Nine Profound Concepts from Ray Dalio’s Principles (Part 2/4)

This overview of Principles’s most salient concepts describes everything you need to know about Dalio’s meritocracy manual, if you aim to contribute to a successful organisation (as, in one way or another, I hope we all do).

Previously, I provided a terse overview of the book and its author. This deeper dive selects and explores nine specific concepts from Principles that I found particularly profound, and at times, provocative.

For anyone interested in self-help, self-improvement, and self-actualisation, Dalio’s ideas on pain, failure, and suffering are worth taking the time to contemplate and meaningfully internalise. He’s noticed (often the hard way) that satisfaction from success is not the result of achieving a goal.

We all implicitly know his point is correct. In fact, each and every time we shrug off celebrating goals that were achieved without effort, we demonstrate to ourselves that achievement of a goal does not invariably lead to satisfaction. Indeed, it’s not the goal itself that makes us celebrate; rather it’s achieving a difficult goal through perseverance, or as Dalio puts it, “struggling well,” that brings satisfaction and celebratory mood.

It’s important to celebrate whenever we struggle. By strengthening the relationship between struggle and reward, we become increasingly attracted to struggle itself. And the more attracted to struggle we become, the more we will struggle well. And the more we struggle well, the more we’ll be satisfied.

Thus, pain is not something to ignore or even attempt to avoid. Pain — especially when it comes from making mistakes — is a form of knowledge. Dalio explains that Michael Jordan would “revel in his mistakes.” This trait is probably a large contributing factor for how Jordan was able to excel beyond all his competition. He wasn’t afraid to focus on the problems in his technique. Jordan flipped the script on pain.

We all can learn from this. By inviting pain into our lives at appropriate moments, we grow stronger and are rewarded accordingly.

Image for post
Image for post
Injured on my first attempt at summiting and skiing down Mt. Blanc. That first failure, and the subsequent struggle, was what made success the next season so enjoyable.

Should we be astonishing with how much emphasis Dalio puts on expertise? I mean, the experts are experts — right? Well, Dalio appreciates expertise with a little more subtlety than usual.

Throughout Principles, Dalio reminds us that smart people who have proven that they know a lot about a particular topic (through repeated correct predictions or other successes) are more likely to provide valuable advice on that topic, than someone who has not proven themselves. The very fact that Dalio hammers on this point again and again indicates that he’s frequently observed others failing to take the relative expertise of an individual into account when weighing the value of their advice. And the very fact that Dalio figured it was worth his time to try to define a new term here (the term “believable”) instead of sticking with usual language (“expert” would seem fine), indicates that he feels there is a distinction between an expert and a believable person. Specifically, Dalio emphasises that to become a believable person, you need a proven track record — it’s not enough to have experience in a particular field. You also need objective successes within that field to become “believable”.

Dalio doubles down when writing that ”listening to uninformed people is worse than having no answers at all.” I would add however, that at least some of the time, uninformed people, due to an uninhibited lateral viewpoint, can provide out-of-context information that may spark novel solutions. The key is to weigh advice according to believability. Weigh everything you hear.

The world of subjectivity is an imprecise mess. Therefore, the more we find ways to turn subjective information into objective information, the more precisely we can define our problems. Meanwhile, the better defined a problem is, the easier we can make an informed decision that leads to the desired outcome. For this reason, we ought never throw our arms in the air when something seems entirely subjective or a matter of opinion. This response is unhelpful at best, and destructive at worst. We must instead, strive to tease apart subjectivity and identify underlying elements that can be measured objectively.

Similarly, when in an argument’s key factors are subjective, we are better off seizing this as an opportunity to re-define the argument such that it can draw from objective data. Doing so enables teams to work together, with logic and evidence, towards the truth. Without objectivity, we have no hope of ever coming to a consensus.

By reminding us that “anything is possible” and that “it’s the probabilities that matter,” Dalio encourages us to be real about our arguments. It is a failure not to realise that every disagreement is an opportunity for learning. After all, in virtually every argument, at least one person is wrong.

As somebody that has looked at business from the outside, most of my life, I found it a little surprising how ardently Dalio emphasises the critical importance of honesty and transparency. In Principles, he even writes “dishonest people are dangerous, so keeping them around isn’t smart.” It’s comforting to see such a successful businessman argue for honesty within an organisation. I’m on board. Honesty makes life simpler 99% of the time, provided you can separate your emotions from your business.

Dalio is clearly a big believer in using the word “I.” This doesn’t at all mean he undervalues teamwork. Rather, he understands that taking personal responsibility is motivating and — best of all — objective. When one individual is in charge of getting something done, it is abundantly clear who’s responsible for that accomplishment (or lack of thereof). We didn’t leverage this powerful concept at MI much before I read Principles, but we have since made it a structural component in how we plan out the key results and initiatives that lead us to accomplishing our objectives.

This clear designation of one — and only one — responsible person also helps ensure that people don’t try to take credit for things they didn’t do. Dalio warns against the individual who focuses more on being recognised than on their actual performance. At the end of the day, the team objective should make the pie bigger. If people focus more on being recognised than on performing well, there is a very real risk that those same people will allow the pie to shrink whenever it makes them look good in comparison. Those are dangerous individuals indeed, and not welcome at MI.

Dalio argues very strongly that it is the duty of every individual in a team to articulate their point of view with logic and evidence. He writes, “if you and others don’t raise your perspectives, there’s no way you’ll resolve your pursuits.” He’s right. I’ve been in countless arguments with people who fail to articulate their arguments either because they are afraid of confrontation or, just as pathetic, too intellectually lazy to gather their thoughts into a cohesive argument. The result is that both people lose out. For this reason, fostering and protecting an environment in which people are rewarded for articulating the logic and evidence behind their ideas, is one of my most important responsibilities as the CEO of MI.

The human mind can only truly focus on one thing at a time. To put this another way: If we are able to concentrate our mental power on a single task or activity, we’ll naturally have better outcomes. Therefore, Dalio recommends compartmentalising our thinking. He recommends breaking a discussion down into finite pieces and dealing with each of them one at a time.

We have always done this at MI. For example, when we had to revise our system for integrating the feedback we receive on Am into the product’s roadmap, step one was to define the goal. We didn’t discuss anything else. We only talked about the goal of whatever system we were about to develop. We next focused exclusively on defining the optimal output of the system so that it would achieve that goal. Third, we carefully defined the inputs to the system (all the sources and varieties of comments, user data and feedback). Forth, we combined the information from steps one, two, and three, and synthesised an accurate picture of what the system should look like, knowing it’s inputs, outputs, and the overarching goal. Finally, in step five we built the system.

During this process, naturally people provided input on something that was not the current focus, and it was my job as the individual leading the discussion to keep everyone focused on the specific problem at hand. In about 2.5 hours we had not only built the full framework for our revised system, but also had input a ton of information and tested its ability to deliver outputs toward the goal. Had we started directly with building the system at the onset, or — heaven forbid — jumped around in our conversation, the process would have been much less efficient, or would have resulted in a less robust system.

As alluded to above, the idea of compartmentalising thought wasn’t introduced to me by Dalio. In fact, I remember learning the powerful concept at UBC in a second year chemistry class when my professor explained how assuming that an unknown value remained constant in a given equation, provides a partial solution that could later be leveraged to calculate the true change in the unknown value. Since then, I’ve routinely simplified my life with assumptions that enable me to focus on a single aspect of any problem. Usually I find that after solving an initial part, the rest comes more easily. The common military tactic “divide and conquer” isn’t much different. The idea is break things down and concentrate on the smaller pieces.

At MI, we actually take the concept of compartmentalisation even further by dividing our time between “thinking” and “doing.” We take great care to decide what is our best course of action and then we execute it. When we are in execution mode, we try not to deviate from the plan. After all, when in execution mode, we are unlikely to make decisions as insightful as those formed in thinking mode. Sticking to the plan also helps prevent us from growing lazy, or from reevaluating our goals based on whatever initiatives we feel like doing in the moment. We make a point to trust our past selves and the decisions we made while in thinking mode. Unless very significant new information is presented, we do not deviate.

Most importantly, in order to become better at thinking, we need to be able to evaluate how good we are at thinking. Such an evaluation can only be undertaken when we carry through with the thought-out plan, such that its conclusion — and the thinking process that went into it — can be examined. Any company that, or any individual who, drops tasks when the going gets tough or when the situation changes slightly, is a company or individual that is unlikely to accomplish anything of significant value in the long run.

It surprised me how adamantly Dalio recommends leveraging computer processing power and algorithms to guide the decisions in every part of our business. To be clear, from my read of Principles, Dalio isn’t simply recommending we leverage computers to run calculations related to investments or core company activities, but that we ought to leverage computers whenever possible. He suggests nothing shy of a symbiotic relationship between carbon and silica when writing “this combination of man and machine is wonderful.” The obvious — and I would argue inevitable — progression of this idea is cybernetics. I personally think humans will be full-blown cyborgs not long after we find a way for computer chips to run off calories. On our route to this inevitability, the winners will always be those pushing the envelope on how intimately we can synergise human intelligence and computing power.

However, I couldn’t help but feel that Dalio’s success has made him overconfident in his ideas about human biology and behaviour. He used personality profiling to such great effect at Bridgewater that he is convinced such a system is best for everyone, and that somehow human biology supports this. He envisions a day in the future when “you will be able to ask [a computer] what lifestyle or career you should choose given what you’re like, or how to best interact with specific people.” I think he’s wrong. I think he’s forgetting something very central to human biology. Human minds need the feeling of finding their own way because that is how the brain itself is organised. After all, we know the brain assembles reality from the inputs it receives. This need to find our own way could have a very beneficial purpose that Dalio overlooks. Using a computer is Dalio’s own way. What is yours?

He also seems to misunderstand computer algorithms, purporting that they are “immune to the biases and consensus-driven thinking of crowds.” In fact, algorithms also have biases, and machine learning algorithms trained on data from a number of different people will typically be fine-tuned to perform well on the largest groups within these populations. While this isn’t “consensus-driven thinking,per se, it is consensus-driven processing (the algorithm’s version of thinking).

One of the most profound and new concepts I encountered in Principles was the notion of becoming “free to die.” To an individual like myself with goals on timescales far beyond my own lifetime, the idea of ever being ready to hang up my hat seems lofty — there’s always more I can do. Yet if I look at my responsibilities from a different perspective, can I comfortably breath my last? Am I free to die once I’ve done all I could to steer the universe in the direction that prevents the heat death? Or am I never free to die because there is always something more I could do?

Leaving behind the notion of physical death, the concept of achieving enough to satisfy an exit is familiar to me. Leaving academia to focus fully on MI was only possible because I felt I had already contributed enough to basic neuroscience research for one lifetime, and was therefore free to let my basic research career die. I had to after all, if I had any hope of truly letting my translational research career live. Will there ever be a time when I’ve accomplished enough and set in motion sufficient forces that I’ll be free to allow my career with MI die? I hope so. It’s a goal anyway.

My first seven highlights above support Dalio’s primary thesis that “radical open-mindedness” underlies the very “idea meritocracy” that we must strive to achieve if we strive for excellence, success, survival. He emphasises this point by articulating that “being open-minded is much more important than being bright.”

I read every page of Principles carefully because his ideas resonated with me and challenged me. I want MI to be more successful than Bridgewater. I want to have a galvanised team that, together, represent the most powerful and meaningful healthcare company on Earth.

I will return to Principles again and again as MI expands. I consider Dalio as a mentor and am forever indebted for the inspiration and practical knowledge that he shares in this idea meritocracy bible.

Mentors are not infalible of course, and in the next installment of this four part review, we’ll go toe-to-toe with Mr. Dalio on the merits and morals of personality profiling.

Credits: The photo used in this story (but obviously not the book cover) was captured by the author. Copy and line editing completed by Prof. Judith Scholes of Cascadia Editors Collective.

Image for post
Image for post
Cover of Principles, screenshot from my Books app.

Neuroscientist & CEO @ Mobio Interactive. I support my team in the pursuit of effective and accessible healthcare for every human.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store