New Directions in Assessing Performance Potential of Individuals and Groups Workshop Summary (2013) / Chapter Skim
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4 Emerging Understandings of Group-Related Characteristics
4 Emerging Understandings of Group-Related Characteristics
Pages 51-78
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From page 51... ...
During the second day of the workshop, the third panel, Group Composition Processes and Performance, was devoted specifically to issues related to assessments that can provide insights into group performance and the effective assembly of groups. Invited pre sentations from Anita Williams Woolley, Scott Tannenbaum, and Leslie DeChurch included discussion of the "collective intelligence" of a team, how to assess and predict team performance, and how best to assemble teams.
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From page 52... ...
. Collective intelligence, Woolley explained, can be thought of as a group version of the general intelligence factor, g, for individuals.
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From page 53... ...
. Most importantly, Woolley emphasized, the collective intelligence factor did a far better job of pre dicting performance on the video game simulation than did the IQ of the individual group members.
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From page 54... ...
However, as the solid lines in Figure 4-2 illustrate, while teams with either high or low collective intelligence improved, $3,400 $3,200 Earnings per Round $3,000 $2,800 $2,600 $2,400 Rounds FIGURE 4-1 Collective intelligence and learning as measured in a behavioral economics game. SOURCE: Adapted from Aggarwal et al.
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Test Score FIGURE 4-2 Collective intelligence (CI) in classroom teams.
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were compared with the highest individual score on each team (dashed lines in Figure 4-2) , the teams with low collective intel ligence scored no better than their best team member 50 percent of the time, while the teams with high collective intelligence consistently scored significantly better than their best team member.
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From page 57... ...
By studying communication in these groups, Woolley has also found that uneven distribution in speaking turns is negatively correlated with collective intelligence, so groups in which one person dominates the con versation tend to have lower collective intelligence (Woolley et al., 2010)
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From page 58... ...
She has also been working to refine her battery of tests so that it can be used in other environments to predict team performance and also so that it can be used to experiment with tools that enhance various processes that improve collective intelligence. Discussion: Collective Intelligence in Online Groups In the discussion period following her presentation, Woolley noted that she had recently finished a study comparing face-to-face teams with online teams and found that the pattern of relationships still held.
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From page 59... ...
"What it suggests," Woolley noted, "is that the measure generalizes to other modes than simply the visual identification of emotional expression." PREDICTING TEAM PERFORMANCE To a certain degree, well-qualified individuals are more likely to per form well as a team on various tasks, relative to a team of less-qualified individuals. However, as Woolley's work on collective intelligence found, individual characteristics tell only part of the story (Woolley et al., 2010)
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From page 60... ...
This relative contribution model, represented by the lower left quadrant in Table 4-1, assesses individual characteristics in a team framework. The most complex model, represented by the lower right quadrant of the table, is the team profile model, which seeks to optimize the blend, synergy, and profiles of the team members.
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From page 61... ...
They also compared the TREO characteristics with the usual Big Five ersonality p traits and found that, while there are some logical correlations, the TREO characteristics generally do not overlap with the standard personality traits. Tannenbaum said that this makes sense because the Big Five are intended to measure individual personality, while TREO is looking at how people act when they are in team settings.
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From page 62... ...
Although he has done only a few studies testing whether TREO can predict team performance, Tannenbaum views the preliminary data as promising. He briefly described results from three studies, one that looked at 45 Army transition teams and two that used student samples -- one with 110 teams doing a simulated aviation task and the other with student teams that worked together over a 10-week period on a variety of tasks (Tannenbaum et al., 2010)
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The tool, called the Team Composition System (TCS) , is still in the proto type stage, but Tannenbaum described it to illustrate possible approaches for improving team assembly.
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TCS, as Tannenbaum explained, monitors and manipulates many more factors than any individual could, so it can make the team assembly process more effective and efficient. Mechanisms and Modalities in Assembling a Team In her presentation, Leslie DeChurch described a different way of thinking about team assembly.
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DeChurch explained that currently the litera ture emphasizes only one level of factors, called team composition, but she believes there are at least four levels that should be considered. She referred to these four levels, or ways of thinking about what is important in determining the functioning of a team, as "team assembly mecha nisms," which are illustrated in Figure 4-4.
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From page 66... ...
This level goes beyond prior individual relationships, DeChurch continued, "we are only going to see it if we model the ecosystem, which includes current teams in the context of all the teams that have come before them." Team Assembly Modalities In addition to examining team assembly mechanisms, DeChurch said that it is also important to understand assembly modalities -- that is, the way in which teams are formed. For example, team members can be assigned to various teams, or they can self-organize.
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What effect does the amount of available information or the degree of agency have on team assembly mech anisms, team relationships, and, ultimately, team performance? Second, what is the relative impact of the different mechanisms on team processes, states, and performance?
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From page 68... ...
Four weeks after the teams were formed, relationships among teams were measured using sociometric surveys that captured the patterns of communication in a team, the efficacy of communication, people's confidence in their ability to work with each specific member of the team, their trust in the others on the team, and their reliance on one another for leadership of that team. As a comparison, DeChurch likened the My Dream Team Builder tool to Amazon's recommender system for products or Netflix's system for movies, she said, "only ours recommends people you might want to form a team with." People who used it provided information about their attributes and their social networks.
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in various ways. The Effect of Team Assembly Mechanisms on Formation of Team Relationships In testing whether team assembly mechanisms explained the relation ships that formed in the teams, DeChurch and her colleagues modeled those relationships in two different ways.
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. DeChurch's analysis also found that teams whose members all played a role in their organization, either by using the team builder tool or simply by choosing their friends, communicated more and were more confident in their ability to work together effectively than teams with any members who were appointed, even if three of the four team members were selforganized.
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From page 71... ...
= 4.63, F(3,25) = 4.50, p = .045, 2 = .44 p = .015, 2 = .34 p = .01, 2 = .36 p = .012, 2 = .35 Mode of Team Assembly FIGURE 4-6 The effect of team assembly modality on the density and centralization of team communication and efficacy networks.
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From page 72... ...
So this opens up a lot of interest ing possibilities about information that can be considered in advance to make a team more effective that previously would have been unavailable without some sort of infrastructure." These new possibilities, in turn, suggest three new directions in team staffing and assembly. First, she said, programmatic research on team assembly mechanisms is needed that considers all four of the l evels rather than just one.
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From page 73... ...
"What information would you want to get pre-accessioning -- which is where we collect most of this information," Goodwin asked, "and what infor mation would you want to get somewhere else, and when and where would you want to get it? " Woolley replied that social perceptiveness and communication skills are two things that could be measured in the pre-accession phase to increase the likelihood that recruits will perform better on teams.
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From page 74... ...
For example, TREO could prove to be quite useful in assisting assignment decisions, as it allows for multiple variables to be maintained and manipulated simulta neously when considering potential team combinations. DeChurch added that, when assembling groups, she considers it important to know about previous relationships among the potential team members.
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From page 75... ...
individual personality variables. So I think the intervention point there is probably more at the team level." Tannenbaum added that a related concept is team resilience, which he characterized as referring to how teams respond when they find them selves in difficult situations -- and whether they do it in a way that main tains resources and team functionality in addition to just getting through it.
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"As the unit of analysis goes up, it's more difficult to gather data." It is harder to gather data at the team level than at the individual level and harder to gather data at the organizational level than at the team level, he said. If the payoffs seem great enough, then it might make sense to carry out " nobtrusive measurements" on Army teams that have already been u assembled and are operational, specifically to gather data to use in analy ses.
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. Team assembly mechanisms deter mine collaboration network structure and team performance.
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From page 78... ...
. A meta-analytic review of relationships between team design features and team performance.
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