As Ray Dalio, founder of the largest hedge fund in the world, writes in his book of management principles:

“Even the most benevolent leaders are prone to becoming more autocratic, if for no other reason than because managing a lot of people and having limited time to do it requires them to make numerous difficult choices quickly, and they sometimes lose patience with arguments and issue commands instead.”¹

Even if you consider yourself benevolent (who doesn’t?), there is an ever-present impulse to be more autocratic—an impulse exacerbated by the situation. As a leader, if you want to encourage speaking up to improve decision making and team member satisfaction, you need to be more mindful of overcoming autocratic impulses and openly soliciting ideas from others. To openly solicit ideas from others is to be more democratic.

The distinction between autocratic and democratic leadership styles has a long history in applied psychology and was the focus of one of the “founding fathers” of the field, Kurt Lewin, who studied these leadership styles in the late 1930s. Understanding the consequences of these styles was of great personal and practical importance to Lewin. He was born in Poland and lived in Germany through most of his life, serving in the German army in World War I.

As a Jewish individual, Lewin fortuitously left Germany in the early 1930s and would work the remainder of his career in the U.S. As a scholar, he wanted to shed scientific light on the political turmoil that was happening in the world, such as the rise of Nazism in Germany. Thus, studying the effects of democratic and autocratic leadership was of utmost importance and an area of study that could use more precise evidence. As he asks in a 1939 publication, “Is not democratic group life more pleasant, but authoritarianism more efficient? These are the sorts of questions to which ‘opinionated’ answers are many and varied today, and to which scientific answers, are, on that account, all the more necessary.”²

To develop a scientific answer, Lewin and colleagues experimentally created three “social climates”—authoritarian, democratic, and laissez-faire. To create these “social climates,” an adult would act in accordance with one of these styles while leading a group of 10-year-old boys. To be authoritarian, the leader would determine all the policies of the group and dictate the work task. To be democratic, the leader would encourage group discussion about policies and facilitate group decision making. Laissez-faire leadership allowed complete freedom for the group with little or no participation from the leader. Accordingly, a laissez-faire style of leadership was deemed so ineffective for group functioning that it was abandoned in future studies as a leadership style.³

In Lewin’s studies, they found that when leaders were present, performance was roughly equal between the autocratic and democratic groups, but when the leaders left, performance declined for those in the autocratic group but not for the democratic group.⁴ They also found, as one might guess, more submission of group members to authoritarian leaders and a greater need for instructions and directions.

They also observed more hostility in the autocratic compared to the democratic group, most notably when the leader was absent. Among many factors, Lewin and colleagues surmised this was a result of the “tension” created in the group (what we might now call “stress”), and that this tension needed an outlet which was through hostility.⁵ While Lewin and colleagues were interested in how leadership styles promoted aggression, one might conclude that a more hostile environment with more submission is not a climate where individuals will freely speak their minds.

Although Lewin’s studies were with children, (with obvious drawbacks to interpreting the results in the workplace), the conceptual distinction between autocratic and democratic leaders was a major advance that helped leadership scholars in future decades. More recently, in a meta-analysis of 23 studies on the impact of leadership styles on productivity, democratic leadership was found to be more effective (compared to autocratic leadership) on “moderately or highly complex tasks.”⁶ In these tasks, you need the wisdom of the group to be fully used in comparison to the dictates of a leader.

In summarizing the field, John Gastil defined democratic leadership as “giving group members responsibility, improving the general abilities and leadership skills of other group members, and assisting the group in its decision-making process.”⁷ The below table offers an outline of the key features of autocratic and democratic leadership in their “pure forms.”

While autocratic leadership can be viewed more charitably–as occasionally being directive and making decisions with little input from others–it can be portrayed with stronger moral overtones. This includes being demeaning and abusive to subordinates and demanding loyalty and submissiveness.⁸ This, of course, can be a dangerous form of autocratic leadership, but as Dalio notes, a central point is overcoming autocratic impulses, which even the most benevolent of us might have given the circumstances. Thus, I am stressing how we might overcome being a “good-natured” autocrat, who, for whatever reason, is slipping towards being too directive and is making decisions with little or no deliberation from others.

While being autocratic or democratic is described in its pure form, we can, of course, switch styles given the dictates of the situation. When is being autocratic functional? When is being democratic functional? By and large, democratic leadership has many advantages. However, in some instances, the situation may warrant autocratic impulses, especially if there is time pressure. In addition, a leader’s judgment may be well-grounded given his or her experience in a domain, and thus his or her expertise and judgment is better than others.

Although in some situations this may be true, in others you need to harness all the knowledge and expertise of a diverse group to make the best decision possible. This requires, of course, a realization that you don’t know everything. A certain degree of intellectual humility is needed to realize that in most situations, but not all, the collective or majority will make a better decision than a single individual. This humility may be hard to come by but can often result from past failures where we realize our limitations.

While we can be both autocratic and democratic given a situation, we are also likely to be predisposed to one style over another. In an overview of the factors increasing the likelihood of being autocratic, Peter Harms of the University of Alabama and colleagues outline several factors. These include, among others, being less agreeable, having a high need for power, being less emotionally stable (e.g. suspicious), and being narcissistic. These are suggestive traits that impact one’s likelihood of being autocratic. One’s predisposition to be autocratic would be a very complex mix of someone’s inherited predispositions, life history, and situational conditions.

Thus, to improve performance on your team and encourage speaking up, ask yourself: Am I more autocratic or democratic? Only indulge your autocratic impulses at strategic moments. Avoid laissez-faire leadership at all costs and be mindful of being more democratic in your leadership style.

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References:

1. (Dalio, 2017, p. 532).

2. (Lewin, Lippitt, & White, 1939, p. 271).

3. (Gastil, 1994a).

4. (Harms et al., 2018; White & Lippitt, 1960).

5. (Lewin, et al. 1939).

6. (Gastil, 1994a, p. 402).

7. (Gastil, 1994a, p. 403).

8. (Harms et al., 2018).

Dalio, R. (2017). Principles: Life and work. Simon & Schuster.

Gastil, J. (1994a). A meta-analytic review of the productivity and satisfaction of democratic and autocratic leadership. Small Group Research, 25(3), 384-410.

Gastil, J. (1994b). A definition and illustration of democratic leadership. Human Relations, 47(8), 953-975.

Harms, P. D., Wood, D., Landay, K., Lester, P. B., & Vogelgesang Lester, G. (2018). Autocratic leaders and authoritarian followers revisited: A review and agenda for the future. Leadership Quarterly, 29, 105-122.

Lewin, K., Lippitt, R., & White, R. K. (1939). Patterns of aggressive behavior in experimentally created “social climates.” Journal of Social Psychology, 10, 271-299.

White, R. K. & Lippitt, R. (1960). Autocracy and democracy: An experimental inquiry. Harper Brothers.

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As the Dutch philosopher Erasmus stated: “Live as if you were to die tomorrow, study as if you were to live forever.”

I first came across this quote while listening to a podcast, and it stuck with me, in particular how it reframes time to overcome a hesitancy we might have to learn a new topic. We face a constant dilemma of how to spend our time and learning can lack a sense of immediacy given our daily demands. It can also seem like a luxury (think of going to graduate school or taking time to read a book related to your field). But, if you expand your time horizons, as Erasmus urges us to do, it doesn’t seem like such a tradeoff. Ask yourself: What would you learn now, if you were going to live forever?

Asking the question presumes time is unlimited and removes it from the equation. Yet, Erasmus first states “live as if you were to die tomorrow.” Putting us squarely back in the dilemma we just escaped. Time is extremely limited, then time is unlimited. It may be that his sequencing leaves us with “live forever,” or that we are already familiar with the dictum to “seize the day,” but the quote seems more like a license to learn and explore as if time were unlimited. At least that is the meaning that has stuck with me.

Along with Erasmus’ dictum to consider time unlimited, I’ve noticed several companies have similar maxims that are meant to expand their time horizons.

For example, Jeff Bezos insists employees at Amazon act like it is “Day 1.” He doesn’t want to be a “Day 2 company.” In his words, “Day 2 is stasis. Followed by irrelevance. Followed by excruciating, painful decline. Followed by death. And that is why it is always Day 1.” Being a Day 1 company means you are just at the beginning. It invites exploration and a beginner’s mind. It helps avoid stasis because you know you have a long way to go. And it promotes long-term thinking about what the future might hold.

Likewise, at Facebook one of their maxims (and one posted on many of their walls) is that “this journey is 1% finished.” If the journey is only 1 percent finished, you need a lot more knowledge. Spending time to read, explore industry trends, or talk to customers, are all going to help you for that long journey. Of course, I’m taking a charitable interpretation of the slogan. Cynically, one might interpret it as advocating for world domination or trying to inflate the growth prospects of their stock, but if you had a similar slogan for yourself or your organization, might it help spur exploration?

Considering yourself at “Day 1” or that your “journey is just 1 percent finished” can help weather the dip in immediate performance that might occur if we invest more time in learning and development. Individually, think of heading back to graduate school. If performance is measured by your income, if you leave your job, your “performance” drops to zero, but it is done with the intent of raising your performance long-term.

Similarly in organizations, Elizabeth Keating and colleagues at MIT observed how immediate performance often suffered from an improvement program. They call this the “improvement paradox.” In a manufacturing context, they state: “It takes time for improvement effort to bear fruit. Therefore, the first effect of an increase in improvement effort is a reduction in the time employees can devote to throughput. The short run effect of improvement effort is a decline in output, exactly the opposite of the goal” (Italics in original, p. 121).

They describe this “worse-before-better” pattern with a Du Pont Preventative Maintenance Program where there was a decline in performance before a long-term improvement. This dip in performance isn’t preordained, of course, and is most likely pronounced when there is a tight coupling between time on task and our outputs. Nevertheless, in a world of constantly demonstrating our worth by visible outputs, learning can seem unproductive in the short-term, by comparison.

Thus, to combat a hesitancy to explore and learn, regularly ask yourself what you’ll learn now if you’ll live forever. In doing so, you’ll expand your time horizons to promote learning and growth for the long-term.

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References:

Bezos, J. (2017, April 17). 2016 letter to shareholders. https://www.aboutamazon.com/news/company-news/2016-letter-to-shareholders

Erasmus, D. (1978). The antibarbarians. (translated and annotated by M. M. Phillips). In C. R. Thompson (ed.), Collected works of Erasmus (vol. 23-24). University of Toronto Press. (Originally published 1520), p. 76.

Keating, E., Oliva, R., Repenning, N., Rockart, S., & Sterman, J. (1999). Overcoming the improvement paradox. European Journal of Management, 17(2), 120-134.

Facebook, Inc. (2012). SEC, Form S-1. https://www.sec.gov/Archives/edgar/data/1326801/000119312512034517/d287954ds1.htm, p. 94

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One of my biggest pet peeves is being in meetings or venues where everyone is acting like they have all the answers—whether because they believe they do or they are performing like they do. This is particularly true, from my experience, in consulting contexts, where there is a high performative aspect to presenting and speaking. In Organizational Learning and Performance, I draw upon research about having a performance-prove orientation, where you’re mostly concerned about appearing as if you have all the answers. This is in contrast to a learning orientation where you are willing to ask questions and probe what you know and don’t know.

To illustrate a performance-prove orientation, I often use a quote from Steve Levitt, of Freakonomics fame:

“What I’ve found in business is that almost no one will ever admit to not knowing the answer to a question. So even if they absolutely have no idea what the answer is, if it’s within their realm of expertise, faking is just an important part. I really have come to believe teaching MBAs that one of the most important things you learn as an MBA is how to pretend you know the answer to any question even though you have absolutely no idea what you’re talking about. And I’ve found it’s really one of the most destructive factors in business—is that everyone masquerades like they know the answer and no one will ever admit they don’t know the answer, and it makes it almost impossible to learn.”

BUT, to my surprise, I recently came across research that more precisely diagnoses the issue: “pseudo-profound bullshit.”

I hadn’t been aware that B.S. had a respectable line of research for all these years.

As Pennycook and colleagues (2015) describe in the opening to their article in Judgment and Decision Making, “the philosopher Frankfurt (2005) defines bullshit as something that is designed to impress but that was constructed absent direct concern for the truth” (p. 549).

The authors continue with several statements, such as:

• “Hidden meaning transforms unparalleled abstract beauty.”

As the authors say, “Although this statement may seem to convey some sort of potentially profound meaning, it is merely a collection of buzzwords put together randomly in a sentence that retains syntactic structure” (p. 549).

In contrast to Frankfurt, they argue that “pseudo-profound bullshit betrays a concern for verisimilitude or truthiness.” And their prefix of profound “reveals an important defining characteristic of bullshit (in general): that it attempts to impress rather than to inform; to be engaging rather than instructive” (p. 550).

To research the topic, Pennycook and colleagues created a B.S. Receptivity Scale which lists ten meaningless statements such as:

• “The future explains irrational facts.”
• “Consciousness consists of frequencies of quantum energy. ‘Quantum’ means an unveiling of the unrestricted.”

Participants rated how profound these statements were on a scale of 1-5. They found that participants who scored higher on the Cognitive Reflection Test (a measure of one’s willingness to question one’s intuitive responses), were more likely to see B.S. for what it is.

In more recent research, a Bullshitting Frequency Scale was developed to measure the act of bullshitting rather than your receptivity to it (Littrell, Risko, & Fugelsang, 2021). The researchers, citing the philosopher Gerald Cohen (2013), describe how “the aim of some bullshitters is to impress using discourse constructed with ‘unclarifiable unclarity’; that is, relying on vacuous, confusing buzzwords which obscure that the statements, while superficially impressive, contain no discernible meaning” (p. 249). In their research, Littrell et al. (2021) found that bullshitting frequency is negatively correlated with honesty, sincerity, and self-worth.

Unfortunately, B.S. is all too common in organizations where a desire to impress can lead us to speak in ways that obscure a deeper understanding of an issue. This combines with an understandable desire among listeners to not ask questions for the risk of appearing to be the only one that doesn’t get it. The result is one of the greatest barriers to learning in organizations.

There aren’t simple answers to counteract B.S., but you can start by asking questions to help understand issues (you might uncover others have similar questions). If you are in a position to set norms for your team or organization, you can highlight behaviors such a being candid or intellectually humble (being willing to admit what you know and don’t know). Or you can more aggressively aim to “forgo B.S.” in a more forthright attempt to learn and address issues you are facing.

For the moment, at least, take heart that there is a group of dedicated researchers shedding light on the opaque phenomenon of bullshit.

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References:

Cohen, G. A. (2013). Complete bullshit. In M. Otsuka (Ed.), Finding oneself in the other (pp. 94–114). Princeton University Press.

Frankfurt, H. G. (2005). On bullshit. Princeton University Press.

Pennycook, G., Cheyne, J. A., Barr, N., Koehler, D. J., & Fugelsang, J. A. (2015). On the reception and detection of pseudo-profound bullshit. Judgment and Decision Making, 10(6), 549-563.

Levitt, S. (2012, January 5). Why is “I don’t know” so hard to say? Freakonomics Radio [Audio Podcast] Retrieved from http://freakonomics.com

Littrell, S., Risko, E. F., & Fugelsang, J. A. (2021). The bullshitting frequency scale: Development and psychometric properties. British Journal of Social Psychology, 60, 248-270.

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As is human nature, if we know the preferences of a group leader, we’ll tend to conform to that preference. If you’re a group leader or care about making better decisions, that’s a problem. However, one study found a way around this, which was to promote the goal of “getting at the truth” (versus “getting along”) and to promote individual accountability for decision-quality (rather than accountability diffused throughout a group) (Quinn & Schlenker, 2002).

For example, imagine yourself in a situation where you are a middle manager. Perhaps a senior executive has indicated his or her preferred course of action. You are aware of his or her preference and the desire to conform will be strong. What can counteract this pressure? The social norm to get an accurate picture of reality, and if you have to publicly explain your position. As you imagine this future meeting, you don’t want to say you came to your viewpoint because “the senior executive said so.” Instead, if you have to individually explain and justify your viewpoint, and there is a social norm to “get at the truth,” you have a better chance to overcome the pervasive conformity pressure in most organizations.

In the research study that tested this hypothesis, the researchers had individuals primed for either “getting along” or “getting at the truth” by reading different scenarios (Quinn & Schlenker, 2002). How do you prime individuals for “getting at the truth” or “getting along?” They would read a collection of scenarios that either described a search for truth or when your behavior needed to be tailored to the situation (Chen, Schechter, & Chaiken, 1996).

For example, in the “getting at the truth” scenario, you would read about a reporter trying to get the facts of a story. For “getting along,” participants read a scenario about being on a blind date set up by a close friend but quickly realizing there was little attraction. After reading each of the scenarios, participants were asked what actions they would take in that scenario. For example, if they read the priming scenario about being a reporter, an individual might suggest going to the library to look up facts or speaking with an expert.

After reading the priming scenarios, participants then read a case study and had to choose between two different courses of action. In this case, how to allocate a marketing budget between an American and European lager. If participants had been primed with the “getting at the truth” scenario, they were more likely to choose the option that provided an “objectively better return on marketing investment.” However, if they were primed with the “getting along” scenario, they were more influenced by the choice of their discussion partner, regardless of whether it led to an objectively better return on marketing investment.

In addition, the positive effect of being primed to “get at the truth” was most pronounced when participants had to “explain and justify” their decision (i.e. being held accountable). In the case of the experiment, it was having your decision written on a “decision sheet” and shared with a partner. Accountability has many connotations, but accountability can be having to publicly explain your reasoning for a decision, perhaps in a meeting (Lerner & Tetlock, 1999).

As the researchers conclude:

“Accountability to an audience whose preferences are known does not invariably doom people to subpar decisions that are biased by conformity pressures. If people are focused on the goal of making accurate decisions when they are accountable, the quality of their decision making increases as compared to when people are not accountable or to when people have the goal of getting along” (Quinn & Schlenker, 2002, p. 481-482).

These results are a hopeful antidote to the conformity pressures faced in most organizations (and found in most social psychology experiments).

So how do you foster a motivation to “get at the truth” in an organization? At Bridgewater Associates, one of the world’s largest hedge funds, there is a constant refrain and insistence that employees think for themselves and ask “Is it true?” (Dalio, 2017). Likewise, when I spoke with a Chief Investment Officer at a different hedge fund, he set up a monthly meeting with his direct report who would have to answer the question, “What is something you don’t think I want to hear, but you think is true?” Over time, this helped promote the notion of “getting at the truth” over “getting along,” and there was accountability because the CIO’s direct report knew that at each monthly meeting, he’d have to state his viewpoint.

Thus, while conformity is ever-present, if we set up the norm for “getting at the truth,” and ask individuals to explain and justify their viewpoints, we can increase viewpoint diversity in the pursuit of making better decisions.

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References:

Chen, S., Schechter, D., & Chaiken, S. (1996). Getting at the truth or getting along: Accuracy- versus impression-motivated heuristic and systematic processing. Journal of Personality and Social Psychology, 71(2), 262-275.

Dalio, R. (2017). Principles: Life and work. Simon & Schuster.

Lerner, J. S., & Tetlock, P. E. (1999). Accounting for the effects of accountability. Psychological Bulletin, 125(2), 255-275.

Quinn, A., & Schlenker, B. R. (2002). Can accountability produce independence? Goals as determinants of the impact of accountability on conformity. Personality and Social Psychology Bulletin, 28(4), 472-483.

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To be following a slow hunch is to be at the fuzzy edge of our current knowledge. It is to be actively putting vague intuitions into words and building a conceptual map at the edges of understanding. These slow hunches help explain the experience of being at the edge of scientific discovery, as explained by the writer Steven Johnson in his book Where Good Ideas Come From. Johnson compares one-off ideas with innovative ideas that incubate and develop over a longer period of time. As he states:

“Most hunches that turn into important innovations unfold over much longer time frames. They start with a vague, hard-to-describe sense that there’s an interesting solution to a problem that hasn’t yet been proposed, and they linger in the shadows of the mind, sometimes for decades, assembling new connections and gaining strength….But that long incubation period is also their strength, because true insights require you to think something that no one has thought before in quite the same way” (Johnson, 2010 p. 77).

Scientific discovery, by and large, illustrates how a “hunch” (or more formally conceived as a “hypothesis”) guides the pursuit of understanding. Over time, hunches are tested and either gather support or are discarded. In this way there is a certain trial and error to our thinking, where the strongest ideas survive, both in our own minds and in conversation with others (see Weick, 1989).

In the field of economics, the process of following “slow hunches” is what Richard Thaler describes as he and colleagues would eventually revolutionize the field of economics to create the field of behavioral economics. Behavioral economics brings insights from psychology into standard economic questions such as savings and investment decisions. It is work that eventually won Richard Thaler the Nobel prize in economics, but it all started with noticing “anomalies” and following slow hunches. As Thaler describes:

“A slow hunch is not one of those ‘aha’ insights when everything becomes clear. Instead, it is more of a vague impression that there is something interesting going on, and an intuition that there could be something important lurking not far away. The problem with a slow hunch is you have no way to know whether it will lead to a dead end. I felt like I had arrived on the shores of a new world with no map, no idea where I should be looking, and no idea whether I would find anything of value” (Thaler, 2015, p. 40).

Thaler was noticing cases where we fall short of the rational model of behavior. The rational model of behavior often describes our behavior, but not always. We sometimes exhibit self-control, but in many situations we do not. We often plan for the future, but often fall short. The rational model of behavior sets a standard of what we should do, and this model was largely at the heart of economics. Thaler and colleagues, however, began adding descriptive realism into how we behave. For example, one of the signature programs developed from behavioral economics is Save More Tomorrow. Save More Tomorrow starts with the insight that as our income increases in the future, rather than save it, we’ll likely spend it. But, if you ask anyone, they will tell you they should save more in the future. Save More Tomorrow is an automatic plan to increase the percentage of savings from your paycheck when you receive a pay increase in the future. It makes sense that we will fall short of our intentions for savings, but this kind of descriptive realism was largely absent from economics.

This doesn’t mean, of course, that any slow hunch will lead us to revolutionize our respective fields, but we’d never develop innovative ideas if we always ignored a vague notion that our current understanding is incomplete—if we never followed our curiosity.

But how do “slow hunches” and incubation work exactly? The process of incubation seems to happen in three ways (Sio & Ormrod, 2009): First, incubation can help us access greater knowledge networks (both externally and within our own minds) through spreading activation. In this way, over time, new knowledge networks are activated and provide new avenues to approach a problem. Second, incubation can help with selective forgetting of a dominant approach. We can get anchored on initial solutions and be unable to flexibly see the problem in different ways. Incubation can foster selective forgetting which allows a more appropriate solution to surface. Finally, incubation can lead to a restructuring of the problem in more productive ways. Restructuring can be a fundamental shift in how you represent the problem, allowing you to see it in a new light (e.g. the nine-dot problem). In a meta-analysis of 117 studies that examined incubation, support was found for all three aspects of incubation: spreading activation, selective forgetting, and restructuring (Sio & Ormerod, 2009). The positive effects for incubation were found to be strongest for creative problem solving tasks, especially when there are multiple solutions options.

But how do we distinguish a productive slow hunch from a “dead end?” As Thaler mentions, “The problem with a slow hunch is you have no way to know whether it will lead to a dead end.” I often see a preoccupation with wanting to avoid “dead ends” or “rabbit holes.” But, dead ends and “rabbit holes” are only revealed in retrospect, after we’ve spent some time pursuing a line of inquiry. If we are overly concerned with predicting, in advance, if a line of inquiry will lead to a “dead end” we run the risk of not following productive hunches that can lead to innovative ideas. Of course, we face a never-ending dilemma of opportunity cost with our time, but if we’re aiming for innovative ideas, then we need to be more willing to follow slow hunches.

So, if you are aiming for innovative ideas in your work, be more willing to follow slow hunches. An innovative solution may emerge slowly over time and will be well worth your effort.

References:

Johnson, S. (2010). Where good ideas come from: The natural history of innovation. New York: Riverhead.

Thaler, R. H. (2015). Misbehaving: The history of behavioral economics. New York: Norton.

Sio, U. N., Ormerod, T. C. (2009). Does incubation enhance problem solving? A meta-analytic review. Psychological Bulletin, 135, 94–120.

Weick, K. E. (1989). Theory construction as disciplined imagination. Academy of Management Review, 14(4), 516-531.

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