Math has always been my favorite subject since a young age. If pressed why, I’d have to attribute it to the lack of subjectivity. There's only one solution, even if there are multiple routes to get there. It's similar to a puzzle in that respect. And, once I started the puzzle, it had to be finished.

With age, my horizons have expanded as I've been exposed to the fields of computer engineering, financial analysis, programming, and data science. While divergent in name, these experiences still share common ground rooted in that same mathematical objectivity. The pursuit of a truth if you will - a program, an investment, an insight, a model, etc.

Based on time with clients and the corporate world, I'd argue this pursuit of truth is the core tenant of how companies, governments, institutions, and individuals should operate. Akin to the scientific method, we should develop hypotheses, collect the best sources of truth, generate key metrics, mine insights, (in)validate our hypotheses, and repeat. This cycle ends up creating a flywheel effect, generating more value the longer it’s in existence. It greases the organizational machine by defining its culture and reinforcing the foundation for other experiments.

I imagine this doesn't come off as rocket science. After all, we learn the scientific method from an early age in school.

The key thing about this process, though, is that it only really works when we care about the truth. Truth is the engine powering the rocket, but it’s also constantly fighting against the pull of gravity:

  • Galileo was held in contempt for nearly 30 years for his discovery of heliocentrism.
  • Propaganda and book burning have been employed in wars throughout the ages to combat unpopular ideas.
  • Enron and WeWork employed creative accounting to mask business challenges and fraud investors.

Fortunately, despite the immediate challenges, the truth has tended to prevail in the long run. It’s hard to argue against mounting piles of evidence that build up, especially during generational power transitions and/or when there’s profit to be made. This is also what gives me confidence in a similar turnout for modern “heliocentricisms" like climate change and vaccines.

What can be disheartening though is the short run. Even if women suffragists knew in 1850 that they would win the right to vote in 70 years time, it would not undo the years of trials and tribulations they go onto experience. It is acutely hard when it’s not that you’re right at the wrong time, but when the majority is wrong at the time to be right.

From this it can be mutually agreed that truth is important, but even more important is accelerating the path to truth. I decompose this problem into one of quintessential Economics 101: supply and demand curves. In this case, data, knowledge, and evidence are our supply while popular interest becomes our demand. This leads to two important postulates about the compounding, decreasing cost of the truth.

  • First, that the more evidence that builds up, the lower the cost of that truth. This happens because the cost of the truth is inverse to its quantity. So, more people are able to be reached and exposed to the truth as a result. As the truth scales, more demand is created for it which translates into even more supply. Self-perpetuating cycle.
  • Second, popular interest can be shifted and manipulated. This swaying of popular opinion can shift the equilibrium point further away just as easily as it brings it closer. This swaying can assume a variety of forms such as authority, financing, and publicity. I suspect increasing ownership of a decision (I.e., putting skin in the game) can also shift an individual’s receptivity as it encourages more critical thinking of the topic via reward and risk.

Consider when a ground-breaking story comes out surfacing illegal activity at a company or institution. At first, there will be denial or "no comment” statements from the accused, and swaths of the public may not be bought into the story yet. However, with the passage of time and more journalists catching onto the story’s scent (to say nothing of the authorities), the evidence compounds as the supply of truth continues to increase. With the validation of more publications, the public also becomes increasingly more receptive to the story till it finally becomes a majority truth. For a recent expose on this and the importance of journalism, see Theranos.

In my neck of the woods, the enterprise world, I’ve seen this play out forward and in reverse. An analysis surfacing a 7-digit opportunity is killed due to internal politics at one client; at another, it’s overturned by the CEO given the holistic value to the company and industry research reinforcing the strategy. Microsoft went through both cycles of this with the modern smartphone: famously critical of the market's potential at the outset before joining the game (too) late after the evidence continued to pile that the smartphone wasn’t just here to stay but was the new form of personal computing.

It is this power of data to galvanize towards truth that reminds me of my younger fascination with math. The world is of course much more complex than a problem set full of equations, but it is this complexity that amplifies data's importance as a factual foundation to argue upon. Courses of action may diverge to accommodate different needs and risk profiles, akin to the multiple routes to the same math solution. However, they will share common perceptions of reality that consistency propel our rocket forward. It is this need in the world that gives the field of data (“science”, algorithms, infrastructure, analyses, machine learning, insights, etc.) its outsized impact and importance in the world.

Back on topic, how does this alleviate the short-term pain though? Referring back to the truth supply and demand, we leverage both axioms and note their presence in the examples above and beyond.

First, we make an effort to increase the demand for truth, which I recognize is actually the harder to change under inertia and the bystander effect. Those later in their career with power/respect/influence will experience the highest return on scale though given their ability to set culture and process in their respective field. Consider the thought leader, media personality, or influencer's scale to put this in perspective. As for the collective, it has become a common refrain to assume that if no one cares about XYZ, then the individual input does not matter. The contrary is actually equally true though as it is the individual that actually matters the most. For flipping the refrain, if every individual advocates then of course XYZ will matter.

Second, we lower the cost of truth and let compounding interest... well, compound. This is the work of every scientist, journalist, activist, researcher, analyst, writer, engineer, publisher, blogger, YouTuber, podcaster, radio host, reporter, environmentalist, geologist, physician, and more. Given the 1% rule, this is where the individual can have the most leverage early in their career. Equally true, this is where someone later in their career can capitalize on their accumulated capital.

The cautionary tale of these truth supply demand curves is that their reinforcing nature is dual faceted. Just as they have the potential to take us to new Enlightenments, they also have the potential to silence us the way of Galileo. This is what I believe has inspired the voices of recent generations into action, and it's also what I believe will continue to inspire generations to come. Truth will beget more truth, and our efforts today will lead to more tomorrow. Q.E.D.