The most important caveat is that lab studies find much larger effect sizes than in the field, to the extent that the average field effect for the ingratiating tactics is negative. This is probably due to the fact that lab experiments can be better controlled.
The first sentence seems really important and I'm wondering how to interpret the second. One hypothesis that is consistent with the first sentence is that studies show that in lab environments where arbitrary people are thrown into very short term interactions ingratiation works quite well... but that in the iterated environment of real long term working relationships it is detected and causes more problems than it helps with. Call this the hypothesis that "bullshit only works at first".
The second sentence argues against this hypothesis, but I'm not sure how strongly the second sentence is supported. Is it on-the-spot speculation? Is it the considered opinion of most experts in the field?
If the hypothesis that "bullshit only works at first" is the correct one it suggests that ingratiation should be avoided, or at the very least it suggests that ingratiation should be avoided in relationships that are dissimilar from random short term laboratory interactions. Am I off track here? Is the hypothesis (and its implied behavioral upshot) clearly ruled out by the research you explored and are summarizing? Clarification would be useful :-)
This is a good point.
If you look at tables 8 and 9 from Gordon you can see that once you control for "transparency" (i.e. how obvious the bullshit is) the setting is no longer a significant predictor. So I'm not sure I agree that it's the "iterated" part of real-world interactions which cause this result (it seems likely that you can more easily tell if someone's changing their behavior to follow an experiment if they are a close coworker than a random student, for example), but I think your point about transparency being important is relevant.
I tend to agree.
Some minor questions improvements to rough corners:
In the first table the predictors "Education Level" and "Cognitive Ability" are not explained nor referred to.
In the second table the tactic "Rendering Favors" has no description and I'm not clear what that might be. I'd like to see an example.
dito for the third table. And if it's a simple "see above".
"The Dilbert Effect" used as title but not really related to in text. I think I know what is meant but it's really not clear.
Also I'd like to see a quote about the lab experiments to get a feel of type of politics gamed.
From Ng et al.:
Political knowledge and skills included the following two measures: political knowledge (e.g., Chao, O’Leary-Kelly, Wolf, Klein, & Gardner, 1994; Seibert, Kraimer, & Crant, 2001) and supervisor-focused political tactics (e.g., Wayne, Liden, Graf, & Ferris, 1997)
Taking the Chao paper as an example, they look at things like "do you know who the most influential people in your organization are?" and "do you know what to do to get the most desirable work assignments?"
The Wayne paper looked at how frequently people used the tactics I listed in the article.
These findings might also be useful for choosing between high-variance and low-variance careers, insofar as you are able to predict how much better at each of these skills you are than average.
For example, engineering is a field where most people earn a decent wage and some people earn a very decent (but not obscene) wage. I think the average salary of an engineering graduate is about $58,000, with the vast majority of that made up by people working in the $30,000-$50,000 band with a couple of hotshots pulling down six-digit salaries and almost nobody grinding out a subsistence wage. By contrast writing a book is a field where one or two people become megastar billionaires like J K Rowling or John Grisham and everybody else earns practically nothing. Pretty amazingly (I think it’s amazing) the Bureau of Labour Statistics reckons the average wage for a writer is almost exactly the same as the average wage of an engineer ($56,000), but it seems likely to me the median salary is much lower than in engineering (maybe something like $15,000-$25,000) with the mean heavily skewed by the handful of super-rich authors.
What this suggests is that you can – on a probabilistic basis – determine whether you are likely to end up at the top or bottom of the income distribution of your chosen profession. If you know your political knowledge and skills are weak, it would be a good idea to pick engineering over writing (assuming you are equally good at both) because you are more likely to end up earning $30,000 than $100,000. If you are excellent at office politics you are much more likely to form the sort of connections that give you a bestseller, and so writing might offer you the highest expected earnings even though the average salary in both professions is (nearly) identical.
This is complicated by the fact that ‘political knowledge and skills’ are not consistent between careers (the most insensitive politician is likely to be far more manipulative than the smoothest political operator in database administration), but I think it is probably possible to allow for this and still have more information about career choice than you did before.
Pretty amazingly (I think it’s amazing) the Bureau of Labour Statistics reckons the average wage for a writer is almost exactly the same as the average wage of an engineer ($56,000), but it seems likely to me the median salary is much lower than in engineering (maybe something like $15,000-$25,000) with the mean heavily skewed by the handful of super-rich authors.
Are you sure about that? http://www.bls.gov/ooh/media-and-communication/writers-and-authors.htm reports only the median not the mean (good for them), at $55k, and in a tab gives an idea of the tails:
The lowest 10 percent earned less than $27,770, and the top 10 percent earned more than $117,860.
Most people who write for a living are not novelists, they are marketers, technical documentation authors...
Ah yes, this makes a lot of sense and explains my earlier confusion; although it may still be true that there is a high variance in income between novelists, not all writers are novelists (for that matter, I suppose not all novelists are writers, at least as far as the BLS will bin them). I think that indicates my illustrative example is flawed, although I hope the wider point still stands.
Writers != Novelists
Per the BLS site, "Writers and authors develop written content for advertisements, books, magazines, movie and television scripts, songs, and online publications....Writers and authors work in an office, at home, or wherever else they have access to a computer. Most work full time. However, self-employed and freelance writers usually work part time or have variable schedules. About two-thirds were self-employed in 2012."
In other words, a lot of writers are neither struggling along at $15,000-$25,000 nor making John Grisham levels of money. Some even collect salaries and benefits. I made a pretty good living as a fulltime writer for about 12 years, during which time I wrote essentially no fiction.
Hi elharo,
Your criticism is absolutely correct; not all writers are novelist so even if novelists show the income variation I assert, that wouldn’t show up on the BLS statistics. I think that shows that my illustrative example is flawed, but I hope it doesn’t undermine the main conclusion too much.
This is complicated by the fact that ‘political knowledge and skills’ are not consistent between careers
Also (and I suspect even more importantly) by the fact that the impact of political knowledge and skills may be different in different careers. Not only because some careers simply have more room for variation, but also because some careers have more scope for effective evaluation on non-political factors.
I suspect that both engineering and novel-writing have lower impact-of-politics than average, but even though novel-writing is higher-variance I suspect that there's more scope to turn political skill into career success in engineering than in novel-writing.
the most insensitive politician is likely to be far more manipulative than the smoothest political operator in database administration
I think this is a slightly misleading way of putting it, for a couple of reasons. I would expect the average political skill level among full-time politicians to be pretty high, but mostly because politics is almost as high-variance a career path as writing or music: for every full-time legislator or lobbyist, there are dozens, maybe hundreds, of low-level organizers, party functionaries, and so forth, all the way down to campaign workers and school board members. It's just that most of the lower-level people in politics are doing it as a hobby or sideline, and getting paid part-time if at all, just like most musicians have day jobs.
Also, I think you're probably underestimating the amount of political skill that can be applied to technical jobs -- though many people with more political than technical savvy drift into management at some point.
When I saw the title, the first things I thought of were Ramit Sethi's videos on negotiation and the CFAR income negotiation workshop. This seems more focused on promotions than raises, but are you aware of any meta-studies that examine specifically the effect of different types of negotiation strategies?
I'm sorry if this post is a little bit off-topic or maybe-relevant.
I'm 20 years old and wondering what I can do to make the most money and fun. Maybe you're going to say "You're not planning to give, so why should I help you?" and I'll respond with:
Also, another question, is this research adjusted for variables? Does it apply no matter where you live? Does it apply no matter what your job?
Last question: This post assumes you have the job. Is there anything on job interviews?
I hope I didn't reply to a dead-end.
Summary: This article is intended for those who are "earning to give" (i.e. maximize income so that it can be donated to charity). It is basically an annotated bibliography of a few recent meta-analyses of predictors of income.
Key Results
The degree to which management “sponsors” your career development is an important predictor of your salary, as is how skilled you are politically.
Despite the stereotype of a silver-tongued salesman preying on people’s biases, rational appeals are generally the best tactic.
After rationality, the best tactics are types of ingratiation, including flattery and acting modest.
Ng et al. performed a metastudy of over 200 individual studies of objective and subjective career success. Here are the variables they found best correlated with salary:
|
Predictor |
Correlation |
|
Political Knowledge & Skills |
0.29 |
|
Education Level |
0.29 |
|
Cognitive Ability (as measured by standardized tests) |
0.27 |
|
Age |
0.26 |
|
Training and Skill Development Opportunities |
0.24 |
|
Hours Worked |
0.24 |
|
Career Sponsorship |
0.22 |
(all significant at p = .05)
(For reference, the “Big 5” personality traits all have a correlation under 0.12.)
Before we go on, a few caveats: while these correlations are significant and important, none are overwhelming (the authors cite Cohen as saying the range 0.24-0.36 is “medium” and correlations over 0.37 are “large”). Also, in addition to the usual correlation/causation concerns, there is lots of cross-correlation: e.g. older people might have greater political knowledge but less education, thereby confusing things. For a discussion of moderating variables, see the paper itself.
There are two broad models of career advancement: contest-mobility and sponsorship-mobility. They are best illustrated with an example.
Suppose Peter and Penelope are both equally talented entry-level employees. Under the contest-mobility model, they would both be equally likely to get a raise or promotion, because they are equally skilled.
Sponsorship-mobility theorists argue that even if Peter and Penelope are equally talented, it’s likely that one of them will catch the eye of senior management. Perhaps it’s due to one of them having an early success by chance, making a joke in a meeting, or simply just having a more memorable name, like Penelope. This person will be singled out for additional training and job opportunities. Because of this, they’ll have greater success in the company, which will lead to more opportunities etc. As a result, their initial small discrepancy in attention gets multiplied into a large differential.
The authors of the metastudy found that self-reported sponsorship levels (i.e. how much you feel the management of your company “sponsors” you) have a significant, although moderate, relationship to salary. Therefore, the level at which you currently feel sponsored in your job should be a factor when you consider alternate opportunities.
The strongest predictor of salary (tied with education level) is what the authors politely term “Political Knowledge & Skills” - less politely, how good you are at manipulating others.
Several popular books (such as Cialdini’s Influence) on the subject of influencing others exist, and the study of these “influence tactics” in business stretches back 30 years to Kipnis, Schmidt and Wilkinson. Recently, Higgins et al. reviewed 23 individual studies of these tactics and how they relate to career success. Their results:
|
Tactic |
Correlation |
Definition (From Higgins et al.) |
|
Rationality |
0.26 |
Using data and information to make a logical argument supporting one's request |
|
Ingratiation |
0.23 |
Using behaviors designed to increase the target's liking of oneself or to make oneself appear friendly in order to get what one wants |
|
Upward Appeal |
0.05 |
Relying on the chain of command, calling in superiors to help get one's way |
|
Self-Promotion |
0.01 |
Attempting to create an appearance of competence or that you are capable of completing a task |
|
Assertiveness |
-0.02 |
Using a forceful manner to get what one wants |
|
Exchange |
-0.03 |
Making an explicit offer to do something for another in exchange for their doing what one wants |
(Only ingratiation and rationality are significant.)
This site has a lot of information on how to make rational appeals, so I will focus on the less-talked-about ingratiation techniques.
How to be Ingratiating
Gordon analyzed 69 studies of ingratiation and found the following. (Unlike the previous two sections, success here is measured in lab tests as well as in career advancement. However, similar but less comprehensive results have been found in terms of career success):
|
Tactic |
Weighted Effectiveness (Cohen’s d difference between control and intervention) |
Description |
|
Other Enhancement |
0.31 |
Flattery |
|
Opinion Conformity |
0.23 |
“Go along to get along” |
|
Self-presentation |
0.15 |
Any of the following tactics: Self-promotion, self-deprecation, apologies, positive nonverbal displays and name usage |
|
Combination |
0.10 |
Includes studies where the participants weren’t told which strategy to use, in addition to when they were instructed to use multiple strategies |
|
Rendering Favors |
0.05 |
Self-presentation is split further:
|
Tactic |
Weighted Effect Size |
Comment |
|
Modesty |
0.77 |
|
|
Apology |
0.59 |
Apologizing for poor performance |
|
Generic |
0.28 |
When the participant is told in generic terms to improve their self-presentation |
|
Nonverbal behavior and name usage |
-0.14 |
Nonverbal behavior includes things like wearing perfume. Name usage means referring to people by name instead of a pronoun. |
|
Self-promotion |
-0.17 |
|
Moderators
One important moderator is the direction of the appeal. If you are talking to your boss, your tactics should be different than if you’re talking to a subordinate. Other-enhancement (flattery) is always the best tactic no matter who you’re talking to, but when talking to superiors it’s by far the best. When talking to those at similar levels to you, opinion conformity comes close to flattery, and the other techniques aren't far behind.
Unsurprisingly, when the target realizes you’re being ingratiating, the tactic is less effective. (Although effectiveness doesn’t go to zero - even when people realize you’re flattering them just to suck up, they generally still appreciate it.) Also, women are better at being ingratiating than men, and men are more influenced by these ingratiating tactics than women. The most important caveat is that lab studies find much larger effect sizes than in the field, to the extent that the average field effect for the ingratiating tactics is negative. This is probably due to the fact that lab experiments can be better controlled.
It’s unlikely that a silver-tongued receptionist will out-earn an introverted engineer. But simple techniques like flattery and attempting to get "sponsored" can appreciably improve returns, to the extent that political skills are one of the strongest predictors of salaries.
I would like to thank Brian Tomasik and Gina Stuessy for reading early drafts of this article.
Cohen, Jacob. Statistical power analysis for the behavioral sciences. Psychology Press, 1988.
Gordon, Randall A. "Impact of ingratiation on judgments and evaluations: A meta-analytic investigation." Journal of Personality and Social Psychology 71.1 (1996): 54.
Higgins, Chad A., Timothy A. Judge, and Gerald R. Ferris. "Influence tactics and work outcomes: a meta‐analysis." Journal of Organizational Behavior 24.1 (2003): 89-106.
Judge, Timothy A., and Robert D. Bretz Jr. "Political influence behavior and career success." Journal of Management 20.1 (1994): 43-65.
Kipnis, David, Stuart M. Schmidt, and Ian Wilkinson. "Intraorganizational influence tactics: Explorations in getting one's way." Journal of Applied psychology 65.4 (1980): 440.
Ng, Thomas WH, et al. "Predictors of objective and subjective career success: A meta‐analysis." Personnel psychology 58.2 (2005): 367-408.