Marina Gorbis's Blog, page 1485

Algorithms Won’t Replace Managers, But Will Change Everything About What They Do

The labor market is about to be transformed by machine intelligence, the combination of ubiquitous data and the algorithms that make sense of them. That’s according to economist Tyler Cowen, in an argument spelled out in his recent book Average is Over. As Cowen sees it, your job prospects are directly tied to your ability to successfully augment machine intelligence. He writes:

Workers more and more will come to be classified into two categories. The key questions will be: Are you good at working with intelligent machines or not? Are your skills a complement to the skills of the computer, or is the computer doing better without you? … If you and your skills are a complement to the computer, your wage and labor market prospects are likely to be cheery. If your skills do not complement the computer, you may want to address that mismatch. Ever more people are starting to fall on one side of the divide or the other. That’s why average is over.

But what about management? I interviewed Cowen last month about his vision of the future, and where he sees managers fitting into it. An edited version of our conversation follows.

WF: What do you see as the main career lessons of the book?

TC: One thing the book suggests is that only being technically skilled may not be that useful, because those jobs can be outsourced or even turned over to smart machines. But people who can bridge that gap between technical skills and knowing some sector in a way that’s more creative or more intuitive, that’s where the large payoffs will come.

A classic example is Mark Zuckerberg with Facebook. Obviously a great programmer, but had he just gone out to be paid as a programmer he wouldn’t be that well off. He was a psychology major — he understood how to appeal to users, to get them to come back to the site. So he had that integrative knowledge.

For people who are not technically skilled, marketing, persuasion, cooperation, management, and setting expectations are all things that computers are very far from being good at. It comes down to just communicating with other human beings.

WF: Where does management fit into this?

TC: In any company, you need someone to manage the others, and management is a very hard skill. Relative returns to managers have been rising steadily; good managers are hard to find. And, again, computers are not close to being able to do that. So I think the age of the marketer, the age of the manager are actually our immediate future.

WF: I was talking recently with Andrew McAfee of MIT, whom you reference the book, and he mentioned the way software might even replace some pieces of management, though not managers themselves. Do you see algorithms and software encroaching majorly into that area?

TC: If it’s just measuring how hard people work, how long they’re at their desks, how good a job they do, how good a doctor or a salesman is adjusting for quality of customer, there’s a huge role there for software. But to actually replace managers, for the most part I don’t see that. At least not for the time horizon I’m writing about, 10 to 20 years out.

WF: One thing that McAfee talks about is the idea that people want to get their information from a human; they can be very distrustful of a computer just spitting out a recommendation.

Do you see that being true in a management context as well? That part of my job, if I’m running a company or division, is being able to understand machine intelligence and deliver it personally?

TC: That’s right. You will translate what the machine says and try to motivate people to do it. Professors and teachers will be more like coaches or tutors, rather than carriers of information. They’ll steer you to the program, tell you which classes to take, and be a kind of role model to get you excited about doing the work.

It’s a very important skill, and hard to learn. But I think you’ll see this kind of pattern again and again.

WF: How else do you see management changing?

TC: Management — for all the change we like to talk about — has actually been pretty static for a while. But smart machines and smart software are going to change management drastically, and in general we’re not ready for this. We will need truly new managerial thinking, not just new in the cliched sense of repackaging with new rhetoric and new categories.

WF: I wanted to ask you a little more about the machine-human teams. Freestyle chess — where human and computer teams play together, and outperform either on their own – is the example throughout the book.

What skills does the freestyle chess master have that the grandmaster doesn’t?

TC: The program, of course, does most of the calculations. The one skill the human needs when playing freestyle is how to ask the program good questions. Knowing what questions to ask is how you beat a solo program playing against you, and you don’t even have to be very good at chess. You need to understand chess at some core level, and you need to understand what different programs can and cannot understand.

It’s a kind of meta rationality. Knowing not to overrule the programs very much, but also knowing they’re not perfect, and knowing when to probe. And I think that, in management, those will be the important human skills.

WF: How do you determine where the line is between when the employee is able to add value above and beyond what computer intelligence is giving them, and when the software itself can replace them?

For example, I’m imagining some analytics software. Someone is very skilled at using it, they’re drawing some conclusions, they’re presenting them to people. But the next version of software may have built-in the ability to make those inferences. What skills keep that human from being replaced?

TC: People who can judge that there’s more to the matter than the software can grab; people who can judge the fact that there’s a need for a different kind of software for the problem; people who know when to leave the software alone and get out of its way.

Those are difficult to acquire and often quite intangible skills, but I think they’re increasingly valuable. You can think of other professional areas, like law or medicine, where you let the software do a lot of the work but you can’t uncritically defer to it. Software is bad at common sense in a lot of ways and it misses a lot of context. It’s people who can provide context.

WF: You have an interesting section in the book with respect to specialization in science. Do you see the path towards greater specialization as the path to career security? Or is there still a role for generalists?

TC: There’s a role for both, but you need to ask whether these terms lose some of their meaning. If someone says to you “I specialize in being a generalist,” it’s not actually a crazy claim. Most people cannot be a generalist, and you have to work really hard at a bunch of particular things to be good at it. You’re specializing in doing that. These are people who integrate and understand the contributions of others — that’s a lot like managing. So what you call generalists — I would not oppose them to specialists — there’s a big and growing role for them.

WF: You can’t go a day without seeing a story about who should learn to code or not learn to code. The same thing with respect to statistics. Given the way you see the labor market breaking out, are there specific things you advise people go out and learn?

TC: Statistics will be an increasingly big area. And even knowing a little can have a pretty high return. Coding’s tricky. If you can learn it, great. But if you can’t do it right, you really shouldn’t bother. There’s no half way.

But if you’re a manager or you work in health care, you might not ever be doing statistics, but if you can grasp some basic stuff that you can teach yourself, there’s a very high return. And it’s really quite feasible, unlike coding where it’s a major undertaking. If you’re a doctor trying to figure out which parts of the hospital are bringing in the money and someone hands you statistics — if you’re helpless, that’s really bad.

WF: One area that strikes me as one of the more difficult for machine intelligence is strategy. Where to position your business in a marketplace seems like on the far end of what machines can tell us.

TC: Yeah, that’s all humans, though you might consult machines for background information. But in no sense are machines close to being able to do that. That’s a very long way away.

All of our sectors are all on different paths, and the differential timing actually will be useful because we won’t have to figure it out all at once. We’ll get lessons from different areas sequentially and adjust. Humans will switch into the sectors they’re still good at in a rolling way. And that will make this socially more stable and better for most people.

If you woke up one morning and the machines were better than you at everything, that would be pretty disconcerting. That’s the science fiction scenario but it’s not that realistic.

Talent and the New World of Hiring
An HBR Insight Center




How an Auction Can Identify Your Best Talent
The American Way of Hiring Is Making Long-Term Unemployment Worse
We Can Now Automate Hiring. Is that Good?
Learn How to Spot Portable Talent

Strategic Humor: Cartoons from the January–February 2014 Issue

Enjoy these cartoons from the January–February issue of HBR, and test your management wit in the HBR Cartoon Caption Contest at the bottom of this post. If we choose your caption as the winner, you will be featured in next month’s magazine and win a free Harvard Business Review Press book.

“Call me old-school, but if I don’t take notes in cuneiform, it goes right out of my head.”

Michael Shaw




Bob Eckstein



“I regret not taking management classes.”

Roy Delgado

And congratulations to our December caption contest winner, Kevin Thomas of Williamstown, Massachusetts. Here’s his winning caption:

“It still works in theory.”

Cartoonist: Paula Pratt

NEW CAPTION CONTEST

Enter your own caption for this cartoon in the comments field below — you could be featured in next month’s magazine and win a free book. To be considered for the prize, please submit your caption by January 7, 2014.

Cartoonist: Paul Kales

What Change Agents Value at Work

When it comes to change management, half the battle is making sure you have the right leaders in place. And that means looking carefully at their competencies, behavioral styles, and values.

To help with that challenge, my colleagues and I have created a change-agent profile. In our work assessing people for the right job fit, we’ve collected and analyzed extensive data on Fortune 1000 executives across a wide spectrum of industries. Here’s what we’ve discovered about change agents in that senior group:

They’re somewhat rare. Approximately 20 percent of senior executives scored high on five key competencies that correlate with effective change management.
Executives with those five competencies are more task-oriented than people-oriented.
They also appear to be motivated most by achievement. Power is a close second.

And here’s how we arrived at those high-level findings.

We analyzed competencies.

In our years of experience working with organizations in transition, we’ve identified the following strengths as key indicators of effective change management:

Demonstrates flexibility and resilience. Works well with a variety of individuals or groups. Adapts as the requirements of a situation change.  Manages pressure and copes with setbacks effectively.
Recognizes growth opportunities. Looks for ways to improve. Demonstrates skill in minimizing others’ resistance to change.
Strives for results. Focuses on improving performance.
Leads courageously. Takes charge of initiatives and situations. Takes responsibility for making difficult decisions, even in the face of dissent. Shares feelings, opinions, and needs with clarity and conviction. Does not avoid conflict or differences.
Gains buy-in.  Explores alternative perspectives and ideas to reach solutions that have support from others in the organization.

So after surveying more than 600 executives about their experiences dealing with a range of change-related business problems, we analyzed the data for statistical relevance to the competencies above.

We examined behavioral styles.

Next, we looked at the four behavioral styles from our own version of the DISC methodology personality assessment: driving (assertive, independent, driven to win, on the go), impacting (talkative, social, emotional, and spontaneous), supporting (empathic, accommodating, and trustworthy), and contemplating (reserved, analytical, quiet, and unhurried).

Even though the people-oriented “impacting” executives tend to implement change effectively, it turns out that the more task-oriented “driving” executives are even better at it. They score the highest, of everyone surveyed, on all five change competencies. They have a strong need to dominate, and they’re directive when they deal with problems. Decisive and results-focused, they are uncomfortable with the status quo and likely to be strong change agents.

We correlated competencies with values.

Finally, we looked at how executives with all five competencies scored on values, which helped shed light on the type of work environment they find most motivating and rewarding. We saw the strongest positive correlation with the desire for achievement, followed by the desire for power, adventure, and creativity, respectively. Leaders who scored high on independence and altruism tended to score lower on the five change competencies.

If your organization is facing transition, try evaluating people against our change-agent profile when hiring, assigning, or promoting them. During interviews, zero in on the key competencies, and ask how they’ve demonstrated the related behaviors in their current and previous roles. Further, ask yourself whether they show evidence of being task-oriented and are strongly motivated by achievement and power.  The executives who do are the ones best equipped to make change happen.

The Seven Imperatives to Keeping Meetings on Track

There’s nothing more annoying than a meeting that goes on and on and on. As a manager, it’s your job to make sure people don’t go off on tangents or give endless speeches. But how can you keep people focused without being a taskmaster or squashing creativity?

What the Experts Say

The good news is that meeting management isn’t rocket science; you probably already know what you should be doing. The bad news is that keeping your meeting on track takes discipline, and few people make the effort to get it right. “The fact is people haven’t thought about how to run a good meeting, or they’ve never been trained, or they’re simply too busy,” says Bob Pozen, a senior lecturer at Harvard Business School, senior fellow at Brookings Institute, and author of Extreme Productivity. “Organizations are moving faster and faster these days and few managers have time to think through their meetings in advance,” says Roger Schwarz, an organizational psychologist and author of Smart Leaders, Smarter Teams. But rushing now is only going to cost you more time later. So whether you’re getting ready for a weekly team meeting or convening a larger group to discuss your division’s strategy, it’s important to put in the effort. Here’s how to make your next meeting your most productive one yet.

Make the purpose clear

You can head off a lot of problems by stating the reason for getting together right up front. Schwarz recalls seeing a sign in a conference room at Intel’s headquarters that read: If you don’t know the purpose of your meeting, you are prohibited from starting. This is a wise rule. Send an agenda and any background materials ahead of time so people know what you’ll cover. Consider sending a list of things that won’t be discussed in the meeting as well. Schwarz suggests that you list agenda items as a question — rather than “Discuss video schedule” write “When will videos be completed?” to show what outcome you have in mind. Next to each item, you can also indicate participants’ roles — are they sharing information, contributing ideas, or making a decision?

Control the size

Meetings can get out of control if there are too many people in the room. “Chances are they won’t be attentive or take responsibility for what’s happening,” says Pozen. But with too few people, you may not have enough diversity of opinion. Only include those who are critical to the meeting. “Don’t feel you have to invite everyone who ever thought about the problem,” he says. “If you think someone might be offended, you can send out a memo and loop back with them afterward so they know what’s happening.”

Set the right tone

As a manager, it’s up to you to ensure that people feel comfortable enough to contribute. “You’re there to be a steward of all the ideas in the room,” says Schwarz. Set the right tone by modeling a learning mindset. Instead of using the time to convince people of your viewpoint, be open to hearing other’s perspectives. Explain that you don’t have all the answers, nor does anyone else in the room. Be willing to be wrong. Schwarz says you want “participants to see the team meeting as a puzzle — their role is to get the pieces out on the table and figure out how they fit together.”

Manage ramblers

“People often give speeches instead of asking questions,” says Pozen. It’s tough to cut a rambler off, but sometimes it’s necessary. Schwarz suggests saying, “OK, Bob, you’re absolutely right and is it ok if we talk about that later?” Getting his buy-in will ensure that he doesn’t return to his speech at the next opportunity. For someone who is prone to long-windedness, talk with her ahead of time or during a break, and ask that she keep her comments to a minimum to allow others to be heard.

Control tangents

Sometimes it’s not that an individual goes on too long but he raises extraneous points. “If two or three people bring up things that are contiguous but not really related, the meeting can degenerate,” says Pozen. Try to refocus them on the stated agenda. On occasion, someone may intentionally go on a tangent. Maybe he feels territorial about a decision you’re making or is unhappy with the direction you’re taking the conversation. “Rather than accuse the person of trying to derail your meeting, ask what’s going on. Pozen suggests you say something like, “You’ve diverted us several times. Is there something’s that bothering you?” Addressing the underlying issue head on can help appease the dissenter and get your meeting back on topic.

Make careful transitions

“Typically leaders go from topic to topic, moving ahead when they’re ready to,” says Schwarz. “But people don’t always move with you and they may get stuck in the past.” Before you transition from one agenda item to another, ask if everyone is finished with the current topic. “You need to give people enough air time,” says Pozen. This will help keep the conversation focused.

End the meeting well

A productive meeting needs to end on the right note to set the stage for the work to continue. Pozen suggests you ask participants, “What do we see as the next steps? Who should take responsibility for them? And what should the timeframe be?” Record the answers and send out an email so that everyone is on the same page. This helps with accountability, too. “No one can say they’re not sure what really happened,” says Pozen.

Principles to Remember

Do:

Make the meeting purpose clear and send an agenda out ahead of time
Talk to anyone who might monopolize meeting time before you get in the room and ask him to keep comments to a minimum
Send out a follow-up email after the meeting that lists next steps, who’s responsible for them, and when they’ll get done

Don’t:

Feel obliged to invite lots of people — only include those who are critical to making progress
Move on to a new topic until everyone feels they’ve been heard
Let the group get distracted by tangents — ask if you can address unrelated topics another time

Case study #1: Let everyone be heard

As the vice president of maintenance, repair, and overhaul at American Airlines, Bill Collins was tasked with improving the company’s relationship with unionized workers. To help facilitate conversation, Bill set up town hall-style meetings with Tulsa operation’s 6,500 employees. He quickly realized that these gatherings weren’t efficient or productive. “There hadn’t been town-hall meetings in 15 years and people had a lot of pent up anxiety that they wanted to get off their chests. They wanted to hang me,” he says. The meetings were scheduled for one hour but often lasted two.

Bill decided to make some changes. First, he made the meetings smaller by dividing them up by business and shift so that each only had about 250 people. “They still wanted to hang me but as least the conversation was manageable,” he says. Second, he changed the tone of the meeting by opening with a proposed agenda and asking for input. “I’d say, ‘Here’s what we want to discuss. What do you want to discuss?’” And if someone wanted to talk about something that wasn’t on the agenda, Bill would respond, “We’ll go to any level of detail you’d like on that topic during the Q&A. Is that OK?” He’d then wait for at least a head nod before moving on.

When Bill first described this approach to his fellow executives, many expressed concern that the meetings would take even longer if everyone had the chance to be heard. But he was invested in making it work. “The natural tendency for the workforce is to not trust management,” he says. “This process builds trust.” And, after the first of these newly revamped meetings, he had the proof he needed. “There were no raised voices,” he says. “It was calm, cordial, and it ended well. Leaders of the local union said it was the best meeting they’d been to.”

Case study #2: Actively manage disrupters

When Betsy Stubblefield Loucks took over as executive director of HealthRIght, a nonprofit focused on healthcare policy in Rhode Island, one of her responsibilities was to convene a monthly meeting with 20 people from various organizations with a stake in healthcare reform, such as labor, hospitals, insurers, and consumer advocates. The goal was to problem-solve and reach agreement about how the organization should approach different aspects of reform. In the past, the meetings were structured around specific topics but they didn’t have stated outcomes or a process for reaching resolution. As a result, participants would often just talk about issues they cared most about. “People had hot button issues and would make speeches about them,” she says.

Betsy decided to do something different with the agenda; she put the desired outcomes for each meeting at the top. This helped focus the conversation. She also made an effort to build relationships with people who tended to dominate the conversation. “Health care reform is a very broad — and deeply sensitive — topic. Our members are very passionate about their issues, and some people would have the same debates over and over because they didn’t feel heard,” she says. She set up meetings with these participants in advance of the monthly coalition meeting to let them vent to her personally and check her understanding of their perspective. Then when the group was together, she would represent that person’s opinion — with their permission — in a more concise way.

For particularly difficult people, she would assign someone to actively manage them during the meeting. “There was one person who would give the same stump speech over and over,” she says. So she asked a member of her executive committee to sit next to him, and when he started going on, to interrupt him. The executive committee member did this respectfully saying, “I think you’re making a great point,” and then would summarize his perspective. This helped the rambler feel like his point had been understood. It also helped Betsy keep focused on the meeting. “That way I wasn’t the only one playing traffic cop and he didn’t have to get mad at me,” she says.

Betsy uses these same approaches in smaller meetings as well. “Anytime I meet with more than one other person, I use these tactics. When I have the right people in the room, send out a clear agenda, and talk to any difficult people in advance, my meetings go much more smoothly,” she says.

It’s a Good Thing You Waited Until Now to Found Your Start-up

Cloud computing and other tech developments have drastically cut the cost of founding a company, says Stanford University finance professor Ilya Strebulaev. The new technologies have reduced the expense of building high-tech start-ups by a factor of 10, a development that has opened up the start-up world to angel investors as never before. Angels, who tend to prefer small deals, are enjoying a growing competitive advantage over traditional venture-capital firms and now supply the overwhelming majority of high-growth start-ups with their first money (after the founders have tapped family and friends), Strebulaev says.

Boards with More Women Pay Less for Acquisitions

Companies that have more women on their boards of directors make fewer bids for mergers and acquisitions — and pay less for acquired companies. That’s the finding from a new paper ( Levi, Li, and Zhang, 2013 ) by Maurice Levi and Kai Li of the Sauder School of Business at the University of British Columbia and Feng Zhang at the David Eccles School of Business at the University of Utah.

Professor Li, defend your research. What makes M&A activity and boards ideally suited to a study of gender and leadership behavior?

Li: There are three main reasons. First, M&A is a very important corporate decision that can make or break a company. Many have been catastrophic — just think of the classic example, AOL and Time Warner. So it clearly called for further scrutiny: most companies barely break even on these deals, so why do they still go ahead with them? And are there any mitigating forces that reduce a company’s tendency to be acquisitive and thus better protect shareholder interests?

Second, M&As are different than regular organic growth in that completing such a deal is associated with much greater uncertainty. You’re buying an unknown entity, possibly also entering a new market. Past research, which we cite, has shown that men and women behave differently when faced with uncertainty in terms of how overconfident they are. Everyone is overconfident — we always think we are better than our true selves — and when men and women are dealing with knowns they tend to be fairly similar in that regard as well. But when they are looking at unknowns, or when feedback is delayed or uncertain instead of specific and immediate, women demonstrate less overconfidence than men. So the M&A setting is an ideal setting in terms of how it amplifies gender differences in responding to uncertainty with overconfidence.

The third reason is that while a board is not engaged in day-to-day operations like a CEO, it is very involved in M&A decision making and in the deal making process. It’s more likely that a single voice from a female director would be heard, and that we could be able to capture that.

Women make up such a small percentage of directors. Is that really enough of a sample size to be able to tell what’s going on?

Actually, this research has evolved over time — at the very beginning we were very ambitious and were just looking at the very top females in the corporate hierarchy, female CEOs. But they are just so few in number that we didn’t have enough to go on. But women make up about 10% of boards of directors. A typical board is about 10 people, so a majority of U.S. companies have at least one female director. So in that sense, compared with female CEOs, there are many more of them. And while that is still a small number, it’s growing because of increasing awareness and because there are so many female students in business education, both MBA programs and undergraduate programs, and they are climbing up the corporate hierarchy.

Most M&As fail, so from that perspective it sounds like fewer and smaller takeover bids is actually a good thing. But in part of the paper you conclude that there’s no evidence that women are “better monitors.” What do you mean by that?

That’s derived from other work [Chen, Harford, and Li, 2007] where we look at institutional investors and stock price reactions to deal announcements. If female directors are good monitors they would be monitoring how things proceed after the deal is announced. If you announce your takeover bid and your stock drops 20%, if you are a good monitor you might use the time between the announcement and the deal going through to revise the deal or cancel it. But we saw no difference in how men or women responded to negative market reactions to an M&A — once the board has made their decision, they generally just go ahead with it.

In the paper you write that each woman on a board reduces likelihood of an acquisition bid being made by 7.6% and reduces the bid premium of any takeover bid by 15.4%. At what point would that stabilize? For instance, if you had a board that was 100% female it’s tough to imagine they would never make any takeover bids.

A 100% female board is almost a counterfactual, while 100% male boards are a fact of life. So for a statistician that is really difficult to measure.

But we did see a nonlinear effect to having multiple women on a board; having two women produces a stronger effect than having a single female director. Having multiple women present, versus a lone voice, means that they can reinforce each other and also make it more likely that their views will be heard.

But so few boards have more than two women, we don’t know what would really happen after that, if the effect would keep compounding or if it would plateau.

Do female directors correlate with decreases in other risky activities?

In fact, we did find a similar result in R&D spending and capital expenditures — female board members also correlate negatively with those activities. That’s for the same reasons about overconfidence and uncertainty that effect M&As.

Did you find any differences in the kind of men who were more or less likely to move ahead with a risky M&A deal?

In a previous paper [Levi, Li, and Zhang, 2010] we did examine the role of testosterone in M&As. Testosterone increases your combativeness and dominance-seeking, and younger male CEOs with more of the hormone were more acquisitive than older CEOs, who didn’t have as much. If you’ve got more testosterone and it’s increasing your sense of dominance, then you want to buy companies and build a bigger empire.

Binge TV and the Art of Creating a Committed Customer

Netflix has turned my wife into a binge viewer. No jokes necessary about how she now enjoys more time in bed with her iPad than with her husband. This behavioral transformation has been fascinating to witness. She now explicitly seeks out shows—typically dramas—that can be watched three to four hours at a time. I would never have picked her for having this aesthetic sensibility or taste.

The company recently released a survey showing that—surprise!—61% of Americans described themselves as regular binge viewers. What’s more, 75% of those surveyed say that watching several episodes of their favorite shows in a row makes the program experience more enjoyable. Netflix also observed that its data demonstrated that roughly half of binge viewers polished off an entire season over the span of a single week and the bingeing majority committed to one show at a time rather than more promiscuous consumption.

The essential empirical insight here is that Netflix has effectively created a new genre of committed customer; one demonstrably underserved and underappreciated by broadcasters, cable TV, DVR, DVD and other media platforms. The binge viewing segment has played no small part in driving Netflix’s brand equity and market cap. Just as importantly, binge viewers are driving Netflix’s business model development, as well.

Netflix, more than any other company this past year, most brilliantly addresses the theme and answers the question posed by my Harvard Business Review Press’ ebook, Who Do You Want Your Customers to Become?  Netflix wants its customers to become binge viewers. The company ingeniously invests in content and creativity designed to make its customers more willing to spend more time enjoying their binges. Asked another way, is bingeing on entertainment to Netflix what searching for information is to Google?

The original series the company produces—such as “House of Cards” and “Orange is the New Black”— are crafted with binge viewing in mind. As surely as the rise of the syndicated rerun marketplace in the 1970s prompted television producers to create series and shows worth viewing more than three or four times, the bingeing phenomenon now asks the creative community to produce programming capable of being enjoyably consumed for hours at a time. That’s a non-trivial challenge but one promising all the riches, recognitions and rewards a successful pop culture breakthrough can provide.

Remember the $1 million prize Netflix offered to get people to improve its movies recommendation engine? You can bet the company’s savvier marketing leaders are looking to launch recommendation engines suggesting what programs would be best for hours of binge viewing. Nobody wants to binge on unappetizing programs.

If Netflix’s investments are designed to enhance the BQ —Binge Quotient—of its customers, what other innovations are likely? The company clearly has an economic stake in going beyond the individual binge to couples and families: to wit, the family that binges together, hinges together. Expect recommendation engines suggesting binge-worthy comedies for twenty-somethings and old marrieds.

How might parents safely and ethically train children to binge responsibly on “The Simpsons” and/or “The Muppets”? Bingeing counterparts to musical mix-tapes seem inevitable. Transforming Netflix’s customers into bingers or (at least) people willing to binge a few times a year seems like a remarkably strategic and strategically remarkable value proposition.

This Netflix transformation offers important insights to innovators worldwide: how are your organization’s products and services transforming how your customers spend their time and attention? How should you invest in enhancing that behavioral change? What is your company’s “binge”?

But Netflix better make sure it doesn’t become too successful at binge-worthy transformations. Just as McDonalds was criticized for the role its “supersizing” initiatives played in promoting possible obesity and overindulgence, we’ll see regulators worldwide look to set limits on how much bingeing is too much. As Mae West (you can find her on Netflix) once observed, “Too much of a good thing is wonderful.” But will Netflix’s regulators agree?

The Bias Undermining Your People Analytics

People analytics – the fast-growing practice which companies use to analyze large amounts of data to quantify employee performance – has the potential to revolutionize the workplace and vastly improve how all of us are rewarded for our efforts. But used the wrong way, people analytics can be just as blind and biased as human beings have always been.

One of the most well-established findings in social psychology is the “fundamental attribution error” which essentially describes how observers over-attribute their explanations for the causes of behavior to “the person” and under-attribute the causes of behavior to “the situation.” In careers and the workplace, this means that credit or blame for performance is likely to be assigned to an individual more based on his or her perceived character, personality, intentions or efforts rather than on the situation, context, opportunities or constraints within which that individual is working. This cognitive bias explains why salespeople who are lucky enough to be selling the right products to the right market at the right time get credit and get viewed as talented “A players,” while those who have the misfortune of selling the wrong products to the wrong market at the wrong time instead receive blame and become branded as mediocre “B” or “C” players. This bias also explains why a CFO may be perceived as cheap by disposition or why a team might attribute its internal conflicts to incompatible personalities instead of resulting from organizational incentives to compete rather than collaborate with one another.

In this evolving age of data, the latest manifestation of the fundamental attribution error arises in the rapidly growing field of people analytics. Organizations can now conduct large-scale analyses with all kinds of variables in order to try to predict which employees are likely to succeed, and which are not. Companies use variables such as college or graduate school grades, SAT or GMAT scores, years of working experience, and the results of cognitive ability or personality tests, to predict turnover rates, promotions, sales volume, or other performance outcomes. With the explosion of data that companies collect and compile about their employees, it is tempting to both categorize and classify employees who currently work at the organization and to simultaneously build profiles of ideal candidates, who will be likely to perform well, remain at the organization, get promoted, and be satisfied with their jobs.

But just as people are susceptible to making the fundamental attribution error, organizations risk making what might be called the fundamental analytic error. That is to say, in many instances, critical information is missing from human capital or people analytics: situational or contextual variables. An argument can be made that for the purposes of predicting, explaining, and improving variance in performance, situational variables might actually prove better than individual variables. Using the example of salespeople, more of the variation in sales volume may be attributable to product or territory than by which sales person happens to be selling a given product in a given location. What remains indisputable, however, is that the combination of individual and situational variables together will explain much more of the variance in performance or employee engagement than individual variables or situational variables could ever explain alone.

The fundamental analytic error tempts organizations for several reasons. It’s often much more politically expedient to blame individuals when things aren’t going well than to search for the underlying organizational causes of their difficulties. If the talents or efforts of individuals get credited or blamed for performance, then performance that doesn’t meet expectations does not raise tough questions about whether culture, product, strategy, incentives, or technologies might be improperly configured or misaligned with one another. In other words, poor performance can readily get attributed to employees rather than to their leaders, who are directly or indirectly responsible for creating the conditions that should enable people to succeed. If products are not selling, it may be very appealing to initiate an analytics project to look at salespeople’s attributes instead of getting customer feedback about the company’s products. If turnover is high among entry level employees, it could much more politically palatable to analyze the personality, style, education, experience level, and referral source of the employees who leave the organization, rather than to analyze the capabilities or managerial skills of their supervisors. And no amount or kind of human capital analytics is going to save an organization in denial about disruptive changes occurring in its industry or markets.

There is a better way. The most valuable human capital or people analytic initiatives get deployed in a scientific manner. Hypotheses, nested in some kind of conceptual framework, get formulated and tested and theories and hypotheses are all subject to falsification. So, if some associates in a law firm are performing well, while others perform poorly, it is reasonable to hypothesize that their law school grades, LSAT scores, and whether or not they clerked for a judge might help predict, and partially explain, their performance as attorneys. If the associates who have high grades and scores and clerked for a judge are high performers, and associates with low grades and scores who did not clerk are poor performers, a researcher could hypothesize that this correlation indicates causation: that intelligence and motivation are reflected in the lawyers’ resumes, and that higher intelligence and motivation in turn cause higher performance.

But before conclusions can be drawn, other explanations need to be considered and alternative analyses need to be conducted. The hypothetical law firm, for example, might look beyond human capital analysis of its associates and consider the impact of practice area, geographic location, and types of cases on associate retention and performance. A courageous investigator, willing to risk stirring up organizational politics, might even suggest that the law firm conduct analyses to learn whether associates who work for some partners outperform associates who work for others. These additional analyses might determine that variance in associate performance is a function of whether the partners they happen to be working for provide coaching, mentoring and support, and not a result of the associates’ grades, scores or personalities.

Human psychology and organizational politics are both biased towards attributing too much causality to people and their individual attributes and not enough causality to situations and organizational context. Human capital and people analytics, despite their big data-fueled power, can easily get misused in ways that serve only to justify existing organizational systems and to unfairly scapegoat individuals who are not performing well in no small measure because of the weaknesses and constraints of those systems. Only by taking a broader, more open, less biased and less political approach to conducting analyses about the factors that predict and explain performance can organizations hope to improve it over the long term.

When You Criticize Someone, You Make It Harder for that Person to Change

“If everything worked out perfectly in your life, what would you be doing in ten years?”

Such a question opens us up to fresh possibilities, to reflect on what matters most to us, and even what deep values might guide us through life. This approach gives managers a tool for coaching their teams to get better results.

Contrast that mind-opening query with a conversation about what’s wrong with you, and what you need to do to fix yourself.  That line of thinking shuts us down, puts us on the defensive, and narrows our possibilities to rescue operations. Managers should keep this in mind, particularly during performance reviews.

That question about your perfect life in ten years comes from Richard Boyatzis, a professor at the Weatherhead School of Management at Case Western, and an old friend and colleague.  His recent research on the best approach to coaching has used brain imaging to analyze how coaching affects the brain differently when you focus on dreams instead of failings. These findings have great implications for how to best help someone – or yourself — improve.

As I quoted Boyatzis in my book Focus: The Hidden Driver of Excellence,  “Talking about your positive goals and dreams activates brain centers that open you up to new possibilities. But if you change the conversation to what you should do to fix yourself, it closes you down.”

Working with colleagues at Cleveland Clinic, Boyatzis put people through a positive, dreams-first interview or a negative, problems-focused one while their brains were scanned. The positive interview elicited activity in reward circuitry and areas for good memories and upbeat feelings – a brain signature of the open hopefulness we feel when embracing an inspiring vision. In contrast, the negative interview activated brain circuitry for anxiety, the same areas that activate when we feel sad and worried. In the latter state, the anxiety and defensiveness elicited make it more difficult to focus on the possibilities for improvement.

Of course a manager needs to help people face what’s not working. As Boyatzis put it, “You need the negative focus to survive, but a positive one to thrive. You need both, but in the right ratio.”

Barbara Frederickson, a psychologist at the University of North Carolina, finds that positive feelings enlarge the aperture of our attention to embrace a wider range of possibility and to motivate us to work toward a better future. She finds that people who do well in their private and work lives alike generally have a higher ratio of positive states to negative ones during their day.

Being in the positive mood range activates brain circuits that remind us of how good we will feel when we reach a goal, according to research by Richard Davidson at the University of Wisconsin. That’s the circuit that keeps us working away at the small steps we need to take toward a larger goal – whether finishing a major project or a change in our own behavior.

This brain circuitry — vital for working toward our goals — runs on dopamine, a feel-good brain chemical, along with endogenous opioids like endorphins, the “runner’s high” neurotransmitters. This chemical brew fuels drive and tags it with satisfying dollops of pleasure. That may be why maintaining a positive view pays off for performance, as Frederickson’s research has found: it energizes us, lets us focus better, be more flexible in our thinking, and connect effectively with the people around us.

Managers and coaches can keep this in mind. Boyatzis makes the case that understanding a person’s dreams can open a conversation about what it would take to fulfill those hopes. And that can lead to concrete learning goals. Often those goals are improving capacities like conscientiousness, listening, collaboration and the like – which can yield better performance.

Boyatzis tells of an executive MBA student, a manager who wanted to build better work relationships. The manager had an engineering background; when it came to getting a task done, “all he saw was the task,” says Boyatzis, “not the people he worked with to get it done.”

His learning curve involved tuning in to how other people felt. For a low-risk chance to practice this he took on coaching his son’s soccer team – and making the effort to notice how team members felt as he coached them. That became a habit he took back to work.

By starting with the positive goal he wanted to achieve – richer work relationships – rather than framing it as a personal flaw he wanted to overcome,  he made achieving his goal that much easier.

Bottom line: don’t focus on only on weaknesses, but on hopes and dreams. It’s what our brains are wired to do.

The Downside of the Fed’s Increasingly Complicated Expectations Game

Yesterday, the Federal Reserve announced that it’s kind of sort of about to start ever-so-timidly pulling back on the massive monetary stimulus it’s been pouring out since the financial crisis. Then, stock prices around the world jumped.

In the traditional view of monetary policy, this isn’t supposed to happen. Tightening by the Fed should make financial assets less valuable. And in fact the prices of the particular financial assets that the Fed announced that it will buy less of, Treasury bonds and mortgage-backed securities, did drop slightly on the news Wednesday. But stocks didn’t.

When you view this reaction in terms of expectations, it makes a bit more sense. As economist Barry Eichengreen put it in the FT, the announcement of the start of the “taper” — the unwinding of the Fed’s bond-buying efforts — was widely expected. What was news in the announcement was that “future policy would remain loose for at least slightly longer than previously anticipated.”

Still, even Eichengreen thought the policy shift was too inconsequential to justify the market reaction. Maybe he’ll turn out to be right, and the post-announcement jump will soon be undone. I think there’s more afoot than that, though.

Long ago, a central bank’s job may have been as simple as taking away the punch bowl just as the party gets going, to paraphrase William McChesney Martin, the Fed’s chairman from 1951 to 1970. But in Martin’s day, the Federal Open Market Committee was able to make its monetary policy decisions in relative obscurity. The media paid little attention to its decisions and there was as yet no cottage industry of “Fed watchers” interpreting and forecasting its moves. Financial markets on the whole played a much smaller role in the economy.

Nowadays financial markets often drive the economy, and while this would seem to give the Fed more power, the amount of effort and attention now put into forecasting monetary policy and assessing its impact mean that exercising that power is far more complicated than it used to be.

Consider what happened in the mid-1990s, when the Fed raised short-term interest rates sharply in order to stamp out what it perceived as a possible overheating of the economy. “For the first time we got a so-called safe landing,” then-Fed-chairman Alan Greenspan recalled recently. “As soon as we let up, off it went, which suggests to me that what happened was that the equilibrium level of the Dow Jones Industrial Average [rose], because of our actions that failed to knock the economy down despite a three-percentage-point increase in the Federal Funds rate. [It] elevated the long-term asset value expectation.”

This is from a conversation I had with Greenspan at the end of November, which will be published here in a fuller version soon. “If that is true,” he went on,

and I raise it as a hypothesis because I don’t know how you could prove it one way or the other, it is saying that our very efforts made the situation worse. The notion that you could calibrate monetary policy to suppress a boom against the human nature bubbling up has no factual basis. The only place it exists is in the econometric models where the equations are so constructed that if you tighten monetary policy you smooth out the boom.

By adroitly managing a soft landing in the mid-1990s, then, the Fed conditioned markets to expect further such competence and economic stability, setting the stage for the great stock market bubble of the late 1990s. Greenspan again: “I think the evidence probably is conclusive, that a necessary and sufficient condition for a bubble is a prolonged period of economic stability, stable prices, and therefore low risk spreads, credit risk spreads.”

You could read this as trying to deflect blame for what transpired later: The crisis happened because we did such a great job! But I think the man is on to something. Expectations drive financial markets, they always have. What’s different is that the expectations-manufacturing industry has grown, a lot, and its impact on the economy has too. In the rational-expectations paradigm of a couple decades ago, this would be good news — better-informed markets would better anticipate what comes next. But reality is far noisier and more emotional than that, and market participants devote an awful lot of their brainpower to, in John Maynard Keynes’ words, “anticipating what average opinion expects the average opinion to be.”

From the perspective of Fed chairman Ben Bernanke and his soon-to-be-successor, Janet Yellen, the market’s initial reaction to the beginning of the taper is great news, for now. If markets come to expect that reductions in bond-buying by the Fed don’t result in meltdowns, the task of undoing the vast quantitative easing effort and getting Fed policy back to something approaching normal will be that much easier. But financial-market optimism and confidence have a tendency to eventually morph into exuberance and complacency. And it may be beyond the Fed’s power to control that cycle.