New Forrester study: Why modernizing data streaming is about more than cost savings

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A new Forrester Total Economic Impact™ (TEI) study commissioned by Confluent, an IBM company and data streaming platform, found that a representative composite organization achieved 137% ROI, USD 2.1 million in net present value and a 10-month payback period. Those are meaningful results. The ROI is notable. What's more interesting is where the value came from.

Modernization is often framed as an infrastructure problem. Leaders compare platform costs, migration and operating costs. Platform teams are also expected to support more business priorities, including analytics, digital operations and AI, while engineering capacity remains constrained.

And as organizations invest in AI, many are discovering that their biggest constraint isn't model access but rather how quickly they can move trusted, governed, real-time data across the business.

That's why I believe the most important finding in the study isn't about cost savings. It's about capacity.

What leaders often underestimate about platform burden

When leaders think about platform operations, they naturally focus on infrastructure costs. But the larger impact is often opportunity cost.

Platform work has a way of consuming more engineering time than leaders may realize. The composite organization also went from 12 platform incidents a year to 4. Fewer fires is capacity too. The study highlights just how much effort organizations can devote to platform operations and enablement activities before more standardized and managed approaches are in place.

One thing leaders consistently underestimate is how much platform expertise gets tied up in keeping the lights on. You don't see that cost on a budget line, but you feel it every time an initiative waits for engineering capacity.

One finding that caught my attention was the reduction in platform operations and enablement effort. After moving from self-managed open-source Kafka to Confluent Cloud, the representative composite organization reduced annual requirements from 10.5 full-time equivalents (FTEs) to 3.5 FTEs. That represents 7 FTEs’ worth of focus moving from keeping Kafka running to the higher-value work waiting behind it. That one line is 79% of the quantified benefit in the study, USD 2.84 million of USD 3.58 million over three years." The capacity isn't a side effect of the ROI. It is the ROI.

The business doesn't ultimately measure success by how efficiently a platform is maintained; it measures success by how quickly new ideas become real outcomes.

The modernization question leaders should be asking

For years, modernization discussions have started with a straightforward question:

"How much will this cost?"

The study suggests a more useful question:

"What opportunities are we delaying because our teams are spending time maintaining infrastructure instead of delivering value?"

The representative composite organization in the study avoided 360 technical delivery hours for each new or materially updated production streaming use case. Interviewees also described benefits such as greater reuse of streaming data, simpler data movement, faster onboarding and more consistent governance practices.

More importantly, these findings point to a shift in how organizations scale data. When governance, access controls and data standards are applied once at the source, every new consumer can build from the same trusted foundation. Teams spend less time recreating integrations, reviews and controls for each downstream application. Over time, that changes the economics of growth: the twentieth consumer of a data stream can be far less expensive to support than the first.

The conversation can't stop at infrastructure savings. The bigger question is what your teams could deliver if they spent less time operating the platform and more time using it.

From operating a platform to creating business value

One customer interviewed for the study captured the shift in a single sentence:

“There was a time when my platform team was the main team trying to keep the platform up. Now the platform is up. Let's focus on bringing more business.” —Senior Director, Data Streaming Platform at a hospitality company

The same interviewee described loyalty points that used to post in two days now landing in fifteen minutes. That is what the recovered capacity buys: outcomes customers can feel.

That observation resonates because it reflects what most leaders actually want from modernization efforts.

Rather than spending their day operating platforms, the best platform teams want to help the business build what’s next. Whether the next priority is AI, customer experience, operational efficiency or new digital services, the value comes from what teams can accomplish with the time and focus they get back.

The financial outcomes are based on a composite organization Forrester built from four customer interviews, a global enterprise of roughly USD 20 billion in revenue and 25,000 employees, modeled over three years. However, they offer an informative framework for evaluating how modernization can affect engineering capacity, delivery speed, operational efficiency and business outcomes.

If you're evaluating the future of your data streaming strategy, I encourage you to explore the full findings.

Download the Forrester Total Economic Impact™ study.

Source: The Total Economic Impact™ Of Confluent, An IBM Company: Cost Savings And Business Benefits Enabled By Confluent, September 2026, a commissioned study conducted by Forrester Consulting on behalf of Confluent, an IBM company. Results are based on a representative composite organization and may not be representative of all customer experiences.

  • As General Manager and VP Product for Confluent's Data Streaming Platform (DSP), Mike manages a product portfolio that includes stream processing, connectors and integrations, governance, partnerships and developer tooling. Over the last eight years at Confluent, Mike has held various product leadership roles spanning Apache Kafka, Confluent Cloud and Confluent Platform working closely with customers, partners and R&D to drive adoption and execution of Confluent products. Prior to his work at Confluent, Mike was the founder and CEO of Terrain Data (acquired by Confluent in 2018). Mike earned his MBA from Stanford's Graduate School of Business and his B.S. in Computer Science from Stanford University.

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