With that in mind, here are seven thought experiments related to happiness and suffering that might make you see your intrinsic values a bit differently:

— we don’t necessarily know our values —

Unfortunately, our deepest values are not something we automatically know about ourselves. The conscious side of our mind doesn’t have direct access to the rest of our mind. And much of what we care about lies in the subconscious, meaning that our explicit beliefs about our values may not be comprehensive or even accurate. So this at least opens the possibility that we might subconsciously value increasing strangers’ well-being more than we realize.

— our values are affected by our beliefs —

Some of what we value hinges on our beliefs about what’s true. And so if some of our relevant beliefs are false, or we haven’t fully explored all the implications of those beliefs (e.g., two things we believe imply a third thing but we haven’t realized that), then what we think we value may be, in a certain sense, “wrong”. So this at least opens the possibility that we might hold beliefs that are false or that contradict each other, such that, once they are corrected or the contradictions are resolved, we may end up caring more about increasing the well-being of strangers than we think we do now.

— our understanding of our values evolves —

We figure out our own values over time as we carefully introspect, discuss our values with others, compare options, notice and resolve contradictions, refine our understanding of the truth, flesh out the implications of what we already think is true, and infer things about ourselves from our own reactions. Hence, it is not that strange to think that our understanding of our values may change as we engage in reflection.

— a growing ember of classical utilitarianism —

So we may not fully understand what we value.

And I am proposing that through thought experiments about values, if carefully considered and reflected upon, quite a lot of people may realize that they care more about working to increase happiness or reduce suffering than they had originally thought. That many people are *partly* classical utilitarians in their values, even if they haven’t realized it, and that thought experiments can expose this.

— the thought experiments —

Warning: references to intense suffering and very difficult tradeoffs

(1) Suffering is bad, and not just for me

Remember that time when you felt really intense physical suffering (e.g., maybe you had a really nasty stomach flu)? Don’t dwell on that time, because I don’t want you to suffer now, but remember it just for a moment. Remember how much that suffering sucked?

Now take a few seconds to imagine a stranger. Someone you’ve never met and never will meet, but perhaps you passed them on the street at some point in your life. Take a moment to picture their face.

Now, suppose that right now this stranger is suffering in that same exact way that you recalled yourself suffering a moment ago. Assume this person is not someone who has done something terrible to deserve that suffering.

How do you feel about a state of the world where this stranger is suffering? Contrast it to a state of the world where that person is happy. I bet you think the latter world is better than the former.

I ran a survey asking people about their intrinsic values, that is, those things they value that they would continue to value even if no other consequences occurred as a result of that thing. In it, 49% of people (from the general U.S. mechanical Turk population that seemed to understand the question) reported that “people I don’t know suffer less than they do normally” is an intrinsic value, and 50% reported that “people I don’t know feel happy” is an intrinsic value.

It’s tough to measure people’s intrinsic values, and this is not a population that is fully representative of the U.S. population, so the exact numbers should be taken with a grain of salt. But these results suggest to me that many people do care about the suffering of strangers.

But now, the next question is, what properties should your caring about strangers have?

—

(2) Your friends care about the suffering of their friends

You presumably want the world to contain more of what your friends value (and less of what they disvalue) insofar as these values don’t conflict with your own.

Well, there’s a very good chance that one of the things your friends value is that their friends don’t suffer. Another thing your friends probably value is that their own friends get the things they value too, which presumably includes not wanting the friends of their friends (who are the friends of your friends’ friends) to suffer.

In other words, just by caring about the values of your friends, you may also care about the suffering of a whole host of other strangers. Not necessarily all strangers, but a lot of people you will never meet.

—

(3) More suffering is worse (a.k.a. scope sensitivity)

Suppose that 1 innocent person experiences a painful electric shock for one hour. How bad do you feel that is? Now suppose that, instead of that, 100 innocent people each experience the same electric shock for one hour. How much worse does that seem to you? Take a moment to consider it.

Now 10,000 people. How bad is that? Now 1,000,000 people. How bad is that?

At first, you may feel on a raw gut level that the 1,000,000 suffering is not that much worse than 1 person suffering. But are you really taking into account how many people 1,000,000 is? That’s about the entire population of San Francisco.

Notice how, when you really think about it, and you really try to get the enormity of the large numbers, 1,000,000 innocent people each experiencing a painful electric shock for one hour is way, way, way worse than 1 person experiencing it. Not just, say, twice as bad. But MUCH worse.

That implies that, for instance, eradicating a common and horribly debilitating disease that ten million people would otherwise get is not just a little bit more valuable than helping, say, 1000 people live slightly easier lives. It’s way, way, way more valuable!

I’m not saying you necessarily value a reduction in 1 million units of suffering as being 1 million times more valuable than a reduction in one unit of suffering, just that you probably do think it’s MUCH more valuable.

—

(4) Selfishness does not dominate

What’s the thing you value most in the world? Your life, maybe? Or your happiness? Or maybe something involving another person? My guess is that no matter how much you value this, there is an amount of suffering you’d be willing to give this up to alleviate.

For instance, if you had to give up your life to prevent all future suffering on earth, I bet you would do it, as terrible and unfair a choice as it would be to make.

—

(5) We should help suffering strangers when it is easy (a version of the famous drowning child thought experiment that Peter Singer has popularized)

Suppose a stranger you’re walking behind suddenly teeters and then collapses in front of you. The person is now lying on the ground, clearly in tremendous pain. You are the only person nearby.

I think most of us feel that even though we didn’t cause this person to be ill, we still have a moral obligation to try to help them. That is, (a) not being the cause of suffering doesn’t make us totally off the hook with regard to trying to relieve that suffering.

Furthermore, suppose that it would be a small inconvenience for us to help this person (e.g., we might have to show up 15 minutes late to a fairly important work meeting). I think most of us would still help this person (and would feel that it is the right thing to do). If true, that suggests that (b), if the size of the potential reduction of suffering to another person is much greater than our own loss by our helping them, we probably should help.

Finally, suppose that instead of this being a stranger right in front of us, we imagine that this is a stranger who we happened to have accidentally just Skype called by accident (by entering our friend’s user ID incorrectly). Assuming we don’t believe the person on the other end is faking, shouldn’t we still try to figure out some way to help this person (assuming it is feasible), even though they are far away? Of course, if we have no way to help them, obviously, we have no obligation to help. But suppose we can think of an easy way to help, shouldn’t we do it? This suggests that (c) our obligation to help doesn’t depend on how far away someone is, only on our ability to help that person.

We must then remember, of course, that there are people we could help around the world at little inconvenience to ourselves.

Even if you agree with (a), (b), and (c), that doesn’t mean that you think you should devote all your time and money to helping people who are suffering. But if you do agree with those points, then I suspect your value system tells you that you should expend at least some of your resources helping reduce suffering in others, if you have the means to do so without too much sacrifice.

—

(6) Other values may seem to diminish when happiness is even slightly reduced as a consequence of them

Suppose that you happen to have found out that (through no action on your part) certain people have a false belief about a certain topic. Furthermore, you know they would believe you if you corrected this belief.

The problem is that these people would all be slightly less happy if they knew the truth about this thing, and in fact, nobody would benefit in any way from this truth being known.

Would you tell these people? Well, you may think truth is important (I do too), but you may feel that it substantially takes the wind out of the sails of truth if all people involved are less happy because of it, and nobody benefits. I think in this case, some people will say, “What is the point of the truth if everyone suffers slightly more because of it?” In other words, they might feel the value of truth is reduced to almost nothing.

This isn’t just about truth. For instance, you can do a version of this thought experiment about equality (what if, in a particular group of people, you could make the group more equal in some dimension, but every single member of the group would be slightly less happy as a result). Or you can do it for almost any other value.

My guess is that these other values seem quite a bit less valuable (and perhaps to some not even valuable at all) when everyone is slightly less happy as a consequence, highlighting the potential importance of happiness in your value system.

Note that you may not necessarily feel this property is symmetrical with other values. For instance, suppose that someone reduces suffering a significant amount, but in doing so causes the people involved in the situation to have slightly less accurate beliefs. You may not feel that the slight reduction in accurate beliefs makes the reduction in suffering itself any less valuable.

—

(7) We can at least agree on suffering

Some people like apples and others like oranges. Some want to spread atheism, and others want to spread theism. Some people think you should obey authorities, while others value freedom of thought. But one of the few dimensions we are just about all similar on is that we don’t want to suffer ourselves, and we don’t want the people we love to suffer.

Some people are perhaps exceptions (e.g., Christopher Hitchens claimed Mother Teresa believed suffering to be at least sometimes good, quoting her as saying “I think it is very beautiful for the poor to accept their lot, to share it with the passion of Christ. I think the world is being much helped by the suffering of the poor people.”) I’m not sure what she meant by that or whether she would apply that to her own suffering or that of her loved ones, but it’s a possible exception.

That being said, though, disagreement on the badness of suffering seems really rare. Nearly everyone seems to find suffering bad, at least when it happens to themselves or their loved ones.

So if we all had to work as a species to reduce one thing, suffering seems like a pretty good contender. It’s hard to think of another thing we all dislike more.

— final thoughts —

Taken together, these thought experiments suggest (insofar as you buy into them) that you may believe:

(1) Suffering is bad when it happens to strangers

(2) You at least somewhat care about the suffering of many strangers by virtue of caring about the values of those people you care about

(3) More suffering of strangers is worse than less, and way, way more suffering is much worse still

(4) Your own self-interest is not more valuable than the potential for reducing all the suffering in the world

(5) We should put at least a little effort into reducing the suffering of strangers if it’s not too costly for us to do so, and we should not care whether those strangers are far away or near

(6) Most other values don’t seem as great if the result of producing them is to cause everyone involved to suffer slightly more, with no one benefiting, and these other values may even seem to lose their value in these cases

(7) We can all at least agree that suffering is bad and work together to reduce it

These points are not the same as classic utilitarianism, but they point in roughly the same direction as it does, I think. And anecdotally, some people seem to be quite impacted in their ethical views by thought experiments like these (though of course we can’t be sure it’s because they are revealing their deeper values as opposed to actually reshaping those values).

I don’t think that increasing the happiness of and/or reducing the suffering of conscious beings is the ONLY thing you care about. Nor do I think you SHOULD only care about those things.

But perhaps these thought experiments will make you realize that you care more about them than you thought you did, or that you’re more of a classic utilitarian than you realized.

This piece was first written on June 2, 2018, and first appeared on my website on December 2, 2025.

Note: here, I use the term “success” merely in terms of achievement, career success, or high levels of expertise, NOT in terms of happiness, living a good life, morality, having strong social bonds, etc. There is nothing wrong with not wanting to be successful in the way this post focuses on. But if you DO want “success” in the sense in which it is used in this post (or you are interested in being able to predict it in others), you may find some of the models here useful.

I’m also interested to know: which model (below) do you find most useful for thinking about success, and which one of these factors (used in the models) do you think is currently most limiting your success?

1. Noise theory:

success = luck

2. Genetic determinism:

success = (innate) aptitude + luck

Note: whenever I use “luck,” I mean random factors not already accounted for in the other factors in the model. So in the case above, “luck” means luck other than the random chance of what your aptitude is.

3. Traditional right:

success = aptitude + surrounding culture + hard work

4. Social justice left:

success = privilege + luck

5. Economic left:

success = social/economic class you’re born into + luck

6. Cynical theory:

success = some combination of self-promotion, bullshitting, social skills, good-lookingness, starting resources, and luck

7. Gladwell: 

success = whoever practiced for 10,000 hours + luck

8. Dweck: 

success = aptitude + growth mindset + luck

9. Duckworth: 

success = aptitude + growth mindset + grit + luck

10. Seligman: 

success = skill * effort * self-promotion * luck

11. Psychometrics: 

success = IQ + conscientiousness + low neuroticism + luck

12. Ericsson: 

success = luck + hours spent doing “deliberate practice” (i.e., with specific goals and tight performance feedback loops, while analyzing mistakes and dividing skills into micro-skills that can be practiced independently, ideally all done under the supervision of expert coaches)

13. My mega model:

success at a fixed goal = luck^a

* (resources+opportunities)^b

* (community/collaborator quality and supportiveness)^c

* (innate aptitude at relevant skills)^d

* intelligence^e

* rationality^f

* (creativity and resourcefulness)^g

* (social skills)^h

* (hours of deliberate practice)^i

* (unitary or obsessive focus on the goal)^j

* (conscientiousness and self-control)^k

* (physical or mental health)^l

* confidence^m

* (ambition and agency/self-directedness)^n

* (self-promotion skill and effort)^o

* courage^p

* (goal/task-specific factors)^q

* (efficiency and prioritization)^r

Each exponent a, b, c, …, r is a different number from 0 to 1. Note that each of these traits is selected because I believe, on average, having more of them improves the chance of success – that’s why I exclude negative exponents. Furthermore, I’m claiming that these factors, on average, each have diminishing marginal returns. That’s why the exponents are each less than 1 (making a concave function).

The values of the exponents vary depending on the field and type of skill. For instance, in some areas, courage is a minor factor (in which case the courage exponent, n, would be close to 0, and in other fields, courage is essential, in which case n would be close to 1). So, in other words: success is a PRODUCT of roughly 18 factors, and how much each factor matters depends on what you’re trying to do.

Note that this is designed so that if you have literally 0 of any factor, then the level of success is automatically 0 (since 0 times any number is 0). For instance, if you have literally no physical health, you are, presumably, dead, and if you have literally no ambition, presumably you just sit around all day or do the minimum you need to eat.

It’s worth noting that the factors above are not completely statistically or causally independent in reality (becoming higher in one may make you higher in another, on average). But I think the enormous extra complexity of trying to account for these dependencies probably is not worth it in practice.

How do you improve your odds of success?

A lot of times, when people are extremely successful, I think it’s because they avoid being TOO low in any of the factors, and they have one or two factors where they are exceptionally high. Many factors are “bounded” ones: for instance, you can’t work more than 24 hours per day. So it’s impossible to work more than 3x the amount the average person does. But there are some “unbounded” factors where you can potentially be WAY higher than the average person (e.g., “creativity”), which can drive the success score very high (as long as no other factor is close enough to zero to drag it back down). Hence, this model leads to an approach for thinking about how to be more successful (if that’s something you care about).

Put simply, success often flows from not being TOO weak on really important factors and having one or two really strong (and relevant) strengths.

Getting into more detail, here is a process you might use to consider how to increase your odds of great success:

1. For the goal/task you’re trying to succeed at, figure out which of the above factors matter substantially (which maps onto trying to – very roughly – figure out the exponents for each factor).

2. If your strong/weak factors are not a good fit for the goal, consider changing the goal to better play to your strengths, or consider teaming up with someone (e.g., a co-founder) to compensate for your weaknesses.

3. Once you have settled on a goal, identify any especially low factors (relevant to that goal) that are driving your potential for success down, and think about how you can improve at those. Due to multiplicative effects, very low factors can really drag down your potential for success. For instance, if you have severe mental health challenges that interfere with your day-to-day tasks, working on that first can be a great idea (even if you’re just optimizing for success).

4. Identify your strongest factors (that are relevant to that goal) and think about how you might improve at them or hone them to get them VERY high. You can also figure out how to make even more use of these great strengths of yours to achieve good outcomes. Often, one of the most effective things we can focus on is leaning into our greatest strengths (for instance, by designing a path towards our goals that leverages them or working to enhance them even more). This is especially the case once we’ve gotten barriers to success out of the way (i.e., we’ve worked on improving our especially low factors).

A question for you: right now, which of the factors listed above is the one that is most significantly limiting your success?

This piece was first written on September 12, 2021 and first appeared on this site on March 25, 2022.

For a new project, how do you decide WHAT to do WHEN? We propose that there are two main types of projects: ‘Jigsaw Puzzles’ and ‘Quests’. Let’s explore each type and how to best prioritize the tasks that they involve.

Type 1: Jigsaw Puzzles

A ‘Jigsaw Puzzle’ has a finite scope; you know what the steps are, more or less. Each piece of the puzzle has to be included in the project, so the question is just what order to do them in. A good example of a ‘Jigsaw Puzzle Project’ is completing an essay assignment for school, constructing a bookshelf for your room, or making a meal according to a new recipe. There are two guiding principles for prioritizing steps in ‘Jigsaw Puzzles’:

• The Laziness Principle: which steps make subsequent steps easier? Do those steps first because they reduce the effort of the whole project. With a literal jigsaw puzzle, trying to fill in the middle section too early may just waste time and effort, whereas doing the edges of the puzzle first will make the middle easier. You should focus first on the parts of your project that simplify future parts.
• The Motivation Principle: right now, work on the hardest parts of the project that you have sufficient energy, motivation, or focus to tackle. That way, life will be easier for future-you, who may have less energy, motivation, or focus left to spare. Be kind to your future self! You’ll be glad you did. Putting off hard parts makes the work as a whole more stressful.

Since, with a ‘Jigsaw Puzzle’ project, all the parts have to be completed at some point, all you’re really deciding on is the order in which you complete the project. It makes sense to choose an order to minimize total effort and stress (while maximizing your effectiveness). The two principles above make this possible.

Type 2: Quests

The other type of project is Quests. Unlike Jigsaw Puzzles, Quests are open-ended projects, both in how long they will take and in what steps should be completed. Good examples of quests include founding a tech startup, getting fit and healthy, or undertaking a big creative project. How do you prioritize the parts of a Quest?

Goal 

Figure out what you’re truly trying to achieve in your Quest that is of value (for instance, is the goal of your startup, fundamentally, to make people more productive, to make them happier, to reduce stress, to help them have better relationships, or something else?) 

For external-facing Quests, the ultimate goal should be framed in terms of the value you are seeking to deliver to your users (and so is based on a hypothesis about what your users truly find valuable). For internal facing quests (i.e., personal projects), the Quest should be framed in terms of what YOU value.

As you get deeper into a project, you’ll eventually have subgoals to your goals and sub-subgoals to your subgoals. But you must always remember the reason you’re doing the project in the first place. In other words, you must never stop thinking about the value (for your users in an external project, or for yourself for a personal project) that you are trying to create. Many different pressures can push you away from creating actual value: what’s exciting, what’s cool or trendy, what’s socially rewarded, what your investors want, what a committee can agree on, and so on. It’s incredibly common to start veering off course from the value you intend to create, and to spend years working on something that doesn’t create value at all! Don’t make that mistake: always keep the ultimate value in sight, even if you are working on a sub-sub-subgoal; otherwise, you’ll inevitably start adding bells and whistles to your project that don’t produce any value.

Options

Brainstorm options for the next steps of your Quest. There are many things you could do at any moment to work towards your project. Keep a broad view when considering the options for which task you should work on to reduce the chance of missing really good options. To generate ideas for steps, show your intended audience what you have so far, look at related projects, discuss with friends and experts, run surveys, and so on.

Remember, the choice you make for what to work on is only as good as the best option you considered! On the other hand, don’t overwhelm yourself by generating 50 different options that you’ll then go crazy trying to choose between. You need to strike a reasonable balance between over and under optimizing the steps for your Quest.

Score

Rate each potential option for what to work on by how valuable you think it is (for users, if an external project, to you, if a personal project), and how effortful it would be to implement (in terms of time, energy, cost, etc.). The best options to work on are those with the highest value in relation to the required effort (that is, value divided by effort is maximal). This basic approach of scoring options by both value and effort (or, in some cases, urgency, and importance) goes by a lot of different names, including the Priority Matrix or Eisenhower Box. What you’ll learn below is a somewhat more sophisticated version of this basic idea.

Compare

Group these options based on effort and value. This leads to FOUR options, as shown in this diagram:

Option 1: ‘Low Hanging Fruit’

These are the low-effort, high-value actions (upper left of the chart) that you should address first.

As soon as you start to run out of this kind of action, do more brainstorming, do more customer interviews, talk to more experts, analyze more data, etc. to discover more. You should always be searching for low hanging fruit, and as long as you have some available, that’s what you should be working on!

Option 2 and 3: ‘Quick Wins’ and ‘Leaps’

While looking for more ‘Low Hanging Fruit’, it’s good to include a mix of ‘Quick Wins’ — low value but low effort tasks, such as minor tweaks and bug fixes — and ‘Leaps’ — high value but high-effort tasks, such as new features. When there is no ‘Low Hanging Fruit’ (and you haven’t yet found more), doing a mix of ‘Quick Wins’ and ‘Leaps’ in parallel is usually best. If you only focus on ‘Quick Wins,’ you’ll get stuck in local optimals that prevent you from taking the project to the next level. If you only do ‘Leaps’, then you won’t have the feeling of making progress and may end up investing a lot of time in something that ultimately has to be thrown away, leading to a lack of project momentum.

For ‘Leaps’, you have to be really confident in their value before undertaking them since they burn up a lot of time/energy. Customer interviews, surveys, expert feedback, quick prototypes, data analysis of existing use, and playing devil’s advocate on your own assumptions can reduce the chance of wasteful leaps. Gathering more information is often critical before deciding to take a ‘Leap’. Meanwhile, ‘Quick Wins’ and ‘Low Hanging Fruit’ don’t require as much confidence as ‘Leaps’ because they are lower effort.

One other thing to keep in mind about ‘Quick Wins’, is that, as time passes, it can become increasingly costly to overlook them. For instance, what is now a minor issue with your database system can grow into major data corruption, or some dampness in the house you’re building can grow into pervasive mold. We’ll call these “Smoldering Quick Wins.” Those should be prioritized above ‘Leaps’ and other ‘Quick Wins’ because now they are easy, but soon they could represent a substantial problem.

Option 4: ‘Traps’ 

The 4th type of task is ‘Traps’ – the high effort, low-value tasks. Avoid these! They are a waste of time. Try to be clear-eyed when evaluating tasks; there is always a risk of getting sucked into ‘Traps’, for example, because a very small but very vocal group of users wants certain functionality, or by not calculating in advance how much effort certain tasks will take. You will also likely encounter situations where you just feel motivated or excited to work on a ‘Trap’ for some reason. Resist this temptation!

So, how to prioritize more effectively? For Jigsaw Puzzles, remember:

• Decide the order in which you complete the project by minimizing effort and stress while maximizing effectiveness.

For Quests, remember:

• Identify the value you are trying to create with your project, and always keep it in sight.
• Generate a multiple options for what you could do next
• Score options based on the value produced and effort/cost
• Narrow down your options into the four types: Low Hanging Fruit (high value, low effort), ‘Quick Wins’ (low value, low effort), ‘Leaps’ (high value, high effort), and ‘Traps’ (low value, high effort)
• Tackle ‘Low Hanging Fruit’ first, and as soon as you start to run out of it, start seeking more by getting feedback, talking to experts, brainstorming, etc.
• Then complete a mix of ‘Quick Wins’ and ‘Leaps’. Remember that ‘Leaps’ require confidence to proceed, so it is usually wise to gather information before moving forward with them.
• Be on the lookout for ‘Smoldering Quick Wins’ that are now easy to take care of, but could escalate if not dealt with. Complete these before ‘Leaps’ and other ‘Quick Wins’!
• Avoid ‘Traps’!

With that definition in mind, there are many reasons a work team may have low productivity. To make a team more productive, I suggest first trying to pinpoint the predominant causes of inefficiency, since different failure points typically have different solutions. The key is to identify and then focus on just the 1-3 of these causes that seem to be the biggest recurring blockers of team productivity.

Once these biggest blockers are identified, an analysis needs to be made of why they are occurring (e.g., using a method like the “5 whys”, where you try to uncover the root cause of the issue). Then, strategies need to be developed to try to resolve the blockers, and one or two strategies that have sufficient team buy-in need to be selected for implementation. Finally, re-evaluation needs to occur to make sure the problems are actually improved by those strategies.

Below is a list of these potential failure points or blockers.

There are four main facets of team productivity (Planning, Effectiveness, Resources, and Communication), which break down further into specific reasons for low productivity. You can use this list by considering each potential reason and scoring the degree to which you think it’s a problematic factor on your team (or having all team members anonymously score each potential reason for how big a problem it is, and then aggregating the responses to find the few most important seeming issues).

—

Reasons For Low Team Productivity:

—

(A) Planning

(1) Wrong Goal – the work is focused on achieving a goal that is not actually particularly valuable.

      e.g., the team is building a new feature that customers don’t want

(2) Poor prioritization – rather than focusing on the very most important things, the team focuses on things of secondary importance.

      e.g., the team lead keeps pushing team members to make tiny improvements to existing features, even though there are really major features where implementation hasn’t even begun.

(3) Slow Path – the planned route for achieving the team’s goal is not as efficient as other routes to achieving the same goal.

      e.g., the team could use a well-tested plugin to help them solve their problem, but the team lead insists they build their own alternative to this plugin.

(4) Incompletion – there is no pressure to finish projects, or team members work on far too many projects at once, so work doesn’t get completed, or takes much longer than it should.

      e.g., when a crisis comes up, the projects already in progress are abandoned, and rarely are they picked up again.

(5) Feature Creep – the project takes a really long time to be released because its scope or feature set keeps unnecessarily increasing, repeatedly delaying the launch.

      e.g., the client keeps making more and more requests about what to include in the next version.

(6) Missing Buy-in – team members don’t actually care about achieving the team’s goals (i.e., they don’t view the goal as valuable, and don’t feel like a genuine team, such that they care about the team’s success).

      e.g., Bill doesn’t think the product they are building is worthwhile, Sally doesn’t feel invested in the success of her team members or the team overall.

(7) Incentive Misalignment – some team members have incentives that cut against the project going well, or are focused on optimizing for personal goals at the expense of project goals.

      e.g., team members know that if they succeed at the goal, then someone else will take all the credit, and if they fail at it, there will be no negative consequences, and Bob actually wants the project to fail because then he’ll get to move on to a different project he likes more.

(8) Missing Skills – certain skills are needed to accomplish the goals, but no one on the team has these skills, and there are no external consultants that can be called on.

      e.g., no one on the team has a good eye for design, so the interface you’re building has the right features but looks bad.

(9) Reactivity – the team is constantly reacting to crises or imminent deadlines, which means there isn’t time to focus on achieving the long-term goals.

      e.g., every month or two, there is a major system failure, followed by weeks of scrambling simply to get things back to normal.

(10) Groupthink – team members do not feel comfortable sharing their unique ideas, or challenging the team lead, or getting their ideas heard above the most vocal person, or contradicting the group consensus, so the best ideas don’t filter to the top.

      e.g., the first proposed solution to a problem was accepted because no one wanted to challenge the person who proposed it, and since no one spoke up, everyone assumed the other group members must be in consensus.

(11) Guessing – the team doesn’t have enough data or information to solve the problems they are working on, but rather than gathering this data or information, they guess at solutions that aren’t very likely to work.

      e.g., the team has the goal of reducing customer churn, but they haven’t conducted customer interviews or carefully analyzed the churn data, so they are merely guessing at why churn is occurring and developing inadequate solutions based on those guesses.

—

(B) Effectiveness

(12) Insufficient Time – people not working enough hours.

      e.g., a culture of showing up at 10 am and leaving at 4 pm.

(13) Waste – spending time engaged in unnecessary processes or pointless meetings.

      e.g., a culture of constant meetings where you have little time to get your actual work done, or a requirement to tediously document all your work.

(14) Distraction – people may not be able to get “in the zone” on their work because of frequent distractions, or an environment where it is hard to focus.

      e.g., a noisy office environment where colleagues continuously interrupt you to ask you questions.

(15) Burnout – people may feel stressed, depressed, disinterested, bored, or exhausted, and find it is psychologically difficult to get their work done.

      e.g., a culture where bosses regularly yell at, blame, and fire employees for things that are not their fault.

(16) Bad Foundations – the work may be building on other work that was not well made, slowing down additional progress.

      e.g., programmers inherit a massive, buggy, and poorly written spaghetti codebase (i.e., high levels of technical debt).

(17) Disempowerment – team members are not allowed to do certain things (or make certain decisions) that would move the project forward, or they are required to follow a bureaucratic or standardized process that is not an efficient or effective process.

      e.g., a user experience researcher is not allowed to pay customers for doing interviews, but customers won’t do the interviews for free.

(18) Intrinsic Difficulty – the work may genuinely be intrinsically difficult, with progress speed inherently limited.

      e.g., work involving proving new theorems that others have failed to prove.

—

(C) Resources

(19) Slow Platforms – the systems or platforms on which the work is performed make progress more difficult, slower, or more complex than it needs to be.

      e.g., teams are forced to work on Windows 98 and experience regular computer crashes, or teams are forced to work using old and out-of-date software.

(20) Lacking Tools – the team members don’t have the best tools to do their work.

      e.g., a construction team is forced to use a saw that is inappropriate for the job because they don’t have access to the right kind of saw.

(21) No Training – there is a lot of relevant information about how to do the job well that team members are not told, and have to laboriously figure out on their own, or struggle to get by without.

      e.g., programmers are expected to figure out how the undocumented API works on their own via trial and error.

(22) Insufficient Assistance – when team members are stuck, they have no one knowledgeable they can go to (or that they feel comfortable going to) for help.

      e.g., a machine learning researcher can’t get her neural network model training properly and has no one she can ask for advice.

(23) Insufficient Skill – team members are not sufficiently skilled at the tasks they are trying to do.

      e.g., the team members responsible for writing documentation are not skilled at clear communication.

—

(D) Communication

(24) Blocking – team members are waiting on each other to do things before they can get their own work done.

      e.g., Sam needs approval from Sally to move forward, but Sally requires approval from Samantha in order to give Sam permission.

(25) Conflict – team members dislike each other, don’t trust each other, or have clashing personalities.

      e.g., Bill refuses to work with Sam, Jill thinks that Jenny is trying to undermine her, Tim and Tammy get into heated arguments.

(26) Discordant Goals – different team members are working towards different long-term goals, because they are not on the same page about what the purpose, mission, or primary goal of the team is.

      e.g., the product manager is trying to add features, whereas the engineering team is trying to do a feature freeze so they can focus on stability and efficiency.

(27) Ambiguity – the goals are not clear enough, leading to confusion, false starts, and stops, or circling around problems without directly solving them.

      e.g., there is agreement that the user interface needs to be “easier to use,” but little clarity on what that means.

(28) Duplication – team members end up repeating work that has already been done (or that is in the process of being done) by others, either because they don’t know that other work exists or because they don’t trust the quality of it.

      e.g., the new lead engineer doesn’t trust the code developed by the prior lead engineer and so decides to rewrite it from scratch.

(29) Unassigned work – it is not clear who is supposed to tackle certain work (e.g., it is not in any particular person’s job description or current assignments), so some important work just doesn’t get done by anybody.

      e.g., nobody has been assigned the responsibility of bug testing, so bug testing simply doesn’t get done, and therefore, the product is highly buggy.

(30) Siloed Information – team members need information from each other to do their work well, but this information is not transmitted reliably.

      e.g., the team member doing customer interviews isn’t reliably communicating what they learn to the team member planning UX changes.

A big shoutout goes to Eddie Liu, who helped develop this framework.

This piece was first written on July 3, 2019, and first appeared on my website on January 22, 2026.

There is a simple formula for thinking about how to be more productive that most people aren’t familiar with. It breaks down productivity into the product of three factors, namely:

PRODUCTIVITY = TIME x EFFICIENCY x OBJECTIVE

More explicitly:
PRODUCTIVITY
(i.e., the total value – according to your own values – of your work each week on a goal of yours)
= TIME
(i.e., the total hours you work on the goal each week)
x EFFICIENCY
(i.e., the average fraction of the goal you complete *each hour* of time you spend on it)
x OBJECTIVE
(i.e., the total value – according to your values – that would be achieved from *fully* completing the goal)

To make a metaphor for this equation: imagine you’re trying to drive across the country. TIME would be how long you spend driving each day, EFFICIENCY would be the number of miles you make it on average towards your destination each hour (i.e., related to your speed but also to what route you take), and OBJECTIVE would be how valuable it actually is to you to make it all the way to the other side.

This equation assumes that you do eventually achieve your goal (since for some goals, such as getting into a PhD program, not fully completing the goal may produce zero value to you). It also only measures the value in an “average” sense.

To see that this equation really works, consider how the units cancel each other out:

TIME x EFFICIENCY x OBJECTIVE

= (hours) x (fraction_complete/hour) x (value_for_completing_all)

= fraction_complete x value_for_completing_all

= value_for_fraction_you_completed = PRODUCTIVITY

When it comes to PRODUCTIVITY, people are often concerned with spending more time on their goal, but as the equation above makes clear, there are two other unrelated ways to increase productivity. Increasing any of the three factors by the same amount (say, 10%) is equally valuable when it comes to productivity since the equation is fully symmetrical in the three factors. I’ll take a moment now to examine each of the three factors and some of the tricks for increasing them.

(1) TIME in our lives is fixed, so making more time is usually about some form of prioritization, that is, taking time away from something else (e.g., social media, chores, sleep, hobbies, friends) to make more time to work on a goal. Though in some cases, it is about leveraging some resource (e.g., money or people you can delegate to) towards making more time.

TIME-related productivity tips include:

-don’t do tasks that are neither important nor urgent (just ignore these time-wasting tasks)

-make a list of all your goals and then permanently cut out all of them except the one or two or three most important ones, and focus for years on just those

-delegate and outsource as much as you can (e.g., if you manage people, delegate to them, or if you can afford it, considering hiring a part-time assistant)

-if you can afford it, buy time-saving devices (e.g., a laundry machine/dishwasher/cleaning robot like Roomba) and services (e.g., a cleaning service)

-know the value of your time so that you know how much money to spend on time-saving stuff (you can calculate it using our tool here: https://bit.ly/2Fwiy8r)

-get comfortable saying “no” more (in a way that doesn’t offend) when people ask you to do things

-avoid addictive things and time-wasting activities (where afterward you don’t feel good about that use of time) and consider using plugins to block websites you spend too much time on

-automate tasks you do regularly (e.g., by making excel templates, or by using Zapier or IFTTT to connect services together, or using our system GuidedTrack.com to create repeatable processes/reusable tools)

(2) EFFICIENCY is about working effectively during each hour spent.

EFFICIENCY tips include:

-figure out what times of day you are most effective, and do your most important and challenging work at those times

-use caffeine to help regulate which hours are most productive (i.e., to make the most important hours work best for you)

-avoid getting too little sleep and avoid low sleep quality if you can (e.g., don’t drink caffeine at night)

-do restorative activities when you need a mental break from work if you can, such as quick exercise, yoga, taking a walk, or meditation

-turn off all non-essential phone and computer notifications so that you don’t get pulled out of the work you are doing

-avoid multi-tasking since it tends to lead to both slower and lower quality work

-leave long blocks of uninterrupted work time if you can (e.g., at least two-hour-long blocks with no meetings or distractions) so that you can achieve deep focus

-use the Pomodoro technique if it makes you more efficient (e.g., https://bit.ly/1gCYr3U)

-learn to use your tools faster (e.g., learn the key commands on your computer so that you can use the mouse less, and learn the shortcuts for the email program you use)

-if you can, make sure to have high-quality equipment for your work (e.g., if you spend 10 hours a day on your computer/using the internet, make sure your computer and internet run fast)

-get feedback from other efficient people about the process they do to do similar work, and see what ideas they have for streamlining your process

-break down the difficult tasks you do into sub-skills, and practice those sub-skills until you get good at them. For instance, if you are a slow typer, specifically practice your typing if it influences the speed at which you do all your other work.

-plan your route to achieving your objective carefully. Don’t just jump into working on the goal immediately; try to figure out the most efficient path to get you there. Compare multiple possible plans for achieving your goal to figure out the most efficient one.

-get others to critique your plan of how you’re trying to achieve your goal to see if they have ideas for a better path you may not have thought of.

(3) OBJECTIVE is about making sure the goal you are working towards is one that, if achieved, will produce a ton of value (according to what you consider valuable).

OBJECTIVE-related tips include:

-spend time reflecting on what you think is truly valuable, since the better you understand what is valuable, the easier it is to seek value in your goals

-don’t just pick a goal right away; compare multiple potential goals and evaluate how valuable they are before deciding between them

-explain your values to other people whose opinions you trust, and explain which goals you are considering, to see if they have thoughts about which goals to pick

-make sure you are aware of what the actual results of achieving a goal will be. For instance, if your goal is to become a doctor, investigate thoroughly in advance what it is like to be a doctor (ideally by talking both to current doctors and to people that decided to leave medicine).

-make sure that the goals you choose are based on what you believe is valuable and that you aren’t accidentally basing them on what others think is valuable instead (e.g., due to social pressures you experience)

It is in this OBJECTIVE variable that you tend to see the largest multiplier effects on PRODUCTIVITY since some goals are, in an expected value sense, at least 100x more valuable than others. Though typically, in those cases of very large amounts of value, the uncertainty in the value is also high (so one goal might be 100x better in expected value but still have a substantial chance of producing no value).

Oddly, some goals we may choose may have negative expected values (even according to our own value systems). Consider, for instance, someone who works for years towards a goal because they think it will make their parents happy (and it makes them miserable to work towards it). But it turns out they are wrong, and their parents are actually indifferent to them achieving the goal! In that case, due to a false belief about the world relating to their parents, the OBJECTIVE factor in the equation ends up being negative, making the whole productivity equation negative (hence the more TIME that is spent, the *less* value is produced, reversing the usual relationship!)

So, keeping all this in mind, what should you do if you want to be more productive? Well, remember that productivity is about three factors – TIME, EFFICIENCY, and OBJECTIVE.

It’s not just about how many hours you work towards a goal, but also about how efficient each hour of that work is and about how valuable the goal is to achieve in the first place. Each factor has unique techniques and tricks that can help you increase your total productivity.