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Team Intelligence The Foundations of Intelligent Organizations - A Literature Review
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The underlying change driving an increased use of groups and teams for coordination is the increasing specialization, and the number of experts and specialists needing to come together and coordinate. This, in turn, drives complexity, and the only way for organizations to deal with complexity in the long run is by intelligence, that is intelligent coordination. Essential in this intelligent coordination of organizations will be the group level. Teams or micro-systems is the operational unit in which the organization’s need of coordination becomes dependent of the intelligence, behavior, emotional and social skills of individuals. These factors create a variance in collective intelligence. Average collective intelligence at micro-system level is therefore a fairly new way of describing organizational performance. The purpose of this report, which is a literature review, is to give an overview of how collective intelligence at micro-system level has been defined, how it relates to organizational performance, what factors have been identified as causing variance and what types of interventions at team level have been discussed. A total of 92 articles and two dissertations were selected based on a search of EBSCO/Business Source Premier.
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... Lack of authority in an organization can also lead to dishonest information, which can impede the flow of information and lead to unequal distribution of that information. Other research has established a causal link between an individual's intellectual capacity and the collective intelligence of the organization they work for Glynn (1996), Runsten (2017). It is believed that an organization's intelligence should include a network of "expert analyzers" and information technology that helps validate and analyze to the extent that can transform knowledge into actionable intelligence that can support the sense-making and decision-making processes within the organization (Wilensky 1967;Glynn 1996;De Angelis 2013). ...
... It is the collective intelligence of the organization's human resources that gives the organization its intelligent quality (Glynn 1996;Runsten 2017). The authors were strong believers in the effectiveness of collective intelligence, of which an organization's intelligence cannot be produced in the absence of a collective of intelligence derived from its human resources. ...
Despite the fact that many managers and researchers have discussed the idea on organizational intelligence and subject its impact on an organization's efficiency; however, there has been relatively little analysis of the literature on the subjects. This study aims to describe facilitative relationship between organizational intelligence and an organization’s effectiveness as well as generalize the definitions of organizational intelligence. In other words, this study will highlight some of the elements that support the notion that organizational intelligence contributes to increase organizational effectiveness. Additionally, this article will also offer managerial recommendations for improving an organization's capacity for learning and adapting, hence increasing organizational intelligence. The paper concludes with a critique of previous studies and directions for future research.
... Intelligence manifests in the capacity to learn, understand, adapt, and influence others within a specific context (Runsten, 2017). According to Jean et al. (2020), Ci materialises based on how well a group collaborates with the perspective that individual actions become a collective system. ...
This study, ‘Adaptive-Intelligence Learning Architecture: Utilising an African aphorism to increase organisational adaptive quotient’, investigated the challenges organisations face within an exponentially disrupted business environment. The research problem studied is the possible incapacity of the organisation’s current learning systems to rapidly increase an organisation’s adaptive quotient. The problem encases the growing possibility of the dehumanisation of organisations through vast technological disruptions. Therefore, the study aims to describe a novel learning architecture utilising an African humanness aphorism that could increase organisational adaptive quotient when re-settling into any ‘new normal’.
The qualitative abductive approach to the research is based on post-positivism and metamodernism within conceptual relativism and a social constructivism philosophy. A blended research methodology, using hermeneutic phenomenology and grounded theory, was utilised to distil the phenomenon’s essence, telling the story of the life experience of the research participants in their current and foreseen future world of work. The study, which took place between 01 October 2019, and 30 November 2021, followed a multi-step design that collected multi forms of research data from 15 participants who were interviewed individually, three focus group discussions and, 14 teams with 120 participants in total were observed.
The study delivered a complexity of findings, which centre on the five themes identified during selective coding. In broad terms, the study found that most current learning efforts lack an intentional focus on Organisational Adaptive Quotient. Most Organisational Learning Systems (OLS) show low connectedness and collectiveness, indicative of a slow reaction to problem ecologies. There is a general ignorance of the Coherence-Correlation-Dynamics required within learning efforts. Most OLSs do not actively promote the Adaptive Intelligence of their people system. Finally, the study’s key findings further indicated Requirements for a new learning architecture that can oscillate between enabling the OLS and energising the OLS.
The study’s results present an Adaptive-Intelligence Learning Architecture (AiLA) framework. The AiLA framework advocates for an organisational learning system that weaves adaptive intelligence into its learning efforts focused on competency improvement. Through its focus on organisational adaptive quotient, the AiLA places African Humanness as the core energy of the learning system to provide the energy to the architecture in combating system entropy.
Key Words: Adaptive-Intelligence, Organisation Adaptive Quotient, AiLA Framework, African Humanness, ‘Being levels’ of existence, Learning Architecture, Organisational Learning System, Spiral Dynamics, Metamodernism, Integral, African Aphorism
... A number of HR specialists believe that one of the most priority areas will be the management of changes in teamwork (International trends in personnel management, 2020; Runsten, 2017) and, first, the change of human resources itself, both external (the use of exocortex, neural network HTTP 2.0 protocols and biological feedback, active cooperation/symbiosis with artificial intelligence, etc.) and internal (development of engagement and meta-competencies, first of all cognitive-communicative, the use of more complex multi-focus logical models of the reality description, visual thinking technologies and system analytics, that take into account dynamic complexity and network hierarchy of problem situations in the mode of initiality and self-building) (Belbin, 2003). Among the most actual goals of personnel management with the use of artificial intelligence for the issues of team management, these should be highlighted: considering new requirements related to dynamics of career and educational trajectories of teams; the need for mobile cognitive selection that considers psych emotional contacts and neurophysiological features; active learning, first of all, meta-competencies in real time and on a regular basis; creating a systematic "positive" employee experience for an employer brand; developing HR platforms that have analytics functions, including predictive one; new leadership -"digital leader" and transform-teams in symbiosis with artificial intelligence resources (Fedotova, 2019); the development of cultural diversity and equal opportunities; open talent economy; robots, cognitive computing and artificial intelligence (International trends in personnel management, 2020). ...
The article considers issues related to the use of artificial intelligence methods in the technoscience concept while moving from personnel management to human resource management using artificial intelligence elements. Authors consider the development of human resources at the expense of cognitive-communicative resources of personnel in specific (transformed) conditions of consciousness when a synergy of neurocognitively enhanced human capabilities and artificial intelligence occurs. Such situations are considered in predicting the productivity of project teamwork, characterized by various aspects: organizational, cognitive-communicative, socio-psychological, etc. It is analyzed a specific example of predictive analytics related to the assessment of future results of newly created teams (shift teams) and results that are corrected based on already existing teams (V. K. Finn’s DSM-method of automatic hypotheses generation, as a way to organize knowledge using the non-Aristotelian structure of concepts, 2009). Some difficulties of using the shift form of labour organization are considered. The methodology for predicting the teams’ assessment is based on the results of express diagnostics of their work on specific test cases and the general database of characteristics and results already existing successful and unsuccessful teams.
... For the analysis of the technology acceptance characteristics across the four groups, this study conducted a one-factor analysis of variance (ANOVA) considering the model variables from the UTAUT (Venkatesh et al., 2003), which is a widespread and accepted theory of technology acceptance. In particular, we considered technology-related (i.e., performance expectancy, effort expectancy), contextual (i.e., social influence, facilitating conditions), and psychological acceptance and usage factors (i.e., hedonic motivation, attitude) (Venkatesh et al., 2003;Runsten, 2017;Dwivedi et al., 2019). In addition, we considered individual involvement (Svendsen et al., 2011). ...
This study provides new insights into the dynamics of attribute-specific customer requirements in innovation processes. For this purpose, a panel study with three survey time points was conducted based on the Kano model. These time points were localised before and after the launch of a novel scientific online platform. In contrast to previous research, subjects’ responses were linked across the three measurement time points. This matching of the respondents enabled the identification of segments of homogeneous time-dependent shifts in customer requirements and their description based on sociodemographic, acceptance- related, and usage-based characteristics. The results provide academics and managers with practical implications and avenues for future research.
... The stated obstacles encountered when coordinating multiple forms of expertise and intellectual diversity motivate discussion of, first, the notion of collective intelligence and, second, what leadership is and how it should be exercised in TD projects. Although definitions vary (for an overview, see [27]), collective intelligence can be seen as a collective competence that, according to Heylighen, occurs when "a group of initially independent agents develop a collective approach to the tackling of some shared problem that is more powerful than the approach any of them might have developed individually" [28] (p. 1); he argues that the emergence of collective intelligence is intrinsically a process of selforganization since a single individual leader would likely impose a consensus view on the other group members. ...
Although issues concerning indoor environments and their interaction with humans span many disciplines, such as aerosol technology, environmental psychology, health, and building physics, they are often studied separately. This study describes a research project with the transdisciplinary aim of bridging such disciplinary boundaries. Semi-structured interviews were conducted with the twelve project members to explore their understanding of transdisciplinarity regarding the conceptual as well as social aspects of collective learning and leadership and the measures taken to achieve this. The interviews were coded in NVivo (QSR International, Doncaster, Australia), which was used to identify themes concerning notions associated with transdisciplinarity, collective leadership, collective intelligence, and learning. A shared understanding of transdisciplinarity meant that the researchers transcended their disciplinary boundaries by moving into each other’s fields. This collective learning process was facilitated by introductory lectures on each other’s fields, contributing to collective leadership and a safe atmosphere. We argue that a transdisciplinary approach is appropriate in order to address indoor environment issues as well other complex problems, for which additional time and resources should be allocated for individual and collective learning processes.
... Included within this review are studies that: attempt to directly or conceptually replicate a collective intelligence factor (i.e., the c-factor) in the broader context of its effect on group performance; completed data collection and reporting between the initial publication of Woolley et al. in September 2010 and November 2019-including published or unpublished reports. Articles/reports were excluded if: quantitative results were not available by publication, pre-print, or inspection by personal request (e.g., Jones 2015); they were based on simulation rather than data representing real humans (e.g., Chmait et al. 2016;De Vincenzo et al. 2018); results were primarily conceptual and/or qualitative such as case studies, ethnographies, essays, or conceptual reviews (e.g., Gunasekaran et al. 2016;Krafft 2018;Nagar 2016;Runsten 2017;Salminen 2012); full text was not available in English (e.g., Del Cerro et al. 2016); used empirical methods, such as a survey or questionnaire, but failed to employ the group IQ testing approach outlined in Woolley et al. (2010) (e.g., Kaur andShah 2018;Lee and Jin 2019); failed to explicitly test for the existence of the c-factor and/or its effect on group performance (e.g., Hansen and Vaagen 2016). ...
Collective intelligence (CI) is said to manifest in a group’s domain general mental ability. It can be measured across a battery of group IQ tests and statistically reduced to a latent factor called the “ c- factor.” Advocates have found the c- factor predicts group performance better than individual IQ. We test this claim by meta-analyzing correlations between the c- factor and nine group performance criterion tasks generated by eight independent samples ( N = 857 groups). Results indicated a moderate correlation, r , of .26 (95% CI .10, .40). All but four studies comprising five independent samples ( N = 366 groups) failed to control for the intelligence of individual members using individual IQ scores or their statistically reduced equivalent (i.e., the g- factor). A meta-analysis of this subset of studies found the average IQ of the groups’ members had little to no correlation with group performance ( r = .06, 95% CI −.08, .20). Around 80% of studies did not have enough statistical power to reliably detect correlations between the primary predictor variables and the criterion tasks. Though some of our findings are consistent with claims that a general factor of group performance may exist and relate positively to group performance, limitations suggest alternative explanations cannot be dismissed. We caution against prematurely embracing notions of the c- factor unless it can be independently and robustly replicated and demonstrated to be incrementally valid beyond the g- factor in group performance contexts.
... Further, the adjectives that describe organizations capable of "operational art", such as intelligence agencies an d special forces, are the same adjectives which have high correlations with trait openness [20,70,141,142]. Openness is not the only component of Five -Factor analysis which may offer insight on the personality and intelligence of organizations -as analyses of the organizational equivalents of components such as neuroticism and conscientiousness have been done as well [143,144]. . Following this mapping between intelligence of individuals and intelligence of teams, there is a literature on "Goal Setting" whic h has been used as a dynamical analogy to catalyze the development of Artificial Intelligence [145]. ...
... Further, the adjectives that describe organizations capable of "operational art", such as intelligence agencies an d special forces, are the same adjectives which have high correlations with trait openness [20,70,141,142]. Openness is not the only component of Five -Factor analysis which may offer insight on the personality and intelligence of organizations -as analyses of the organizational equivalents of components such as neuroticism and conscientiousness have been done as well [143,144]. . Following this mapping between intelligence of individuals and intelligence of teams, there is a literature on "Goal Setting" whic h has been used as a dynamical analogy to catalyze the development of Artificial Intelligence [145]. ...
Our society is progressing from an industrial society to a knowledge society and thereby establishing constant changes with unprecedented extent and speed. This is due to the urge of mankind to improve quality of life by gaining knowledge and insights, and to the steadily increased power of information technology. For enterprises, the changing environment constantly opens new chances and existential risks, which force them to adapt to their changing contexts on time. So, to survive and succeed, enterprises must organize digital transformation as a process to steadily shape their future, and they must consider their context in a wider scope than usual. Also, entrepreneurs are facing increasing challenges. With these insights, we propose a novel human-centric view on enterprises, their digital transformation, and their position in the society. It combines technical and business levers with enterprise culture. We introduce a reference model-based approach for a continuous, holistic enterprise evolution and focus on the orchestrated solution provider (OSP) as the future enterprise model. It supports the entrepreneur and self-responsible teams to master digital transformation and to sustain the success of their enterprise in the knowledge society. In this sense, the OSP follows the vision of Industry 5.0 for a sustainable, human-centric and resilient European industry, while going far beyond with its holistic view.
Purpose: An interorganizational learning (IOL) Web-based platform provides an ambidextrous working area, where employees can switch between exploration and exploitation-related activities. This study aims to present new indications on how to increase the acceptance and use of Web-based platforms for IOL. Specifically, it proposes how acceptance rates can be increased by focusing on the key mechanisms in Web-based platforms that are important from the users’ perspective. Design/methodology/approach: Survey data were collected from employees in universities, companies, government agencies and research and technological development performers. Data analysis applies a multi-group analysis (MGA) based on the partial least squares structural equation modeling. Findings: Performance expectancy is important in explorative, exploitative and ambidextrous organizations. Moreover, effort expectancy is an important driver of platform acceptance in explorative organizations, facilitating conditions in exploitative organizations and hedonic motivation in ambidextrous organizations. Originality/value: This study contributes to the IOL literature by analyzing specific acceptance characteristics of potential users of a Web-based IOL platform for research and development. As the first paper published in this research context, it explicitly considers explorative, exploitative and ambidextrous organizations based on interactive and integrative interorganizational ambidexterity.
Shared Leadership: Reframing the Hows and Whys of Leadership brings together the foremost thinkers on the subject and is the first book of its kind to address the conceptual, methodological, and practical issues for shared leadership. Its aim is to advance understanding along many dimensions of the shared leadership phenomenon: its dynamics, moderators, appropriate settings, facilitating factors, contingencies, measurement, practice implications, and directions for the future. The volume provides a realistic and practical discussion of the benefits, as well as the risks and problems, associated with shared leadership. It will serve as an indispensable guide for researchers and practicing managers in identifying where and when shared leadership may be appropriate for organizations and teams.
Measuring and managing for team performance: Emerging principles from complex environments" Teamwork has always been an important component of successful military operations. However, as the nature of military operations evolves in the post-cold war era, the ability of teams to work effectively in a dynamic and complex environment may play an even more critical role. As the nature of military organizations evolves and becomes more complex, it will be important to understand why some teams function better than others and how to instill the requisite skills in numerous geographically dispersed teams. The authors of this paper extracted twenty principles of teamwork from studies of decision making teams working in three complex tactical naval settings. Nine of the principles regard the nature of teamwork; seven regard team leadership; four regard the roles of individual team members. The findings presented here provide suggestions for managing teams effectively, measuring team performance, and for training teams in complex settings. They have application to peacekeeping operations, which are highly complex.