Sean handed Chad the original box (the one Chad had assembled and Sean had disassembled), and Chad got to work. This time, he worked somewhat faster, but he abandoned his strategy; perhaps he felt he no longer needed an organizational strategy, or maybe he felt that the extra step was unnecessary.
Meanwhile, Sean slowly took apart the second Bionicle Chad had just finished and placed the parts back into the second box. After Chad finished the third Bionicle, he looked it over and handed it to Sean. “That makes five sixty-seven,” Sean said. “Would you like to make another?”
Chad checked his cell phone for the time and thought for a moment. “Okay,” he said, “I’ll make one more.”
Sean handed him the second Bionicle for the second time, and Chad set about rebuilding it. (All the participants in his condition built and rebuilt the same two Bionicles until they decided to call it quits.) Chad managed to build both his Bionicles twice, for a total of four, for which he was paid $7.34.
After paying Chad, Sean asked him, as he did with all participants, whether he liked Legos and had enjoyed the task.
“Well, I like playing with Legos, but I wasn’t wild about the experiment,” Chad said with a shrug. He tucked the payment into his wallet and quickly left the room.
What did the results show? Joe and the other participants in the meaningful condition built an average of 10.6 Bionicles and received an average of $14.40 for their time. Even after they reached the point where their earnings for each Bionicle were less than a dollar (half of the initial payment), 65 percent of those in the meaningful condition kept on working. In contrast, those in the Sisyphean condition stopped working much sooner. On average, that group built 7.2 Bionicles (68 percent of the number built by the participants in the meaningful condition) and earned an average of $11.52. Only 20 percent of the participants in the Sisyphean condition constructed Bionicles when the payment was less than a dollar per robot.
In addition to comparing the number of Bionicles our participants constructed in the two conditions, we wanted to see how the individuals’ liking of Legos influenced their persistence in the task. In general, you would expect that the more a participant loved playing with Legos, the more Bionicles he or she would complete. (We measured this by the size of the statistical correlation between these two numbers.) This was, indeed, the case. But it also turned out that the two conditions were very different in terms of the relationship between Legos-love and persistence in the task. In the meaningful condition the correlation was high, but it was practically zero in the Sisyphean condition.
What this analysis tells me is that if you take people who love something (after all, the students who took part in this experiment signed up for an experiment to build Legos) and you place them in meaningful working conditions, the joy they derive from the activity is going to be a major driver in dictating their level of effort. However, if you take the same people with the same initial passion and desire and place them in meaningless working conditions, you can very easily kill any internal joy they might derive from the activity.
IMAGINE THAT YOU are a consultant visiting two Bionicles factories. The working conditions in the first Bionicles factory are very similar to those in the Sisyphean condition (which, sadly, is not very different from the structure of many workplaces). After observing the workers’ behavior, you would most likely conclude that they don’t like Legos much (or maybe they have something specific against Bionicles). You also observe their need for financial incentives to motivate them to continue working on their unpleasant task and how quickly they stop working once the payment drops below a certain level. When you deliver your PowerPoint presentation to the company’s board, you remark that as the payment per production unit drops, the employees’ willingness to work dramatically diminishes. From this you further conclude that if the factory wants to increase productivity, wages must be increased substantially.
Next, you visit the second Bionicles factory, which is structured more similarly to the meaningful condition. Now imagine how your conclusions about the onerous nature of the task, the joy of doing it, and the level of compensation needed to persist in the task, might be different.
We actually conducted a related consultant experiment by describing the two experimental conditions to our participants and asking them to estimate the difference in productivity between the two factories. They basically got it right, estimating that the total output in the meaningful condition would be higher than the output in the Sisyphean condition. But they were wrong in estimating the magnitude of the difference. They thought that those in the meaningful condition would make one or two more Bionicles, but, in fact, they made an average of 3.5 more. This result suggests that though we can recognize the effect of even small-m meaning on motivation, we dramatically underestimate its power.
In this light, let’s think about the results of the Bionicles experiment in terms of real-life labor. Joe and Chad loved playing with Legos and were paid at the same rate. Both knew that their creations were only temporary. The only difference was that Joe could maintain the illusion that his work was meaningful and so continued to enjoy building his Bionicles. Chad, on the other hand, witnessed the piece-by-piece destruction of his work, forcing him to realize that his labor was meaningless.* All the participants most likely understood that the whole exercise was silly—after all, they were just making stuff from Legos, not designing a new dam, saving lives, or developing a new medication—but for those in Chad’s condition, watching their creations being deconstructed in front of their eyes was hugely demotivating. It was enough to kill any joy they’d accrued from building the Bionicles in the first place. This conclusion seemed to tally with David’s and Devra’s stories; the translation of joy into willingness to work seems to depend to a large degree on how much meaning we can attribute to our own labor.
NOW THAT WE had ruined the childhood memories of half of our participants, it was time to try another approach to the same experiment. This time the experimental setup was based more closely on David’s experience. Once again, we set up a booth in the student center, but this time we tested three conditions and used a different task.
We created a sheet of paper with a random sequence of letters on it and asked the participants to find instances where the letter S was followed by another letter S. We told them that each sheet contained ten instances of consecutive Ss and that they would have to find all ten instances in order to complete a sheet. We also told them about the payment scheme: they would be paid $0.55 for the first completed page, $0.50 for the second, and so on (for the twelfth page and thereafter, they would receive nothing).
In the first condition (which we called acknowledged), we asked the students to write their names on each sheet prior to starting the task and then to find the ten instances of consecutive Ss. Once they finished a page, they handed it to the experimenter, who looked over the sheet from top to bottom, nodded in a positive way, and placed it upside down on top of a large pile of completed sheets. The instructions for the ignored condition were basically the same, but we didn’t ask participants to write their names at the top of the sheet. After completing the task, they handed the sheet to the experimenter, who placed it on top of a high stack of papers without even a sidelong glance. In the third, ominously named shredded condition, we did something even more extreme. Once the participant handed in their sheet, instead of adding it to a stack of papers, the experimenter immediately fed the paper into a shredder, right before the participant’s eyes, without even looking at it.
We were impressed by the difference a simple acknowledgment made. Based on the outcome of the Bionicles experiment, we expected the participants in the acknowledged condition to be the most productive. And indeed, they completed many more sheets of letters than their fellow participants in the shredded condition. When we looked at how many of the participants continued searching for letter pairs after they reached the pittance payment of 10 cents (which was also the tenth sheet), we found that about half (49
percent) of those in the acknowledged condition went on to complete ten sheets or more, whereas only 17 percent in the shredded condition completed ten sheets or more. Indeed, it appeared that finding pairs of letters can be either enjoyable and interesting (if your effort is acknowledged) or a pain (if your labor is shredded).
But what about the participants in the ignored condition? Their labor was not destroyed, but neither did they receive any form of feedback about their work. How many sheets would those individuals complete? Would their output be similar to that of the individuals in the acknowledged condition? Would they take the lack of reaction badly and produce an output similar to that of the individuals in the shredded condition? Or would the results of those in the ignored condition fall somewhere between the other two?
The results showed that participants in the acknowledged condition completed on average 9.03 sheets of letters; those in the shredded condition completed 6.34 sheets; and those in the ignored condition (drumroll, please) completed 6.77 sheets (and only 18 percent of them completed ten sheets or more). The amount of work produced in the ignored condition was much, much closer to the performance in the shredded condition than to that in the acknowledged condition.
THIS EXPERIMENT TAUGHT us that sucking the meaning out of work is surprisingly easy. If you’re a manager who really wants to demotivate your employees, destroy their work in front of their eyes. Or, if you want to be a little subtler about it, just ignore them and their efforts. On the other hand, if you want to motivate people working with you and for you, it would be useful to pay attention to them, their effort, and the fruits of their labor.
There is one more way to think about the results of the finding pairs of letters experiment. The participants in the shredded condition quickly realized that they could cheat, because no one bothered to look at their work. In fact, if these participants were rational, upon realizing that their work was not checked, those in the shredded condition should have cheated, persisted in the task the longest, and made the most money. The fact that the acknowledged group worked longer and the shredded group worked the least further suggests that when it comes to labor, human motivation is complex. It can’t be reduced to a simple “work for money” trade-off. Instead we should realize that the effect of meaning on labor, as well as the effect of eliminating meaning from labor, are more powerful than we usually expect.
The Division and Meaning of Labor
I found the consistency between the results of the two experiments, and the substantial impact of such small differences in meaning, rather startling. I was also taken aback by the almost complete lack of enjoyment that the participants in the Sisyphean condition derived from building Legos. As I reflected on the situations facing David, Devra, and others, my thoughts eventually lighted on my administrative assistant.
On paper, Jay had a simple enough job description: he was managing my research accounts, paying participants, ordering research supplies, and arranging my travel schedule. But the information technology that Jay had to use made his job a sort of Sisyphean task. The SAP accounting software he used daily required him to fill in numerous fields on the appropriate electronic forms, sending these e-forms to other people, who filled in a few more fields, who in turn sent the e-forms to someone else, who approved the expenses and subsequently passed them to yet another person, who actually settled the accounts. Not only was poor Jay doing only a small part of a relatively meaningless task, but he never had the satisfaction of seeing this work completed.
Why did the nice people at MIT and SAP design the system this way? Why did they break tasks into so many components, put each person in charge of only small parts, and never show them the overall progress or completion of their tasks? I suspect it all has to do with the ideas of efficiency brought to us by Adam Smith. As Smith argued in 1776 in The Wealth of Nations, division of labor is an incredibly effective way to achieve higher efficiency in the production process. Consider, for example, his observations of a pin factory:
. . . the division of labour has been very often taken notice of, the trade of the pin-maker; a workman not educated to this business (which the division of labour has rendered a distinct trade), nor acquainted with the use of the machinery employed in it (to the invention of which the same division of labour has probably given occasion), could scarce, perhaps, with his utmost industry, make one pin in a day, and certainly could not make twenty. But in the way in which this business is now carried on, not only the whole work is a peculiar trade, but it is divided into a number of branches, of which the greater part are likewise peculiar trades. One man draws out the wire, another straights it, a third cuts it, a fourth points it, a fifth grinds it at the top for receiving the head; to make the head requires two or three distinct operations; to put it on, is a peculiar business, to whiten the pins is another; it is even a trade by itself to put them into the paper; and the important business of making a pin is, in this manner, divided into about eighteen distinct operations, which, in some manufactories, are all performed by distinct hands, though in others the same man will sometimes perform two or three of them. I have seen a small manufactory of this kind where ten men only were employed, and where some of them consequently performed two or three distinct operations. But though they were very poor, and therefore but indifferently accommodated with the necessary machinery, they could, when they exerted themselves, make among them about twelve pounds of pins in a day. There are in a pound upwards of four thousand pins of a middling size. Those ten persons, therefore, could make among them upwards of forty-eight thousand pins in a day.1
When we take tasks and break them down into smaller parts, we create local efficiencies; each person can become better and better at the small thing he does. (Henry Ford and Frederick Winslow Taylor extended the division-of-labor concept to the assembly line, finding that this approach reduced errors, increased productivity, and made it possible to produce cars and other goods en masse.) But we often don’t realize that the division of labor can also exact a human cost. As early as 1844, Karl Marx—the German philosopher, political economist, sociologist, revolutionary, and father of communism—pointed to the importance of what he called “the alienation of labor.” For Marx, an alienated laborer is separated from his own activities, from the goals of his labor, and from the process of production. This makes work an external activity that does not allow the laborer to find identity or meaning in his work.
I am far from being a Marxist (despite the fact that many people think that all academics are), but I don’t think we should wholly discount Marx’s idea of alienation in terms of its role in the workplace. In fact, I suspect that the idea of alienation was less relevant in Marx’s time, when, even if employees tried hard, it was difficult to find meaning at work. In today’s economy, as we move to jobs that require imagination, creativity, thinking, and round-the-clock engagement, Marx’s emphasis on alienation adds an important ingredient to the labor mix. I also suspect that Adam Smith’s emphasis on the efficiency in the division of labor was more relevant during his time, when the labor in question was based mostly on simple production, and is less relevant in today’s knowledge economy.
From this perspective, division of labor, in my mind, is one of the dangers of work-based technology. Modern IT infrastructure allows us to break projects into very small, discrete parts and assign each person to do only one of the many parts. In so doing, companies run the risk of taking away employees’ sense of the big picture, purpose, and sense of completion. Highly divisible labor might be efficient if people were automatons, but, given the importance of internal motivation and meaning to our drive and productivity, this approach might backfire. In the absence of meaning, knowledge workers may feel like Charlie Chaplin’s character in Modern Times, pulled through the gears and cogs of a machine in a factory, and as a consequence they have little desire to put their heart and soul into their labor.
In Search of Meaning
If we look at the labor market through this lens, it is easy
to see the multiple ways in which companies, however unintentionally, choke the motivation out of their employees. Just think about your own workplace for a minute, and I am sure you will be able to come up with more than a few examples.
This can be a rather depressing perspective, but there is also space for optimism. Since work is a central part of our lives, it’s only natural for people to want to find meaning—even the simplest and smallest kind—in it. The findings of the Legos and the letter-pairs experiments point to real opportunities for increasing motivation and to the dangers of crushing the feeling of contribution. If companies really want their workers to produce, they should try to impart a sense of meaning—not just through vision statements but by allowing employees to feel a sense of completion and ensuring that a job well done is acknowledged. At the end of the day, such factors can exert a huge influence on satisfaction and productivity.
Another lesson on meaning and the importance of completion comes from one of my research heroes, George Loewenstein. George analyzed reports of one particularly difficult and challenging undertaking: mountaineering. Based on his analysis, he concluded that climbing mountains is “unrelenting misery from beginning to end.” But doing so also imparts a huge sense of accomplishment (and it makes for great dinner-table conversation). The need to complete goals runs deep in human nature—perhaps just as deep as in fish, gerbils, rats, mice, monkeys, chimpanzees, and parrots playing with SeekaTreats. As George once wrote:
My own suspicion is that the drive toward goal establishment and goal completion is “hard wired.” Humans, like most animals and even plants, are maintained by complex arrays of homeostatic mechanisms that keep the body’s systems in equilibrium. Many of the miseries of mountaineering, such as hunger, thirst and pain, are manifestations of homeostatic mechanisms that motivate people to do what they need to survive . . . the visceral need for goal completion, then, may be simply another manifestation of the organism’s tendency to deal with problems—in this case the problem of executing motivated actions.2