Why Habit Formation is Hard

Recently, I moved from Las Vegas to Seattle. In the process I realized that activities like moving belongings and getting a new driver’s license are not the hardest part. The difficulty of moving habits is much higher. About 80% of the cost of a move, I suspect, is the cost of moving habits. We lose months of time in the run-up to a move and after.

An example is your gym routine. It’s possibly the most important habit in your life. But it is surprisingly hard to “move” from one context to another.

In my case, I signed up for a gym very similar to the one I used to go to in Vegas. It has similar facilities and a similar range of equipment, trainers and programs. Like my old Vegas gym, my Seattle gym is about a mile and a half from home. The membership cost is about the same.

Yet, it’s been more than a month and I still haven’t found my rhythm. By contrast, when I joined the Vegas gym, it took me less than a week to settle into a great routine.

Why is this?

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Annealing the Tactical Pattern Stack

Human behaviors are complicated things. They are easy to describe, as fragments of narratives, but hard to unpack in useful and fundamental ways. In Tempo, I offered a model of behavior where universal tactics (universal in the sense of arising from universally shared conceptual metaphors, and being enacted in domain-specific ways) form a basic vocabulary, and are enacted through basic decision patterns, which are like basic sentence structures in language.

I suggested that there are four basic kinds of tactical pattern: reactive, deliberative, procedural and opportunistic, that could be conceptualized via this 2×2, where the x-axis represents the locus of the information driving the action (inside/outside your head) and the y-axis represents whether the information has high or low visibility (i.e. whether it is explicit and in awareness, or whether it is part of the frame/background, and below awareness).

 While writing the book, I tried to figure out whether these behaviors also form a natural hierarchy of sorts. I was unable to make up my mind, so I did not include the idea in the book. Now I think I have a good model. The stack looks like this (the simplicity is deceptive):


Why? And how should you understand this diagram?

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Breakout Moves and Exponential Outcomes

Humans differ in abilities by at most an order of magnitude along dimensions that can be meaningfully measured, such as speed or height. When humans compete on the basis of such “Olympics” variables, you tend to get a linear relationship between effort and outcome. If you can run twice as fast as me, you will cover twice as much distance over any given period of time.

It takes civilized tools and social constructs to create greater differences. Written language and mathematics are civilized conceptual tools. Guns and computers are civilized physical tools (because it takes civilizations to manufacture them).  Money is a social construct.

A race that depends strongly on tools, and with outcomes measured in terms of social constructs, can lead to exponential relationships between efforts and outcomes (due to compound-interest style accumulation dynamics), as well as orders of magnitude differences in relative outcomes.  How does this work?

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Positioning Moves versus Melee Moves

My general philosophy of decision-making de-emphasizes the planning/execution distinction. But I am not an agility purist. Nobody is. You can think of the Agility Purist archetype as a useful abstraction. This mythical kind of decision-maker believes that a mind and personality that is sufficiently prepared for a particular domain (say programming or war or biochemistry) needs no preparation for specific situations or contingencies. This magical being can jump into any active situation in that particular domain and immediately start acting effectively.

At the other extreme you have an equally mythical Planning Purist archetype who has thought through every possible contingency all the way through the end and can basically hit “Start” and reach a successful outcome without further thinking. In fiction, this is best represented by jewelry heist capers based on long, involved and improbably robust sequences of moves, as in Ocean’s Eleven or The Italian Job. A few token things go wrong, but overall, these narratives play out like Rube Goldberg machines.

Clearly, reality lives somewhere in the middle. But planning vs. execution is not always a good pair of trade-off variables to create reality out of these two asymptotic myths. That distinction only works when there are a lot of known, hard temporal constraints  or formal logical constraints (socks before shoes) in play. These actually help simplify things and make planning/execution a useful model.

When there is none of this temporal structure (what David Allen calls “a hard landscape”) and everything is rather fluid and chaotic, I find it useful to think in terms of a different distinction: positioning moves vs. melee moves. I learned of this distinction from Alfred Thayer Mahan’s The Influence of Sea Power Upon HistoryHere’s a brief primer.

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Fertile Variables and Rich Moves

Engineers and others attracted to comprehensive systems views often fail in a predictable way: they translate all their objectives into multi-factor optimization models and trade-off curves which then yield spectacularly mediocre results. I commented on this pathology as part of a recent answer to a question about choosing among multiple job offers on Quora  and I figured I should generalize that answer.

Why is this a failure mode? Optimization is based on models, and  this failure mode has to do with what you have left out of your model (either consciously or due to ignorance or a priori unknowability). If there are a couple of dozen relevant variables and you build a model that uses a half-dozen, then among those chosen variables, some will have more coupling to variables you’ve left out than others. Such variables serve as proxies for variables that aren’t represented in your model. I’ll overload a term used by statisticians in a somewhat related sense and call these variables fertile variables. Time is a typical example. Space is another.  Money is a third, and particularly important because ideological opinions about it often blind people to its fertile nature. Physical fitness is a fourth.

Fertile variables feed powerful patterns of action based on what I will call rich moves. 

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Analysis-Paralysis and The Sensemaking Trap

Analysis-paralysis is when you get into a loop of continuous analysis that prevents you from breaking on through to the “other side” where action can begin. I am beginning to get a handle on the problem, but it is not going to make much sense to you unless you’ve read the book. So this is in the advanced/extra-credit department. Perhaps after some more thought I’ll be able to capture this idea in a simpler way.

In the Double Freytag model of narrative decision-making, analysis-paralysis corresponds to getting stuck in the sense-making phase. Why does this happen?

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Hacking Grand Narratives

Grand narratives are probably the most frequently mentioned subject in reactions I get to Tempo, even though I carefully restricted myself to individual narratives in the book. Apparently the urge to apply narrative models to collectives is irresistible. Several readers have gone ahead and sort of hacked the narrative models I discuss in Tempo, and applied them to grand narratives. To be frank, I don’t completely understand most of these attempts. I know of applications to unconventional crisis response, the political process in Honduras, the history of Western art, and the history of debt/finance.

But as I’ve mentioned in previous posts, I am treading carefully here.  I’ve learned something from each hacking attempt people have told me about (do share if you’ve tried this sort of thing), and I’ve made two experimental attempts myself: applying the model to 19th century American business/technology history and on a smaller scale, to software projects. I am starting a third experiment: applying narrative analysis to wannabe-Silicon-Valley tech hubs like Boulder and Las Vegas. But overall, I am not satisfied that my models (or anyone else’s) are good enough yet.

But let me try and lay out the problem here, and have you guys weigh in.

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The Fundamentals of Calendar Hacking

I am always amused by time-management amateurs who have found a system that works for them and a few of their friends, and start imagining that they’ve created a perfect system.  “Universal time management system” is the perpetual motion machine of the self-improvement industry.

The zeroth thing you need to know about personal time management is that in a certain theoretical sense, there are no universal  systems. Only calendar hacks. What’s more, you cannot pick some compendium of calendar hacks and easily sort out the ones that will work for you. You need to learn the art of calendar hacking.

That’s what this post is about: the fundamentals of calendar hacking. I’ll be straight with you: the ideas in this post are going to be somewhat tough to grasp if you haven’t already encountered them, but I’ll keep it non-technical and provide several hopefully illuminating examples along the way.

The key is diagrams like the one below.


Diagrams like this are known as empirical computational complexity phase transition diagrams in computer science. I’ll show you how to read and draw informal, non-technical versions in a minute, but the key idea behind them is that an impossibly hard scheduling problem is not impossibly hard everywhere and at all times.

The key to calendar hacking is separating out the hard and easy regimes and dealing with them differently. This is one of my favorite technical ideas, and my excuse for playing fast and loose with it, as I am about to, is that my heart is in the right place. I mentioned this idea in a footnote somewhere in Tempo, but I figured I ought to do a proper post on the idea.

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Steer, Ready, Fire

I like various permutations and adaptations of the phrase ready, aim, fire to think about decision-making between the extremes of pure contemplation and pure action. Playing around with this phrase led me to this 2×2 (I seem to be thinking a lot in 2×2 form these days). I’ll connect the dots in a minute.


Aiming versus Feedback

The apparently logical sequence, ready, aim, fire describes a feedforward model. You get your mind in the right place, then you figure out how to be effective (aim can map to waterfall planning at any level), then you take action.

The phrase ready, fire, aim, preferred by the action-oriented in uncertain and dynamic environments, is a response to the analysis-paralysis that can happen if you try to get to ideal starting conditions and perfect information before starting to act.

The absurdity of aiming after firing can only be resolved via appeal to the logic of iteration and feedback. You converge on the successful course of action through feedback from failed actions. This works well as a motto for startup types and others who believe in the release early and often, and fail fast approach to projects.

Then there is the phrase, ready, fire, steer. I am not sure who came up with that one, but I’ve heard it attributed to Paul Saffo.  This replacement of aim with steer suggests that real-time feedback and control can be continuous. It is the logical limit of iterating faster and faster. Heat-seeking or radar-guided missiles are perfect examples.

The Role of “Fire”

The variant ready, fire, steer made me wonder about why fire is even necessary. Within your basic firearm metaphor, firing gives you all your momentum (kinetic energy) in one big dose. Of course, you also have whatever positional advantages (potential energy) you possess.  It maps well to situations like getting investment in a startup, coming into a trust fund, or using a rocket to launch satellites.

But there are also cars and airplanes, with more continuous energy-generation models. There are also renewable energy models like sail ships, and models that create a net surplus of energy, like a solar car with more energy than it needs.

These don’t need a fire step. You could do with just ready, steer thinking (or ready, start, steer if you insist). A lot of bootstrapped business models would qualify, as you use tiny or zero cash investments to get started, and nurture cash flows slowly to get where you want. You may be accumulating a surplus of cash or attention that you can conserve for later use.

It takes a lot more foresight to work without the boost of a fire stage, but in return you get more control and efficient use of resources, in cases where the fire represents borrowed energy, provided on terms that you don’t like.

In fact, you can often dispense with ready as well. The idea that you need a ready, independent of information preparedness is more psychological fiction than reality. While you are contemplating doing anything, your readiness level changes over time, even before you adopt any sort of intention. As you process relevant information, your situation awareness may increase or degrade in quality, and you may become more or less oriented.

Ready really only matters in situations where there are decisive go/no-go thresholds defined by irreversible (or very expensive to reverse) actions, such as quitting your job or getting married, but ready as an internal state doesn’t really capture that. You’ll never be really ready. But as a continuously-changing state, your readiness may cross a minimum threshold associated with a given irreversible decision.  That threshold is set by external conditions.

This means that you start steering the moment even a tiny amount of readiness bubbles up into your consciousness. After that, the feedback process that is steer automatically moves your readiness level along.

So steer is really at the heart of it all. Continuous feedback control of energy, using information.

Ready is useful to add in where there is an important, unavoidable and irreversible decision inside the decision process.

Creating an Opening

Fire can actually come at the end as well, and this is the case that interests me the most these days .

In cases where you maneuver for an opening starting from unfavorable conditions (ready, steer), you could be accumulating a surplus capacity for action while waiting for a good opportunity to use it.

This could be a purely passive wait, or you could be actively trying to engineer an opening through “set up” moves.

This accumulating surplus might be money, information, a slowly-grown marketing asset like a blog, or going to night school to get a degree. Or it might simply involve waiting and watching for environmental conditions, trending in a certain direction, to hit a threshold.

Within a large corporation, this could be a matter of making specific allies and accumulating a strong position around a currently unattractive business asset (such as a dog of a product that people think cannot do well in the future, or a sales region that nobody wants) and waiting for, or engineering, a way to work it.

For example, there was an optimal window of time for streaming video businesses to be launched, based on falling bandwidth costs. If you were in that business, you’d have been wise to adopt a ready, steer hold-and-accumulate strategy, waiting for your moment to fire.

Today, the emerging sector of 3D printing is in the wait zone for many people: once the technology becomes sufficiently cheap and some basic technology to exploit it has emerged (such as stable, cheap and easy to use software for generating designs), a lot of people are going to jump in.

Bootstrapping to Big

Since ready has to do with crossing externally-determined irreversibility thresholds more than being in some mystic state of perfect readiness, the steer, ready, fire sequence is great for maneuvering to create an opening, and then triggering an irreversible action that requires a burst of informed energy. This is what is typically referred to as a go-big-or-go-home moment.

One application of steer-ready-fire thinking is bootstrapped businesses that intend to grow big at the right time. These days, we’ve somehow bought into the illusion that bootstrapping is for lifestyle businesses and that you need professional investors to go big.

This is obviously false. If you steer to ready with sufficient foresight, carefully build cash-flow assets, and  wait for or create the right opening, you can bootstrap and go big. Many big businesses before the 1940s were grown in precisely this fashion. Before investment banking  became a big business in its own right in the 1870s in America (and later, the sub-sector of venture capital in the post World War II era), big fortunes — including those of the two biggest Robber Barons, Vanderbilt and Rockefeller — were built through this sort of bootstrapped, leveraged model. There were times when Rockefeller in fact had more capacity to move the markets from the outside, than his famous finance contemporary, J. P. Morgan, had on the inside.

Stepping back a bit, what’s common to all these approaches to thinking about decision processes is the interplay of energy and information in some abstract sense (where energy can be money or marketing potential for instance, in our running startup sector example). Acting with either too much or too little information, given your energy levels, is inefficient.  Having neither information nor energy is of course a stable situation.

Mindfulness is when energy and information dance together well. Note that you don’t necessarily have to keep them balanced at a specific moment. You can store both. So you might wait for energy to catch up with information, or vice-versa. Or you can accumulate both and unleash a ferocious burst of mindful action driven by a store of heavily-informed energy.

Sudden Actions, Entropy and OODA

That last part (accumulating both energy and information to enable sudden movements) took me a while to get to. For a long time, I was unable to reconcile sudden, high-power movements with the idea of mindfulness because I was fixated on the thought that mindful actions are necessarily smooth actions. They needn’t be. Jerky movements have a role to play in our world.

But there is a deeper level at which “slow” and “smooth” matter. This is where an abstract notion of entropy is relevant. Slow, smooth actions cause low increases in entropy. Quick, jerky actions cause high increases in entropy. Unfortunately, you cannot always work with low-entropy behavior because there is a lot of messiness in the outside world — the world that you don’t completely control. The smaller and more closed your world, the more you can approach the idea of working purely with slow, low-entropy actions.

This is why readiness is best thought of in relationship to irreversible-action thresholds determined by external conditions. In thermodynamics, isentropic processes (those that don’t increase energy) are reversible. Entropic processes are not.

When you unleash a sudden action, entropy will increase. In decision-making terms, it means you’ll trigger action that is so fast that you cannot process the information being generated by feedback, so it will effectively act as noise. But there are situations where you know enough to know that this chaos you are unleashing will mostly favor you. This is reflected in the attitude that “I think it will all work itself out.” Eventually, when the dust settles, you will be able to get back to a more mindful engagement with the situation.

And of course, there will always be net entropy increases even after the dust settles. Being mindful about this realization is the same as accepting the inevitability of death.

Of course, this extended thermodynamic metaphor needs to be carefully applied in abstract situations, but I believe the correspondence is a very close one. This thermodynamic metaphor, and the interplay of ready, fire, aim and steer in various permutations and combinations, is one approach to understanding how Boyd’s OODA model really works.

Smart Money and Dumb Money

You can extrapolate this sort of thinking to larger groups and organizations, and think about how energy (usually money in the human world) and information are distributed within a organization and the environment it operates in.  You can talk about whether energy drives information or vice-versa.

In larger systems of people, power distributions often emerge out of the interplay of energy and information. Smart money represents information in control of energy. Dumb money represents the converse situation.

In the world of dumb money, entrepreneurs must chase investors. In the world of smart money, investors court entrepreneurs. Why?

In entrepreneurship, smart money is often used to refer to investment from people who can also provide information and advice. This is actually not particularly smart money. If an investor holds all the cards — money and information — what exactly does the entrepreneur bring to the table besides talent? That sort of relationship defines employment, not investment. Truly valuable information comes from unlikely places. Information from well-known sources, such as seasoned investors or former entrepreneurs, is unlikely to be particularly special or exclusive.  It is in fact likely to be common knowledge — it will help you lower costs of doing business, but not provide a competitive advantage.

A collaboration between a party with too much energy, and one with too much information, is fraught with tension. It is very hard to merge the two in mindful ways. One party is impatient and the other party is frustrated. Meetings between parties with unbalanced and complementary assets, who are also mindful about what they have and what they need, are quite rare.

The result is that power dynamics are triggered while things are sorting themselves out. This is one reason I advocate a slightly evil philosophy. Engaging the world outside your personal control means dealing with all this. Trying to be purely good is like trying to work with just smooth, slow, isentropic actions. It is just not workable when there are transient openings and irreversibility thresholds in the environment.

So it isn’t just individuals who have to gradually become more mindful decision-makers, gradually lowering the amount of sloth, impatience and frustration in their thinking. Organizations have to do it too. I can think of many frustrated, slothful or impatient organizations and groups, ranging in size from married couples to Fortune 500 companies and entire nations.


Squeakastination: The Opposite of Procrastination

I recently made up a 2×2 that’s proved rather useful. If you classify behaviors based on whether they relate to unpleasant or pleasant tasks, and based on whether we delay doing them or over-prioritize them, you get four classes of prioritization behaviors.


This post is about our tendency to prioritize certain unpleasant tasks too much. This tendency has no commonly accepted name, so I’ve decided to call it squeakastination for reasons that will become clear in a minute. It is the opposite of procrastination, and in my opinion, far more dangerous.

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