People in China are used to seeing new constructions rise quickly. Sites are filled with workers, noise, sparks, shouting, and the constant movement of multiple cranes swinging heavy loads to high floors. Within a few weeks, what started as an empty plot has developed into a deep hole, then tall scaffolding, and finally the skeleton of a building, waiting for cladding.
Few buildings, though, have risen faster than the Mini Sky City in Changsha, the capital of Hunan province. From breaking ground in 2015 to completing the 57th and final floor, construction company Broad Sustainable Building took just 19 days. On average, the company was able to build three floors every day, complete with 19 atriums, 800 apartments, and office space for 4,000 people.
It’s hard not to admire the productivity of that rate of construction but Broad Sustainable Building had a secret. The company wasn’t using a special management method that enabled it to squeeze more out of a workforce that was more inclined to stop for tea and take long lunch breaks. It was using a new construction method. Each floor had been prefabricated over the previous year. The builders only needed to knit together 2,736 pre-made modules.
That process isn’t ideal for every construction project. Liu Peng, the associate director of engineering consulting firm Arup Beijing, told the Associated Press that developers tend to want personalized architecture rather than modular construction. City planners don’t want identical buildings and neighborhoods that lack individual character.
But it does show one simple way in which companies can make their teams more productive—and it’s a method that they’ve been using since the days of Henry Ford. Make the work simple and repetitive, and you can churn out identical products quickly. Managers can build teams that work at maximum efficiency.
Today, though, that’s much harder than it sounds. It’s not just property developers who want quality, customized products; technology firms also need to customize their software. As products become more complex, so simple repetition becomes much harder to implement. A couple of studies suggest there are other ways to get more out of a production team, even one working on a production line.
The Team to Build a Lego Tower
In 2019, Vittorio Loreto of the Sapienze University of Rome, and Bernardo Monechi of Sony Computer Science Laboratories conducted an experiment. They placed three building platforms in a room together with three large stashes of Lego bricks. Each platform had an assigned topic, such as “spring” or “Halloween.” Over three days, from 9am to 7pm, participants could wander in and out of the room and between the tables, helping to build on the platforms. As they entered the room, they took an RFID sensor that monitored their location and measured the amount of time they spent with other participants. At the same time, infra-red depth sensors on the platforms measured the speed at which construction on each of the platforms developed.
By comparing the contacts between participants, the time that each participant spent next to each table, and the speed the models grew, the researchers were able to correlate patterns of social contact with productivity.
They found that self-organized teams work best when they include:
- An optimal balance between strong and weak ties—when the teams include both people who work together consistently and new ideas from people who participate occasionally.
- Committed individuals who stay and focus on a single project.
- Influential individuals who have the ability to spread their ideas throughout the team.
Less surprisingly, they also found that larger teams tend to perform better than smaller teams.
“The experiment revealed that larger working teams are building at faster rates and that higher commitment leads to higher growth rates,” the researchers concluded. “Even more importantly, there exists an optimal number of weak ties in the social network of creators that maximizes the growth rate. Finally, the presence of influencers within the working team dramatically enhances the building efficiency.”
The researchers also argue that their findings can be applied across very different settings, both physical and online, whenever a group aims to produce a creative collective outcome.
So a company looking to design some new software or build a marketing pitch should first assign a committed lead to the project. The lead should be someone influential and admired, someone with the experience and the expertise to be able to persuade others but not necessarily someone of higher rank. In the Lego experiment, the teams weren’t hierarchical. The individuals who exerted enough influence to keep the construction rising didn’t rely on their seniority to tell people to keep adding bricks or show them where to put them; they depended on their ability to persuade people that their idea was the best and worth pursuing.
It’s that sort of charismatic individual that companies should assign to a team first.
Having built a team around that individual, the company should then ensure that the project remains open to new ideas from others.
That may be harder than it sounds. Not all teams welcome input from outsiders who haven’t been involved in the project from the beginning and have worked on it throughout its stages. But the experiment showed that a mixture of strong ties between committed builders and the weak ties of occasional contributors produced the fastest progress. It will be up to the team lead—that committed, charismatic contributor—to show that they welcome occasional, outside contributions.
In practice, though, businesses rarely have that kind of flat structure. The committed individual the company assigns to a project won’t just be charismatic and influential. Other team members are also likely to see them as the boss, and that can have a negative influence on productivity.
Put Up a Curtain
In 2012, Ethan Bernstein of Harvard University embedded some Chinese-born research students onto a Precision Mobile production line in southern China. The factory employed 14,000 people across a million square feet and was part of a manufacturing space covering 3.1 million square feet and employing more than 65,000 people. At the time, Precision Mobile was the second biggest producer of mobile devices in the world, making up to two million devices every week for well-known brands.
The research assistants joined the production line. They lived in dormitories with the other workers, built relationships with co-workers who were unaware of their status as embeds, and worked on the line for up to twelve hours each day. Every four hours, they would report their observations to Bernstein who waited in a room on a different floor.
What Bernstein found was that workers on the production line were hiding from supervisors techniques that they used to speed up production. “One of the first rules in which my researchers were trained by peers was how to act whenever a customer, manager, line leader, or any other outsider came in sight of the line,” Bernstein says. “First the embeds were quietly shown ‘better ways’ of accomplishing tasks by their peers—a ‘ton of little tricks’ that ‘kept production going’ or enabled ‘faster, easier, and/or safer production.’ Then they were told, ‘Whenever the [customers/managers/leaders] come around, don’t do that, because they’ll get mad.’”
For example, the official process for attaching protective chip covers with unique, identifying stickers involved attaching each cover and each lid separately then scanning the bar codes on the tray. The workers instead first scanned all the labels then they attached them to the covers, then they put the covers on the chips. Asked why they used that method, a worker explained that it made applying the bar codes four times faster. Scanning the codes when they were still on the sticker was ten times faster than having to aim and re-aim the scanner once the labels were on the chip covers. And their method meant only taking the chip boards off the rack once instead of twice.
If the workers had applied the covers as they had been instructed, the worker said, work would have piled up and management would have complained that they were being too slow. If they had added more people to handle the load, there would have been too little work and management would have complained that they were standing around and talking instead of working.
Whenever the line workers were out of sight of management, they would use their own methods. Whenever a supervisor appeared, they would quickly return to the official methods, and production would slow. “A bird’s-eye observer of the floor could indeed observe bubbles of less productive behavior surrounding any outsider walking the lines,” said Epstein.
Epstein then ran a second experiment. For five months, he placed curtains round four lines producing 3G USB data cards, and compared the productivity of those lines with the productivity of the rest of the factory. He found that the workers who worked out of sight of their managers were between 10 and 15 percent more productive than those who were under constant supervision.
What Bernstein found was that work practices evolved faster than managers can identify or approve them. No one told the line operators that if they scanned the labels while they were still on the sticker roll, they could save time and still apply the stickers to the chip covers. No one told them how to avoid the hassle of removing the chips from the trays twice. They tried those methods for themselves, found that that they were faster, and spread their learning across the factory.
The workers were still given general parameters. The factory had strict production targets that workers knew that had to meet. Their production innovations were driven not by a desire to make their own lives easier or the work less onerous but their motivation to meet the challenge presented by their targets.
One lesson from Bernstein’s study then is that to maximize productivity, the role of a manager needs to be distant. Rather than dictate how work should be performed, the manager should set the goal and lay out the guidelines but let the workers themselves determine how to get there within those guidelines. They need to tell the workers how many pieces they need to produce in a set period of time, describe an acceptable error rate, and give teams the freedom to innovate. Because they’re the ones doing the work, they’re the ones who will see the most efficient techniques evolve.
That might sound like a very different management role to the one described by the Lego study, but actually the two have much in common. Both depend not on a top-down management approach but on the emergence of influential leaders, committed to the cause, and who can persuade others to work in a particular way. Both are capable of learning on the job and of then encouraging others to apply those lessons.
To maximize productivity in a team then, step back. Provide targets and guidelines. Give space for people with commitment to find the best path and show it to others, and allow outsiders with weak links the freedom to make suggestions and insert new ideas.
You might not be able to build a skyscraper in a couple of weeks but you should find that you’re building what you need in record time.
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