The New Science of Building Great Teams the Chemistry of High-Performing Groups Is No Longer a Mystery

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Spotlight on the secrets of great teams The New Science of Building Great Teams The chemistry of high-performing groups is no longer a mystery. by Alex “Sandy” Pentland

This article is made available to you with compliments of Alex "Sandy" Pentland. Further posting, copying or distributing is copyright infringement. Spotlight on the secrets of great teams Artwork Andy Gilmore, Chromatic, 2010 Spotlight Digital drawing

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Alex “Sandy” Pentland is a professor at MIT, the director of MIT’s Human Dynamics Laboratory and the MIT Media Lab Entrepreneurship Program, and the chairman of Sociometric Solutions. The New Science of Building

Great TeamsThe chemistry of high-performing groups is no longer a mystery. by Alex “Sandy” Pentland

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If you were looking for teams to rig for success, a bers were talking about. That suggested that the call center would be a good place to start. The skills key to high performance lay not in the content of a required for call center work are easy to identify and team’s discussions but in the manner in which it was hire for. The tasks involved are clear-cut and easy communicating. Yet little of the research on team to monitor. Just about every aspect of team perfor- building had focused on communication. Suspect- mance is easy to measure: number of issues resolved, ing it might be crucial, we decided to examine it customer satisfaction, average handling time (AHT, more deeply. the golden standard of call center efficiency). And For our studies, we looked across a diverse set the list goes on. of industries to find workplaces that had simi- Why, then, did the manager at a major bank’s call lar teams with varying performance. Ultimately, center have such trouble figuring out why some of our research included innovation teams, post-op his teams got excellent results, while other, seem- wards in hospitals, customer-facing teams in banks, ingly similar, teams struggled? Indeed, none of the backroom operations teams, and call center teams, metrics that poured in hinted at the reason for the among others. performance gaps. This mystery reinforced his We equipped all the members of those teams assumption that team building was an art, not a with electronic badges that collected data on their science. individual communication behavior—tone of voice, The truth is quite the opposite. At MIT’s Human body language, whom they talked to and how much, Dynamics Laboratory, we have identified the elusive and more. With remarkable consistency, the data group dynamics that characterize high-performing confirmed that communication indeed plays a criti- teams—those blessed with the energy, creativity, cal role in building successful teams. In fact, we’ve and shared commitment to far surpass other teams. found patterns of communication to be the most These dynamics are observable, quantifiable, and important predictor of a team’s success. Not only measurable. And, perhaps most important, teams that, but they are as significant as all the other fac- can be taught how to strengthen them. tors—individual intelligence, personality, skill, and the substance of discussions—combined. Looking for the “It Factor” Patterns of communication, for example, ex- When we set out to document the behavior of teams plained why performance varied so widely among that “click,” we noticed we could sense a buzz in a the seemingly identical teams in that bank’s call team even if we didn’t understand what the mem- center. Several teams there wore our badges for six weeks. When my fellow researchers (my colleagues at Sociometric Solutions—Taemie Kim, Daniel Olguin, and Ben Waber) and I analyzed the data collected, we Why Do Patterns of Communication Matter So Much? found that the best predictors of productivity were a It seems almost Yet if we look at our evolutionary history, we can team’s energy and engagement outside formal meet- absurd that how see that language is a relatively recent develop- ings. Together those two factors explained one-third we communicate ment and was most likely layered upon older sig- of the variations in dollar productivity among groups. could be so much nals that communicated dominance, interest, and Drawing on that insight, we advised the cen- Iemotions among humans. Today these ancient pat- ter’s manager to revise the employees’ coffee break more important to success than what terns of communication still shape how we make schedule so that everyone on a team took a break at decisions and coordinate work among ourselves. the same time. That would allow people more time we communicate. Consider how early man may have approached to socialize with their teammates, away from their problem solving. One can imagine humans sitting workstations. Though the suggestion flew in the face around a campfire (as a team) making suggestions, of standard efficiency practices, the manager was relating observations, and indicating interest or baffled and desperate, so he tried it. And it worked: approval with head nods, gestures, or vocal signals. AHT fell by more than 20% among lower-performing If some people failed to contribute or to signal their teams and decreased by 8% overall at the call center. level of interest or approval, then the group mem- Now the manager is changing the break schedule at bers had less information and weaker judgment, all 10 of the bank’s call centers (which employ a total and so were more likely to go hungry. of 25,000 people) and is forecasting $15 million a year in productivity increases. He has also seen employee

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What Data the Sociometric Idea in Brief Badges Collect What managers sense communication that are as- as an ineffable buzz sociated with productive teams, or esprit de corps in a regardless of what kind of work good team is actually they do. The data do not take observable, measur- into account the substance able, and learnable. of communication, only the patterns, but they show that In data collected by wearable those patterns are what matter electronic sensors that capture most—more than skill, intel- WHEN PEOPLE body position body language, ARE TALKING and relative to others— including arm and people’s tone of voice and ligence, and all other factors their tone of whether people hand movements voice, but not face each other and nods, but not body language, we can see the that go into building a team WORDS and how they stand facial expressions highly consistent patterns of combined. in a group

satisfaction at call centers rise, sometimes by more ple as they go about their lives, at an unprecedented than 10%. level of detail. The badges produce “sociometrics,” Any company, no matter how large, has the po- or measures of how people interact—such as what tential to achieve this same kind of transformation. tone of voice they use; whether they face one an- Firms now can obtain the tools and data they need other; how much they gesture; how much they talk, to accurately dissect and engineer high performance. listen, and interrupt; and even their levels of extro- Building great teams has become a science. Here’s version and empathy. By comparing data gathered how it works. from all the individuals on a team with performance data, we can identify the communication patterns Overcoming the Limits of Observation that make for successful teamwork. When we sense esprit de corps, that perception Those patterns vary little, regardless of the type doesn’t come out of the blue; it’s the result of our in- of team and its goal—be it a call center team striv- nate ability to process the hundreds of complex com- ing for efficiency, an innovation team at a pharma- munication cues that we constantly send and receive. ceutical company looking for new product ideas, or But until recently we had never been able to ob- a senior management team hoping to improve its jectively record such cues as data that we could then leadership. Productive teams have certain data sig- mine to understand why teams click. Mere observa- natures, and they’re so consistent that we can pre- tion simply couldn’t capture every nuance of human dict a team’s success simply by looking at the data— behavior across an entire team. What we had, then, without ever meeting its members. was only a strong sense of the things—good leader- ship and followership, palpable shared commit- ment, a terrific brainstorming session—that Just by looking at the made a team greater than the sum of its parts. Recent advances in wireless and sensor sociometric data, we’ve been technology, though, have helped us over- come those limitations, allowing us to mea- able to foretell which teams will sure that ineffable “It factor.” The badges developed at my lab at MIT are in their seventh win a business plan contest. version. They generate more than 100 data points a minute and work unobtrusively enough that we’re We’ve been able to foretell, for example, which confident we’re capturing natural behavior. (We’ve teams will win a business plan contest, solely on the documented a period of adjustment to the badges: basis of data collected from team members wearing Early on, people appear to be aware of them and act badges at a cocktail reception. (See “Defend Your unnaturally, but the effect dissipates, usually within Research: We Can Measure the Power of Charisma,” an hour.) We’ve deployed them in 21 organizations HBR January–February 2010.) We’ve predicted the over the past seven years, measuring the commu- financial results that teams making investments nication patterns of about 2,500 people, sometimes would achieve, just on the basis of data collected dur- for six weeks at a time. ing their negotiations. We can see in the data when With the data we’ve collected, we’ve mapped the team members will report that they’ve had a “pro- communication behaviors of large numbers of peo- ductive” or “creative” day.

April 2012 Harvard Business Review 5 This article is made available to you with compliments of Alex "Sandy" Pentland. Further posting, copying or distributing is copyright infringement. Spotlight on the secrets of great teams Mapping Teamwork Concerned about uneven performance across its branches, a team communication was the rule, communication outside teams bank in Prague outfitted customer-facing teams with electronic was much higher, suggesting that those teams were desperately sensors for six weeks. The first two maps below display data col- reaching out for answers to their problems. Teams at the modern lected from one team of nine people over the course of differ- facilities showed high energy and less need to explore outside. ent days, and the third illustrates data collected on interactions After seeing initial data, the bank’s management published these between management and all the teams. dashboard displays for all the teams to see and also reorganized By looking at the data, we unearthed a divide between teams at the teams so that they contained a mix of members from old and the “Soviet era” branches of the bank and teams at more modern new branches. According to the bank, those measures helped facilities. Interestingly, at the Soviet-era branches, where poor improve the working culture within all the teams.

Ideal Amount of Internal team A Team A communication Team energy member A between teams Energy Amount of I B Informal I B energy

H C H C

G D G D

F E F E 10 eam 2 eam 3 eam 4 eam 5 eam 6 eam 7 eam 8 eam 9 T T T T T T T T eam Total team energy Amount Amount of T

(Dot’s position of energy communication anagement

reflects who contributed between individuals M contributes most) to Team Energy Engagement Exploration How Team Members Contribute How Team Members Communicate How Teams Communicate to a Team as a Whole with One Another with One Another Clearly, these data come from a team This diagram shows that the same team’s This map shows that management is at a branch with poor customer service. engagement skews heavily to the same doing a lot of exploring. Although its We can see that A, C, and E give off more three people (A, B, and C). G is making internal team energy is relatively low, informal energy than the rest of the team an effort to reach the decision makers, that is OK. Energy and engagement can- does. A, B, and C contribute a lot to the but the team within the team is where not be high when exploration is, because team, while the others contribute noth- the engagement is. Those three people when you’re exploring you have less time ing. The pattern illustrated here is often may be higher up the ladder or simply to engage with your own team. In a high- associated with hierarchical teams in more extroverted, but that doesn’t functioning organization, however, there which a boss (C) issues commands while matter. This pattern is associated with would be more exploration among all the his lieutenants (A and B) reinforce his lower performance because the team teams, and you’d see an arc between, directions. The three are a “team within is not getting ideas or information from say, Teams 3 and 4, or Teams 5 and 9. A a team,” and it’s likely that the others many of its members. Leaders can use time lapse view of all the teams’ explora- feel they have no input. Often leaders are this map both to assess “invisible” team tion would show whether teams were os- shocked and embarrassed to see how members (How can they get them more cillating between communication within much they dominate a team and imme- involved? Are they the right people for their own group (shown by the yellow diately try to change the pattern. Sharing the project?) and to play the role of a dots) and exploration with other teams such a map with the team can make it “charismatic connector” by bringing to- (shown by the green arcs). If they’re not, easier for less energetic individuals to gether members who ought to be talking it could mean silo busting is needed to talk about their sense of the team’s dys- to one another and then helping those encourage proper exploration. function, because data are objective and members share their thinking with the elevate the discussion beyond attacks or entire group. complaints. Courtesy of Sociometric Solutions

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The data also reveal, at a higher level, that suc- ing events, rule changes, and other administrative cessful teams share several defining characteristics: details. These meetings are invariably low energy. 1. Everyone on the team talks and listens in But when someone announces a new discovery in roughly equal measure, keeping contributions short the same group, excitement and energy skyrocket as and sweet. all the members start talking to one another at once. 2. Members face one another, and their conversa- The second important dimension of communi- tions and gestures are energetic. cation is engagement, which reflects the distribution 3. Members connect directly with one another— of energy among team members. In a simple three- not just with the team leader. person team, engagement is a function of the av- 4. Members carry on back-channel or side conver- erage amount of energy between A and B, A and sations within the team. C, and B and C. If all members of a team have rela- 5. Members periodically break, go exploring out- tively equal and reasonably high energy with all side the team, and bring information back. other members, engagement is extremely strong. The data also establish another surprising fact: Teams that have clusters of members who engage in Individual reasoning and talent contribute far less high-energy communication while other members to team success than one might expect. The best do not participate don’t perform as well. When we way to build a great team is not to select individu- observed teams making investment decisions, for als for their smarts or accomplishments but to learn instance, the partially engaged teams made worse how they communicate and to shape and guide the (less profitable) decisions than the fully engaged team so that it follows successful communication teams. This effect was particularly common in far- patterns. flung teams that talked mostly by telephone. The third critical dimension, exploration, in- The Key Elements of Communication volves communication that members engage in out- In our research we identified three aspects of com- side their team. Exploration essentially is the energy munication that affect team performance. The first between a team and the other teams it interacts with. is energy, which we measure by the number and the nature of exchanges among team mem- bers. A single exchange is defined as a com- The most valuable form of ment and some acknowledgment—for example, a “yes” or a nod of the head. communication is face-to- Normal conversations are often made up of many of these exchanges, and in a team face. E-mail and texting are setting more than one exchange may be go- ing on at a time. the least valuable. The most valuable form of communication is face-to-face. The next most valuable is by phone or Higher-performing teams seek more outside con- videoconference, but with a caveat: Those technolo- nections, we’ve found. We’ve also seen that scoring gies become less effective as more people participate well on exploration is most important for creative in the call or conference. The least valuable forms teams, such as those responsible for innovation, of communication are e-mail and texting. (We col- which need fresh perspectives. lect data on those kinds of communication without To measure exploration, we have to deploy using the badges. Still, the number of face-to-face badges more widely in an organization. We’ve done exchanges alone provides a good rough measure so in many settings, including the MIT Media Lab of energy.) The number of exchanges engaged in, and a multinational company’s marketing depart- weighted for their value by type of communication, ment, which comprised several teams dedicated to gives each team member an energy score, which is different functions. averaged with other members’ results to create a Our data also show that exploration and engage- team score. ment, while both good, don’t easily coexist, because Energy levels within a team are not static. For in- they require that the energy of team members be put stance, in my research group at MIT, we sometimes to two different uses. Energy is a finite resource. The have meetings at which I update people on upcom- more that people devote to their own team (engage-

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Mapping Communication over Time How to read these maps The maps below depict the communica- sales, support, development, and manage- thickness of arcs indicates tion patterns in a German bank’s marketing ment. Besides collecting data on in-person the amount of communication department in the days leading up to and interactions with sociometric badges, we between groups Green indicates face-to-face immediately following a major new product gathered e-mail data to assess the balance communication launch. The department had teams of between high-value face-to-face communi- Gray indicates communication four members each in customer service, cation and lower-value digital messages. via e-mail

Day 2 Management is clearly doing Day 6 Management by most of the communicating. e-mail continues.

Customer Customer Management Development Sales Support Service Management Development Sales Support Service

Most communication is via e-mail, Customer service Management is communicating Only sales and support not face-to-face. In an ideal situ- is the least con- face-to-face a little bit with every interact with each other ation, the green arcs would be nected to other team except customer service, a lot in person—most thicker than the gray ones, and teams. and most groups aren’t talking likely because they are there would be strong connec- much to one another. prepping for the launch. tions among all teams.

ment), the less they have to use outside their team “right” number of exchanges in a team is as many (exploration), and vice versa. as dozens per working hour, but that going beyond But they must do both. Successful teams, espe- that ideal number decreases performance. We cially successful creative teams, oscillate between can also state with certainty that in a typical high- exploration for discovery and engagement for inte- performance team, members are listening or speak- gration of the ideas gathered from outside sources. ing to the whole group only about half the time, and At the MIT Media Lab, this pattern accounted for when addressing the whole group, each team mem- almost half of the differences in creative output of ber speaks for only his or her fair share of time, using research groups. And in one industrial research lab brief, to-the-point statements. The other half of the we studied, it distinguished teams with high creativ- time members are engaging in one-on-one conver- ity from those with low creativity with almost 90% sations, which are usually quite short. It may seem accuracy. illogical that all those side exchanges contribute to better performance, rather than distract a team, but Beyond Conventional Wisdom the data prove otherwise. A skeptic would argue that the points about energy, The data we’ve collected on the importance of engagement, and exploration are blindingly obvious. socializing not only build on conventional wisdom But the data from our research improve on conven- but sometimes upend it. Social time turns out to be tional wisdom. They add an unprecedented level of deeply critical to team performance, often account- precision to our observations, quantify the key dy- ing for more than 50% of positive changes in com- namics, and make them measurable to an extraordi- munication patterns, even in a setting as efficiency- nary degree. focused as a call center. For example, we now know that 35% of the varia- Without the data there’s simply no way to under- tion in a team’s performance can be accounted for stand which dynamics drive successful teams. The simply by the number of face-to-face exchanges managers of one young software company, for in- among team members. We know as well that the stance, thought they could promote better commu-

8 Harvard Business Review April 2012 This article is made available to you with compliments of Alex "Sandy" Pentland. Further posting, copying or distributing is copyright infringement. For article reprints call 800-988-0886 or 617-783-7500, or visit hbr.org Mapping Communication over Time We did not provide iterative feedback uneven communication among groups. in this project, but if we had, by the end If these issues had been addressed, the of week one, we would have pointed out problems with the product might have three negative trends the group could surfaced much earlier, and the responses have corrected: the invisibility of customer to them would probably have improved. service, overreliance on e-mail, and highly

Day 15 As the launch approaches, Day 23 Two days after launch, teams are communication is startlingly low. finally communicating in person, as they triage a disastrous campaign.

Customer Customer Management Development Sales Support Service Management Development Sales Support Service

Sales is now clearly Customer For the first time, e-mail The big jump in com- Customer engaging with development, service is still communication is lower munication here might service and probably to learn the final not involved. than face-to-face com- be a result of sales’ support are details of the product munication. In a crisis hammering develop- locked in all- offering and understand its people naturally start ment about why the day meetings technical aspects. talking more in person. product isn’t working trying to patch and how it can be fixed. the problems.

nication among employees by hosting “beer meets” Step 1: Visualization. In raw form the data don’t and other events. But the badge data showed that mean much to the teams being measured. An energy these events had little or no effect. In contrast, the score of 0.5 may be good for an individual, for exam- data revealed that making the tables in the compa- ple, but descriptions of team dynamics that rely on ny’s lunchroom longer, so that strangers sat together, statistical output are not particularly user-friendly. had a huge impact. However, using the formulas we developed to cal- A similarly refined view of exploration has culate energy, engagement, and exploration, we can emerged in the data. Using fresh perspectives to create maps of how a team is doing on those dimen- improve performance is hardly a surprising idea; sions, visualizations that clearly convey the data and it’s practically management canon. But our re- are instantly accessible to anyone. The maps starkly search shows that most companies don’t do it the highlight weaknesses that teams may not have rec- right way. Many organizations we’ve studied seek ognized. They identify low-energy, unengaged team outside counsel repeatedly from the same sources members who, even in the visualization, look as if and only at certain times (when building a business they’re being ignored. (For examples, see the exhibit case, say, or doing a postmortem on a project). The “Mapping Teamwork.”) best-performing and most creative teams in our When we spot such people, we dig down into study, however, sought fresh perspectives con- their individual badge data. Are they trying to con- stantly, from all other groups in (and some outside) tribute and being ignored or cut off? Do they cut the organization. others off and not listen, thereby discouraging col- leagues from seeking their opinions? Do they com- How to Apply the Data municate only with one other team member? Do For management tasks that have long defied objec- they face other people in meetings or tend to hide tive analysis, like team building, data can now pro- from the group physically? Do they speak loudly vide a foundation on which to build better individual enough? Perhaps the leader of a team is too domi- and team performance. This happens in three steps. nant; it may be that she is doing most of the talking

April 2012 Harvard Business Review 9 This article is made available to you with compliments of Alex "Sandy" Pentland. Further posting, copying or distributing is copyright infringement. Spotlight on the secrets of great teams Mapping Communication Improvement Our data show that far- flung and mixed-language teams often struggle to gel. Distance plays a role: Electronic communication at meetings and needs to work on encouraging oth- munication. But does that translate to improved doesn’t create the same energy and engagement that ers to participate. Energy and engagement maps will performance? Yes. The third and final step in using face-to-face communication make such problems clear. And once we know what the badge data is to map energy and engagement does. Cultural norms play they are, we can begin to fix them. against performance metrics. In the case of the a role too. Visual feedback on communication patterns Exploration maps reveal patterns of communi- Japanese-American team, for example, we mapped can help. cation across organizations. They can expose, for the improved communication patterns against the For one week we instance, whether a department’s management is team’s self-reported daily productivity. The closer gathered data on a team composed of Japanese failing to engage with all its teams. Time-lapse views the patterns came to those of our high-performance and Americans that were of engagement and exploration will show whether ideal, the higher productivity rose. brainstorming a new design teams are effectively oscillating between those two We’ve duplicated this result several times over, together in Japan. Each day the team was shown activities. It’s also possible to layer more detail into running similar feedback loops with teams aiming maps of its communication the visualizations. We can create maps that break to be more creative and with executive teams look- patterns and given simple out different types of communication among team ing for more cohesiveness. In every case the self- guidance about what makes good communication (active members, to discover, for example, if teams are fall- reporting on effectiveness mapped to the improved but equal participation). ing into counterproductive patterns such as shooting patterns of communication. off e-mail when they need more face time. (For an Through such maps, we often make important example, see the exhibit “Mapping Communication discoveries. One of the best examples comes from Day 1 The two Japanese team members (bottom and over Time.”) the bank’s call center. For each team there, we lower left) are not engaged, Step 2: Training. With maps of the data in hand, mapped energy and engagement against average and a team within a team we can help teams improve performance through it- handling time (AHT), which we indicated with color. seems to have formed around the member at the erative visual feedback. (See the exhibit “Mapping Communication Against top right. Work we did with a multicultural design team Performance.”) That map clearly showed that the composed of both Japanese and American members most efficient work was done by high-energy, high- offers a good example. (Visual data are especially ef- engagement teams. But surprisingly, it also showed fective at helping far-flung and multilingual groups, that low-energy, low-engagement teams could out- which face special communication challenges.) The perform teams that were unbalanced—teams that team’s maps (see the exhibit “Mapping Communica- had high energy and low engagement, or low energy tion Improvement”) showed that its communication and high engagement. The maps revealed that the was far too uneven. They highlighted that the Japa- manager needed to keep energy and engagement in nese members were initially reluctant to speak up, balance as he worked to strengthen them. leaving the team both low energy and unengaged. If a hard metric like AHT isn’t available, we can Every day for a week, we provided team mem- map patterns against subjective measures. We have Day 7 The team has im- bers a visualization of that day’s work, with some asked teams to rate their days on a scale of “creativ- proved remarkably. Not only light interpretation of what we saw. (Keep in mind ity” or “frustration,” for example, and then seen are the Japanese members contributing more to energy that we didn’t know the substance of their work, just which patterns are associated with highly creative or and engagement (with the how they were interacting.) We also told them that frustrating days. Teams often describe this feedback one at the bottom becom- the ideal visualization would show members con- as “a revelation.” ing a high-energy, highly engaged team member) but tributing equally and more overall contributions. By Successful tactics. The obvious question at some of the Day 1 “domina- day seven, the maps showed, the team’s energy and this point is, Once I recognize I need to improve tors” (on the lower right, for engagement had improved vastly, especially for the energy and engagement, how do I go about doing example) have distributed their energy better. two Japanese members, one of whom had become a it? What are the best techniques for moving those driving force. measurements? The notion that visual feedback helps people Simple approaches such as reorganizing office improve quickly shouldn’t be surprising to anyone space and seating are effective. So is setting a per- who has ever had a golf swing analyzed on video or sonal example—when a manager himself actively watched himself deliver a speech. Now we have the encourages even participation and conducts more visual tools to likewise improve teamwork through face-to-face communication. Policy changes can im- objective analysis. prove teams, too. Eschewing Robert’s Rules of Order, Step 3: Fine-tuning performance. We have for example, is a great way to promote change. In seen that by using visualizations as a training tool, some cases, switching out team members and bring- teams can quickly improve their patterns of com- ing in new blood may be the best way to improve the

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Mapping Communication Against Performance Visualizations can be used to compare energy and engagement with estab- lished performance metrics. The map below plots the energy and engagement levels of several teams at a bank call center against the center’s metric of energy and engagement of the team, though we’ve efficiency, average handling timeA ( HT). found that this is often unnecessary. Most people, The expected team efficiency is based on a statistical analysis of actual given feedback, can learn to interrupt less, say, or to team AHT scores over six weeks. Blue indicates high efficiency; red low -ef face other people, or to listen more actively. Lead- ficiency. High-energy, high-engagement teams are the most efficient, the map ers should use the data to force change within their shows. But it also indicates that low-energy, low-engagement teams outper- teams. form teams that are out of balance, with high energy and low engagement, The ideal team player. We can also measure or low energy and high engagement. This means the call center manager individuals against an ideal. In both productivity- can pull more than one lever to improve performance. Points and are focused and creativity-focused teams, we have dis- equally efficient, for example, but reflect different combinations of energy and covered the data signature of what we consider the engagement. best type of team member. Some might call these The manager wanted to raise energy and engagement in lockstep. We sug- individuals “natural leaders.” We call them “char- gested instituting a common coffee break for each team at the call center. ismatic connectors.” Badge data show that these This increased the number of interactions, especially informal ones, and people circulate actively, engaging people in short, raised the teams’ energy levels. And because all team members took a break high-energy conversations. They are democratic at once, interactions were evenly distributed, increasing engagement. When with their time—communicating with everyone we mapped energy and engagement against AHT afterward, the results were equally and making sure all team members get a clear: Efficiency in the center increased by 8%, on average, and by as much as chance to contribute. They’re not necessarily extro- 20% for the worst-performing teams. verts, although they feel comfortable approaching other people. They listen as much as or more than they talk and are usually very engaged with whom- gh gh Hi ever they’re listening to. We call it “energized but Hi focused listening.” The best team players also connect their team- mates with one another and spread ideas around. Average

And they are appropriately exploratory, seeking ideas nt Performance ncy e AFTER e from outside the group but not at the expense of m e Once a common coffee group engagement. In a study of executives attend- break was instituted, ing an intensive one-week executive education class Efficiency Among the Effici teams increased by at MIT, we found that the more of these charismatic Engag connectors a team had, the more successful it was. Average 8% Performance BEFORE OW

Team building is indeed a science, but it’s young and L evolving. Now that we’ve established patterns of Low Energy High communication as the single most important thing to measure when gauging the effectiveness of a We imagine a company’s entire staff wearing group, we can begin to refine the data and processes badges over an extended period of time, creating to create more-sophisticated measurements, dig “big data” in which we’d find the patterns for every- deeper into the analysis, and develop new tools that thing from team building to leadership to negotia- sharpen our view of team member types and team tions to performance reviews. We imagine changing types. the nature of the space we work in, and maybe even The sensors that enable this science are evolv- the tools we use to communicate, on the basis of ing as well. As they enter their seventh generation, the data. We believe we can vastly improve long- they’re becoming as small and unobtrusive as tra- distance work and cross-cultural teams, which are ditional ID badges, while the amount and types of so crucial in a global economy, by learning their pat- data they can collect are increasing. We’ve begun to terns and adjusting them. We are beginning to create experiment with apps that present teams and their what I call the “God’s-eye view” of the organization. leaders with real-time feedback on group communi- But spiritual as that may sound, this view is rooted in cations. And the applications for the sensors are ex- evidence and data. It is an amazing view, and it will panding beyond the team to include an ever-broader change how organizations work. set of situations. HBR Reprint R1204C

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