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- A new research study demonstrates that large organizations measure return on investment (ROI) from data streaming investments via both operational and business metrics.
- Top operational metrics include improvements in end-to-end latency, data freshness, and system uptime.
- The most popular business metrics include increased revenue, improvement in customer satisfaction, and an increase in the accuracy and speed of real-time decision-making.
Evaluating Investments Through Operational and Business Lenses
Organizations measure their investments from both operational and business perspectives. This is one finding from a survey1 of 200 senior IT and data executives at large companies with an annual revenue of $50 million or more.
RELATED: New Study shows enterprises unlocking major value from data streaming investments
Research from the intelligent data hub Conduktor shows that 93% of surveyed IT leaders utilize multi-platform data streaming. The same study found that 43% are now applying data streaming to AI training and deployment.
Respondents have identified a series of operational measures to evaluate the success of data streaming initiatives. The top three include: end-to-end latency (time from ingestion to action or insight); data freshness (time from event creation to availability for use); and system uptime and failure recovery times.
Other measures include processing cost per gigabyte or per event, volume of events processed successfully per second (throughput), scalability to handle peak loads without degradation, accuracy and completeness of streamed data (no loss, no corruption).
Business metrics
Respondents name the top three business metrics as being:
- Increased revenue driven by real-time data services or products
- Improvements in customer satisfaction or NPS related to real-time experiences
- Enhanced accuracy and speed for real-time decision making
Additional KPIs include reduction in fraud, security incidents, or financial losses; faster time-to-market for data-driven products or features; and a reduction in operational costs through automation and faster incident detection.
Nicolas Orban, CEO of Conduktor, said: “Organizations carefully track streaming performance (latency, throughput, uptime), but struggle to connect these operational metrics to business outcomes like revenue growth or customer satisfaction.
This measurement gap reveals a deeper issue: without unified governance across streaming platforms, teams optimize individual systems while enterprise-wide ROI remains unclear. The solution isn’t better metrics; it’s governed infrastructure that makes the connection between technical performance and business value transparent.”
Real-Time Data Processing Demand Fuels Market Growth
According to Dataintelo, the global market size for streaming data processing system software was valued at approximately USD 9.5 billion in 2023 and is projected to reach around USD 23.8 billion by 2032, reflecting a compound annual growth rate (CAGR) of 10.8% over the forecast period.
Dataintelo says that: “The surge in the need for real-time data processing capabilities, driven by the exponential growth of data from various sources such as social media, IoT devices, and enterprise data systems, is a significant growth factor for this market.”
Learn more about Conduktor’s streaming data hub here: https://conduktor.io/
