Monday, February 27, 2017

Can Uber Recover?

By now, everyone has read about the serious problems at Uber.  On February 19, former Uber engineer Susan Fowler published a blog post in which she described serious transgressions by managers at the firm, including sexual harassment.  Soon, newspaper accounts documented a culture that appeared to be out of control.   CEO Travis Kalanick has tried to address the situation, though his early moves have been met with criticism.  He appointed a panel to investigate the situation, but people have objected by noting that all three members are essentially "insiders" at the firm.  Kalanick himself has been criticized for comments in the past that have contributed to the dysfunctional culture.   

Can Uber recover from this fiasco?  Will there be lasting damage?  I see several potential long term negative consequences for Uber.  First, Uber will have a challenging time attracting top talent moving forward, particularly highly successful female engineers and managers.   Why would they wish to work for a firm with this reputation?  Talent acquisition and retention will be a problem for Uber, no matter the promise of financial rewards that they may offer.  Second, investors may begin to scrutinize Uber more closely.  Will they tolerate the huge losses and be as patient as they have been while Uber forsakes profits for aggressive growth?  Third, will corporate governance change?  Will the Board members begin to recognize their own vulnerability here, and will they start asking tougher questions?  Management could face a very different environment in future Board meetings.  

How can Uber recover?  They have to address multiple issues very quickly.  First, they have to insure that the outside review truly is objective.  Perception is reality.  If people perceive the current appointees as insiders who cannot be objective, it will be difficult to persuade people that the conclusions of the review are valid.  Second, they must confront and remove employees who engaged in unethical or even illegal behavior immediately.  Now is not the time for second and third chances.  People have to be held accountable.  Third, Uber must address how it evaluates and rewards employees.  Excusing the inappropriate behavior of brilliant jerks must end.  People must be evaluated and rewarded not simply on the results they achieve, but how they go about achieving them.  Fourth, Kalanick must address his own behavior and past comments.  He has to acknowledge his own culpability in molding and shaping this dysfunctional culture.  Moreover, he has to be very transparent as the review is conducted and changes are made.   Next, the company must address various informal rituals (the push-ups, for example) that have evolved over the years at the firm.  Are these rituals productive?  Should they be stopped? What new rituals should emerge?  Finally, Uber has to redefine the core values for which it stands.  The company is known for its 14 cultural values.  The company has to take a hard look at those values.  Are they the right values?  Have the current values enabled some unintended, but dangerous, behaviors and attitudes?   The company needs to think hard about the message that each value sends... and recognize the ways in which it has enabled bad behavior on the part of many managers. 

Saturday, February 25, 2017

Disturbing Finding on Happiness

Knowledge@Wharton reports on the intriguing, but perhaps rather disturbing, findings of Professor Maurice Schweitzer's latest research.   Schweitzer has studied how people perceive others who appear to be very happy people.  He explains the conclusions from the research:

The pursuit of happiness is deeply embedded in our national thinking. Yet sometimes people who are very happy are exactly the kinds of people who are exploited. That’s what we document in our research, where we look at people who are very happy. If they seem more happy than baseline happiness — people who are very happy, always chipper, always upbeat — they strike us as naive. We found that link consistently. One of the most robust findings in our research is that people see very happy individuals as naive, and in our last couple of studies we found that people are more likely to exploit those individuals.

I don't think the implication is that we should be less happy, or stop presenting ourselves as satisfied and content with our lives, jobs, etc.   However, perhaps we need to open our eyes a bit, and recognize that others may perceive us as naive at times.  Unfortunately, some people may try to take advantage of perceived naivete.  

Thursday, February 23, 2017

Why Do We Make Recommendations to Others?

Why do we make recommendations to others?  Are we simply being altruistic?  Are we trying to help our friends, perhaps by sharing information and knowledge that we have acquired so that others can avoid the mistakes we have made?  New research suggests that another key motivation may drive our desire to recommend products and services to others.  Scholars Andrea Bonezzi, Alessandro Peluso, Matteo Deangelis, and Derek Rucker have conducted a series of experimental studies that challenge our assumptions about the motivations behind recommendations.  

In their studies, they examined how people chose the amount and type of automobile insurance to purchase.  This task often proves challenging and difficult for many consumers.  The scholars found that individuals are more likely to offer advice to others if they feel insecure about the decision themselves.  In short, people have a need for control.  When they feel a loss of control or experience a sense of insecurity, they try to regain control by offering recommendations to others.  It bolsters their view of themselves after the task itself has threatened their self-perceptions.   Of course, these findings do not mean that the recommendations provided by these individuals are worthless or counterproductive.  It does, however, suggest that companies should understand what truly drives people's behavior when trying to encourage recommendations and word-of-mouth advertising of their products and services.  It also might mean that we should take recommendations with a grain of salt when the purchasing decision is highly complicated and stressful.  

Wednesday, February 22, 2017

Algorithm Aversion: How Can We Overcome It?

Algorithms can help us make better decisions in a variety of situations.  However, human beings tend to have an aversion to using algorithms.  They trust their gut more than the computer, even though the algorithms may lead to better decisions. Knowledge@Wharton reports on a stream of fascinating research by Cade Massey, Joseph Simmons, and Berkeley J. Dietvorst.  They found that you can persuade people to use algorithms if you give them a choice as to whether to use the algorithm or not.  In other words, don't force them to use it; make them feel a sense of control.  That will help convince them to choose the algorithm.  However, many people stop using the algorithm after some period of time, because they become frustrated with the mistakes that the computer makes.  Of course, the computer might make fewer mistakes than a human using intuition, but people don't recognize that possibility. Instead, they fixate on the mistakes and lose faith in the algorithm. Simmons points out, "People want algorithms to be perfect and expect them to be perfect, even though what we really want is for them to simply be a little better than the humans."

The scholars also found that you could persuade people to use the algorithms if you gave them an ability to adjust the computer's recommendation slightly.   Of course, the algorithm's predictions and recommendations become less accurate when humans intervene in this manner.  However, the researchers found that you only have to give people an ability to adjust the algorithm slightly to enhance adoption.   Providing them an ability to adjust more substantially does not increase adoption more than offering a slight adjustment possibility.  Thus, you might be willing to tolerate a bit of degradation in the algorithm's accuracy simply because giving people some sense of control increases adoption of the computer-assisted decision-making system.  For more on this research, see the video below in which Massey and Simmons are interviewed about the research.  



Tuesday, February 21, 2017

Should I Tell That Joke at Work?

The Wall Street Journal has a nice summary of recent research on humor in the workplace written by scholars Alison Wood Brooks and T. Bradford Bitterly.   The scholars point out some of the positive effects of humor in the workplace.  For instance, they cite one study by Nale Lehmann-Willenbrock.  Here is the summary of those findings:

Research led by Nale Lehmann-Willenbrock at VU University Amsterdam studied how patterns of humor in conversation—such as a joke followed by another joke or a joke followed by laughter—predicted other types of communication, as well as team performance, more broadly. The researchers found that teams that tell more jokes and laugh together also made more supportive and constructive statements to each other, things like “that’s a great idea” or “we could solve this problem by doing X.” That, in turn, led them to perform better on a number of measures, such as hitting goals and improving efficiency. The researchers surmised that humor could improve team interaction by triggering positive forms of communication.

Of course, one always worries about the inappropriate use of humor in the workplace. Will you offend someone?  Could you cross the line and face disciplinary action for something you say?  Could it even get you fired?   The problem, according to researchers, is that we are not very good predictors of what others will find to be funny.  In fact, we aren't good predictors even when we know the person quite well.  Here's one study that examined this situation:

In a recent study led by Michael Yeomans at Harvard University, pairs of museum-goers were asked to predict what their companion would find funny. Many of the pairs included married couples, or people who had known each other for years. Even with the close connection between people, Dr. Yeomans found that they weren’t very good at predicting what their partner would find funny. A statistical prediction model turned out to be much better at rating how funny their companion would rate a joke.

Friday, February 17, 2017

Why People Quit

Why do people quit their jobs?  Fast Company reported this week on a new analysis conducted by Glassdoor.   The firm studied approximately 5,000 workers who switched jobs over the past decade.   They found that three most important reasons for quitting are:
  • Company culture
  • Employee salary
  • Getting stuck in the same job for long periods of time
The firm discovered that, "On average, we find that a 10% higher base pay is associated with a 1.5% higher chance that a worker will stay at the company for their next role."  In addition, the probability of quitting rises by 1% for every 10 extra months someone stays in the same role at a company. 

What didn't matter as much with regard to quitting?  Interestingly, "they found that while work-life balance, liking their senior leadership, and benefits may matter for overall employee satisfaction, they don’t impact turnover."

Tuesday, February 14, 2017

Marketing Your Products as Designed by Users: Benefit or Hindrance?

The Boston Globe reported this weekend on the fascinating new research of Vienna University Professor Martin Schreier.   He studied the marketing of crowdsourced products.  Schreier found that marketing an item as user-designed tended to increase sales more than marketing a product as created by a firm's own designers.  Why this positive effect?  Schreier discovered that, "People believe their peers understand their needs better, and therefore, come up with better solutions."   Moroever, Schreier found that people tend to react more positively if informed that the user-designers had something in common with them.   For instance, female consumers tended to prefer user-designers who were women similar to them.  

Is there a potential downside to marketing a product as "user-designed"?  Schreier found that the effect does not appear to be positive for luxury items or high tech goods.  Why?  For technologically sophisticated products, the consumer trusts experts with high levels of knowledge and expertise more so than fellow users.  As for luxury items, the explanation is quite different.  In those cases, consumers "want to set themselves apart."  Thus, they tend not to prefer something sourced from the crowd.