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Laura Weis, PhD
Master's in Psychology and a PhD in Organisational Psychology
Today's workplace is characterized by a complex knowledge environment where information flows through a poorly understood mix of technologies, resources, and quickly changing projects and teams. This complexity has redefined office work, which is no longer seen as straightforward or procedural. Instead, employees juggle multiple tasks simultaneously, often causing interference and increasing the cognitive burden on individuals and teams alike.
Team Cognitive Load refers to the collective cognitive burden experienced by a group working together, where the combined demands on their cognitive resources exceed their capacity to process information effectively. As organizations continue to embrace more collaborative and interdisciplinary approaches, teams are often tasked with integrating diverse skill sets and knowledge bases to tackle intricate projects. This places a significant collective cognitive burden on team members, potentially overwhelming their ability to process information and make effective decisions.
Interactions with colleagues and tools are intricate and frequently involve work-arounds to standard procedures, further contributing to the cognitive load. Workspaces are no longer limited to physical areas but span across various different spaces, each with its own organizational structures and workflow demands. The shift to virtual meetings and digital communication has exacerbated this issue, changing how information is shared and processed, and often increasing the cognitive demands on teams.
Understanding and managing Team Cognitive Load has become increasingly crucial in this environment. Inadequate handling of this load can lead to errors, burnout, and reduced job satisfaction, ultimately affecting the organization's bottom line. Conversely, recognizing and mitigating excessive cognitive load can enhance team efficiency, foster a more supportive work environment, and lead to more innovative solutions.
The implications of managing Team Cognitive Load effectively are far-reaching. Organizations that prioritize this aspect of team dynamics are likely to see improvements in decision-making quality, faster problem-solving, and higher levels of employee engagement and retention. In an age where knowledge work is paramount, and the ability to innovate is a key competitive advantage, understanding and optimizing Team Cognitive Load can be a decisive factor in achieving sustained success.
Cognitive overload is similar to electrical overload—it occurs when the cognitive load exceeds sustainable levels. Momentary cognitive overload can lead to long-term cognitive drain.
Table 1 below shows theories relevant when considering team cognitive overload in organizations, where the complexity and volume of information can be overwhelming. Cognitive Load Theory (CLT) is essential for designing training and instructional materials that optimize learning without overloading team members' working memory. Cognitive Overload Theory directly addresses the negative impact of excessive cognitive load on team performance, underscoring the need to balance task demands to maintain productivity. Information Overload Theory highlights the challenges of managing vast amounts of information, which can lead to stress and decreased efficiency if not properly handled. Capacity Theory of Attention and Resource Allocation Theory provide frameworks for understanding how team members allocate their limited cognitive resources among various tasks, emphasizing the importance of prioritizing and distributing workloads effectively. Attentional Control Theory brings in the emotional aspect, illustrating how anxiety and stress can impair focus and performance, suggesting the need for supportive (social) environments that help teams manage stress.
Together, these theories inform strategies for mitigating cognitive overload, enhancing teamwork, and maintaining high levels of performance in modern organization settings. Integrating these theories allows for a holistic approach to managing team cognitive load, ensuring both individual and team productivity and well-being.
Table 1 Theories relevant to Team Cognitive Load
In a team setting, cognitive load can be distributed among its members, allowing them to collaboratively tackle more complex problems than an individual could handle alone. This collaborative approach leverages the diverse skills and perspectives within the group, leading to more innovative and effective solutions. However, it's important to consider the cognitive load caused by the need for communication, coordination, and social dynamics within the group. These transaction costs can include time spent in meetings, clarifying misunderstandings, and ensuring that everyone is on the same page.
For example, psychological safety and role ambiguity are factors that can significantly impact cognitive load. Psychological safety, the belief that one can speak up without fear, is essential for collaboration. When psychological safety is lacking, cognitive strain increases. Similarly, role ambiguity, or unclear responsibilities, adds confusion and stress. Both issues can be mitigated by establishing clear, well-defined roles, which allow team members to focus more effectively on their tasks.
While the benefits of shared cognitive load are significant, the efficiency of the group depends on effectively managing these transaction costs to maximize the group's overall productivity and problem-solving capabilities.
Measuring cognitive load through questions can indicate whether cognitive load is high or low, but it does not explain why the load is high or low or what areas need focus to reduce cognitive load, and as such is not particularly actionable. Therefore, we focus on aspects in a team setting that create cognitive load—the predictors or drivers of cognitive load. Understanding these predictors and drivers is necessary for making effective changes, similar to how understanding the predictors of employee turnover is necessary for addressing churn in organizations. By focusing on these drivers, interventions can be targeted and data-driven, fostering a supportive work environment that addresses specific employee concerns and challenges. This approach promotes systemic changes that can prevent team cognitive load from occurring, thereby enhancing employee well-being, performance, and overall organizational efficiency. We categorized these drivers into four clusters:
Teamperature is designed to be context-agnostic and usable beyond software teams.
The scale consists of self-report items. The development process was systematic, involving item generation, expert review, and psychometric evaluation to ensure the scale's accuracy and relevance for the target population.
1. Clarify the Purpose. The scale is designed to be used for research and organizational development, assessing cognitive load within teams. The target population includes teams across various industries, ensuring the scale was broadly applicable. Factors such as reading level, context specificity, and response format were considered to enhance the scale's practical relevance and usability.
2. Define the Construct. The initial step involved defining the construct of Team Cognitive Load through an extensive literature review and expert interviews. Key identified drivers included team composition (complexity and competence), member roles (role clarity, role fit, and role load), team culture (alignment, interaction, and psychological safety), task characteristics (problem definition, solution alignment, and complexity), work practices and processes (efficiency, effectiveness, adaptability), and work environment and tools.
3. Generate a Pool of Potential Likert Items. An initial pool of items was generated to cover all identified dimensions of cognitive load drivers. Each item was written to be clear, concise, and free from ambiguity, avoiding slang, jargon, and double negatives. Double-barreled and leading questions were also avoided. This initial pool contained more items than needed to ensure the final scale's psychometric robustness, allowing for the identification of sub-dimensions and related constructs.Team
4. Select and Revise Items Experts. in psychology, organizational behavior, and human resources reviewed the initial item pool. They evaluated the relevance and clarity of each item, providing feedback for revisions. The validation process involved pilot testing the items with a sample of almost 200 participants, ensuring the sample was representative of the target population, allowing for robust psychometric analysis.
5. Evaluate the Psychometric Properties
The psychometric properties of the items were evaluated through statistical analyses. Specifically, Cronbach’s Alpha for each sub-construct was calculated to ensure values between 0.7 and 0.9, thereby identifying the most accurate questions. Exploratory factor analysis was conducted to confirm consistency, and the least related question was removed to enhance tool accuracy.
Steps 4 and 5 were iterative, involving continuous refinement of the item pool based on feedback and psychometric analysis. This iterative process ensured that the final scale had strong empirical support and theoretical grounding.Team
By conducting some additional research, we further demonstrated that the scale constructs were correlated with outcomes of importance, as expected based on theory. For example, we hypothesized that high scores on cognitive load drivers would be positively associated with burnout and turnover intent, and negatively with employee satisfaction and eNPS. These assumptions were confirmed, showing significant correlations across the board.
Further, in this study, we discovered notable demographic differences in workplace experiences based on gender, remote work, sector, and other organizational factors. Females reported better conditions for continuous learning compared to males, who experienced greater role clarity. Remote workers enjoyed a superior work environment but faced higher contextual and team complexity, along with poorer knowledge exchange, compared to their in-person counterparts. In the private sector, employees encountered more contextual complexity than those in the public sector. Work familiarity was positively correlated with various sub-constructs, indicating that increased familiarity reduced cognitive load. Similarly, team familiarity also reduced cognitive load. Conversely, larger organizations and teams were associated with higher cognitive loads, with larger teams specifically linked to lower psychological safety and higher team complexity, although they had better metrics tracking.
