Governing Dynamics

  Noise, Bias, and Signal

What are Noise, Bias, and Signal?

Noise, Bias, and Signals are three essential terms (classifiers) for every investor, entrepreneur, leader, and government official to understand. For the purposes of our work, we strictly apply these classifiers to business and market information flows and how they apply to making better decisions.

When you read noise, bias, or signal on this site, I want you to think about different types of information and their usefulness (or lack of usefulness) in achieving your goals. The most useful kind of information we can cultivate, receive, and use is signal. Signal is your information superhero who helps you achieve your goals and saves you from making avoidable and costly mistakes. The most dangerous and least useful type of information is noise. It's like a drunk invisible supervillain that will cause you harm but in different and unpredictable ways. Biased information is also dangerous and not useful, but this one isn't a supervillain. This one is just the weird relative you see at all the family events and is consistently wrong in the same way. The more you’re aware of this relative, the easier it is to spot them and ignore their advice.

Now that we have our superhero, supervillain, and weird relative, let's see how they can help, harm, mislead and confuse us in our respective pursuits of success.

Using an Olympic dart game, three groups of players (Team Noise, Team Bias, Team Signal), and you, as the observer/judge, we can easily demonstrate how each one works. Your job is to pick the most accurate and consistent team to represent your country in the upcoming Olympic games. When each team plays, their dart positions are recorded on a piece of paper that is laid on the dartboard.

*If you googled to see if darts are an Olympic sport, well done, they aren't. But maybe in 2024, darts could be an Olympic sport.*

Signal is the high-quality, useful, and applicable information you need to achieve your goals, make better decisions, uncover positive/negative asymmetries, avoid mistakes, and much more. Team Signal threw all of their darts and they were all grouped closely on the bull's eye.

Bias is consistently wrong information, and it is wrong in the same way. Bias can come in many forms, and numerous biases can be present in an information flow. Team Bias threw all of their darts, and they were all grouped just above to the left of the bull's eye.

Noise is wrong information, but it is wrong in random/unpredictable ways. Unlike bias, it does not group consistently in any region of the dartboard. When Team Noise threw all of their darts, they were all over the place. Some were close to the bull's eye; others were too high, too low, too far right, and too far left.

It would be very easy for you to choose Team Signal for your Olympic team in a situation like this. However, the information we receive is not so neatly packaged, labeled, or obvious in real life. When trying to identify Signal, Noise, and Bias, not only are they combined, but they also don’t come with neat bull's eyes to indicate which one is the signal, which one is the noise, and which one is the bias. Using our methods, frameworks, and matrices, you’ll be able to identify, label, and use your signal in the sea of noise and bias.

How I Believe it Applies.

We all want to make better decisions, gain better insights, avoid issues, and achieve our respective goals. In our case, we want to identify significant problems we can convert into products, services, and new companies with the least risk, errors, or setbacks. The fastest, least expensive, and highest probability way to do this is via accurate signal identification and proactive management of bias and noise.

Over my career, the main issue I’ve observed is how many super-intelligent people are completely unaware of the bias and noise in their decision-making process, information flows, and data gathering strategies. In most cases, individuals cannot differentiate between signal and noise, using them interchangeably to craft the foundations of their project, business, initiative, etc. When left unchecked, this can lead to developing products, services, offerings, and companies that don’t have a home in the market. They fizzle out at varying speeds. Not because the team is dumb, but rather because they fell victim to information that misled them to the wrong destination.

Noise and bias influence and impact every decision, whether we want to admit it or not. It impacts me, my teams, my companies, and that is why we’ve spent so much time developing frameworks and methods to use in our work to identify the noise and bias in our information flows (external/internal.) These methods help us understand the quality of the information we are generating, how to rate the information sent to us, and how to balance the information flows to make them useful.

Companies, teams, and leaders who embrace this way of thinking have a greater probability of success in their projects and new ventures. Now let’s see just how much information is swirling around us. It’s more than you might think.

Why Should You Care.

Every company, organization, government, and individual should take a deep interest in honing their abilities to identify signals. Noise and bias have always been present in our decision-making, but for the first time in human history, we are doubling the amount of information available roughly every 18-24 months. The amount of information available in the world grew by 50 times between 2010 and 2020.

To give you a point of reference, "It is estimated that one weekday edition of today's New York Times contains more information than the average person in seventeenth-century England was likely to come across in an entire lifetime." According to David Shenk, this data point is in wait for it….1997. That's before the real internet boom, Facebook, YouTube, the rise of big data, AI, machine learning, smartphones, Twitter, and all the other forms of online media. If you were to account for all the information you consume on a daily basis, it would be several times that of a weekday edition of the New York Times.

Applying this to ourselves, we are overloaded with noisy and biased information that hides the real signals from us when we are: looking for answers, researching, running a market research study, conducting R&D, getting feedback from customers, looking for new opportunities, and trying to understand risks. If these unfiltered information flows were food, it would be a big bag of processed sugar. Sometimes it just makes everything taste so good that you don't want to check to see if it's really the right thing for you. Why would bad information taste good? In many cases, it confirms your bias and doesn't challenge you. Other times, it gives you false confidence and sense of direction. The list goes on.

Just like processed sugars, bad (biased/noisy) information in small doses is fine for the most part. But when consistently consumed in large quantities, over time, the bad information will cause massive problems that can lead to missed opportunities, loss in valuation, unnecessary setbacks, and often times, the closing of a business.

On the other hand, signal is the food equivalent of "(enter your favorite food here)," but without any negative side effects. The more you consume it, the fitter, better looking, brilliant, and successful you become. It's the data equivalent of a superfood for decision-making.

We've developed methods, frameworks, and programs that we use in our own companies to sift through information, the same way you do for gold. You can review our RQ:RA Method, Signal Amplification Matrix, and other frameworks to learn more.

Here is a quick test to see if you have unfiltered information flows in your business:

• What processes have you put in place to identify and adjust for noise pre, post, and real-time?

• What parts of your business are most subject and least subject to noise contamination?

• How do you test for bias in product development, market research, company strategy, etc.?

• How is outgoing information (marketing/messaging/etc.) managed, tested, and verified?

• Who is (are) responsible for tracking and mitigating noise and bias in your business?

How Does it Tie Into Our Methods & Services?

We’ve spent almost two decades studying, analyzing, and mastering signal identification. We’ve developed comprehensive solutions backed by proven methods, frameworks, and market expertise that effectively identify bias and noise in a broad range of information flows and decision-making processes. Review our Signal Amplification Matrix, RQ:RA Method, Dynamic Believability Matrix, and other frameworks to learn more.

Contact us today if you are ready to amplify your signal, reduce noise, and mitigate bias in your business.