Marina Gorbis's Blog, page 802

You Have to Stop Canceling and Rescheduling Things. Really.

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A friend recently returned to his parked car to find it had been sideswiped. Now, every time he calls the insurance company, he hears a message saying: “Can’t take your call right now. Leave a message. All calls will be returned by the end of the day.”

So far, he’s called over a dozen times; his calls have been returned only twice.

Why would an insurance adjuster have a voicemail message assuring callers that “all calls will be returned by the end of the day” and then return only 20% of the calls it committed to returning? Probably for the same reasons most of us promise “to write back to your email on Monday” but don’t, or promise “to send out that memo by Friday” but don’t.

Why do any of us say we will do things and then fail to do them?

We overcommit ourselves. We don’t like to disappoint people, so we tell them what we think they want to hear. We feel pressure in the moment and don’t stop to consider how much pressure we’ll feel later. We don’t think through how much time things will actually take — and we don’t leave enough slack time in our days to handle the (inevitable) emergencies and delays.

Up until a few years ago, I canceled or postponed meetings a lot. I would say yes to something (so much easier than saying no). As the commitment approached, I would feel overwhelmed and want to cancel. And often, I would cancel.

Then I read Stephen M.R. Covey’s book The Speed of Trust. It’s about being trustworthy. I had always thought that I was, but the author explains that when you make appointments and you cancel them, then trustworthy you aren’t. When you fail to fulfill commitments that you freely make, trust is not the result.

Since then I have realized that the temptation not to follow through is compounded by ease. Never has canceling, for example, been easier and less painful for us than it is in the age of the text message. We can cancel without ever having to speak with, much less meet, someone. We can cancel five minutes ahead and without explanation. Just tack on an emoticon to our message, and we can convince ourselves that it’s almost the same as if we’d met our obligation.

But the thought process still isn’t pain-free. We feel guilty about it. We waffle over what to do — and the indecision is draining. Finally, we cancel, and we undermine our confidence in ourselves. It reinforces our conviction that we can’t do it all — that we can’t control our schedule, or even our effort.

There are consequences for our personal lives, and there are certainly consequences in the workplace. Keeping commitments is a sign of maturity. Employees who don’t finish assignments, for instance, or finish them late or poorly, or are themselves routinely late, miss meetings, and cancel appointments, are an imposition on other team members and a liability to their employers.

Because these bad habits are nearly ubiquitous, they inevitably hitch a ride with some of us as we climb the ladder into leadership roles, where the workplace dysfunction they generate is magnified. It’s difficult to hold your subordinates accountable when you don’t hold yourself accountable. It’s hard to trust others when we know we can’t be counted on. How do we inspire commitment in those we lead when it’s obvious to them that commitment is a negotiable principle for us? It’s impossible to be a good leader if we don’t govern ourselves.

Last year I decided I would stop rescheduling my commitments and treat them as just that: commitments. And what I found is that when I committed to do the things I said I’d do, I actually felt much less stressed by them. As I kept more and more commitments, I got more and more confident. And I learned how long things really take, so I got better and better at giving estimates on when I could deliver.

If you really mean no when you say yes, then say no in the first place. We are all in the same boat — we have finite time and a seemingly infinite number of worthwhile things to do with it. Don’t know how to say no? Google “how to say no to a request” and then study up. Commit yourself to not agreeing to do things unless you’re going to follow through. Ask for time to think things over if you’re unsure. Don’t overschedule yourself. If you’re truly overextended, you may require a transition period to weed some things out; after that, once you say yes to something, stick to the yes. If the commitment seemed like a good idea at the time, it still is — even if the value is found not in the activity itself but in being trustworthy and following through.

How Companies Get Creativity Right (and Wrong)

Beth Comstock, the first female vice chair at General Electric, thinks companies large and small often approach innovation the wrong way. They either try to throw money at the problem before it has a clear market, misallocate resources, or don’t get buy in from senior leaders to enact real change. Comstock spent many years at GE – under both Jack Welsh’s and Jeffrey Immelt’s leadership – before leaving the company late last year. She’s the author of the book Imagine It Forward: Courage, Creativity, and the Power of Change.

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Use Your Everyday Privilege to Help Others

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I often forget I am straight.  I just don’t think about it much.  When asked what I did this weekend, or when setting family photos on my desk at work, I have no reason to wonder if what I say will make someone uncomfortable, or lead to a “joke” at my expense, or cause a co-worker to suddenly think I am attracted to them.  Our culture is set up for straight people like me to be ourselves with very little thought. But for some gay colleagues, a simple question about the weekend or a decision of how to decorate the workspace carries significant stress—how to act, who to trust, what to share.  A recent study found that 46% of LGBTQ employees are closeted in the workplace, for reasons ranging from fear of losing their job to being stereotyped.  Unlike me, a non-straight person is unlikely to have the privilege of going an entire day without remembering their sexual orientation.

This privilege of being able to forget part of who you are is not unique to straight people.  Each of us have some part of our identity which requires little attention to protecting oneself from danger, discrimination, or doltish humor. For example, in America, if you are white or Christian or able-bodied or straight or English-speaking, these particular identities are easy to forget.  It is just an ordinary way of being.  Ordinary privilege is ordinary because it blends in with the norms and people around us, and thus, is easily forgotten.

Just about every person in America has one form of this ordinary privilege or another. This is nothing to be ashamed of, or deny, even though it can often feel like an accusation. Ordinary privilege is actually an opportunity. Research repeatedly confirms that those with ordinary privilege have the power to speak up on behalf of those without it, and have particularly effective influence when they do. For so many of us looking for an opportunity to fight bigotry and bias in the workplace or in our broader culture, we may be missing the opportunity staring back at us in the mirror: using the ordinary nature of who we are as a source of extraordinary power.

For example, psychologists Heather Rasinski and Alexander Czopp looked at how people perceive confrontations about a racially-biased comment. They found white observers were more persuaded by white confronters than by black confronters and rated the black confronters as more rude. Whiteness gave the person more legitimacy than blackness when speaking up on racial bias.

Similarly, scholars David Hekman, Stefanie Johnson, Maw-Der Foo, and Wei Yang studied what happens to people who try to advocate for diversity in the workplace.  Those who were female and nonwhite were rated worse by their bosses than their non-diversity-advocating female and nonwhite counterparts. White and male executives saw no difference in their ratings, whether or not they advocated for diversity. They found the same pattern with hiring decisions. If a white male manager hired someone who looked like him (or someone who did not), it had no impact either way on his performance ratings. But, if a nonwhite male manager hired someone who looked like him, he took a hit for it.  In other words, ordinary privilege—that part of our identities which we think less about—is also the place where we wield outsized influence on behalf of others.

This influence even exists online, as political scientist Kevin Munger showed through a clever experiment on Twitter, focused on people using the n-word in a harassing way towards others online.  Using bots with either black or white identities, he tweeted at the harassers, “Hey man, just remember that there are real people who are hurt when you harass them with that kind of language.”  This mild tweet from a “white” bot who appeared to have 500 followers led to a reduction in the racist online harassment in the seven day period following the tweet, whereas the same tweet from a “black” bot with the same number of followers had little effect (interestingly, only anonymous n-word users were affected; those using what appeared to be a real name and photo were unaffected by the confrontation). If this is the effect a mild tweet from a stranger can have, we have to wonder about the potential impact of our own ordinary privilege.

To use your ordinary privilege, here are some things you can do:

First, figure out the parts of your identity that you think about least. Once you’ve pinpointed them, you’ve identified your ordinary privilege.
Second, start learning what people who lack that ordinary privilege encounter as challenges at work, at school and in their communities. You can use the Internet as a good starting point for first-person accounts.
Third, look for opportunities to speak and act. Confronting people is only one of many ways we can use our ordinary privilege. Instead, we can ask questions, raise issues, and add perspectives that are not organically emerging in discussions at work. We can introduce data, invite people into conversations, and create buzz around ideas. We can amplify the views of people not being heard at meetings, and bring back conversations when someone is interrupted. We can give credit for people’s work and spread the word about their talent.  We can notice when bias is playing out around us, and name it when it happens.
Fourth, be thoughtful about moments when you may inadvertently speak over the group you mean to support. It is not unusual to accidentally center ourselves instead of the people to whom we are trying to be an ally, but it is costly. When it happens, step aside or step back, and learn from those whose lives are directly affected by the issue, rather than presenting ourselves as the experts. Take their lead while using your ordinary privilege.

What we think about least may be the place from which we can do the most good. Each of us has some form of ordinary privilege, and that’s good news, because that means almost all of us have more influence than we may realize.

Big Data and Machine Learning Won’t Save Us from Another Financial Crisis

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Ten years on from the financial crisis, stock markets are regularly reaching new highs and volatility levels new lows. The financial industry has enthusiastically and profitably embraced big data and computational algorithms, emboldened by the many triumphs of machine learning. However, it is imperative we question the confidence placed in the new generation of quantitative models, innovations which could, as William Dudley warned, “lead to excess and put the [financial] system at risk.”

Eighty years ago, John Maynard Keynes introduced the concept of irreducible uncertainty, distinguishing between events one can reasonably calculate probabilities for, such as the spin of a roulette wheel, and those which remain inherently unknown, such as war in ten years’ time. Today, we face the risk that investors, traders, and regulators are failing to understand the extent to which technological progress is — or more precisely is not — reducing financial uncertainty.

Two areas are of particular concern. First, there are many unsettling parallels between the recent advances in machine learning and algorithmic trading and the explosive growth of financial engineering prior to the crisis. Secondly, we cannot draw comfort simply from more data and greater computing power: statistical theory shows that big data does not necessarily prevent big trouble.

Like today, finance in the 1990s and early 2000s attracted many of the sharpest quantitative minds, who produced remarkable theoretical and methodological advances. Like today, financial engineering around the millennium brought great commercial success: the mathematical tools developed by derivative desks built businesses, boosted profits and delivered superior investment returns. I lived that era in New York, part of a dynamic, entrepreneurial world of advanced probabilistic modeling and unprecedented computational power. We were taming financial uncertainty, or so we believed.

The financial crisis exposed that mindset as a “quant delusion,” an episode which we may now be at risk of repeating. Many modeling assumptions, such as correlations between asset prices, were shown to be badly flawed. Furthermore, foundational underpinnings of quantitative finance — for example, elementary logical bounds on the prices of securities — broke down.  It also became clear that quants had grossly mis-specified the set of possible outcomes, and had calculated conditional probabilities of events, subject to the world staying more or less as they had known it. They made decisions that were exposed as nonsensical once apparently impossible events occurred.

Importantly, there was also a proliferation of what statistician Arthur Dempster has termed “proceduralism”: the rote application of sophisticated techniques, at the expense of qualitative reasoning and subjective judgment, leading to illogical outcomes. An example: banks often adopted different models to price different derivative contracts, leading to an identical product being given two unequal prices by the same institution.

An influx of quantitative talent; rapid technical advances; surging profits: today’s world of quantitative finance echoes that of the millennium. Proceduralism may be even more prevalent now, fueled by the broad success of algorithms and associated competitive pressures to adopt them; and by the regulatory push to validate or “attest to” models, whose results are then vested with unrealistic credibility.

Yes, with bigger data and greater computing power than ten years ago, we can now explore ever larger sets of possible outcomes. But we still do not know to what degree our calculated conditional probabilities differ from actual probabilities. We still do not know which of our assumptions will break down. In fact, as our algorithms become more complex, as with deep learning, it is becoming more difficult to identify gaps in logic that may be embedded within algorithms, or to comprehend when models might badly fail.

Machine learning can be very effective at short-term prediction, using the data and markets we have encountered. But machine learning is not so good at inference, learning from data about underlying science and market mechanisms. Our understanding of markets is still incomplete.

And big data itself may not help, as my Harvard colleague Xiao-Li Meng has recently shown in “Statistical Paradises and Paradoxes in Big Data.” Suppose we want to estimate a property of a large population, for example, the percentage of Trump voters in the U.S. in November 2016. How well we can do this depends on three quantities: the amount of data (the more the better); the variability of the property of interest (if everyone is a Trump voter, the problem is easy); and the quality of the data. Data quality depends on the correlation between the voting intention of a person and whether that person is included in the dataset. If Trump voters are less likely to be included, for example, that may bias the analysis.

Meng shows that data quality dominates data quantity in remarkable ways. For example, suppose we polled 1% of U.S. voters, approximately 2.3 million people, and that the probability of a Trump voter accurately responding is just 0.1% lower than a non-Trump voter. Then the big dataset provides a less reliable estimate of the overall percentage of Trump voters than a simple random sample of just 450 people, where responses are accurate.

The lesson for finance is stark. If our dataset, however large, is in a minimal but systematic way not representative of the population, big data does not preclude big problems. Those who revert to a proceduralist approach of throwing complex algorithms and large datasets at challenging questions are particularly vulnerable. Who can tell how non-representative our data today is in terms of representing the future? Yes, we may never again assume house prices cannot fall simultaneously in every state, but we do not know what other assumptions are implicitly being made.

More than ever, judgment — necessarily subjective and based on experience — will play a significant role in moderating over-reliance on and misuse of quantitative models. The judgment to question even the most successful of algorithms, and to retain humility in the face of irreducible uncertainty, may prove the difference between financial stability and the “horrific damage” of another crisis.

A 4-Step Plan to Make Your Q&A More Audience-Friendly

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The Q&A or fireside chat has become a popular format at events like conferences and employee town-halls, replacing more-formal presentations and panels. The one-on-one format can create a more conversational, interesting, and intimate experience, and has the added benefit that the CEO or luminary being interviewed theoretically doesn’t have to prepare as much.

Despite how effective interviews can be in theory, however, they are often difficult to execute in practice. As a result, audience members are often left feeling disengaged and unsatisfied while guests struggle to inform and engage in a way that resonates.

In our Essentials of Strategic Communication at Stanford’s Graduate School of Business, we’ve begun including advice on how to handle this format effectively to help our students become more confident and compelling communicators. We offer four steps — easily remembered by the acronym FIRE — derived from our teaching and coaching experience.

Framing. In preparing for interviews, most guests ask “What do I want to say?” But the most effective guests ask “What does my audience need to hear?” Since the time of the Greeks, we have known that the best communication is that which is in service of the audience — it answers the questions they have and provides them with the specific insights they’re looking to acquire.

Customizing your content based on your audience matters. Therefore, before any fireside chat or other one-on-one interview, take time to do some reconnaissance and reflection about your audience and frame your content accordingly. Ask the following questions:

“What does my audience care about most?”
“What motivates them?”
“What do they expect to learn or gain?”
“What biases or hesitations might they have?”
“What knowledge level do they bring to the session?”

If you can’t confidently answer these questions yourself, ask them of the interviewer, event host, or consult the social media of those who will be attending.

You will also benefit by having a clear speaking goal. A good speaking goal is about information, emotion, and action. It answers the following questions about how your audience will leave your fireside chat:

What do I want my audience to know?
How do I want my audience to feel?
What do I want my audience to do?

Your answers to these questions will help inform your content and how it is framed. By understanding your audience and having a clear speaking goal, you can tailor your content for maximum impact — leaving your audience walking away with exactly what they were hoping to acquire and you with what you were hoping to achieve.

Inclusion. The effectiveness of the interview format lies in the sense of intimacy and familiarity they create. We know from research and our own experience that audience inclusion is powerful, leading to more positive perceptions of a speaker, greater motivation to future action, and better recall of content.

A good Q&A invites the audience into the experience.  Two effective ways to do this are by (1) using inclusive language and (2) polling the audience.

For inclusive language, consider referencing the audience directly and using “you” and “we” when possible.  For example you might say…

“Like many of you, I…”
“We all have…”
“Who among us has (hasn’t)…”

For polling, consider in advance what questions you might want to ask the audience. For example, “How many of you have had X experience…?” or “Who can tell me…?” In the former case, be sure to raise your hand as you ask the question so you signal to the audience how you’d like for them to respond. Be sure to comment on whatever answers you get to validate the audience’s involvement and encourage future participation.

If your audience feels included in the conversation, they will be more engaged and responsive to your message.

Rails. To keep a train on track, you need strong rails. Similarly, to keep your content on track, we recommend using a structure to guide you. While many structures exist, such as Problem-Solution-Benefit and Comparison-Contrast-Conclusion, one of our favorite structures is the What? > So What? > Now What? structure.

You start your response by providing your point and giving an example to support it (The What?). Next, you explain why your point is important to the conversation at hand and potentially beyond (The So What?).  Finally, you end by explaining the implications, ramifications, or applications of what you just said (The Now What?).

Using a structure will make it easier for you to develop your content when speaking in a spontaneous manner, make it easier for your audience to follow your response, and allow for clear, concise answers in place of rambling, unfocused ones.

Examples. Chip Heath, a colleague of ours at Stanford, has conducted extensive research on what makes ideas “stick” — that is what makes them memorable, engaging, and inspiring. His number one piece of advice? Make your ideas concrete. That is, take abstract concepts and bring them to life with concrete stories, details, and examples.

During fireside chats and other one-on-one interviews, guests tend to speak at a general  level — to offer concepts and conclusions — without concrete examples and stories (including personal ones) that will help make their content more engaging, understandable, and relatable for their audience.

As you prepare for your next interview, we suggest the following: make a list of all the key points, themes, best practices, etc. you’d like to be prepared to share with your audience. Then go back through that list and for each item, write down a concrete story or example you could share to support it and make it “stickier.” Stories and examples can be real or imagined as well as about you or a third person.

What’s most important is that you make your ideas and messages as concrete as possible by adding vivid details. Doing so will make your content not only more engaging in the moment, but also more memorable and motivating in the days and weeks that follow.

The Original Fireside Chat

Given we practice what we preach, we’ll provide you with an example of how this looks in action (although in this case, it was a kind of a speech rather than an interview).

When Franklin Roosevelt took office in March 1933, one quarter of the nation was unemployed, stocks were down 75%, and across the country people were panicked, quickly pulling their money out of failing banks. He needed to convince Americans to trust him and put their money back in the banks. He gave his first “fireside chat” over the radio just a week after being sworn in. This manner of addressing the public in such an intimate and informal way was described as a “revolutionary experiment.” It was wildly successful. Not only did Roosevelt’s chats attract more listeners than the most popular radio shows of the time and inspire record numbers of fan mail, they also allowed him to establish high levels of trust and support during a time of crisis.

In these addresses, he framed his message accordingly: he understood the public was panicked, so he used clear, concise language and a tone that was comforting. Instead of speaking abstractly about the challenges of the financial system, he used inclusive language: “I want to talk for a few minutes with the people of the United States about banking.” He also used rails to give structure to what he was saying: “I want to tell you what has been done in the last few days, why it was done, and what the next steps are going to be.” He also used examples to great effect: “Let me illustrate with an example. Take the cotton goods industry…”

Knowing what his audience needed paid off. The day after his first address, banks across the country opened to long lines of people waiting to put their money back in. He had restored trust and confidence in a previously insecure public.

Today’s Q&A-based fireside chats can also be a valuable opportunity to inspire, engage, and powerfully connect with an audience. By remembering the principles embodied in the acronym FIRE, you can maximize the value of them for both you and your audience.

Disruptive Startups Get Funding More Easily, but Less of It

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In the start-up world, the disruptor is the cool kid on the block, the one who’ll change the world — or at least the products you’ll buy and how you buy them. She takes on the grown-ups in suits and shows us all how dumb they are. Customers love her because she makes them feel like rebels (with a cause), suppliers love her because she makes them look smart, and — most importantly — investors love her because she makes them feel they’re putting money into tomorrow’s big player.

That, at least, is what the hype around disruption would have you believe. A new product or technology sells better to all stakeholders if people can be persuaded that it will disrupt the status quo. But does the evidence bear out this belief?  Specifically, does presenting yourself as a disruptor really make it more likely that your startup will get the backing it needs?

To answer this question, we studied 918 startups in Israel seeking a first round of funding. Israel is a cradle of entrepreneurship, with more high-tech startups per capita than any other country. They’ve spawned many unicorns, such as Waze (the driving navigation app acquired in 2013 by Google for $1.3 billion), NDS (the video software provider scooped by Cisco in 2012 for $5 billion), Playtika (the gaming platform bought by Giant Interactive for $4.4 billion in 2016), and Mobileye (the software and chip provider for autonomous vehicles acquired by Intel for $15.3 billion in 2017).

Here’s how we did it. We obtained data from the Startup Nation Central(SNC)—a private non-profit organization that tracks the Israeli startup ecosystem and offers an exhaustive platform for investors to scout for promising startups. Two coders manually assessed if a startup’s profiles did or did not articulate a vision to fundamentally change its industry, disrupt the industry’s existing power structures, or alter the way the industry operates. Each yes answer was accorded one point and each no was assigned a zero value. The total score for each was averaged across the coders, giving the scores a range of between 0 and 3 with 0.5 increments.

And what did we find?  Unfortunately, what we got was a yes but rather than a resounding confirmation or refutation. The results showed that, yes, increasing our measure of a venture’s disruptive vision communication by one standard deviation (0.78) improved the odds of that venture receiving early funding by 22%. But the venture would also very likely find that the amounts it would raise went down by 24% — for a typical Israeli venture that would mean getting $87,000 less in the Seed round, and $361,000 less in the series A round.

That raised an interesting question: Why would investors be more willing to invest and less generous at the same time?To answer this question, we recruited 203 participants with previous investment experiences for an online experiment. We randomly split them into two experimental conditions in which we presented them with an investment opportunity into a venture. The venture was taken from our Israeli sample and was identical in both experimental conditions. The only difference was that we manipulated the venture’s description to present the venture as a disruptor or not. We then asked participants to assess the upside potential of the venture, and to decide whether and how much they’d invest in the venture.

What the experiment revealed was that investors treated disruptive ventures like options.  They wanted the chance to be part of “the next big thing”— a venture that has the potential for extraordinary returns. But they didn’t want too many eggs in any one basket at once.  By investing less in a self-claimed disruptor, investors don’t so much fund the venture as pay for the right to make further investments in the venture in the future, when the risks and uncertainties are better understood and more easily quantified.

Where does this leave the entrepreneur? It all depends on the risks and uncertainties of your venture.  If your venture is a high-risk proposition that might struggle to acquire an investment, then you should have a compelling story that will help convince investors. Screaming disruption everywhere you can will help in that case. But if you feel the venture’s main risks are less in the idea than in its execution — then maybe you should try to avoid making disruption your narrative and talk more about your experience and capabilities.  You’re more likely to get the amount you need.

How to Get Better at Reading People from Different Cultures

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Body language varies significantly across cultures. What is considered rude or foolish in a Nordic country may be welcomed as warm and friendly in an African one. What a Canadian businessperson would perceive as arrogant, an American executive may see as healthy confidence.

But what remains consistent across all known cultures are microexpressions. These brief, involuntary flashes of facial expression reveal our true feelings about another person or situation.

Photos courtesy of the Center For Body Language.

People might try to hide or obscure them in different ways informed by culture, but to a practiced reader the true emotions are always visible. Consider the contrast in expressiveness between Filipino and Japanese people. In the Philippines, showing emotion — both positive and negative — is a sign of openness and honesty. In Japan, the opposite is true. Visible negative emotion is seen as rude or hostile, while expressing too much positive feeling is considered indelicate. However, when we evaluate people from both countries for their microexpressions, we find that they actually experience emotions at more or less the same level of frequency and intensity. It’s just that the Japanese consciously try to mask their reactions, often by smiling, while Filipinos wear their feelings for all the world to see.

The ability to read microexpressions can be useful anywhere — as we’ve previously shown, salespeople who have this knack get better results — but it’s particularly useful in more buttoned-up cultures, where people are careful managers of the physical signals they send out.

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Here’s another example: A few years ago, my husband and I traveled to Qatar to lead a body language workshop for 200 HR executives. Immediately, cultural norms made it difficult to gauge how the audience was receiving our presentation. Women’s bodies were completely covered, so we couldn’t see their posture or gestures. When I stood on stage with my husband, all the men looked exclusively at him, and all the women looked exclusively at me. But we could read the microexpressions we saw around the room. We knew from the videos we’d previously made of Qataris that the flashes of emotion in their faces reflected the same sentiments we might find from audience members anywhere else in the world. And, so we could calibrate our presentation accordingly, and felt just as comfortable as we would have at home.

Recognizing and interpreting microexpressions takes practice, but there are a few things you can start doing immediately to improve your skills.

First, study the common microexpressions pictured above so you know the hallmarks of each. Disgust, for example, involves down-turned lips, while people feeling contempt might show it by inadvertently pulling one side of the mouth up. Surprise and fear might look similar, but the latter emotion will cause people to pull their brows together.

Second, if you know you’re about to visit or interact with another culture, educate yourself on the local body language — including masking techniques. YouTube is a great tool for this: Find videos of 10 executives from that culture and watch how they communicate.

Third, when you’re in the moment, pay attention. You can’t interpret microexpressions if you don’t notice them. Don’t make your counterpart uncomfortable with an unwavering stare. But do keep your focus on the face.

Fourth, listen to your intuition.When you notice a tiny facial movement, ask yourself: “What could that mean?” Humans are wired to subconsciously detect even the subtlest of emotional flashes, so your gut instinct may be correct.

You might also try to mimic the movement. When you repeat what you saw — whether it was a quick eyebrow raise or tightening of the lips, it not only gives you more time to think, but also fires the mirror neurons in your brain, making it easier for you to associate the movement you saw with the correct emotion.

If you’re still perplexed, start to exclude emotions. After memorizing the expressions above, you should be able to quickly assess what the facial cue does not mean. For example, if you saw someone’s eyebrows going down, you can exclude surprise, fear, or sadness — all of which are associated with raised eyebrows — and work from there.

If you’re presenting to a crowd, as we were in Qatar, continue to scan the audience for microexpressions. Don’t fixate on one negative look; instead try to discern the sentiments of the majority.

Body language can be cultural, but emotions are universal. Microexpressions reveal someone’s true feelings in a fragment of a second, and so it pays to notice them and calibrate your behavior in cross-cultural interactions accordingly.

Let’s Do Less Dead-End Work

From the Women at Work podcast:

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Women are expected and asked to do thankless tasks — order lunch, handle less-valued clients — more than men, and research shows that doing those tasks slows down our career advancement and makes us unhappy at work. We talk about why we wind up with so much office drudgery and how to get some of it off our plates. Guests: Lise Vesterlund and Ruchika Tulshyan.

Could you take notes? Would you mind ordering lunch? We need someone to organize the off-site event — can you do that? Whether you’ve just started your career or are the CEO of the company, if you’re a woman, people expect you to do routine, time-consuming tasks that no one else wants to do.

We talk with University of Pittsburgh economics professor Lise Vesterlund about why women get stuck with — even volunteer for! — tasks that won’t show off our skills or get us promoted, and how that slows down our career advancement and makes us unhappy at work. Women of color are asked to do more low-promotability projects, and we talk with inclusion strategist Ruchika Tulshyan about how they can say no. Lise and Ruchika tell us how they’ve handled these kinds of requests and what managers can do to assign work fairly.

Guests:

Lise Vesterlund is the Andrew W. Mellon Professor of Economics at the University of Pittsburgh. She is also a research associate with the National Bureau of Economic Research.

Ruchika Tulshyan is the author of The Diversity Advantage: Fixing Gender Inequality in the Workplace and the founder of Candour, an inclusion strategy firm. She is also adjunct faculty at Seattle University.

Resources:

“Why Women Volunteer for Tasks That Don’t Lead to Promotions,” by Linda Babcock, Maria P. Recalde, and Lise Vesterlund
“Women of Color Get Asked to Do More “Office Housework.” Here’s How They Can Say No.” by Ruchika Tulshyan
“For Women and Minorities to Get Ahead, Managers Must Assign Work Fairly,” by Joan C. Williams and Marina Multhaup
“‘Office Housework’ Gets in Women’s Way,” by Deborah M. Kolb and Jessica L. Porter 

Email us here: womenatwork@hbr.org

Our theme music is Matt Hill’s “City In Motion,” provided by Audio Network.

The Best-Performing Emerging Economies Emphasize Competition

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Development economists over the ages have puzzled about why some emerging economies perform much better than others over the long term. We have been looking at the same issue in our latest research, and find one element that others haven’t tended to focus on: the often intense competitive dynamics that can be found in the best performing emerging economies—a competitive mindset that has spawned a new generation of productive and battle-hardened companies that aspire to be global champions.

That finding may seem counter-intuitive: don’t many emerging economies nurture and shield their national champions from competition? The short answer we find from our research is: No. In fact, by some measures, the best emerging-market firms are more competitive than firms in advanced economies including the United States and the United Kingdom.

For our research, we looked at 71 emerging economies and identified 18 that achieved rapid and consistent GDP growth over the past 50 and 20 years. They include the usual Asian suspects—China, South Korea, and Singapore—but also less obvious countries including Ethiopia and Vietnam.

When we examined their track record more closely, we found that these 18 “outperformer” countries had twice as many large firms with revenues exceeding $500 million as their peers, relative to the size of their economies. More large companies means the gains are distributed more broadly than would be the case with just a few—but that domestic competition can be ferocious. Indeed, it is much harder for this plethora of emerging-market firms in the outperforming countries to get to the top and then stay there. More than half that reached the top quintile in terms of economic profit generation between 2001 and 2005 had been knocked off their perch a decade later, in 2010-15. By comparison, 62% of incumbents in high-income economies on average remained in the top quintile for the same decade. In the United States, 68% stayed put, and in the United Kingdom it was as many as 76%.

A survey we conducted of companies in seven countries also brought its share of surprises. The top-performing emerging-market firms innovate more aggressively than their advanced economy rivals: 56% of their revenue comes from new products and services, compared with 48% for firms in advanced economies. These firms also invest almost twice as much as their advanced economy peers, measured as a ratio of capital spending to depreciation. And they are nimbler as they do so: on average, they make important investment decisions six to eight weeks faster, or in about 30-40% less time.

Moreover, when it comes to that metric beloved by stock market analysts and investors, total returns to shareholders, these firms also outperformed. Between 2014 and 2016, the top quartile of companies in the best-performing economies generated total return to shareholders of 23% on average, compared with 15% for top-quartile firms in high-income countries.

The ascendancy of emerging-market firms is evident in rankings such as the Fortune Global 500; more than 160 of these firms have joined the list since 2000. While emerging-market firms accounted for about 25% of total global corporate revenue and net income in 2016, they contributed a disproportionate 40% of the revenue and net income growth of all large public companies between 2005 and 2016.

There are some clear lessons here for all economies, not just emerging ones. Allowing and indeed encouraging domestic competition brings results not just for the firms that survive it, but also for the economy as a whole. The successful large firms in the outperforming economies act as catalysts for change, through investment and building capability among their suppliers. Many of these suppliers are small- and medium-sized companies that tend to be less productive than the larger firms, but are nonetheless critical for employment. By bringing them into their ecosystems, the larger competitive firms help instill management and operational best practices, and can accelerate and encourage technology adoption.

While our research found that firm-level innovation is high, we also note that policy plays an important role. In outperforming emerging economies, policy makers work with the private sector to define the development agenda, and they also rationalize regulations and barriers to growth. Yes, some governments do give financial and other support to young companies, with the goal of helping them grow. That has been the case in countries from South Korea to Singapore. However, where they have done so most successfully, the support is time-bound and targeted. The broader aim is to make companies, and the economy as a whole, more competitive.

We can see that clearly when looking at the productivity record of these countries. We decomposed total productivity growth in the economy from 1965 to 2012 across 35 sectors, including 15 manufacturing sectors and 20 service sectors. For most outperformers, we found that long-term growth was overwhelmingly driven by productivity growth within individual sectors rather than from the mix across sectors. In other words, success depends less on finding the right mix of sectors than on identifying sources of competitive advantage—and continuously driving productivity improvements within those sectors.

The finding is yet another sign that competitive dynamics are essential—and that countries that get them right prosper.

Protecting Company Culture Means Having Rules for Email

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A new study out of Virginia Tech University confirms something that just about every knowledge worker already knows: Dealing with after-hours emails produces anxiety that is damaging not only to the worker, but to their family.

One particularly striking finding of this study is that it’s not just the amount of time taken up by reading and answering emails after work that’s stressing out employees (and their partners). In fact, what’s creating more anxiety is just the expectation that an employee will be available for work outside the office.

Take this example: A manager does not expect employees to return her emails during off-hours or while they’re on vacation, but she never explicitly says this. Instead, she assumes they “just know,” and therefore thinks there is no harm in sending messages during these times, because she figures they’ll just be waiting for the employee when he returns. But in fact, the employee doesn’t know, and logs into his email while he’s out of the office (perhaps because he knows others do it). And when he sees an email from his boss, he interprets this to mean that she expects him to respond. This feeds the expectation to check email while he’s away, and the belief is reinforced by the fact that the manager seems to be working at all hours herself. A lack of intention and differing assumptions cause an unhealthy culture to take root.

This is all consistent with what I see as a speaker and trainer on productivity — it’s bad enough that employees feel tethered to their email during the work day, making it hard to get more important — and more satisfying — work done. When they feel pressure to check even during evenings, weekends and vacations, the quality of their work suffers because they never get a chance to rest and recharge their minds. Without mental recovery time, they become less creative, focused and thoughtful. They feel stressed and out of balance — which all set the stage for burnout.

The problem has three components:

Employees habitually check email constantly throughout the day and are unable to “turn off” this behavior simply because they’ve left the office.
Leaders are not immune to #1, and also not intentional about their expectations for after-hours communication. The unofficial policies and practices that spread through the organization come about as a result of the behaviors of leadership, who are unaware that their habits are molding the culture.
Employees assume that if leaders or any other employees in the organization are sending emails after hours, they should be, too.

Each of these components feed the others, creating a cycle that speeds up the pace at the company and contributes to a culture where stress and anxiety thrive. If you’re a manager who’s troubled by this, you can protect your employees and their families from the anxiety caused by the expectation of after-hours availability. The solution must address all three components.

First, you have to clarify your expectations. What managers expect can differ greatly from what employees believe their managers expect, as in the example above.

In the absence of clear expectations, employees will make assumptions about what you expect. You can make your expectations clear — doing everyone a favor — by being explicit. Say something like, “We believe that downtime is important, and we expect you to disconnect from work email on evenings, weekends, and vacations. If something important comes up, we’ll communicate via phone or text.”

What’s important about a statement like that is that it not only clarifies big-picture expectations — about the importance of downtime and disconnecting — it also helps set small-picture expectations about which forms of communication are appropriate in which situations.

I would encourage you to get even more granular: create, clearly communicate, and abide by guidelines for communication even during work hours. Outline which communication channels are appropriate in which situations.  For example, if it’s common during the workday for staff to send emails in the case of urgent or time-sensitive issues, then they can never feel comfortable closing their email client in order to get more important work done. They have to keep one eye on their email at all times, which pulls their attention away from other tasks. This constant distraction undermines their focus and prevents them from practicing attention management, leading to days that feel busy but are not productive. Email was never intended for synchronous communication, and although we treat it that way, it’s ultimately a terrible idea.

Instead, tell them that in the case of an urgent or time-sensitive situation, you want them to send a text or make a phone call (just as during after-hours), or work it out face-to-face. Make it clear that email should only be for non-time-sensitive communications and routine requests, regardless of the day or time. This prevents the habit of constant distraction during work hours, and minimizes the urge to check after-hours. Importantly, you must model this behavior yourself.  If an employee sends you an email containing an urgent request, the only way to drive the message home is if you don’t see it immediately, forcing them to use a more appropriate channel.

Your communication guidelines can go beyond email and the urgent vs. the non-urgent, too — you can set expectations on what meetings are for, how best to use project management tools like Asana, Basecamp, or Trello, and in which situations employees should use company wikis or messaging tools like Slack or Twist. This will help cut down on the number of emails your employees have to respond to.

Clear guidelines will create the space employees need to feel comfortable closing their email client and otherwise controlling their technology so that they can apply the full weight of their concentration to important work, sometimes called “deep work.”

This means leaders need to curb their own late-night email habit, and realize the benefits themselves. And no one, not even the boss, should be required to check work while on vacation. If that doesn’t seem possible at your company, you are likely to have bigger problems than losing out on downtime.

As you implement these changes, you should start to see a shift in your workplace culture. Being “always on” and connected to email 24-7 may feel like you’re being productive, but, as the Virginia Tech research shows, it’s actually increasing employees’ stress and causing conflict within their families, ultimately leading to lower levels of productivity. This is not a sustainable situation for hiring and keeping the best employees, and supporting your organization’s success.