor; and broader trust, compliance, or business outcomes.

Risks. The scale of this benefit may vary from organization to organization based on:

• The organization’s regulatory, security, privacy, and control requirements.

• The maturity of message, schema, access, and review standards before the investment.

• The number and role mix of reviewers.

• The proportion of use cases requiring formal review.

• The complexity of messages and data contracts.

• The capabilities included in the deployment.

Results. Forrester reduced this benefit by 25% to account for variation in review requirements, use case mix, and reviewer participation. The three-year, risk-adjusted total PV (discounted at 10%) is $10,000.