creates an incentive to take, which will guarantee you $18.
Since you can’t communicate with one another, giving is a risky strategy. But in the actual study, 15 percent of the participants were consistent givers : they contributed to the group in all six rounds, making a personal sacrifice for the benefit of the group. And it wasn’t as costly as you’d expect. Surprisingly, the consistent givers still ended up doing well: they walked away with an average of 26 percent more money than participants from groups without a single consistent giver. How could they give more and get more?
When the groups included one consistent giver, the other members contributed more. The presence of a single giver was enough to establish a norm of giving. By giving, participants were able to make their group members better off and managed to get more in the process. Even though they earned 50 percent less from each contribution, because they inspired others to give, they made a larger total sum available to all participants. The givers raised the bar and expanded the pie for the whole group.
In this experiment, the consistent givers were doing the equivalent of a five-minute favor when they contributed their money every round. They were making small sacrifices to benefit each member of the group, and it inspired the group members to do the same. Through the five-minute favor, Rifkin is expanding the pie for his whole network. In 106 Miles, the norm is for all five thousand entrepreneurs to help one another. Rifkin explains that “you’re not doing somebody a favor because you’re getting something in return. The goal of the group is to instill the value of giving: you don’t have to be transactional about it, you don’t have to trade it. If you do something for somebody in the group, then when you need it, someone in the group will do something for you.”
For takers and matchers, this type of relentless giving still seems a bit risky. Can givers like Adam Rifkin maintain their productivity, especially when there are no guarantees that their help will come back around to benefit them directly? To shed light on this question, Stanford professor Frank Flynn studied professional engineers at a large telecommunications firm in the Bay Area. He asked the engineers to rate themselves and one another on how much they gave and received help from one another, which allowed him to identify which engineers were givers, takers, and matchers. He also asked each engineer to rate the status of ten other engineers: how much respect did they have?
The takers had the lowest status. They burned bridges by constantly asking for favors but rarely reciprocating. Their colleagues saw them as selfish and punished them with a lack of respect. The givers had the highest status, outdoing the matchers and takers. The more generous they were, the more respect and prestige they earned from their colleagues. Through giving more than they got, givers signaled their unique skills, demonstrated their value, and displayed their good intentions.
Despite being held in the highest esteem, the givers faced a problem: they paid a productivity price. For three months, Flynn measured the quantity and quality of work completed by each engineer. The givers were more productive than the takers: they worked harder and got more done. But the matchers had the highest productivity, beating out the givers. The time that the givers devoted to helping their colleagues apparently detracted from their ability to finish jobs, reports, and drawings. The matchers were more likely to call in favors and receive help, and it appeared to keep them on track. On the face of it, this seems like a stumbling block to the giver style of networking. If givers sacrifice their productivity by helping others, how can it be worth it?
Yet Adam Rifkin has managed to be a giver and stay highly productive as the cofounder of several successful companies. How does he avoid the tradeoff between giving and
Since you can’t communicate with one another, giving is a risky strategy. But in the actual study, 15 percent of the participants were consistent givers : they contributed to the group in all six rounds, making a personal sacrifice for the benefit of the group. And it wasn’t as costly as you’d expect. Surprisingly, the consistent givers still ended up doing well: they walked away with an average of 26 percent more money than participants from groups without a single consistent giver. How could they give more and get more?
When the groups included one consistent giver, the other members contributed more. The presence of a single giver was enough to establish a norm of giving. By giving, participants were able to make their group members better off and managed to get more in the process. Even though they earned 50 percent less from each contribution, because they inspired others to give, they made a larger total sum available to all participants. The givers raised the bar and expanded the pie for the whole group.
In this experiment, the consistent givers were doing the equivalent of a five-minute favor when they contributed their money every round. They were making small sacrifices to benefit each member of the group, and it inspired the group members to do the same. Through the five-minute favor, Rifkin is expanding the pie for his whole network. In 106 Miles, the norm is for all five thousand entrepreneurs to help one another. Rifkin explains that “you’re not doing somebody a favor because you’re getting something in return. The goal of the group is to instill the value of giving: you don’t have to be transactional about it, you don’t have to trade it. If you do something for somebody in the group, then when you need it, someone in the group will do something for you.”
For takers and matchers, this type of relentless giving still seems a bit risky. Can givers like Adam Rifkin maintain their productivity, especially when there are no guarantees that their help will come back around to benefit them directly? To shed light on this question, Stanford professor Frank Flynn studied professional engineers at a large telecommunications firm in the Bay Area. He asked the engineers to rate themselves and one another on how much they gave and received help from one another, which allowed him to identify which engineers were givers, takers, and matchers. He also asked each engineer to rate the status of ten other engineers: how much respect did they have?
The takers had the lowest status. They burned bridges by constantly asking for favors but rarely reciprocating. Their colleagues saw them as selfish and punished them with a lack of respect. The givers had the highest status, outdoing the matchers and takers. The more generous they were, the more respect and prestige they earned from their colleagues. Through giving more than they got, givers signaled their unique skills, demonstrated their value, and displayed their good intentions.
Despite being held in the highest esteem, the givers faced a problem: they paid a productivity price. For three months, Flynn measured the quantity and quality of work completed by each engineer. The givers were more productive than the takers: they worked harder and got more done. But the matchers had the highest productivity, beating out the givers. The time that the givers devoted to helping their colleagues apparently detracted from their ability to finish jobs, reports, and drawings. The matchers were more likely to call in favors and receive help, and it appeared to keep them on track. On the face of it, this seems like a stumbling block to the giver style of networking. If givers sacrifice their productivity by helping others, how can it be worth it?
Yet Adam Rifkin has managed to be a giver and stay highly productive as the cofounder of several successful companies. How does he avoid the tradeoff between giving and
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