A decision to chase a “breakthrough”, led a carbon credit startup to spend half a million dollars on a black-and-white camera with a fancy lens.
From the author: The Art of Decision-Making book is coming soon. But not all case studies have made it into the final manuscript. This one is about a decision-making trap. The moment early success replaces rigour with confidence, scrutiny becomes the first casualty.
There is a particular danger that comes with early, outsized success. Momentum breeds confidence. Confidence, left unchecked, turns into a conviction that the leaders that cracked one hard problem can crack any hard problem, that the judgement which produced the first win can be trusted without the rigour that produced it. Hubris arrives dressed as ambition, accelerates through optimism, and makes itself at home precisely at the moment when pragmatism and scrutiny matter most. The companies that fall hardest are the ones that succeeded too quickly, too easily, and drew the wrong conclusions from it.
A carbon credit startup knew exactly how to win in its niche. Backed by international hedge fund capital, within just a couple of years it had built a focused, scalable model around low-cost emission reductions on gas infrastructure. The formula was working. The revenue was growing exponentially.
Then the founders looked up from what was working and decided to tackle an even bigger problem.
They began the search for the most innovative technology that could redefine how emissions were measured across the oil & gas industry. An expert was hired to scan the frontier, with a brief to prioritise boldness and innovation. Scientific grounding was secondary to ambition.
What they found in the US appeared to fit the brief perfectly. A video-based technology that claimed to distinguish methane and CO2 from other gasses by filming oil & gas flares and power plant smokestacks with real-time quantification of emissions. If it worked, it could redefine global emissions monitoring and unlock hundreds of millions of dollars in investment.
The in-house engineers were unclear about the science behind it. The evidence was scant. But the opportunity was so attractive, that decision to invest was made anyway.
The hunger for a miracle is its own kind of bias. It lowers the bar for scrutiny precisely when the stakes are highest.
Engineers were sent to California to learn the system and validate the results. Half a million dollars and several months later, the verdict arrived. The technology was not what it claimed to be. A visionary team of “inventors” built a black-and-white camera with an unusual lens geometry that was supposed to enable spectral analysis capability. But the best it could produce was blurry monochrome images of flares or smokestacks. It could not distinguish gases. It could not quantify anything. It was a sham.
The financial loss was not the main concern. The founder’s egos suffered more than the balance sheet. The real cost, however, was months of leadership and engineering attention redirected from a pipeline of real but unglamorous opportunities to pursuing unicorns.
This is the pattern the 50:1 framework is designed to catch. The decision to pursue the technology wasn’t buried in the details — it was a clear, visible, leadership-level call. It was a 1%-er. What made it wrong was the objective that drifted from find opportunities that will support our next wave of growth to find a technology that will change everything.
When the search criterion is boldness rather than credibility, you don’t find panacea. You find people selling snake oil.
The right version of this decision — the scientifically-grounded technology search, run with rigour against the actual needs of the business — would have found something valuable. The emission measurement space had real innovation happening. But that search requires a different brief, a different expert, and a different definition of success.
Even boldest of ambitions need an anchor in reality. The 1% decision here should have been to define what “good” looked like before the search began. Get that definition wrong, and no amount of effort, expenditure, or expertise in the field will yield anything of value.
Sometimes the most expensive decision is the one where nobody stopped to ask what problem, exactly, we are trying to solve.