Synergistic Team Composition

Effective teams are crucial for organisations, especially in environments that require teams to be constantly created and dismantled, such as software development, scientific experiments, crowd-sourcing, or the classroom. Key factors influencing team performance are competences and personality of team members. Hence, we present a computational model to compose proficient and congenial teams based on individuals' personalities and their competences to perform tasks of different nature. With this purpose, we extend Wilde's post-Jungian method for team composition, which solely employs individuals' personalities. The aim of this study is to create a model to partition agents into teams that are balanced in competences, personality and gender. Finally, we present some preliminary empirical results that we obtained when analysing student performance. Results show the benefits of a more informed team composition that exploits individuals' competences besides information about their personalities

Formalisation and use of competencies for industrial performance optimisation : a survey.

For many years, industrial performance has been implicitly considered as deriving from the optimisation of technological and material resources (machines, inventories,...), made possible by centralized organisations. The topical requirements for reactive and flexible industrial systems have progressively reintroduced the human workforce as the main source of industrial performance. Making this paradigm operational requires the identification and careful formalisation of the link between human resource and industrial performance, through concepts like skills, competencies or know-how. This paper provides a general survey of the formalisation and integration of competence-oriented concepts within enterprise information systems and decision systems, aiming at providing new methods and tools for performance management

A methodology for prospective operational design co-ordination

Engineering companies are continually faced with the challenge of how best to utilise their design team given some design project. Decisions regarding how to distribute the project workload amongst the members of the design team are the responsibility of a project manager who, in order to do this, often relies upon previous experience and/or the support of some planning tool. Furthermore, a project manager rarely has the opportunity to assess the capability of the design team against the current work load in order to determine what, if any, alterations couldbe made to the team to facilitate appropriate reductions in project time and cost.This paper proposes a mathematical-based methodology aimed at identifying shortfalls in design teams, which if remedied would result in a more efficient project in terms of time and cost. The methodology provides a means of identifying those skills within the design team,with respect to the outstanding work load, in which improvements would have the greatest influence on reducing time and cost. In addition, the methodology employs a genetic algorithm for the purpose of scheduling tasks to be undertaken by potential design teams. The methodology is applied to two practical case studies provided by engineering industry.The first case study involves the assessment of a multi-disciplined design team consisting of single-skilled engineers. In contrast, the second case study entails the assessment of multiskilled engineers within a multi-disciplined design team. As a result of applying the methodology to the case studies, potential improvement to the design teams are identified and, subsequently, evaluated by observing their effects

Capturing the effect of personality on teams with agent-based modelling

Continuing advances in information and communication technology (ICT) have changed the landscape of project management. Now there are increasing occurrences of short-term projects staffed by ad hoc assemblies of temporary team members who have been quickly recruited from a candidate population. However, there is little in the way of general guidelines available concerning how to manage these volatile situations. In particular there are no established approaches for more effective assembly of ad hoc project teams with respect to the collective psychological makeup of the team members. This thesis makes a contribution in this area by providing an examination into improved ways of assembling ad hoc project teams with respect to the psychological (personality) profiles of team members in order to produce more effective project outcomes. This thesis is divided into three main sections. In the first section, we investigate how the strategies that determine the composition of teams can affect team performance. Because of the autonomous nature of team members, we employ agent-based modelling techniques that can be used to predict the assembly of teams and their ensuing performance. Our agent-based simulations in the first section of this thesis demonstrate emergent effects based on different parametrisations. In order to compare the outcomes of these models with real-world situations, a practical method of simply determining individual personality types is needed. In this regard, we have used the Myers-Briggs Type Indicator (MBTI) index to identify personalities. In the second part of the thesis, we develop a team formation model to explain how self-assembly teams tend to evolve in the area of software development. In order to develop an agent-based model intended to predict the teams’ compositions, we describe our assumptions about the factors affecting team formation. A model is developed to explain the mechanism behind team formation and the extent to which our assumptions can predict the compositions of teams. Our model has been validated against a case study known as the “Python Enhancement Proposal” (PEP), which is used by small ad-hoc software teams to enhance the Python programming language. In order to discover the personality of a PEPs developer, we make an additional contribution in this thesis: that is, developing a novel model that infers the MBTI specification of personality from the candidate team members’ writing styles. By comparing PEPs data with the results produced from our agent-based simulations, we can identify the factors that explain the mechanisms behind team formation. In this study, we identified four significant input factors that affect team composition and performance: previous performance, teammate familiarity, MBTI Feeling personality, and MBTI Perceiving personality. The third part of this thesis focuses on the relationships between the personalities of a team and the team’s group performance. We introduced a data-driven methodology that can be customised for different organisations to discover the relationship between personality and team performance. In addition, we identified the team compositions that can result in better performance. One hypothesis that was tested and confirmed in this connection is the positive effect of personality heterogeneity on the performance of software development teams. The thesis makes several methodological and practical contributions. In this thesis, not only have we developed and tested how people do form into a team, but also we investigate how people should form into a team. The models and techniques developed in this thesis can be used to guide and help managers to investigate the assembly and evolution of temporary ad-hoc work teams. Managers can apply these models in connection with conducting various “what-if” analyses by simulating the behaviour of teams under different circumstances

A Complexity-Based Approach to Intra-Organizational Team Selection

Early studies recognized the significance of team's work capacity and suggested the selection of team members based on individual skills and performance in alignment with task characteristics. The equitable team selection method, for example, assigns people to different tasks with even skill distributions for the best overall performance. Recent advancement in organization science also identifies the importance of contextual skills. However, work teams are complex adaptive systems with interdependence between workers and social environment, and exhibit surprising, nonlinear behavior. Optimizing individual stages without taking organizational complexity into account is unlikely to yield a high performing new combination of teams. The objectives of this study can be stated as: a) Utilizing complex system theory to better understand the processes of team selection including forming teams with considering worker's interdependence and replacing the unsuitable members through a time frame; b) Comparing different team selection methods, including random selection, equity method, using knowledge of interdependence in different economic conditions through simulation; c) Comparing different policies of replacing members of teams. This study utilizes a computational model to understand the complexity of project team selection and to examine how diversity of capability and interdependence between workers to effect team performance in different economic conditions. The NK model, a widely used theory for complex systems is utilized here to illustrate the worker's interdependence and fed into an Agent-Based Model. This study uses a small design firm as a case implementation to examine the performance of a variety of team selection approaches and replacement policies. Project data, task assignment, and individual and team performance information were collected for the period of 2009-2011. The simulation results show that while the equity selection method can increase the diversity of capabilities of teams, the net performance is often worse than optimizing worker interdependencies. This study suggests that managers should protect their higher-performing workers with minimal interdependence disruption when they considered team selection. Thus taking the advantages and disadvantages of all three policies into account, transferring low contributors or least supported members are recommended to be enacted before hiring new workers to avoid this last policy's especially large additional costs

Including Generative Mechanisms in Project scheduling using Hybrid Simulation

Scheduling is central to the practice of project management and a topic of significant interest for the operations research and management science academic communities. However, a rigour-relevance gap has developed between the research and practice of scheduling that mirrors similar concerns current in management science. Closing this gap requires a more accommodative philosophy that can integrate both hard and soft factors in the construction of project schedules. This paper outlines one interpretation of how this can be achieved through the combination of discrete event simulation for schedule construction and system dynamics for variable resource productivity. An implementation was built in a readily available modelling environment and its scheduling capabilities tested. They compare well with published results for commercial project scheduling packages. The use of system dynamics in schedule construction allows for the inclusion of generative mechanisms, models that describe the process by which some observed phenomenon is produced. They are powerful tools for answering questions about why things happen the way they do, a type of question very relevant to practic

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Human Factors in Agile Software Development

Through our four years experiments on students' Scrum based agile software development (ASD) process, we have gained deep understanding into the human factors of agile methodology. We designed an agile project management tool - the HASE collaboration development platform to support more than 400 students self-organized into 80 teams to practice ASD. In this thesis, Based on our experiments, simulations and analysis, we contributed a series of solutions and insights in this researches, including 1) a Goal Net based method to enhance goal and requirement management for ASD process, 2) a novel Simple Multi-Agent Real-Time (SMART) approach to enhance intelligent task allocation for ASD process, 3) a Fuzzy Cognitive Maps (FCMs) based method to enhance emotion and morale management for ASD process, 4) the first large scale in-depth empirical insights on human factors in ASD process which have not yet been well studied by existing research, and 5) the first to identify ASD process as a human-computation system that exploit human efforts to perform tasks that computers are not good at solving. On the other hand, computers can assist human decision making in the ASD process.Comment: Book Draf

An optimization model for group formation in project-based learning

We propose an optimization model to tackle the problem of determining how projects are assigned to student groups based on a bidding procedure. In order to improve student experience in project-based learning we resort to actively involving them in a transparent and unbiased project allocation process. To evaluate our work, we collected information about the students\u27 own views on how our approach influenced their level of learning and overall learning experience and provide a detailed analysis of the results. The results of our evaluation show that the large majority of students (i.e., 91%) increased or maintained their satisfaction ratings with the proposed procedure after the assignment was concluded, as compared to their attitude towards the process before the project assignment occurred