Four Ways to Develop Learning Agility and Improve Perspective

There is a method to the way you learn, and it is personal to you.  If you’re not paying close attention, you won’t have thought about the assumptions you make and behavioral patterns you rely upon when you make decisions, think, and act.  Approximately 30 to 50% of executives experience some kind of executive or management derailment in the course of their careers.  Research suggests that this stagnation and underperformance can be attributed to a person’s failure to update his or her mental frameworks in the wake of new experience.

In other words, you can and should be learning from the breadth of your personal and professional experiences to develop systematic thinking.  Monique Valcour in Harvard Business Review describes this skill as “learning agility,” or “the capacity for rapid, continuous learning from experience.”

Agile learners are good at making connections across experiences, and they’re able to let go of perspectives or approaches that are no longer useful — in other words, they can unlearn things when novel solutions are required. People with this mindset tend to be oriented toward learning goals and open to new experiences. They experiment, seek feedback, and reflect systematically.

Develop a desire to improve

How do you develop learning agility?  Its foundation is a desire to improve through (1) the development of new skills and (2) succeeding in new situations.

Agile learners value and derive satisfaction from the process of learning itself, which boosts their motivation as well as their capacity to learn from  challenging developmental experiences.

By finding internal value in the process of learning through new experiences, agile learners “don’t get defensive” and are more “willing to take risks.”  The benefit to this mindset becomes clear when you consider being confronted with a new, uncomfortable, scary experience.  Instead of fearing moving outside of their comfort zone or risking public critique through open discussion, an agile learner broadens experience and improves his or her mental toolkit by taking advantage of the opportunity to learn in a new environment.

Four Mental Tools You Can Use to Sharpen Your Learning Agility

There are discrete practical tools you can use to improve your ability to learn from experience in meaningful ways.

1.      Ask for feedback.

Think of one or more people who interacted with you or observed your performance on a given task. Tell them you’d value their perspective on how you did, and ask what you could do differently the next time. To maximize learning from their feedback — and this is vital — restrain any urge to defend yourself. Thank them for their input, and then ask yourself what you can learn.

This practice depends on your mindset, and will not work if you cling to defensiveness.  Google’s Director of Executive Coaching and Leadership, David Peterson simplifies this into a retrievable motto: “There has to be a better way, and I don’t know it yet.”

The power of the motto lies in the word “yet.” As research on growth mindset by psychologist Carol Dweck has found, if you hold the view that there is always more to learn and embrace the process of wading into unfamiliar waters, you can free your thinking, dissolve your fear of failure, and power your success.

2.     Test Out New Mental Models and Approaches

Expanding your mental toolkit requires you to test and retest different perspectives, models, and approaches.

To identify new behaviors for testing, Peterson recommends reflecting on a challenge you’re facing and asking yourself questions such as “What’s one thing I could do to change the outcome of the situation?” and “What will I do differently in the future?” You can also conduct thought experiments, unearthing possibilities from trying out a different point of view. For example, one of my clients was concerned about leading the first team development offsite with her new team of highly talented country managers. With some reflection, she realized that she had gotten stuck in the perspective that in order to be seen as credible, she had to know more than they did. Since she was new, this was impossible. Holding on to that perspective would have caused her stress and undermined her credibility. By letting go of the assumption that she had to be the subject-matter expert and adopting the perspective that she could add greater value as a facilitator, she was able to design and carry out a meeting at which creative ideas flowed freely. The team, which had previously suffered from poor coordination, developed more collaborative relationships.

We all have biases in our decision-making, many of them hidden from our own view.  This is why developing a broad set of mental models is so important — they cause you to shift perspective and unroot hidden traps in your thinking.  Checking your assumptions and testing new approaches to familiar scenarios will allow you to explore effectiveness of these ideas.

3.     Understand cross-disciplinary connections

This is a key to reaping value from new experiences.  Studying and reading broadly provides you with little value if you do not let new ideas cross-pollenate and fertilize your other areas of knowledge.

Peterson has systematically applied principles he’s used to learn about wine to the domain of leadership development. Oenologists develop expertise by trying many different wines, comparing them, and discussing them with fellow experts. Borrowing these principles, Peterson realized that he could extend his mastery of leadership development by seeking out a wide variety of leaders to coach, comparing leaders to each other on various qualities, and discussing leaders with other experts.

You must have an area of expertise that on its face, has nothing to do with your profession.  But think harder and more deeply to see the connections.  How can you apply the lessons you learned during one area to the other.  This is one benefit of reading broadly across a wide variety of subjects – an understanding of seemingly unrelated areas of study will, upon reflection, turn into a network of mental models that help you approach and solve problems in new ways.

4.   Review and reflect.

To understand the lessons learned from new experience, you need to systematically reflect on those experiences.

A growing body of research shows that systematically reflecting on work experiences boosts learning significantly.  To ensure continuous progress, get into the habit of asking yourself questions like “What have I learned from this experience?” and “What turned out differently than I expected?” Leaders who demonstrate and encourage reflection not only learn more themselves, they also spur increased contextual awareness and reflective practice in others, thereby laying a foundation for higher levels of learning agility in their teams and organizations.

Make time to do this.  Put it on your calendar, and don’t let anything get in the way.  In my experience, review provides the most value if you do it regularly and purposefully.  My weekly reviews let me focus on details, tasks, and short-term goals.  Monthly reviews let me think about bigger lessons learned from projects and check progress towards annual goals. Quarterly and annual reviews let me take stock on my alignment with long-term and life goals.

Go and Seek out the New

Once you have built a desire for improvement and understand these practices, go and seek out new experiences, people, and information.  Valcour highlights the difference you can expect between career development and career stagnation by pointing to examples:

Learning agility also involves being open to new experiences, people, and information. Two senior management professors I’ve encountered at academic conferences over the years exemplify opposite ends of the spectrum. Professor A has a voracious appetite for new ideas. Despite his lofty academic stature, he converses just as enthusiastically with graduate students and junior faculty from little-known universities as he does with fellow academic stars, and he collaborates with a wide variety of scholars. Well into his 70s, he’s vibrant, energetic, and recognized as an active leader in his research domain. Professor B, by contrast, shows little interest in scholars outside of his familiar circle of followers. His presentations generally rehash old ideas; it’s been a long time since he produced anything new. Although he made many important contributions earlier in his career, the low level of learning agility he exhibits now accompanies his fading reputation. He’s fallen into the exact career trap the CEO is seeking to avoid.

artwork: By Peter Pöml [CC BY-SA 1.0 (http://creativecommons.org/licenses/by-sa/1.0)

The Science of Craving and Free Will

Why do we crave things that we do not need, or even worse, things that harm us?

As Aristotle once wrote: “It is of the nature of desire not to be satisfied, and most men live only for the gratification of it.” Buddhists, meanwhile, have endeavored for 2,500 years to overcome the suffering caused by our propensity for longing. Now, it seems, [neuroscientist Dr. Kent] Berridge has found the neuro-anatomical basis for this facet of the human condition – that we are hardwired to be insatiable wanting machines.

You likely have heard an abridged “cocktail party” version of some description of the mind’s reward system.  That version probably goes something like this: exposure to certain stimuli (candy, sex, exercise, cocaine) caused a release of dopamine in the mind, which the brain experienced as pleasure.  The brain then “learned” to seek out repeated exposure to that same stimulus so as to obtain the same dopamine release that it craved.  As time went on, each exposure to the stimulus caused the release of less and less dopamine, requiring greater and greater exposure to that stimulus to obtain pleasure.  So went the road to addiction, it was taught.

But Dr. Berridge has a different theory, based on his research beginning in the mid-1980s.

Berridge, a dedicated young scientist who was more David than Goliath, stumbled upon evidence in 1986 that dopamine did not produce pleasure, but in fact desire. […]

The reward system, he then asserted, has two distinct elements: wanting and liking (or desire and pleasure). While dopamine makes us want, the liking part comes from opioids and also endocannabinoids (a version of marijuana produced in the brain), which paint a “gloss of pleasure”, as Berridge puts it, on good experiences. […]

His most telling discovery was that, whereas the dopamine/wanting system is vast and powerful, the pleasure circuit is anatomically tiny, has a far more fragile structure and is harder to trigger.

Berridge’s insight was to distinguish the brain’s wanting from its actual experience of pleasure:

“It’s easy to turn on intense wanting,” he says.[…] “Massive, robust systems do it. They can come on with the pleasure, they can come on without the pleasure, they don’t care. It’s tricky to turn on the pleasure.” […]

“This may explain…why life’s intense pleasures are less frequent and less sustained than intense desires.”

Pleasure, Berridge explains, cannot be pursued relentlessly, as the mind’s own circuits are designed to produce satiety:

Wanting and liking wax and wane like candle flames. The hungry, wanting state before a meal could be studded with moments of pleasure from a social encounter, or anticipation of good food.  Then, as we eat, pleasure dominates, but wanting still crops up – more salt, a drink of water, a second helping. Before long, the satiety system steps in to render each mouthful less delicious until we stop. If we switch to another food – dessert, cheese, petits fours – we can prolong the pleasure until we’re stuffed, although we may regret it.

The applications of Berridge’s research that are most interesting to me are its implications on the current philosophical debates about free will.  This arises from Berridge’s conclusion that “it is possible to want something without liking it.”  Crazy impulse purchases, eating too much cake, continuing to drink or do drugs past the point of pleasure are all examples.  One must ask the question, who or what is making these choices for us?

Discussions of free will have arisen out of Berridge’s work because wanting and liking can happen both consciously and unconsciously. This is why urgent desires can be irrational and inconsistent, and fly in the face of what we know is best for us in the long run. Unconscious wanting can defy our best-laid plans to end an unhealthy relationship or not polish off that box of chocolates.

Berridge and his colleagues point to meditation as one cognitive tool to distance our conscious minds from the unconscious machinery of wants and needs:

[Berridge] was particularly struck by the effectiveness of meditation in taming our dopamine desires – not only among Buddhists.

Sarah Bowen, an addiction therapist in Seattle who was also invited on the Dalai Lama trip, has had significant success in helping recovering addicts by using mindfulness meditation. Over 12 months, this treatment reduced substance use more effectively than cognitive-behavioural therapy or the 12-step programme. It’s not a cure, and won’t work for everyone, because it requires commitment to get the benefits. But mindfulness’s tentacles are rapidly spreading throughout the Western world, perhaps because it’s one of the few palpable antidotes to the dopamine frenzy of modern life.

via Intelligent Life Magazine.

photo: cyclonebill from Copenhagen, Denmark, via Wikimedia Commons

 

The Monty Hall Problem: Improve Your Predictions with Bayes’ Rule

We predict outcomes and infer conclusions based on information that comes to us many times each day.  Doctors call this diagnosis; financial planners call this investment advice; attorneys call this counsel; executives call this strategic planning.  Good decision-making requires that we use as accurate a baseline as the available data will allow.  If we operate in dynamic and shifting environments, however, probabilities and outcomes are in flux and will change as new events occur and new data becomes available.  Is there a responsible way for us to update our predictions with the availability of new data?

I should start with a very necessary caveat: I am not a mathematician.  I have never taken a statistics or probability course.  I often do work in the legal field, though, where making a probabilistic (even if imperfect) assessment of many potential outcomes in my cases is necessary to my advising clients.  Recently, I have begun to investigate whether there are lessons contained in the concrete world of mathematics and statistics that I might apply even to non-scientific questions.

Bayes’ Rule is one such lesson.  Bayes’ Rule is named after Rev. Thomas Bayes (1701-1761) and demonstrates how to update beliefs or predictions based on the occurrence of a new event or the availability of new data.  Here is the theorem in its mathematical form:

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Defining terms, p(A) is the probability of event A occurring, and p(B) is the probability of event B occurring.  p(B|A) is the probability of event B occurring assuming that event A has occurred, while p(A|B) represents the probability that event A will occur assuming that event B has occurred.  What does this mean?  Bayes’ idea was to represent mathematical changes in the probability of an event based on conditions related to that event.  In other words, if a doctor is interested in determining whether a patient has cancer, and cancer is known to have some relationship to the age of a patient, Bayes’ rule sets out to predict the change in the probability that the patient has cancer if she is of a certain age.

Let’s look at another classic example, known as the Monty Hall Problem.  On the classic game show Let’s Make a Deal, host Monty Hall often gave contestants a chance to win a car by picking from one of three doors.  One door hid a car, the other two doors had no cars.  At this point, the contestant has a one in three chance to win.  Once the contestant picked a door, Hall opened one of the other two doors, but never a door with a car.  Hall then gave the contestant a final choice: stick with his original door or switch to the remaining door.  What is the right move for the contestant?  Bayes’ rule provides an answer that is not immediately obvious: the contestant actually doubles his chances to win by switching doors, from 33% to 66%.

How can this be?  The answer lies in updating our prediction based on new information.  Assume the contestant first picks Door 1.  He has a 33% chance that he has picked correctly.  There is a corresponding 67% chance that the car is behind Door 2 or Door 3.  Hall will then open Door 2 or 3, but will not open a door with a car behind it.  If Hall opens Door 2, the 66% chance lies entirely with Door 3.  The probability that the car is behind Door 1 is still 33%, but the probability that it lies behind Door 3 is doubled.  Switching is the smart move here.

Notice here how the increase in probability from the new information of Hall opening Door 2 comes only after the contestant has already picked Door 1.  Suppose instead, that the contestant was kept off stage, unaware of what Hall was doing onstage.  In this alternate scenario, before the contestant was invited to join the game, Hall opens Door 2 and shows the audience that no car lay behind it.  Hall then brings out the contestant and tells him he can win a car if he correctly guesses whether the car lies behind Door 1 or 3.  What are his odds?  In this scenario, he has a 50% chance of winning – his choice makes no difference.  His probability does not change because he has only one one data point – that the car is behind one of two doors, instead of the two data points in the other scenario – that the car is behind one of three doors, but not the door that Hall then opens.  It is in the cumulative collection of data over time that the wise contestant can observe a change in probability and leverage that to his advantage in the game.

This theorem has application beyond game shows, of course.  Consider a doctor who is called to see a sick child in a rural area without sophisticated diagnostic equipment. The doctor knows based on word of mouth that 90% of sick children in that neighborhood have the flu, while the other 10% are sick with measles.  Based on this, one would assume that there is a 90% chance that the child has the flu, and 10% chance that she has the measles.

Assume that the child also has a rash, which the doctor knows shows up in 95 percent of measles patients, but only 8% of flu patients.  Does this change the doctor’s assessment.  Is the chance that the girl has measles now 95%?

No.  The probabilities of these events influence one another and must be considered together.

Let F stand for an event of a child being sick with flu and M stand for an event of a child being sick with measles. Assume for simplicity that there no other maladies in that neighborhood.

 

Using the formula above, the probability of the girl having measles, given her rash, is equal to p(R|M)p(M) / (p(R|M)P(M) + p(R|F)p(F)), or .95 x .10 / (.95 x .10 + .08 x .90), or 0.57.  So the girl has a 57% chance of having measles, a far cry from the 95% likelihood that her rash might first suggest, but substantially more than the 10% chance predicted by the doctor’s initial data.

Stripped of the equations and technical analysis, the point here is a simple and elegant one: adjust your predictions based on new information.  Do not fall into the trap of an anchoring bias, the all-t00-human tendency to focus on one piece of information in making a decision.

Broadly viewed, Bayes’ rule will affect how you view and relate to new information in your life, and can change your decision-making process.  Our beliefs grow out of our experiences and the information we process day-to-day.  We should continue to test, update, and, if necessary, adjust our personal views?  Julia Galef makes a great case for this type of growth in this Big Think video that I’ll leave you with.

A Zen Buddhist Teacher Explains Death to a Child and Explains That Names Are Not the Same as Things

I am currently working my way through Dropping Ashes on the Buddha: The Teachings of Zen Master Seung Sahn, ed. Stephen Mitchell.  Originally published in 1976, the book is a collection of correspondence, lectures, Zen interviews, between the Zen Master and his students in the West.  I do not recommend it as an introductory book on Zen Buddhism (look to Alan Watts for survey materials written for Western audiences for that), but for those with even a small bit of background understanding of Buddhism and the quirky nature of Zen teachings, Dropping Ashes is a treasure of insight and perspective, drawn from the Soen-Sa’s direct words, often hilariously shared.

Reading today, one particular anecdote caught my attention, both for its sweetness and for the broader lesson it contains.  Zen teaching often demonstrates an ability to reduce questions of overwhelming complexity to simple language and demonstrations.  Soen-sa gives an example of that propensity in recounting his talk with a seven-year old girl named Gita at the Cambridge Zen Center after the Center’s resident cat died after a long illness.  The girl was troubled by the cat’s death, even after watching the cat’s traditional Buddhist burial rituals.

Soen-sa said, “Do you have any questions?”

Gita said, “Yes.  What happened to Katzie? Where did he go?”

Soen-Sa said, “Where do you come from?”

“From my mother’s belly.”

“Where does your mother come from?”

Gita was silent.

Soen-sa then explains, “Everything in the world comes from the same one thing.”  He draws an analogy for Gita between a cookie factory and the universal nature of life force, explaining that all of the different cookies “have different shapes and different names, but they are all made form the same dough and they all taste the same. ”

“So all the different things that you see – a cat, a person, a tree, the sun, this floor – all these things are really the same.”

“What are they?”

“People give them many different names.  But in themselves, they have no names.  When you are thinking, all things have different names and different shapes.  But when you are not thinking, all things are the same.  There are no words for them.  People make the words.  A cat doesn’t say, ‘I am a cat.’  People say, ‘This is a cat.’  The sun doesn’t say, ‘My name is sun.’  People say, ‘This is the sun.’

We often have a tendency to confuse our names and labels for the things we encounter with the nature of the observed object itself.  “Don’t judge a book by its cover,” as we’ve all been taught.  Soen-sa applies this insight to show the little girl the difference between the way we label the world and the world’s true nature:

“So when someone asks you, ‘What is this?’ how should you answer?”

“I shouldn’t use words.”

Soen-sa said, “Very good! You shouldn’t use words.  So if someone asks you, ‘What is Buddha?’ what would be a good answer?”

Gita was silent.

Soen-sa said, “Now you ask me.

“What is Buddha?”

Soen-Sa hit the floor.

Gita laughed.

Soen-sa said, “Now I ask you: What is Buddha?”

Gita hit the floor.

“What is God.”

Gita hit the floor.

“What is your mother?”

Gita hit the floor.

“What are you?”

Gita hit the floor.

“Very good! This is what all things in the world are made of.  You and Buddha and God and your mother and the whole world are the same.”

Gita smiled.

Soen-sa said, “Do you have any more questions?”

“You still haven’t told me where Katz went.”

Soen-sa leaned over, looked into her eyes, and said, “You already understand.”

Gita said, “Oh!” and hit the floor very hard.  Then she laughed.

Soen-sa said, “Very very good! That is how you should answer any question.  That is the truth.”

Soen-sa ends the episode with a humorous observation by Gita that the wonderful Maria Popova described as “a tragic testament to contemporary Western education being a force of industrialized specialization, deliberately fragmenting the unity of all things and deconditioning our inner wholeness:”

“Gita bowed and left.  As she was opening the door, she turned to Soen-sa and said, “But I’m not going to answer that way when I’m in school.  I’m going to give regular answers!”

Soen-sa laughed.

Couple this with “A Child’s Advice on Life and Fear.

Detecting Bias in Your Decision-Making

Warren Buffett is regarded as one of the most successful investors in history.  He and his partner, Charlie Munger, attribute a large part of the success of Berkshire Hathaway to the partnership’s ability to make investment decisions without the influence of cognitive bias that risk every human decision.

Whether it’s about investments, business strategy, political candidates, or personal matters, we all try to make good decisions. Unfortunately, emotion and bias is part of human psychology.  While we can’t eliminate bias completely, we can each develop our own toolkit for detecting and mitigating against those unhelpful mental quirks that can lead us down the wrong path if we’re not careful.

Paul Graham of Y Combinator has written a thoughtful essay describing an elegant but subtle method of detecting bias in the evaluation of applicant pools.  The interesting idea in Graham’s observation is that it allows third-parties to detect bias in an organization’s decision-making, even if that organization makes efforts to screen certain details of its process.

Graham suggests that bias can be detected whenever “(a) you have at least a random sample of the applicants that were selected, (b) their subsequent performance is measured, and (c) the groups of applicants you’re comparing have roughly equal distribution of ability.”  Graham explains that in these circumstances, bias can be measured by comparing the back-end success of different groups of applicants, even if you cannot view the applicant pool itself:

How does it work? Think about what it means to be biased. What it means for a selection process to be biased against applicants of type x is that it’s harder for them to make it through. Which means applicants of type x have to be better to get selected than applicants not of type x. Which means applicants of type x who do make it through the selection process will outperform other successful applicants. And if the performance of all the successful applicants is measured, you’ll know if they do.

Graham provides a helpful example of detecting gender bias in the venture capital world:

For example, many suspect that venture capital firms are biased against female founders. This would be easy to detect: among their portfolio companies, do startups with female founders outperform those without? A couple months ago, one VC firm (almost certainly unintentionally) published a study showing bias of this type. First Round Capital found that among its portfolio companies, startups with female founders outperformed those without by 63%.

Graham’s idea seems applicable to any process through which various individuals or opportunities are screened for participation or selection through some pre-defined criteria.  This could include hiring decisions, investment decisions, account or client decisions, or media or networking opportunities, just to name a few.  If you find that a certain group of applicants, or investments, or account type is outperforming the average of the total selected pool, you may have revealed some cognitive bias in your process disposed against the higher-performing group.

Improving decision-making requires a constant eye scanning your processes for places where bias might hide, and from which it might rise up to influence a decision.  Couple Graham’s idea with Shane Parrish’s The Work Required to Have an Opinion and Musashi’s tactics for understanding the strength and weakness in your position.

Finding Peace by Focusing on the Things in Your Control

It’s Monday morning.  You raced around all weekend, doing errands, buying groceries, shuttling kids to their playdates and practices.  You fit in some time with your spouse or friends on the evenings.  Sunday evening was the predictable mad scramble of planning, packing, and preparing for another busy week, with the clouds of anxiety gathering in your mind as you think about how busy, frenetic, and stressful the coming work and school week will be.  How do you feel on your Monday morning?  Are you behind schedule, anxious, impatient and weighed down by the worry of getting everything right?  Is there any way to shift this mindset to one focused on opportunity and to shed some of the stress?

Nearly two thousand years ago, Epictetus wrestled with this question.  Epictetus (c. AD 55-135), a Stoic philosopher living in the Roman Empire, believed that our capacity to be happy lies entirely in ourselves.  He taught through a series of discourses, many of which have been preserved.  A shorter version of the principal themes of his discourses was recorded in the Encheiridon, or Manual.  According to Epictetus and the Stoics, events are neither good nor bad, but our reactions to those events may be good or bad.  Our experience is, therefore, dictated by the sum of our reactions to the events of our life.

Epictetus begins his work the Encheiridion by distinguishing the things in our control with the things out of our control:

“Of things some are in our power, and others are not.  In our power are opinion, movement toward a thing, desire, aversion (turning from a thing); and in a word, whatever are our own acts: not in our power are the body, property, reputation, offices (magisterial power), and in a word, whatever are not our own acts.”

We have control over our opinion, movement, desire and aversion — “our own acts.”  We lack control over our bodies, our belongings, and our success.  Recognition of this distinction is important, because it is only by differentiating the things we control from the things we do not control that we can find freedom.  According to Epictetus, “the things in our power are by nature free,” but “the things not in our power are weak,” and “in the power of others.”

Suffering lies in our confusion about what we control:

“Remember then that if you think the things which are by nature slavish to be free, and the things which are in the power of others to be your own, you will be hindered, you will lament, you will be disturbed….”

On the other hand, keeping a clear mind about the things that lie in our control is the pathway to mental freedom:

“If you think that only which is your own to be your own, and if you think that what is another’s, as it really is, belongs to another, no man will ever compel you, no man will hinder you, you will never blame any man, you will accuse no man, you will do nothing involuntarily (against your will), no man will harm you, you will have no enemy, for you will not suffer any harm.”

Epictetus’s “live and let live” message of focusing only on the things you can control is easy enough to remember and practice when things are going well.  But how do we implement this type of mental discipline in tough times?  Epictetus recommends the practice of reflection in difficult circumstances as a means to develop peace and find opportunity.

First, Epictetus suggests that we examine obstacles closely to understand exactly what limitation they present:

“Disease is an impediment to the body, but not to the will, unless the will itself chooses.  Lameness is an impediment to the leg, but not to the will.  And add this reflection on the occasion of everything that happens; for you will find it an impediment to something else, but not to yourself.”

We all face obstacles in life.  Often times, however, the obstacle is not the barrier we may initially perceive.  Most importantly, Epictetus reminds us that there can be no obstacle to our own willpower that arises externally.  This is squarely in our own power.  Reviving our willpower in the face of difficulty can be a matter of examining challenge for opportunity:

On the occasion of every accident (event) that befalls you, remember to turn to yourself and inquire what power you have for turning it to use.

The suggestion here, is not that difficult times are easy.  We all face challenges that frustrate us, anger us, and hurt us.  The lessons in those moments, Epictetus suggests, is that pain can teach endurance, not getting what we want can teach patience, dealing with abusive people in our lives can teach understanding.

Finding this pathway to understanding requires us to remember Epictetus’s first point: focus on the things in your control.  We cannot control our external successes or failures, or how others view or treat us.  By remembering this, and developing a practice of reflection, we can find equanimity and peace in our relation to the world.  Epictetus writes that the “condition and characteristic of an uninstructed person” is that “he never expects from himself advantage nor harm, but from externals.”  In contrast, an instructed person “expects all advantage and all harm from himself.”  Ultimately, this is our choice to make:

“You must be one man, either good or bad.  You must either cultivate your own ruling faculty, or external things; you must either exercise your skill on internal things or on external things; that is, you must either maintain the position of a philosopher or that of a common man.”

Epictetus’s belief is that if we practice this, a better view of life awaits:

Seek not the that the things which happen should happen as you wish; but with the things which happen to be as they are, and you will have a tranquil flow of life.

Go tackle your Monday morning.  If it isn’t perfect – and whose ever is? – draw a bit of strength from Epictetus by remembering that while you can’t control the day, you can find peace in your reaction to it.