Only as Strong as the Strongest Link: The Relative Contribution of Individual Team Member Proficiency in Configuration Design

Prior research has demonstrated how the average characteristics of a team impact team performance. The relative contribution of team members has been largely ignored, especially in the context of engineering design. In this work, a behavioral study was conducted with 78 participants to uncover whether the most or least proficient member of a configuration design team had a larger impact on overall performance. Proficiency is an individual's ability to deal with a specific range of problem. It was found that a configuration design team is most dependent on the proficiency of its most proficient member. The most proficient member had a significant positive effect on how quickly the team reached performance thresholds and the other members of the team were not found to have the same positive impact throughout the design study. Behavioral heuristics were found using hidden Markov modeling to capture the differences in behavior and design strategy between different proficiency members. Results show that high proficiency and low proficiency team members exhibit different behavior, with the most proficient member's behavior leading to topologically simpler designs and other members adopting their designs, leading to the most proficient member driving the team design and thus the team performance. These results underscore the value of the relative contribution model in constructing engineering teams by demonstrating that different team members had unequal effects on team performance. It is shown that enhancing the most proficient member of a team is more likely to contribute to increased team performance than enhancing the least proficient member.

[1]  P. John Clarkson,et al.  Managing Sociotechnical Complexity in Engineering Design Projects , 2019, Journal of Mechanical Design.

[2]  Christopher McComb,et al.  Using Hidden Markov Models to Uncover Underlying States in Neuroimaging Data for a Design Ideation Task , 2019, Proceedings of the Design Society: International Conference on Engineering Design.

[3]  Sorin Vâlcea,et al.  Weakest Link Goal Orientations and Team Expertise: Implications for Team Performance , 2019, Small Group Research.

[4]  Elizabeth A. Klock,et al.  Embracing Complexity: Reviewing the Past Decade of Team Effectiveness Research , 2019, Annual Review of Organizational Psychology and Organizational Behavior.

[5]  Eduardo Salas,et al.  Foundations of Teamwork and Collaboration , 2018, The American psychologist.

[6]  Christopher McComb,et al.  Mining Process Heuristics From Designer Action Data via Hidden Markov Models , 2017 .

[7]  Christopher McComb,et al.  Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test , 2017 .

[8]  Caitlin Tenison,et al.  Modeling the distinct phases of skill acquisition. , 2016, Journal of experimental psychology. Learning, memory, and cognition.

[9]  Christopher McComb,et al.  Lifting the Veil: Drawing insights about design teams from a cognitively-inspired computational model , 2015 .

[10]  Christopher McComb,et al.  Rolling with the punches: An examination of team performance in a design task subject to drastic changes , 2015 .

[11]  John R. Anderson,et al.  Discovering the Sequential Structure of Thought , 2014, Cogn. Sci..

[12]  John E. Mathieu,et al.  A Review and Integration of Team Composition Models , 2014 .

[13]  Ingrid C. Chadwick,et al.  The emergence of team helping norms: Foundations within members' attributes and behavior , 2012 .

[14]  D. Meyer,et al.  Supporting Online Material Materials and Methods Som Text Figs. S1 to S6 References Evidence for a Collective Intelligence Factor in the Performance of Human Groups , 2022 .

[15]  Jr. G. Forney,et al.  Viterbi Algorithm , 1973, Encyclopedia of Machine Learning.

[16]  Leslie A. DeChurch,et al.  The cognitive underpinnings of effective teamwork: a meta-analysis. , 2010, The Journal of applied psychology.

[17]  Ute R. Hülsheger,et al.  Team-level predictors of innovation at work: a comprehensive meta-analysis spanning three decades of research. , 2009, The Journal of applied psychology.

[18]  Tammy L. Rapp,et al.  Team Effectiveness 1997-2007: A Review of Recent Advancements and a Glimpse Into the Future , 2008 .

[19]  Suzanne T Bell,et al.  Deep-level composition variables as predictors of team performance: a meta-analysis. , 2007, The Journal of applied psychology.

[20]  G. Stewart A Meta-Analytic Review of Relationships Between Team Design Features and Team Performance , 2006 .

[21]  Terence R. Mitchell,et al.  How, When, and Why Bad Apples Spoil the Barrel: Negative Group Members and Dysfunctional Groups , 2006 .

[22]  Nigel Cross,et al.  Expertise in Design: an overview , 2004 .

[23]  Dennis J. Devine,et al.  Do Smarter Teams Do Better , 2001 .

[24]  Cynthia J. Atman,et al.  A comparison of freshman and senior engineering design processes , 1999 .

[25]  Bob J. Wielinga,et al.  Configuration-Design Problem Solving , 1997, IEEE Expert.

[26]  Gina J. Medsker,et al.  RELATIONS BETWEEN WORK GROUP CHARACTERISTICS AND EFFECTIVENESS: IMPLICATIONS FOR DESIGNING EFFECTIVE WORK GROUPS , 1993 .

[27]  Kipling D. Williams,et al.  Interpersonal Relations and Group Processes Social Loafing: a Meta-analytic Review and Theoretical Integration , 2022 .

[28]  Sanjay Mittal,et al.  Towards a Generic Model of Configuraton Tasks , 1989, IJCAI.

[29]  S. Harkins,et al.  Effects of task difficulty and task uniqueness on social loafing. , 1982 .

[30]  B. Bass Team Productivity and Individual Member Competence , 1980 .

[31]  Robert A. Moffitt,et al.  The Uses of Tobit Analysis , 1980 .

[32]  L. Baum,et al.  A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .

[33]  Andrew J. Viterbi,et al.  Error bounds for convolutional codes and an asymptotically optimum decoding algorithm , 1967, IEEE Trans. Inf. Theory.

[34]  J. Tobin Estimation of Relationships for Limited Dependent Variables , 1958 .