Every day, we make far more decisions than we realize. Many people have tried to quantify the number of decisions, and the most cited number is ~35,000 decisions a day from Cornell, and the corollary to this is ~1 billion decisions in a lifetime (35 000 * 365 * 80 years). However, as it turns out, this number is the result of a citation loop with no valid source.
The only other reputable source seems to be a 2007 study by Cornell University researchers Brian Wansink and Jeffery Sobal concluding that people make approximately 227 food- and beverage-related choices alone, which is roughly 15 times more than they consciously estimate. However, as this article points out, Brian Wansink was removed from his academic position and had 18 of his articles retracted. Although the study discussed here has not been retracted, it has clear methodological and conceptual shortcomings inherent in the study’s design.
Perhaps it’s not so strange that it’s very challenging to quantify the number of decisions we make in a day, as most of them are small and trivial subconscious decisions.
While the vast majority of these decisions are trivial, a small but critical subset carries significant consequences for ourselves and others. Some examples are:
- Marriage
- Career
- Friends
- Kids
- Where to live
- Risks to take
The quality of those big decisions will determine the type of life you live.
The below sections are made in an attempt to help you be more conscious of your decision-making, and hopefully better at it. I examine practical frameworks and tools for making how to think about them the big decisions, and tools for thinking about the big decisions and how to approach them precisely in those high-stakes moments, both as an individual and as a group.
1. Cognitive Foundations: The Two Systems of Thinking
As Daniel Kahneman explains in his seminal book Thinking, Fast and Slow, our brains rely on two systems: the fast and intuitive System 1, and the slower, analytical System 2. The first section below explores these systems and the predictable biases they create. Also see the article on How We Know What We Know.
The Two Systems of Thinking
- System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control (intuitive, emotional, fast thinking). This system typically handles routine matters efficiently.
- System 2 is slower, deliberate, and effortful. It allocates attention to complex mental activities and makes choices (analytical, logical, rational, slow thinking). We must consciously engage this system when the outcomes matter most.
- Most of what we think and do originates in System 1, while System 2 is often lazy and endorses System 1’s suggestions with little scrutiny.
- The interaction between the two systems determines how we think, judge, and make decisions.
Heuristics and Biases
- Far from being rational machines, when we apply our System 1 thinking, we rely on mental shortcuts that protect us in everyday life and are generally useful, but often produce systematic errors and cognitive biases. As a result, much of what we think we “know” is incomplete, distorted, or entirely constructed by the mind, leaving even experts vulnerable to overconfidence in their own knowledge and the certainty of the evidence before them.
- Availability heuristic: We judge probability by how easily examples come to mind.
- Representativeness heuristic: We judge likelihood by how similar something is to a stereotype, often ignoring base rates.
- Anchoring effect: Judgments are heavily influenced by an initial number or value,
even if it’s arbitrary. - We are prone to confirmation bias, hindsight bias, and the halo effect.
Overconfidence and Illusions of Understanding
- We tend to have excessive confidence in our own beliefs and predictions (overconfidence bias).
- The planning fallacy leads us to underestimate time, costs, and risks of future projects.
- We create coherent stories from limited information and
then believe those stories more than the evidence warrants. - WYSIATI (What You See Is All There Is): System 1 draws conclusions based only on the information currently available, ignoring what is unknown.
Choices and Prospect Theory
- People are not rational agents as assumed by classical economics. They are loss-averse.
- Loss aversion: Losses hurt roughly twice as much as equivalent gains feel good.
- Prospect theory explains how people make decisions under risk: they are risk-averse when facing gains and risk-seeking when facing losses.
- The endowment effect and status quo bias make us overvalue what we already own.
- Narrow framing and mental accounting lead to inconsistent choices.
The Two Selves
- The experiencing self lives in the moment and feels pleasure or pain continuously.
- The remembering self evaluates past experiences based on peak moments and how they ended (peak-end rule).
- These two selves often disagree
We choose experiences based on what the remembering self will recall,
not what the experiencing self actually enjoyed. - This explains why we repeat painful experiences, or
remember vacations more fondly than we actually felt during them.
Broader Implications
- Much of human judgment and decision-making is intuitive rather than rational.
- Cognitive biases are not random mistakes, but predictable features of how our minds work.
- Understanding System 1 and System 2 can help us design better policies, organizations, and personal habits.
- True expertise requires deliberate practice and feedback to train System 1
to perform more reliably.
While we cannot easily eliminate our biases, we can recognize them, slow down when it matters (to activate System 2), and design environments (nudges) that help us make better decisions.
With a clear understanding of how our minds actually work, we can now apply practical mental models that directly counteract these biases.
2. Foundational Mental Models
- First Principles Thinking (Elon Musk)
Break every problem down to the most fundamental truths (physics, basic realities) and reason up from there, rather than reasoning by analogy or following conventions. - Challenge All Assumptions (Elon Musk)
Ruthlessly question every requirement, constraint, and “that’s how it’s always been done” belief before accepting it. - Occam’s Razor
A classic simplicity heuristic that pairs well with first principles thinking and challenging assumptions.
Advocates for simplicity and elegance in reasoning, favoring explanations that do not introduce unnecessary complexities or entities beyond what is required. Read more about it in this dedicated article. - Probabilistic Thinking (Elon Musk)
Evaluate decisions based on probabilities and expected value, rather than binary “will this work or not” thinking. - High Agency + Extreme Ownership
Assume you can influence almost any outcome through sufficient effort and creativity, and take full responsibility for results. - Long-Term Prioritization (Elon Musk)
Focus relentlessly on what matters most over the longest time horizon (often 10–100 years), while ignoring short-term noise and conventional metrics.
The Matthew Effect explains why small early decisions (or inactions) compound over decades, which drives home how cumulative advantages can be built up, and further underlines long-term prioritization and second-order thinking.
More Mental Models (beyond decision-making)
3. Decision Classification – Reversibility Matters
“1-Way Door” vs “2-Way Door” Framework
One of the most influential decision-making principles at Amazon, enabling the company to move extremely fast on the vast majority of decisions, while reserving deep scrutiny for the few truly consequential ones. Jeff Bezos distinguishes between two types of decisions:
- 1-Way Door decisions are high-stakes and largely irreversible. Typically extremely difficult and costly to go back. These require slow, deliberate analysis using System 2 thinking because the consequences are long-lasting (e.g., major acquisitions, large infrastructure investments, or fundamental shifts in business strategy). These decisions should typically be lifted to the most senior executives and their teams to ensure the right level of rigor and analysis is being done.
- 2-Way Door decisions are reversible. If the decision turns out to be wrong, you can simply walk back through the door and try something else. Most decisions fall into this category and should be made quickly with experimentation and speed rather than over-analysis. These decisions should typically be done by individuals, or very small teams, deep in the organization.
That is not to say that some level of decision-rigor should not be applied to 2-Way door decisions, but much less is required. One could determine the level of rigor for the process, templates to apply, etc. required to make a good decision based on:- The importance of the decision.
- The frequency of the decision.
Rule of thumb
For reversible decisions, optimize for agility. Do experiments and change course if needed. The biggest risk is not making a bad reversible decision (2-way door decisions), but moving too slowly and missing opportunities.
Short video (3:10 min) in which Jeff Bezos explains 1-way door and 2-way door decisions (uploaded to YouTube by Startup Archive, Jan 2024). This clip comes from Bezos’ full 3-hour conversation on the Lex Fridman Podcast #405 (Dec 2023). The relevant section starts around 1h 30m, but the clip above is a very good edited highlight.
Another way to think about decision classification, is asking yourself whether this decision is like choosing a hat, a haircut or a tattoo.
- A hat is quick to try on and easily changeable.
- A haircut is more long-term, but not permanent.
- A tattoo is long-term and requires deliberate thought before doing it, as it’s not easily reversible.
4. Managing Decision Energy & Fatigue
- Decision-making power is mentally draining and depletes throughout the day (this is known as decision fatigue). This is why System 1 (fast, intuitive, bias-prone thinking, use of mental shortcuts such as reasoning from analogy – as opposed to reasoning from first principles) becomes the default.
- Make your most important decisions early in the day, when mental energy is highest.
- Reduce unnecessary decisions (e.g., wearing the same clothes daily like Mark Zuckerberg, Lex Fridman, Steve Jobs, Barack Obama) to preserve decision-making resources.
Practical implementation tip
See my guide to daily routine optimization for ways to automate small choices
and protect decision-making bandwidth.
5. Individual Decision-Making Techniques
- Pre-Mortem Technique (Gary Klein & Kahneman)
Before deciding, imagine the project has already failed and ask “What caused the failure?” This uncovers hidden risks and weak assumptions that normal planning typically misses. - Inversion (Charlie Munger)
Instead of asking “How do I succeed?”, ask “What would cause this to fail?” and systematically avoid those things. Extremely powerful for both personal and strategic decisions. - 2nd-Order Thinking
Explicitly map out long-term consequences (2nd, 3rd, and 4th-order effects), not just immediate outcomes. Contributes to avoiding solutions that create bigger problems later. - Regret Minimization Framework (Jeff Bezos)
Project yourself into the future and ask which decision you would regret more in 80 years.
To operationalize this for life choices, check out the goal-setting guide. - Outside View / Reference Class Forecasting (Daniel Kahneman)
Look at how similar past projects turned out (base rates), to get a more realistic estimate, instead of relying only on your optimistic inside view. - Circle of Competence (Warren Buffett & Charlie Munger)
Clearly define what you deeply understand versus what you don’t, and stay inside or deliberately expand your circle. - Opportunity Cost Awareness
Explicitly ask “By choosing this, what am I giving up?” Most people severely underestimate opportunity cost when making decisions.
Learn How to Reclaim 40+ Hours per Week, and pair these strategies with high-ROI tools - Commitment Devices & Implementation Intentions
Pre-commit to specific actions (e.g., “If I feel demotivated, then I will do X”, “If X happens, then I will do Y”) to bridge the gap between intention and action. Strongly supported by behavioral science for bridging the gap between intention and action. - Meta Thinking
Ask yourself: “Which biases might be at play right now?“
You can’t make a perfect decision, but which uncertainties and potential biases can endure to move on?
Many of the thinkers referenced here are expanded in our curated book list,
which features Kahneman, Munger, and many others on decision-making and mental models.
6. Group Decision-Making Challenges & Solutions
Group Dynamic
Groups often suffer from conformity (people adapt and converge on a view), social loafing (“everyone’s responsibility is no one’s responsibility”), and the desire for harmony over accuracy. Humans tend to choose the social and relational aspects, rather than accuracy and effectiveness.
We also tend to wrongly assume that others know what I know, so keep quiet rather than raising our voice to share a perspective or a concern.
These issues typically resolve themselves by taking on an owner-mindset. This is the habit of thinking and acting as if you own the outcome, not just the task. Instead of waiting for direction, an owner spots problems early, takes initiative, and feels personally accountable for results, good or bad. They treat resources like their own money, focus on long-term value over short-term comfort, and constantly ask, “If this were my company, what would I do differently?” This shift turns “That’s not my job” into “How can I make this better?” and separates people who execute from people who truly build.
Noise vs Bias (Daniel Kahneman)
Noise, as defined by Daniel Kahneman, refers to the unwanted, random variability in judgments that occurs when different people (or even the same person at different times) reach inconsistent conclusions about the same situation, even when they should agree.
Bias is the systematic deviation in judgments where people consistently err in the same direction due to predictable mental shortcuts, prejudices, or flawed heuristics. Here’s a comprehensive map of human biases.
Together, noise and bias are the two fundamental flaws that degrade the quality and reliability of human decisions.
In his book Noise: A Flaw in Human Judgment, Daniel Kahneman suggests doing a Noise Audit by systematically looking for inconsistency and then revising the process, not the individual answers, to make judgments less noisy.
This entails having multiple interchangeable professionals (e.g., judges, underwriters, or hiring managers) independently evaluate the same set of realistic, but fictional cases without discussing them. You then measure the spread in their ratings or decisions to quantify the hidden variability (often shockingly high). This “audit” serves as a diagnostic revision of the organization’s judgment system.
Amazon 6-Pager / Narrative Memo
Write a full narrative document (typically 6 pages) covering context, goals, tenets, current state, lessons learned, and recommendations. The entire document should be written as a narrative (full prose paragraphs, not bullet points or PowerPoint slides). Distribute it prior to the meeting, so discussion starts after silent reading (usually 15–30 min).
This pre-filled narrative replaces traditional presentations and ensures the meeting focuses on discussion and decision-making, rather than information sharing. Jeff Bezos has emphasized that writing the memo forces clearer thinking and higher-quality conversations.
Short video (6:25 min) in which Jeff Bezos explains 6-pager. This clip comes from Bezos’ full 3-hour conversation on the Lex Fridman Podcast #405 (Dec 2023).
There is no single rigid official template, but the expected content that must be filled in follows this consistent structure:
- Introduction / Context: A clear overview of the topic, why it matters, and what the document will cover.
- Goals: Specific, measurable objectives the proposal or discussion aims to achieve.
- Tenets: The guiding principles or core beliefs that underpin the thinking in the document.
- State of the Business / Current State: A factual description of the current situation, including relevant data and metrics.
- Lessons Learned: Insights from past experiences, what has worked or failed, and why.
- Strategic Priorities / Recommendations: The actual proposals, next steps, or decisions being recommended, supported by reasoning and data.
- Appendix (optional, but common): Supporting data, detailed analysis, charts, or additional context.
Delphi Process
- Use a neutral facilitator (without decision authority) whose job is to manage the process, not the decision itself.
- Every participant independently submit their assessment (e.g. Yes/No) and reasoning to the facilitator before the meeting. This surfaces all views without group pressure and improves preparation among participants. It also makes participants feel more responsible and demonstrates that their view is of importance.
- The neutral facilitator can lift reasoning, shared prior to the meeting, as part of the discussion to ensure that these views are properly considered. This can potentially be done in several steps in which the participants gets to hear others’ reflections and reasoning. Then, conduct another vote/assessment individually, reconvene and then choose some alternative(s) that seems promising.
- Ban Conclusion Talk in Early Discussion
Allow only arguments and perspectives initially, no conclusions, so others can incorporate them before forming their own opinions.
- Techniques to Improve Discussion Quality
Play Devil’s Advocate and use Socratic questioning (intellectual midwifery, helping the people in the group to give birth to knowledge through dialogue.
Combinations
All the above bullets in this section (incl. the Delphi Process and the Amazon 6-pager) could potentially be combined, by sending out the 6-pager narrative memo prior to the meeting. Then, the neutral facilitator for the decision-making process would receive the each participant’s assessment, view and reasoning prior to the meeting, and driven the process based on that starting point.
For further deep dives, go through The Business Fundamentals
and How to Build Stronger, More Innovative, More Inspiring Organizations.
7. Advanced Group Decision-Making: Ray Dalio’s System
One of the most powerful group systems ever built comes from Ray Dalio at Bridgewater Associates (among the world’s largest and most successful hedge funds). It turned subjective opinions into a systematic, data-driven & merit-based process, dramatically reducing the usual problems of hierarchy, politics, and groupthink, and made it the foundation of Bridgewater’s culture and success.
Ray Dalio’s TED Talk “How to build a company where the best ideas win” (2017 | 16:33 min) explains their company culture and decision-making framework very well. Here are the core principles:
Radical Truth & Radical Transparency
Start by demanding absolute honesty and openness about what is true, even when it is uncomfortable. Hide nothing, including weaknesses and mistakes.
Idea Meritocracy
The best ideas must win, regardless of who proposes them. Decisions are not based on hierarchy or status, but on the quality of thinking.
Believability-Weighted Decision Making
Weight people’s opinions according to their track record and expertise in the specific area. Not everyone’s view counts equally.
Practical Implementation
- Believability is quantified and tracked objectively. Every employee has a public “Baseball Card” profile that shows their track record, strengths, weaknesses, and past accuracy on different types of decisions.
- Real-time believability weighting in meetings. During discussions (especially important ones), participants rate each other’s believability on the topic being discussed. Algorithms then mathematically weight each person’s opinion.
- There is always one clearly designated “Responsible Party” (RP) who owns the final decision, but they are strongly encouraged (and often required) to heavily factor in the believability-weighted input from others.
- Tools and systems used
- App
Dot Collector (real-time feedback and believability ratings), which is a real-time app where people give and receive feedback and believability ratings during or after meetings. - Software
Bridgewater Associates built software that calculates weighted averages of opinions based on each person’s historical believability score. - Dispute Resolution process
If there is disagreement, the process automatically escalates to higher-believability people or uses the weighted input to guide resolution. - Cultural rule
You are expected to “speak up” if you disagree, but you must also be willing to be proven wrong. The goal is never to protect egos, it’s to get the closest thing to the truth possible.
- App
The 5-Step Process (core algorithm for any decision or problem)
- Have clear goals.
- Identify and don’t tolerate the problems that stand in the way of your goals.
- Accurately diagnose problems to get at their root causes.
- Design a plan to eliminate the problems.
- Push through to completion with discipline and accountability.
Systematize & Codify into Principles
Turn repeated successful decisions into explicit, written principles that can be refined and used as algorithms. This turns experience into a repeatable decision-making machine.
Pain + Reflection = Progress
Treat mistakes and painful realities as the best source of learning. Systematically reflect on them to evolve your principles.
Mastering decision-making is not about eliminating every bias. It’s about recognizing them, slowing down when it matters, and using the right framework at the right time. The tools above give you exactly that operating system.
📚 Sources and References
- 🕮 Book: “Nudge: Improving Decisions About Health, Wealth, and Happiness” (2008) by Richard H. Thaler
- 🕮 Book: “Influence: The Psychology of Persuasion” (1984) by Robert Cialdini
- 🕮 Book: “Predictably Irrational: The Hidden Forces That Shape Our Decisions” (2008) by Dan Ariely
- 🕮 Book: “Thinking, Fast and Slow” (2011) by Daniel Kahneman
- 🕮 Book: “Noise: A Flaw in Human Judgment” (2022) by Daniel Kahneman
- 🕮 Book: “Superforecasting: The Art and Science of Prediction” (2016) by Philip E. Tetlock & Dan Gardner
- 🕮 Book: “Bedre beslutninger – om kreftene som påvirker vurderingene dine og hvordan du tøyler dem” (2022 | In Norwegian) by Jan-Ole Hesselberg
- 📄 Study: “Mindless Eating: The 200 Daily Food Decisions We Overlook” (2007) by Brian Wansink and Jeffrey Sobal, Environment and Behavior 39:1, 106-123.
- 📄 Article: The myth of 200 daily food decisions, Max-Planck-Gesellshaft (2025)
- 🎙️Podcast: Full 3-hour conversation w/ Jeff Bezos on the Lex Fridman Podcast #405 (Dec 2023).
- 🎬 Video: Ray Dalio’s TED Talk “How to build a company where the best ideas win” (2017 | 16:33 min)
Leave a Reply