High Performance Is Contagious, but Too Many Stars Can Spoil a Team

High Performance Is Contagious, but Too Many Stars Can Spoil a Team

In a recent study of restaurant servers, INSEAD’s Serguei Netessine and Tom Tan of Southern Methodist University explored how the presence of high performers influenced the work of their less competent colleagues. What they found is that competence is indeed “contagious,” at least to an extent:

With algorithmic assistance, it is possible to quantify an individual employee’s innate ability as well as his or her sales performance; but, crucially, stats pertaining to individuals don’t necessarily tell you much about what will be in the till at the end of the night. The critical factor is team performance, which can often be more, or less, than the sum of the parts. …

Having established a baseline skill level for each server, we found that the servers’ sales performance during a given shift would rise or fall depending on who happened to be working with them. Low-skilled servers seemed capable of punching above their weight when the overall skill level of the team was higher. Importantly, this contagion can be charted in an inverted U-shape, meaning that when a shift was stacked too thickly with superstars, the other servers performed below their capacity.

The data doesn’t tell us why the contagion occurs, only that it does. But based on research literature, we can conjecture that for less skilled servers, observing more proficient colleagues kindles a competitive spirit and provides a role model to emulate. A certain amount of anxiety about not meeting the higher overall performance standard may also cause them to up their game. If the standard is set unreasonably high, however, intimidation or negative self-comparison may make them stop trying, creating a drop-off in productivity.

One thing we can glean from the data is that these cross-employee “spillover effects” are sensitive to physical proximity. When low-skilled servers were stationed close to high achievers, their performance improved even more.

Another notable detail is their finding that having too many stars on the team hurts group performance—something other studies have also shown. Yet Netessine goes on to add: “Needless to say, in an ideal world all servers would be excellent.” I wonder whether that’s true, however, given the problems associated with having too many high performers on the same team. It seems that the teaching is about finding the right balance: not too many high performers, and not too many average or low performers on the same team.

What are the implications for leadership teams, where presumably all team members are high performers, otherwise they wouldn’t be in their roles? Perhaps the way the teaching could be extrapolated there is to say that it’s not necessary for every member of a leadership team to excel at every single leadership competency. Instead, organizations should assemble heterogeneous leadership teams that together have the optimal capability mix.

This reminds me a bit of our case study on Cisco’s leadership capability clouds, which CEB Corporate Leadership Council members can read here. The case is not about high vs. low performers (i.e., the practice is not intended to compensate for individual underperformance), but rather individual vs. team capability. Cisco realized that in order to better match existing leadership capability to business needs, they didn’t need to invest in perfecting each individual leader’s capability, but instead they needed to build teams, functions or units with the right capability mix depending on the business context.