Reactive Technologies’ Accidental Discovery: How Failed Experiments Lead to Category Creation

Reactive Technologies’ Accidental Discovery: How Failed Experiments Lead to Category Creation

The experiment worked perfectly. Reactive Technologies had successfully transmitted data signals through the entire UK power grid—exactly what they set out to prove was possible. But something was bothering the engineers. The signal wasn’t reaching all their receiver devices at exactly the same time.

In a recent episode of Category Visionaries, Marc Borrett, CEO and co-founder of Reactive Technologies, shared how this “problem” with a successful experiment led to discovering a phenomenon that had never been measured before. Their story reveals a counterintuitive truth about category creation: sometimes the biggest opportunities hide inside your failures—if you’re curious enough to investigate what went wrong.

The Question That Energy Insiders Never Asked

Reactive Technologies’ founding insight began with a question that only outsiders would consider asking. Marc and his team came from the semiconductor and telecom industries, not energy. This background shaped how they thought about infrastructure.

“When we set up the company, the engineering team that we built were all from the telecom sector,” Marc explains. “So when you have a group of engineers and you put them from the telecom sector and you put them into the energy sector, they want to do things like, can we use the power grid as a communications channel?”

To telecom engineers, any network is potentially a communications medium. To energy engineers, this question probably seemed misguided. Power grids transmit electricity, not data. But that difference in perspective—treating the grid as a network rather than just infrastructure—enabled an experiment that would reveal something entirely unexpected.

Building Something That Shouldn’t Exist

The experiment itself required significant technical effort. Reactive Technologies partnered with a UK grid operator to test whether data could be transmitted through the power grid at national scale.

“We did a first project with a power grid operator in the UK, where we said we would send data through the entirety of the UK grid,” Marc recalls. “And to do that, we had to build something to create that data signal. And then we had to create some devices to hear and decode that signal out of all of the noise of all of the generation assets on the grid.”

The technical challenge was substantial—filtering a deliberate signal out of all the electrical noise generated by power plants, transmission lines, and connected devices across an entire country. But they succeeded. The signal transmitted. The receivers picked it up. By conventional measures, the experiment worked.

But then they looked at the timing data.

When Success Reveals Something More Valuable

The anomaly was subtle. All the receiver devices picked up the signal, but not simultaneously. There were timing discrepancies that didn’t match their expectations.

“When we looked at our data that we found that our signal didn’t travel and get received by each of the measurement or receiver devices as they were then at exactly the same time. And that bothered our engineers,” Marc explains.

This is the first critical decision point where most companies diverge. The experiment had achieved its stated goal—proving grid-based data transmission was possible. The timing discrepancies could have been dismissed as measurement noise, instrumentation error, or an irrelevant side effect. The team could have written up their results and moved on.

Instead, something about the anomaly bothered them enough to investigate. This curiosity—the willingness to explore why something didn’t behave as expected even when the overall experiment succeeded—is what separates discovering new categories from executing known playbooks.

The Investigation That Changed Everything

When the engineers dug into what was causing the timing discrepancies, they discovered something that redefined the entire company’s direction.

“When they looked into it, they found that there was something that was inhibiting our signal getting through the grid. And that thing that was inhibiting it was the stability of the grid,” Marc reveals. “So, basically, we found that the more stable the grid was, it was harder for us to get our message through where the grid was weaker and less stable. It was easier for us to get our message through.”

This discovery was remarkable for what it implied. The timing variations in their signal weren’t random noise—they were systematically related to grid stability. Their communications experiment had accidentally created a measurement instrument for something that grid operators desperately needed to monitor but had never been able to measure in real time.

The irony: their signal’s “failure” to propagate uniformly was actually revealing information more valuable than the original communication capability they were trying to demonstrate.

The Pivot That Created a Category

Recognizing that an anomaly reveals opportunity is one thing. Having the courage to pivot your entire company around it requires a different kind of conviction.

Marc describes the moment they presented this insight back to the grid operator: “We went back to the grid operator, and we said, look, we could turn this on its head and we could measure stability in real time. Would that be of interest? And that was really where we actually got started with measuring grid stability.”

This pivot was profound. They weren’t iterating on their original idea or finding a different application for the same technology. They were abandoning their original goal entirely to pursue something they’d discovered by accident—measuring a phenomenon that had never been measured before.

“Basically, we are having to create, in some cases, an entirely new category,” Marc notes. “So when we talk about measuring the grid, actually, we’re talking about measuring a particular phenomena that has never been measured before.”

The Framework for Recognizing Hidden Opportunities

Reactive Technologies’ accidental discovery reveals a framework that other founders can apply when experiments don’t go exactly as planned:

First, create conditions for unexpected discoveries. Run experiments that explore unconventional approaches, especially in conservative industries. The grid communications experiment had no obvious commercial application, but it created conditions for discovering something valuable.

Second, staff your team with people who care about anomalies. Marc emphasizes that the timing discrepancies “bothered” his engineers. This emotional response—being troubled by unexplained behavior—is crucial. Teams that dismiss anomalies as noise never discover what they reveal.

Third, investigate failures with the same rigor as successes. The communications experiment technically succeeded, but the timing anomalies represented a “failure” of expectation. Treating that failure as worthy of deep investigation unlocked the entire opportunity.

Fourth, ask what the anomaly reveals about the system. The timing variations weren’t just about their signal—they revealed something fundamental about grid behavior that nobody was measuring.

Fifth, evaluate whether the accidental discovery addresses a bigger problem than your original goal. Grid stability measurement turned out to be vastly more valuable than grid-based communications would have been.

Why Accidents Create Categories

There’s a deeper lesson in why Reactive Technologies’ accidental discovery led to category creation rather than just a product feature. Categories often emerge from measuring or solving for things that existing players don’t recognize as problems.

Grid operators had lived with unmeasured stability for decades. They’d built workarounds, developed models, and accepted the limitations as inherent to the system. It took outsiders running an “irrelevant” experiment to reveal that real-time stability measurement was both possible and valuable.

This is why cross-industry expertise enables category creation. Insiders are optimized for solving known problems with proven approaches. They wouldn’t run the communications experiment because it seems tangential to core grid operations. But that tangential experiment revealed a phenomenon that insiders had never thought to measure.

The Uncomfortable Truth About Innovation

The story founders want to hear is about visionary insight—seeing an opportunity others missed through brilliant strategic thinking. Reactive Technologies’ story is messier and more honest. They stumbled into their category through curiosity about why an experiment behaved unexpectedly.

But that “stumbling” required specific conditions: cross-industry expertise that enabled unconventional experiments, engineers who cared about anomalies enough to investigate them, and leadership willing to pivot the entire company based on an accidental discovery.

Most importantly, it required recognizing that sometimes your failures reveal opportunities bigger than your original goals. The key is building a culture curious enough to investigate why things don’t work as expected—and brave enough to pivot when those investigations reveal something more valuable than what you set out to build.