Observing effective leadership and teamwork
This guest blog is written by Dr. Desirée van Dun, Dr. Lara Carminati, Dr. Pauline Weritz, and Aninka Spekle of the Organizational Behaviour, Change Management & Consultancy (OBCC) team within the High-tech Business & Entrepreneurship department at the University of Twente.
Observing effective leadership and teamwork through The Observer XT and BIOPAC software
Society expects organizations to deal with the manifold global challenges that require major (technological) business transformation. In line with the United Nations Sustainable Development Goals, many organizations pursue digital, agile, lean, and green, and employee-healthy ways of working.
The Covid-19 pandemic accelerated the potential of fostering the professional teaming up in virtual and cross-cultural ways. Still, leaders and employees need a wide range of skills and behaviors to support these transformations and thus make a positive impact in our complex world.
To support such an impact, we, the Organizational Behaviour, Change Management & Consultancy (OBCC) team within the High-tech Business & Entrepreneurship department at the University of Twente, research how organizations, leaders, teams, and employees work together to ensure efficient improvements and effective changes. To achieve this, we apply a unique mix of complementary and interdisciplinary areas of expertise and study change processes in a wide array of organizational settings.
Video-based behavioral observation methods
OBCC is specialized in adopting a unique and powerful combination of video-based behavioral observation methods and physiological arousal measures. We used The Observer XT software and the BIOPAC measurement system to do field research to uncover the observable behaviors of effective leaders and teams.
In this blog post, we guide you through the various phases of our research, where we unveil new discoveries and explore the software's wide potential.
Phase 1: Examining how leaders behave and their leadership dynamics
In the first phase, we used The Observer XT software in, among others, a study by Van Dun et al. (2017) to explore how middle managers behave in team meetings. The study focused on examining effective leader behaviors in the context of Lean Management, a way of making organizations work better and more customer friendly.
As the 2007 financial crisis made companies rethink how they work and use their resources, Lean Management was further popularized. Although leadership is crucial in making Lean Management work, leaders' role in Lean practices has often remained unclear.
Hence, we conducted two studies to learn more about how leaders behave in Lean initiatives. In the first study, we reviewed the literature and asked Lean experts for their opinions to develop a list of behaviors and values. In the second study, we video-observed experienced middle managers in Lean Management to find out their specific values and behaviors.
In a second study, we used The Observer XT software to minutely observe 19 specific behaviors, with two independent coders. Examples of those behaviors are “asking for ideas” or “information sharing”. In doing so, we also compared the ‘Lean’ middle managers with the video-observations of another set of effective middle managers from Hoogeboom’s PhD study, which got published in 2019.
Indeed, Hoogeboom and Wilderom (2019) also used The Observer XT in their study to look at generally-effective leaders’ behaviors. For many years, there have been two main ways of thinking about leadership, transformational leadership focusing on motivating and inspiring people, and transactional leadership focusing managing tasks and giving directions.
Their study explored these two polar ways of thinking leadership and tried to dissect which behaviors were important for a leader to be successful whilst also finding better ways to measure these behaviors. Through The Observer XT software, 27 observable leaders’ behaviors were found during regular staff meetings and this helped to gain more insights into effective leadership dynamics.
Also read: How to study human behavior.
Phase 2: Examining the interaction between leaders and team members
In our second phase, we investigated not only the behavior of leaders but also that of their team members. Therefore, we video-observed team meetings as well as on the work floor through video shadowing. The findings of this research have been published in the study of Van Dun and Wilderom (2021).
This study aimed to understand how successful work teams, their leaders, and top-level leaders behave and learn from each other. Grounding our study in a theory that posits that people tend to learn by copying the behavior and values of their successful superiors, we followed five high-performing work teams for three years, using The Observer XT software to study how the teams and their leaders behave, objectively.
The study discovered a collective activity pattern known as a "coactive vicarious learning-by-doing" that helps teams perform well and consistently. Employees started to copy the behaviors of their team leaders, and leaders adapted the employees’ behaviors based on what they observed on the work floor. In other words, the teams learn by copying their leaders’ behaviors and adapting their behavioral repertoire.
The study adds to what we already know about how high-performing teams operate and learn from each other. It offers a more detailed model for how teams can get even better which can inspire future research.
Phase 3: Combining observational data and physiology
Next, based on a study performed by Hoogeboom et al. (2021), we used both The Observer XT software as well as the Empatica E4 measurement system to understand how leaders' physiological arousals are related to their behaviors and how they lead.
We collected data from 36 leaders in an organization during staff meetings, looking at both their physical responses and how they behaved by coding with the same codebook of 19 mutually exclusive behaviors. This unique study found that highly effective leaders had higher arousal levels when engaging in both positive and negative relations-oriented behaviors during meetings, such as, respectively, providing positive feedback or showing disinterest.
Interestingly, these arousal effects were not visible when leaders adopted task-oriented behaviors, such as information sharing. This suggests that effective leaders show distinct physical responses when dealing with people, which is important to consider when studying leadership.
As there currently is increasing interest in biological theories of leadership including the influence of leaders’ physiological responses (Nofal et al., 2018), this cutting-edge study paved the way for far more accurate and insightful leadership studies than the more common perceptual ones. The body never lies.
Phase 4: Measuring team dynamics
Following up on our team’s previous work, in the current fourth phase, we are using 360-degree video cameras, The Observer XT software as well as the BIOPAC measurement system to accurately observe agile team effectiveness and team members’ arousal over the course of several meetings. The advanced research equipment was co-financed by the BMS Lab, the social science innovation lab at the University of Twente (https://www.utwente.nl/en/bmslab/).
The advantage of switching from Empatica E4 to the more sophisticated BIOPAC system offered by Noldus was the possibility of promptly syncing the video observations with the arousal data, easing the data analysis. During the COVID-19 pandemic, with an extension of BIOPAC, we also pioneered the remote tracking of team members’ arousal during virtual meetings.
In this research, we investigate a multitude of factors related to team effectiveness and use the Noldus equipment and software to find new ways of measuring team dynamics over time or concepts that has gained increased attention such as psychological safety (O’Donovan et al., 2020) and emotional intelligence (Van Dun & Kumar, 2023).
In the joint webinar 'How to integrate psychophysiological and behavioral data using both Noldus and BIOPAC tools' we dive deeper into the benefits of integrating data seamlessly. Curious? Watch the webinar on demand now!
Observing effective leadership and teamwork using advanced technology
In conclusion, our journey through several research studies utilizing the powerful combination of high-tech equipment and software offered by Noldus has shed, and will continue shedding, valuable light on the intriguing but fascinating behaviors of (team) leaders and team members. These high-resolution methods allowed us to delve deeper into the behavioral dynamics within teams, providing insights that would be challenging to attain with traditional research approaches.
Our exploration into leadership and team behavior, including the coactive vicarious learning-by-doing phenomenon, has shown the potential of the combination of video and physiological recordings to uncover previously hidden aspects of human interactions in professional settings. By observing and measuring behavior with such precision, we've contributed to a richer and more actionable understanding of effective leadership and teamwork.
The ability to capture the co-occurrence of within-person variability in leaders' bodily responses and their precisely measured behaviors over time in functional social settings has been a significant milestone. Our findings have extended existing theories and opened doors for further explorations in understanding the intricate web of behaviors that shape high-performing teams.
As we look to the future, The Observer XT software and BIOPAC measurement system continue to offer a promising path for those seeking to gain a novel and more profound understanding of leadership, teamwork, and the human dynamics at play within organizations. These tools serve as beacons, guiding us to uncover the behavioral patterns that make teams thrive and leaders excel in their roles. Next steps will be to explore how algorithms might be used to optimize the behavioral coding procedure, enabling even faster data analysis and participant feedback procedures.
In the ever-evolving landscape of organizational-behavior research, we are excited to embark on the next phase of our journey, armed with these innovative technologies, as we continue to unravel the complex tapestry of leadership and teamwork.
References
Hoogeboom, M., Saeed, A., Noordzij, M. L., & Wilderom, C. P. M. (2021). Physiological arousal variability accompanying relations-oriented behaviors of effective leaders: triangulating skin conductance, video-based behavior coding and perceived effectiveness. The Leadership Quarterly, 32(6), 101493. https://doi.org/10.1016/j.leaqua.2020.101493
Hoogeboom, M., & Wilderom, C. P. (2019). Advancing the transformational–transactional model of effective leadership: integrating two classic leadership models with a video‐based method. Journal of Leadership Studies, 13(2), 23–46. https://doi.org/10.1002/jls.21655
Nofal, A. M., Nicolaou, N., Symeonidou, N., & Shane, S. (2018). Biology and management: a review, critique, and research agenda. Journal of Management, 44(1), 7-31. https://doi.org/10.1177/0149206317720723
O’Donovan, R., Van Dun, D. H., & McAuliffe, É. (2020). Measuring psychological safety in healthcare teams: developing an observational measure to complement survey methods. BMC Medical Research Methodology, 20(1). https://doi.org/10.1186/s12874-020-01066-z
Van Dun, D. H., Hicks, J., & Wilderom, C. P. M. (2017). Values and behaviors of effective lean managers: mixed-methods exploratory research. European Management Journal, 35(2), 174–186. https://doi.org/10.1016/j.emj.2016.05.001
Van Dun, D. H., & Kumar, M. (2023). Social enablers of Industry 4.0 technology adoption: transformational leadership and emotional intelligence. International Journal of Operations & Production Management, 43(13), 152-182. https://doi.org/10.1108/IJOPM-06-2022-0370
Van Dun, D. H., & Wilderom, C. P. M. (2021). Improving high lean team performance through aligned behaviour-value patterns and coactive vicarious learning-by-doing. International Journal of Operations & Production Management, 41(13), 65–99. https://doi.org/10.1108/ijopm-11-2020-0809
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