When Engineering Owns the Real-Time Mandate, But Execs Own the Fallout

Your data engineering team built the real-time data pipeline. Your C-suite still didn’t see the problem coming.

It starts with this:

“We didn’t know until the customer escalated it.”

You’ve heard this in war rooms. In postmortems. In QBRs.
Sometimes, even on earnings calls.

But what no one says out loud is this:

Your engineering team delivered real-time infrastructure.
Your business team still got blindsided.

The Setup: Engineering Built It

In the past five years, engineering and data teams have moved mountains.

• Kafka deployed
• Streams flowing
• Connectors wired
• Dashboards visualized
• Infra budgets approved

By every technical metric, your organization is real-time ready.

So why does it still feel like you’re reacting late?

Why are escalations still coming from customers, not systems?

Why are decisions still delayed, even when data is streaming?

The Fallacy: Real-Time Infra = Real-Time Outcomes

Let’s break this down.

Real-time infrastructure solves for throughput and latency.
Real-time business outcomes solve for awareness, response, and impact.

But the gap between the two is where most companies lose the plot.

📊 According to a 2024 survey by McKinsey, while 78% of enterprise leaders say they’ve invested in real-time data infrastructure, only 29% say they’re using real-time insights for frontline decision-making.

That’s a 49-point execution gap.

Real Story. Real Stakes.

A leading travel tech company had real-time GDS booking streams set up.
Every fare update. Every cancellation. Every new segment booked - all piped into a Data warehouse with sub-second latency.

And yet, a pricing mismatch issue went unnoticed for 6 hours.
Why?

• The Kafka stream caught it
• The alert fired
• But no one acted

Why?

Because the alert was routed to an SRE queue, not a revenue manager.
Because the event wasn’t tied to revenue loss just a log anomaly.
Because no one owned the decision layer.

Result? $1.2M in lost margin.
And a C-suite scrambling for answers.

What’s Actually Missing?

Not infrastructure.
Not talent.
Not even tools.

What’s missing is business orchestration.

Here’s what most orgs lack:

This is not a tech problem.
It’s a decision flow problem.

Real-Time Isn’t a Stack. It’s a System of Action.

You can’t delegate real-time to engineering and expect outcomes to change.

It’s time for the C-suite to ask different questions:

• What’s our average Signal-to-Action Time?
• Who owns decision triggers not just infra?
• Which events should never reach a customer before they reach us?
• Are real-time streams routed to decision makers, not just systems?

Because in the absence of ownership, infra delivers data, not decisions.

Signal Detected ≠ Action Taken

Real-time infrastructure has trained us to measure latency.
Milliseconds. Sub-second event delivery. Stream speeds.

But here’s the truth:

Detecting the signal isn’t the win. Acting on it is.

Just because your system picked up the anomaly doesn’t mean your business responded.

That’s where most organizations fall short.
The stream flows.
The alert triggers.
But no one makes a decision.
Or worse the right person never even saw it.

So let’s talk about a metric that actually matters:

🧮 SAT — Signal-to-Action Time

SAT is the time between when something happens… and when the business actually does something about it.

• Your Kafka latency might be 200ms.
• But your SAT could be 3 hours.

That’s the real bottleneck.
Not the system.
The space between signal and action.

If your infra is real-time but your responses aren’t, you’re:

• Running a latency illusion
• Paying a decision debt
• Sitting on customer risk

The fix isn’t more tech.
It’s more alignment.

Real-time isn’t an engineering problem.
It’s a business model upgrade.

Executive Cheat Code: Diagnose Your Org’s Real-Time Maturity

Here’s a simple 5-question diagnostic you can ask at your next leadership sync:

1. Do we have real-time event-to-outcome mapping?
2. Do alerts reach business users, not just devs?
3. Is there a person responsible for each critical stream?
4. Can we measure our average SAT (Signal-to-Action Time)?
5. When something breaks -who acts first: us or the customer?

If more than 2 are a “no” - it’s not a streaming issue.
It’s a systems design issue.