Cal Newport's Blog, page 54

In Choosing a Job: Don’t Ask “What Are You Good At?”, Ask Instead “What Are You Willing to Get Good At?”

I recently received the following note from a career counselor:

I regularly counsel students on their career paths and I was having a hard time giving a student guidance today without referencing passion.  ‘What are you good at?”’ I asked instead, and she replied that she didn’t know.  She doesn’t know because she hasn’t tried enough things.

I like that this counselor is thinking critically about passion. I didn’t, however, agree with her alternative suggestion.

Asking “what are you good at?”, in my opinion, can be essentially the same as asking, “what is your passion?”

In both cases, you’re placing the source of career satisfaction in matching your job to an intrinsic trait.

And this is dangerous.

As readers of SO GOOD know, career satisfaction almost always follows: (a) building up a rare and valuable skill; then (b) using this skill as leverage to take control of your working life.

If you lead a student believe that making the right job choice is what matters for career happiness (whether you’re choosing based on “passion” or identifying “what you’re good at”), you’re setting them up for confusion when they don’t feel immediate and continuous love for their work.

My advice to a student in the above situation is the following:

Pick something that you wouldn’t mind investing years in mastering. If you already have some skills, then it might make sense (though is by no means necessary) to start there, as you already have a head start on mastery, but you should still expect years of deliberate improvement before deep passion can blossom for your work.

The key thing, in other words, is to direct expectations away from match theory — which says passion depends primarily on making the right job choice — and toward career capital theory — which says passion will grow along with your skill.

Deliberately Experimenting with Deliberate Practice — Looking for Subjects to Test My Advice

The Deliberate Practice Pilot Program

I’m fascinated by deliberate practice.

I’m convinced this advanced practice philosophy can help knowledge workers rapidly pick up skills that will make them invaluable and provide control over their career. It is, as I’ve argued here, in my last book, and in the Wall Street Journal, perhaps one of your most effective tools for building a working life you love.

But it’s also really hard to figure out how to adapt these ideas to the world of knowledge work.

I decided a good way to proceed with my investigation of this topic would be to: (1) take my best shot at distilling what I know into a formal system; then (2) recruit a group of people, from a variety of different knowledge work careers, to try out my recommendations and report back what they experienced.

This is exactly what I’m going to do.

Over the past few months, I’ve worked extensively with Scott Young (a master of rapid learning), to create a four week pilot program that walks you, step-by-step, through our best understanding of how to identify key skills and then apply deliberate practice techniques to dominate them in a small amount of time.

Now we want to recruit an (extremely limited) group of participants to give this pilot course a try and tell us how it went. In other words, I want real people, in a variety of real jobs, to kick the tires on these ideas Scott and I have been writing about for so long.

Learn More About This Experiment

I don’t want to clog Study Hacks with tons of logistical posts about the experiment — more details, how to sign-up, etc. — so I created a separate e-mail list for this purpose. If you’re interested in learning more about this pilot program click the link below to sign-up for the list.

This will be the only place where you can hear more details and receive information about the first-come-first-served sign-up that will likely happen as soon as next week.

Click here to sign-up to learn more…

And now back to our regularly scheduled programming…

You Can Be Busy or Remarkable — But Not Both

The Remarkably Relaxed

Terence Tao is one of the world’s best mathematicians. He won a Fields Medal when he was 31. He is, we can agree, remarkable.

He is not, however, busy.

I should be careful about definitions. By “busy,” I mean a schedule packed with non-optional professional responsibilities.

My evidence that Tao is not overwhelmed by such obligations is the time he spends on non-obligatory, non-time sensitive hobbies. In particular, his blog.

Since the new year, he’s written nine long posts, full of mathematical equations and fun titles, like “Matrix identities as derivatives of determinant identities.” His most recent post is 3700 words long! And that’s a normal length.

As a professor who also blogs, I know that posts are something you do only when you have down time. I conjecture, therefore, that Tao’s large volume of posting implies he enjoys a large amount of down time in his professional life.

Here’s why you should care: Tao’s downtime is not an aberration — a quirk of a quirky prodigy — it is instead, I argue, essential to his success.

The Phases of Deep Work

Deep work is phasic.

Put another way, to ape Rushkoff, we’re not computer processors. We can’t be expected to accomplish any job any time we have the available cycles. There are rhythms to our psychology. Certain times of the day, week, month, and even year (e.g., the professor I discussed in my last post) are better suited for deep work than other times.

To respect this reality, you must leave sufficient time in your schedule to handle the intense bursts of such work when they occur. This requires that you constrain the other obligations in your life — perhaps by being reluctant to agree to things or start projects, or by ruthlessly batching and streamlining your regular obligations.

When it’s time to work deeply, this approach leaves you the schedule space necessary to immerse.

When you’ve shifted temporarily out of deep work mode, however, this approach leaves you with down time.

This is why people who do remarkable things can seem remarkably under-committed — it’s a side-effect of the scheduling philosophy necessary to accommodate depth.

Returning to Tao’s blog, the specific dates of his posts support my theory. As mentioned, he posted nine long posts since the New Year. On closer inspection, it turns out that most of the posts occurred in a single month: February.

We can imagine that this month was a down cycle between two periods of more intense thinking.

If my theory is true — and I don’t know that it is — its implication is striking: busyness stymies accomplishment.

If you’re looking for the next Tao, in other words, ignore the guy checking e-mail while running to his next meeting, and look instead towards the quiet fellow, staring off at the clouds, trying to figure out what to do with his afternoon.

(Photo by The Other Dan)

How to Write Six Important Papers a Year without Breaking a Sweat: The Deep Immersion Approach to Deep Work

The Productive Professor

I’m fascinated by people who produce a large volume of valuable output. Motivated by this interest, I recently setup a conversation with a hot shot young professor who rose quickly in his field.

I asked him about his work habits.

Though his answer was detailed — he had obviously put great thought into these issues — there was one strategy that caught my attention: he confines his deep work to long, uninterrupted bursts.

On small time scales, this means each day is either completely dedicated to a single deep work task, or is left open to deal with all the  e-mail and meetings and revisions that also define academic life.

If he’s going to write a paper, for example, he puts aside two days, and does nothing else, emerging from his immersion with a completed first draft.

If he’s going to instead deal with requests and logistics, he’ll spend the whole day doing so.

On longer time scales, his schedule echoes this immersion strategy. He teaches all three of his courses during the fall. He can, therefore, dedicate the entire semester to two main goals: teaching his courses and conceiving/discussing potential research ideas (the teaching often stimulates new ideas as it forces him to review the key ideas and techniques in his field).

Then, in the spring and summer that follow, he attacks his new research projects with the burst strategy mentioned above, turning out 1 – 2 papers every 2 months. (He aims for — and achieves — around 6 major papers a year.)

Notice, this immersion approach to deep work is different than the more common approach of  integrating a couple hours of deep work into most days of your schedule, which we can call the chain approach, in honor of Seinfeld’s “don’t break the chain” advice (which I have previously cast some doubt on in the context of writing).

There are two reasons why deep immersion might work better than chaining:

It reduces overhead. When you put aside only a couple hours to go deep on a problem, you lose a fair fraction of this time to remembering where you left off and getting your mind ready to concentrate. It’s also easy, when the required time is short, to fall into the least minimal progress trap, where you do just enough thinking that you can avoid breaking your deep work chain, but end up making little real progress. When you focus on a specific deep work goal for 10 – 15 hours, on the other hand, you pay the overhead cost just once, and it’s impossible to get away with minimal progress. In other words, two days immersed in deep work might produce more results than two months of scheduling an hour a day for such efforts.
It better matches our rhythms. There’s an increasing understanding that the human body works in cycles. Some parts of the week/month/year are better for certain types of work than others. This professor’s approach of spending the fall thinking and discussing ideas, and then the spring and summer actually executing, probably yields better results than trying to mix everything together throughout the whole year. During the fall, he rests the part of his mind required to tease out and write up results. During the spring and summer he rests the part of his mind responsible for having original thoughts and making new connections. (See Douglas Rushkoff’s recent writing for more on these ideas).

I’m intrigued by the deep immersion approach to deep work mainly because I don’t usually apply it, but tend to generate more results when I do. I’m also intrigued by its ancillary consequences. If immersion is optimal for deep work, for example, do weekly research meetings make sense? When you check in weekly on a long term project, it’s easy to fall into a minimal progress trap and watch whole semesters pass with little results. What if, instead, weekly meetings were replaced with occasionally taking a couple days to do nothing but try to make real progress on the problem? Even doing this just a few times a semester might produce better results than checking in every week.

I don’t know the answers here, but the implications are interesting enough to keep the immersion strategy on my productivity radar.

(Photo by moriza)

Prioritizing Deep Thought in a Distracted World: A Case Study

A Deep Day

I’m a big supporter of deep work. People often ask, however, how to fit this type of persistent concentration into a fractured knowledge work schedule.

To demonstrate my personal answer, I took a snapshot of my calendar from Monday (see the image to the right).

At 9:30, I began my commute, having already tackled enough small logistics to clear my head and allow me to start obsessing on a problem I’m trying to solve (I love thinking in the car). Once I arrived on campus at 10:00, I continued to obsess about this problem until an 11:00 meeting. I then had 2 more hours to obsess. At 2:00, I had another call. Then at 3:00, now mentally exhausted, I turned to a less cognitively demanding logistical task that I’m chipping away at, bit by bit, with the goal of avoiding a schedule-busting scramble the day before the deadline.

(I should note that I teach on Tuesday and Thursday, and, accordingly, devote those full days to class related work — which is why you don’t see such tasks on the sample Monday shown here.)

Here’s the take-away message: On non-teaching days I start with the assumption that the full day will be dedicated to thinking deeply on the projects that will best increase my career capital. I then (only reluctantly) squeeze in the other stuff that simply cannot be ignored. Because I assume the day is mainly about deep work, I tend to ruthlessly batch this extra stuff and push it toward the borders of my day, where it will have a minimal effect on what matters.

How Can Two People Feel Completely Different About the Same Job? — Career Drift and the Danger of Pre-Existing Passion

The Emersonian Doctoral Candidate

I’m flying down to Duke on Tuesday to speak with their graduate students. Preparing for the event inspired me to reflect on my own student experience. In doing so, an Emerson quote came to mind:

“To different minds, the same world is a hell, and a heaven”

Emerson does a good job of capturing the reality of a research-oriented graduate education. Even though students enter such programs — especially at top schools — strikingly homogenous, in terms of their educational backgrounds and achievements, after a few years, the group tends to radically bifurcate.

Some students love the experience and thrive. They dread the possibility that they might have to one day leave academia and take a “normal job.” To them, graduate school is Emerson’s heaven.

Other students hate the experience and wilt. They complain about their advisors, and their peers, and the school, and their busyness. They can’t wait to return to a “normal job.” To them, graduate school is Emerson’s hell.

I began to notice this split about halfway though my time at MIT. I loved graduate school, so I was mildly surprised, at first, to encounter cynical students secretly plotting to abandon ship after earning their masters degree, or to stumble into dark blogs with titles such as, appropriately enough, Dissertation Hell (” a place to rant…about the tortures of writing a dissertation”).

Why do such similar students end up with such different experiences?

Because I happened to be a professional advice writer at the same that I was a student, I studied the issue. I think the answers I found are important to our broader discussion because this Emersonian division is common in many professions, and understanding its cause helps us better understand the complicated task of building a compelling career and the pitfalls to avoid.

Directed vs. Drifting Careers

Graduate students who experience Emerson’s heaven tend to aggressively seek out and develop expertise. Once they have this expertise, they use it as leverage to control their project choices, collaborators, and workflow.

The students who experience Emerson’s hell are more passive. They approach graduate school like college — waiting to be assigned tasks that they can work real hard to complete. Their theory is that hard work alone should yield good results. This theory, of course, is flawed.

When you’re passive about the direction of your student experience, you tend to end up with projects you do not like, bogged down with tasks no one else wanted to do. Over time you’ll begin to see the work as a negative force — leading to cynicism and diminishing motivation.

This division is important because it applies to many different professions. The employees (or entrepreneurs) who thrive tend to actively direct their career using the tenets of Career Capital Theory, just like the successful graduate students.

Those who struggle tend to drift through their working life, hoping, usually in vain, that by simply working hard and doing what they’re told, they’ll end up with a compelling livelihood.

The Passion Pitfall

Their two reasons to discuss these observations. The first is positive: when you understand the dynamics of crafting a compelling career you’re better able to harness them in your own life.

The second reason is negative: Understanding the difference between directed and drifting careers underscores the danger of common career advice; most notably, the ubiquitous entreaty to “follow your passion.”

Apologists for this reductionist theory often claim that it’s worth propagating, because if it helps even one person build the courage to pursue a dream, the effort becomes worthwhile.

But as emphasized by the above discussion, things are not so simple.

Here’s what worries me: When you persuade someone to obsess over the match between their work and a mysterious, innate, pre-existing passion (which, for some reason, we assume everyone has, even though the evidence suggests the opposite), you’re setting them up for career drift.  Passion theory says that your passion pre-exists, so when you find the right job, it will be right from day one.

In reality, as we’ve just seen, a particular job is not likely to become a source of passion until you’ve been actively directing it — sometimes for years — in the right direction.

By telling someone to “follow their passion,” therefore,  you are, quite ironically, reducing the probability that they’ll end up passionate about their work.

To put things another way, the division between Emerson’s heaven and hell is permeable and one we should all hope to cross in the right direction. But we need to understand that this is an active effort, conducted over time, and not the result of a simple match made at the very beginning of our career.

(Photo by USUHSPAO)

On the Art of Ambition

Ambition as an Art Form

I’m fascinated by people who accomplish things of importance. I’m also fascinated by how little we understand this process.

Traditional career thinking, of course, says you must identify your passion then aggressively pursue it. As you know, I have little patience for such childish reductionism.

When we start thinking about our career aspirations like adults, and ask hard questions, the answers tend to be more complex.

When I studied this issue in the context of academia, for example, I found instead that famous researchers often had surprisingly subtle — and well-developed — strategies for pursuing important results.

Consider Richard Feynman and Richard Hamming. Both of these stars talk about a robust process in which they systematically built up collections of open problems, and then, over time, tested out new techniques against these problems, always sifting for a match. This approach required a careful balance between seeking new knowledge and working with what they already knew. I suspect they dedicated a lot of thought to tuning this balance.

The broader point here is that ambition is good. But it’s not simple.

At some point, you have to turn your attention from the advice of commentators whose main credential is success in providing advice, and actually steep yourself in the nuance of how people make remarkable things happen in your field.  I am increasingly convinced that this apprenticeship, which can be long and often ambiguous, is a necessary stepping stone on the path to big things.

The Single Number that Best Predicts Professor Tenure: A Case Study in Quantitative Career Planning

An Interesting Experiment

 How do people succeed in academia?

I have notebooks filled with theories about this question, but I’ve increasingly come to realize that insights of this type — built on gut instinct, not data — are close to worthless. Most knowledge work fields are complex. Breaking into their upper levels requires a deliberate effort and precision that is poorly matched to the blunt, feel-good plans we devise in bouts of blog-inspired reflection.

This was on my mind when, earlier this week, I went seeking empirical insight into the above prompt, and ended up designing a simple  experiment:

I started by identifying well-known professors in my particular niche of theoretical computer science.
For each such professor, I studied their former graduate students. I was looking for pairs of students who earned their PhD around the same time and went on to research positions, but then experienced markedly different levels of success in the field.
Once I had identified such a pair, I studied the first four years of their CVs — the crucial pre-tenure period — measuring the following variables: quantity of publications, venue of publications, and citation of published work in the period.

Each such pair provided an example of a successful and non-successful early academic career. Because both students in a pair had the same adviser and graduated around the same time, I could control for variables that are largely outside the control of a graduate student, but that can have a huge impact on their eventual success, including: school connections, quality of research group, and the value of the adviser’s research focus.

The difference in each pair’s performance, therefore, should be due to differences in their own strategy once they graduated. It was these strategy nuances I wanted to understand better.

Here’s what I found…

The successful young professors published a lot. On average, they published 25 conference papers during their first four years. The non-successful professors published only 10. (Recall, in computer science, it’s competitive conference publications, not journal publications, that matter.) There was, however, high variance in these numbers. I was struck more by the floor function: the successful professors all published at least 4 conference papers a year (with some, but not all, publishing quite a bit more).
Neither the successful nor non-successful professors strayed far from the key conferences in their niche. In theoretical computer science, each niche has its own publication venues, arranged in tiers of quality. There are also a small number of more general venues, which cover all of theoretical computer science, and which are quite competitive and prestigious. Neither of the groups I studied published much in the elite general venues. Both groups published mainly in the quality venues within their niche.
The biggest differentiating factor between the two groups was citations. For each professor, I counted the citations for their five most cited papers published during their first four years (according to Google Scholar). The difference was staggering. The successful professors’ most cited papers from this period received, on average, over 1000 references. For the non-successful professors, the number was closer to 60.

As mentioned, I have notebooks filled with different strategies for succeeding in my research, with each such strategy focusing on a different element that struck me as important at the time.

My above experiment sweeps these compelling sounding ideas off the proverbial table, and replaces them with an approach backed by data. What matters, it tells me, is something we can call: quality cited papers. In more detail, how many papers per year are you publishing that: (a) are in quality venues; and (b) attracting citations?

This metric can tell me if I’m improving or not from year to year. Similarly, it provides clear feedback on which of my research directions should be dropped and which emphasized. When deciding whether to join a project, for example, I should start by estimating the expected impact on my quality cited papers value for the year. When deciding whether to apply for a particular grant, the same question should guide the decision.

This metric, in other words, plays the role for a young professor that batting average plays for a young baseball player. You might not like what it has to say, but it’s saying what you need to hear.

Quantitative Career Planning

The above experiment is a case study of a bigger idea that intrigues me. In knowledge work, we spend shockingly little time trying to understand the reality of how people in our positions succeed. Perhaps, as I’ve argued recently, we prefer our own answers to the truth, as our answers tend to sidestep any efforts that are too hard.

But it’s also possible that we simply need a better method for seeking these insights. The process above, which we can call quantitative career planning (a reference to the quantified self movement that encapsulates it), is an example of what these better methods might look like.

(Photo by bytemarks)

You Need to Master the Rules Before You Can Reinvent Them

A Useful Rejection

Earlier in my career, I submitted a grant proposal to a prestigious program. At the time, I had an interesting research idea bouncing around, so when I saw the deadline approach, I hunkered down for a week of deep work to pull together a submission.

A few months later, while at a workshop, I met the head of the funding program. I told her about my proposal.

“I assume,” she said, “that you had the very best people in your field read it over first.”

I had not.

Soon after this encounter, I received my rejection notification.

Evidence-Based Betting

Reflecting on this experience, I now notice that in my rush to embrace deep work and purposeful bets I had overlooked a more prosaic piece of the puzzle: learning the rules that govern the area where I was making my play.

If I had followed the program director’s advice and pumped experts for feedback, I would have learned about what you absolutely need for a fundable proposal. I avoided this step, I think, because some part of me didn’t want these answers. By writing my grant in isolation, I could ensure an optimal experience, where I had to put in focused hours, but never really challenge myself too much.

This was fulfilling. But it was also a recipe for failure.

I was like the amateur runner who spends her training days doing hard (but not too hard) three mile jogs instead of the brutal interval work she really needs to improve.

I don’t think we emphasize enough the importance of evidenced-based metrics. Deep work is important. Making lots of bets is important. But if these efforts are not grounded in the reality of your field — including the hard truths about what you really do need to potentially succeed, not just what you know how to do — they are wasted.

Do You Need Passion to Succeed as an Entrepreneur? Pam Slim’s Advice for Starting Your Own Business

Start-Up Passion

In So Good They Can’t Ignore You, I argue that “follow your passion” is bad advice.

But what about for entrepreneurs?

I’m asked this question often. It seems logical that the only way to power through the difficulties of starting a new business is to be driven by passion, so people want to know if this path is an exception to my post-passion philosophy.

This is an important question and I want to provide an evidence-based answer. With this in mind, I turned to Pamela Slim, author of Escape from Cubicle Nation, and one of the country’s top thinkers on making the jump to entrepreneurship. I met Pam last summer and was impressed by the sophistication of her thinking on this topic, so I asked if I could interview her and then share her thoughts with you. She graciously agreed.

Here are the highlights from our conversation (my conclusion follows)…

“In terms of starting a business, the first step for many people — particularly those in traditional corporate environments — is to tune into what topics interest you, where your natural strengths are, what lights you up.”

“For many people, however, there is no one thing — we are wired to have many different interests and passions.”

“You have to choose something of interest that is also going to have an economic engine behind it.”

“Take one idea. Find a simple business model. Then test it using the fewest resources possible (time, energy, money), but in a way that gives you a good sense of whether the idea is viable. This is especially important if you are testing an idea while still holding a traditional job.”

“If you put a number of different models through this test, you can determine if you enjoy doing it, and if the market really finds it to be valuable. You need both.”

“I suggest having a clear decision criteria.”

“A word of warning about this process: something I’ve seen people struggle with is this idea that there’s a perfect job or business out there for you. Then, when you start something, and it’s not everything it’s cracked up to be, you worry, when you should instead be committing to building the skills necessary.”

“If you are always attempting to understanding yourself better, identifying environments that support your best work, then commit yourself to do your best work, it will lead to more happiness.”

My Conclusion

When it comes to entrepreneurship, Pam knows her stuff, so I was happy to see that our thinking aligns in so many places. The idea that most caught my attention is the difference between passion and a true calling.

Pam notes that it’s important to feel strongly about a business model/idea/lifestyle before pursuing it. In fact, she frequently uses the word “passion” to describe this feeling.

But she also makes it clear that there’s a difference between this strong feeling and a sense that a particular path is the one and only path for you. It’s this latter thinking that so often leads to worry and disappointment when reality proves less than euphoric. She notes that you might have many different interests, and this fine — choose one. And even if you love the idea you’re pursuing with a singular intensity, you still need to commit to clear and objective testing of the market. Without an “economic engine”, all the passion in the world cannot guarantee you long term reward and engagement.