Exploring the effective agile team model: a qualitative mixed-methods study among practitioners

Purpose Self-managing, cross-functional agile teams are popular, but the predictors of team effectiveness require more study to address a growing need to understand team functioning in complex, constantly-changing, technology-driven environments. This paper aims to report an empirical exploration and enrichment of the predictive model of effective agile teams (EAT) stemming from a previously conducted systematic literature review. Design/methodology/approach A qualitative mixed-methods approach was taken, which started with ten semi-structured interviews with five agile-team scholars and five senior agile practitioners who critically reviewed the EAT model. The adapted model was then further explored by group interviewing six agile teams. All data was analyzed following the Gioia methodology. Findings The EAT model captured the most important agile team effectiveness predictors and was further refined and advanced by removing redundancies (e.g. by integrating “clarity on roles and goals” into the predictor “shared mental models”) and the lowest scoring predictor “team modification” which occasionally contributes to EAT. Closed-loop communication was seen as the most essential predictor followed by team trust. Originality/value Traditional team effectiveness models contrast, on certain aspects, with agile team effectiveness characteristics. This research extends the existing EAT model into a more dynamic one of continuous team adaptation, to explain the inner workings of EATs and brings actionable insights. Agile practitioners will benefit from using the enriched EAT model to improve team effectiveness and, ultimately, lay the foundation to foster an agile culture.

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Publication Details

Journal
Team Performance Management
Published
2025-11-06
DOI
https://doi.org/10.1108/tpm-09-2024-0103
Primary Topic
Team Dynamics and Performance
Type
article
Field-Weighted Citation Impact
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article

Exploring the effective agile team model: a qualitative mixed-methods study among practitioners

Carla A.J. Bastiaansen, Desirée H. van Dun
Team Performance Management
Team Dynamics and Performance
article

Exploring the effective agile team model: a qualitative mixed-methods study among practitioners

Carla A.J. Bastiaansen, Desirée H. van Dun
article en

Abstract

Purpose Self-managing, cross-functional agile teams are popular, but the predictors of team effectiveness require more study to address a growing need to understand team functioning in complex, constantly-changing, technology-driven environments. This paper aims to report an empirical exploration and enrichment of the predictive model of effective agile teams (EAT) stemming from a previously conducted systematic literature review. Design/methodology/approach A qualitative mixed-methods approach was taken, which started with ten semi-structured interviews with five agile-team scholars and five senior agile practitioners who critically reviewed the EAT model. The adapted model was then further explored by group interviewing six agile teams. All data was analyzed following the Gioia methodology. Findings The EAT model captured the most important agile team effectiveness predictors and was further refined and advanced by removing redundancies (e.g. by integrating “clarity on roles and goals” into the predictor “shared mental models”) and the lowest scoring predictor “team modification” which occasionally contributes to EAT. Closed-loop communication was seen as the most essential predictor followed by team trust. Originality/value Traditional team effectiveness models contrast, on certain aspects, with agile team effectiveness characteristics. This research extends the existing EAT model into a more dynamic one of continuous team adaptation, to explain the inner workings of EATs and brings actionable insights. Agile practitioners will benefit from using the enriched EAT model to improve team effectiveness and, ultimately, lay the foundation to foster an agile culture.

Team Performance ManagementVol. 31(7-8)
Politecnico di Milano (IT), University of Twente (NL)
Openalex Percentile: Top 63%
Team Dynamics and Performance
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