Book Club: Principles of Life and Work

For May book club we read the Principles of Life and Work by Ray Dalio. This book is DENSE, so only 2 of us actually finished the book (more than 50 folks are in our book club, although only 10-20 show up monthly), and usually 95% of folks finish the book, so this is fairly rare. That being said, I don’t think it was an indictment of the book so much as the topic is written with a lot of due diligence (a deeply data-driven approach to interpersonal topics), and can be a bit robotic if you don’t relate to a numerical analysis framework. Still there are incredibly good nuggets that came out, and are worth calling out:

1. Write down one’s principles. No one teaches you this, nor is this a typical phase of development in school, at home, or at work. Truly though, don’t you want to be clear about your values and principles? Won’t that help your spouse/partner, children, coworkers, etc. to know what you value, how you think, and therefore the best ways to interact with you? What a blessing to have that insight into another person so you can understand where they are coming from and how to approach a discussion, decision, etc. to help anchor the decision in what matters to them.
2. The concept of an “orchestrator” you vs. the “worker” you. Fundamentally this notion is that you must seek to understand what you are truly good at, and where you should delegate for the sake of the overall project/organization/team. Feedback in this is your greatest friend in this process, particularly negative feedback. NO ONE is good at everything. This truth is not something to bemoan or be ashamed. You have to seek to learn where “worker” you is not good, decide if you want to improve, or enable the “orchestrator” you to ensure that part of the work is with someone else. Ultimately, you own the outcomes of your career and life, and you need to approach it objectively to have excellent outcomes.
3. For a data-driven approach, he discusses the strength of computers and AI, but also the dangers. In a sense that AI will detect patterns, but there is more that goes into decision making than directing patterns–AI without human interpretation and/or validation only reinforces bias, and our goals for our organizations and decision making should be greater than that.

So since so few folks made it through the whole book, I decided to try to write a summary. The 5 Major Life Principles Mr. Dalio states are:

1. Embrace Reality and Deal with It
2. Use the 5-step-process to get what you want in life:
   1. Set clear, audacious goals
   2. Don’t tolerate problems
   3. Diagnose the root causes
   4. Design a plan before you act 
   5. Execute to completion
3. Be radically open-minded
4. Understand how people are wired differently
5. Learn to make decisions effectively

His major work principles fall into similar themes:

1. Build a great team:
   1. Focus on great people 
   2. Build a great culture
   3. Create the machines to ensure your outcomes consistently match your goals 
   4. Align your work with your passions
   5. Do it with people you want to build a future with
2. Get the culture right by surfacing and resolving disagreements
   1. Radical Truth and Radical Transparency
   2. Nurturing Meaningful Work and Meaningful Relationships
   3. Making it a cultural norm to learn from mistakes
   4. Getting people in sync
   5. Using Believability-Weighted Decision-Making
   6. Having an agreed resolution process
3. Get the people right
   1. Put WHO before WHAT
   2. Hire right
   3. Fit the right people into your organizational design by continually training, testing, evaluating and sorting them
4. Build and evolve your machine:
   1. Running your machine as a manager/designer
   2. Not tolerating problems
   3. Diagnosing problems root causes
   4. Continually improving your machine design 
   5. Executing your plans
   6. Using tools and protocols to shape habits, and 
   7. Paying attention to governance

These concepts are simple to write down (it is what makes them so compelling), but are actually hard to execute (which is what makes the book long/detailed). I think believability-weighted decision making seemed difficult to institute culturally (but then again, we all have bias and are bringing it to work anyway, so why not be explicit about the reasons for weighting one person’s input differentially).

I highly recommend this book, as much as an exercise in how to approach an analytical person on the topics of culture, leadership, principles, and values, as for one’s own introspection. You will definitely learn something.