A new kind of advisory is here

In Thinking in Bets, Annie Duke says that decisions are bets on the future, and that they aren’t “right” or “wrong” based on whether they turn out well on any particular iteration. An unwanted result doesn’t make our decision wrong if we thought about the alternatives and probabilities in advance and allocated our resources accordingly. The Asipu of Mesopotamia (~3200 BCE) are sometimes cited as the oldest documented "risk analysts"; priestly advisors who would enumerate possible outcomes of a decision (e.g., whether to make a journey or a marriage) and assign qualitative likelihoods. The cuneiform tablets describing their practice are considered primitive decision matrices.

We humans have a special relationship with risk. We think we know how risk-averse or risk-friendly we are, until we don’t. Or at least I thought I knew. Circa 2015, and I have a steady job in a good company. The job is fine; I get to learn new things here and there. Nothing is especially wrong with anything, only this feeling of boredom that is growing on me. Nothing I hadn’t felt before when staying for several years at the same job doing the same thing time and again. Now, I could have tried the usual: a career refreshment, just to keep things going. A different role in the same company, or asking to work on a different project. That would have been more me, since I’m more for measured, calculated change. But no. Instead, I did something riskier. I took a job on the other side of the world in a very early-stage space company. I sold all my things in roughly two months and flew to a completely new country and culture. As thoughtless as it may sound, I computed the whole thing carefully—as I do—fully aware that it was risky and fully aware of the many ways it could end badly. But I still went for it. Why? I saw the potential. I saw that there were so many things to be figured out. It felt like a blank canvas. The risk was high, yes, but so was the potential reward. And I think that's how our mental computations of risk are never "constant". We do not always consider risk the same way; it depends on the context and the opportunities that are put in front of us. When we see potential and we think there's a good match between the challenge at hand and our capabilities, we raise our bets.

Some years after that decision I made, I raised the stakes again. My job was once more nice, and comfy, but the same feeling crept on me, and the risk taker within me woke up and decided to place another big bet. I quit this job, and I started something even riskier than before. Add on top of everything that I had a family and a loan to take responsibility for. But there I went again. Soon, I found myself registering a space company in Finland, renting office space, touring IKEA to buy cheap office chairs and desks to assemble. Hiring, scaling, motivating engineers. Again, the potential rewards were high: the sole idea of building a tiny society out of nothing, a company, was too appealing to look away. That adventure lasted more than four years and gave me an invaluable breadth of lessons learned on how teams and technology are basically one big system, intertwined and symbiotically coexisting. In the process, I wrote several books that document the journey, and capture the technical and human sides of the adventure.

And there would be a third time. Another bet. That’s when I left that company to found Kano. Because I feel the potential and I have the blank canvas in front of me one more time. And here I am today. And here you are reading these lines. So, now that I have your attention, I will explain now a bit what Kano is about.

Kano is a mission-critical engineering advisory studio.

What does "mission-critical" mean exactly?

“Mission-critical" refers to any system, process, or component that is essential to an organization’s operations, survival, or safety. Failure of these elements causes immediate, severe consequences, such as halted operations, massive revenue loss, or safety hazards. These systems require high reliability and constant availability. Mission criticality is scale free: you can find mission-critical systems of every size; from tiny chips to entire air defence systems.

Kano’s main product is our thinking, grounded in our decades-long expertise in developing mission-critical technology. We observe that clarity and critical judgment are scarce resources these days, and we own large reserves of both. We analyze, we advise. We don't offer "services" in the classic sense of the term. We don't sell hours. We do not fix broken teams or broken projects as interim management. Other companies can do that. We don’t sell magic solutions. We believe that the true business transformation only happens when rooted in trust and credibility. Not with magic formulas or expensive tools. We have a thesis on how mission-critical engineering breaks. How fragile it can be. We know the anti-patterns. We observe that broken organizations engender broken projects, which engender broken systems; ill systems become broken products. We offer our clarity, but with velocity. There is no time for long deliberations. We believe in brevity, and we always maximize signal-to-noise ratio. We communicate it in a clear language, including the uncomfortable truths that may appear along the way, giving our clients the power to decide with certainty. Kano fluently speaks three languages: business, technical, and scientific.

How is Kano different from any other advisories?

Our thesis is that the legacy advisory model is built on the premise that analytical intelligence, if properly trained and structured, can be applied to any business problem. This premise suggests that a smart generalist, equipped with the right frameworks, tools, and a method, can produce useful insights in every domain, without the deep domain knowledge that traditional expertise requires. This thesis allowed advisory firms to scale without accumulating the domain knowledge that would have constrained them to certain industries. In this model, senior partners build client relationships and sell engagements based on branding credibility accumulated over the years. However, delivery is always executed by teams of junior analysts and associates. Thus, the actor who convinces the client will spend a fraction of their time on the actual work. The people spending the rest of their time are applying recipes that were purposely designed to be transferable because it does not depend on domain depth. For some of the problems the model was designed to solve, this works just fine. The limitations of this approach show in full when the problem cannot be reduced to an analytical solution, when buy-in requires credible experience, and when speed of execution is paramount. Additionally, legacy advisories, being large organizations themselves, fall into the same anti-patterns they claim to be able to solve.

When an organization creates complex technology, a gap appears between what the organization imagines and what is actually happening within its engineering walls, and that gap is not easily visible except to those who have been part of similar endeavors before and saw similar gaps appearing and widening. Mission-critical technology is a domain where the quality of the end product is not determined during manufacturing, but continuously. From the very first conversation with stakeholders to the last maintenance decision. It is defined by the quality of the practices that produced it. When organizational cultures let anti-patterns run free, they produce systems with undocumented, hidden failure modes. And when failure finally materializes, it describes every organizational failure that occurred during its creation, most of which never appeared in any risk register and are invisible in a conventional due diligence process. Engaging with mission-critical tech requires people who have been inside the process that creates it. That experience is not easily replicable. It is not transferable through recipes. It accumulates through years of working in environments where the gap between “work as imagined” and “work as done” is real and evolves all the time. The advisory model that this context needs is structurally different from the ones we have known. Filling that gap is what Kano was built to do. As a complement to where traditional advisory meets its limits. Kano performs assessment from the two dimensions that shape every technical endeavor: the tech and the human brains behind the tech. From the physics of the system to the humans who built it to the investment thesis. Kano can see whether an organization pursuing mission-critical tech is capable of doing it the way it's claimed. Kano can size the engineering gaps that inevitably appear.

Last but not least, a note about our name and our identity. The name Kano brings together several ideas. First, there's a haunting beauty in the letter K, in its elusive symmetry and its prevalence in Finnish language (and its contrasting absence in Spanish, my native language). Also, I am inspired by the Kano model developed in the 1980s by Noriaki Kano, which reminds us that, in product development, the relationship between functionality and user satisfaction is not always linear; the challenge is recognizing what customers truly value. Our logo is inspired by the Kappa curve (shaping the letter K, a line that suddenly changes direction, symbolizing the moment when complexity resolves into insight), and the name also nods to Jigoro Kano, founder of judo, whose philosophy emphasized using intelligence, balance, and timing to solve a problem with the most effective and disciplined action.

So, long story short, this is Kano. I am, and We are here to transform technology advisory, working at the intersection of risk, decisions, complex systems, and engineering made by humans and augmented by machines.