Project Teams
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2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Sukhwant Kaur Sagar ◽  
Olugbenga Timo Oladinrin ◽  
Mohammed Arif ◽  
Muhammad Qasim Rana

Purpose Organisational dependence on virtual project teams (VPTs) is growing dramatically due to the substantial benefits they offer, such as efficiently achieving objectives and improving organisational performance. One of the major issues that influence the effectiveness of VPTs is trust building. This study aims to determine the key factors of trust in VPTs and design a model by identifying the interrelationships among the trust factors. Design/methodology/approach Focus group discussion was used to gather data on factors affecting trust in VPTs and their interrelationships. Interpretive structural modelling (ISM) was used to establish the relationship among the factors. Cross-impact matrix multiplication applied to classification analysis was conducted to identify the driving power and the dependence power towards effective VPTs in the construction sector. Findings The finding revealed that “characteristics of team members” (such as ability, integrity, benevolence, competence, reliability and professionalism) is the most significant factor for building trust in virtual team members. Some factors were further identified as having high driving power, while others were defined as having high dependence variables. Practical implications The findings will assist construction managers and practitioners dealing with VPTs identify the factors influencing trust among team members. Taking cognisance of the factors that influence trust will enable them to design more effective virtual team arrangements. Originality/value As the first research of its kind using ISM technique, the study offers insights into interrelationships between trust factors in the construction VPTs. It provides guides for construction managers on the effective management of trustworthy VPTs.

Sharon V Medendorp ◽  
Allison Crumpler

Effective management of a clinical trialrequires having real time access to information that provides useful insightsinto trial progress and that lends itself to collaborative decisionmaking.  Data visualizations using datafrom multiple source systems employed during the conduct of a clinical trialhave become an essential tool in the recent past as support for collaborativedecision making by project teams. Having the ability to access, analyze, read,work with, and present data to support an argument are  important skills that ensure datavisualizations fulfill their purpose in clinical trial management. There is anexpectation that members of the clinical trial team either possess or developthe data literacy skill sets necessary to collaborate on the successfulexecution of a clinical drug development trial. Here we describe thedevelopment of a Data Learning Series program targeted to increase the data literacyskills within a Contract Research Organization in support of the digitalevolution of the drug development industry.

Daniel MBURASEK ◽  

Efficient team formation presents challenges both for the industry and the academia, especially among first year students. In academia, the difficulty is due to a lack of familiarity between instructors and new students at the beginning of each semester while in the industry, the issue is the incomplete picture of new employee’s personality by the supervisors. The quality of the team greatly affects both the team member experience as well as the outcome of assigned projects. There is a strong need to create a tool or a program that allows instructors and supervisors to create effective teams with evenly distributed skills amongst the teams in a timely fashion. Studies show that the balance of skills, rather than the presence of highly skilled individuals, leads to successful teams. The ultimate goal is to create a tool that will give teams the opportunity to operate at their maximum potential. This paper focuses on the creation of teams for first year students of engineering. The outcome is based on the results of a project assigned to a team of second year engineering students. The choice of second year students was dictated by the need to have students who had already experienced the adverse effects of malfunctioning teams during their previous projects. The goal of the project was to design a software and user interface for a tool that instructors could use to create optimal project teams in an efficient manner.

Zsolt T. Kosztyán ◽  
Eszter Bogdány ◽  
István Szalkai ◽  
Marcell T. Kurbucz

AbstractThe adequate allocation of human resources is one of the most important success factors in software projects. Although project teams can be regarded as complex systems in which a team’s performance is highly influenced by the interdependencies among team members, the allocation methods applied to date have focused only on individual skills and consider project teams as units of isolated workers. The existing software project scheduling problem (SPSP) is extended to (1) consider different skills and efficiencies of employees and (2) examine the pairwise synergies between them, as well as to (3) handle the flexible structure of the project that is used in flexible management, such as agile project management. To better understand the impact of synergies on the project’s cost, the solutions of the traditional and extended SPSP versions are analyzed and compared on the generated project networks. The results show not only that this factor has a highly significant impact but also that the project cost strongly depends on the structural parameters of the synergy network (e.g., topology, network size and degree centrality). Among these parameters, a low degree of centrality and some topologies, most notably star and circular networks, obtained the highest reduction in the projects’ total cost.

Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 664
Pavol Mayer ◽  
Tomáš Funtík ◽  
Ján Erdélyi ◽  
Richard Honti ◽  
Tomo Cerovšek

This paper addresses critical success factors for the delivery of BIM projects. The lack of experience with BIM projects on both the demand and supply side often leads to insufficient project teams, unsatisfied clients, schedule, and cost overruns. In order to better structure and control the information delivery in BIM projects requirements, planning and delivery must be standardized. The latter was achieved by EIR (Exchange Information Requirements), new BIM roles, BEP (BIM Execution Plan), and specified digital handover, which must be supported by a common data environment (CDE). This paper provides an analysis of the characteristics of BIM project delivery and duration in Architectural and Engineering companies in Slovakia. The analysis is based on the web survey of BIM managers and coordinators, which reveals that a significant amount of BIM project efforts must be executed by BIM specialists. The results also graphically depict the scope of critical BIM activities across project phases. The presented study is relevant for various project stakeholders and allows for a deeper understanding of the resources needed for the successful delivery of BIM projects in terms of adequate project team capacity, capability, organization, and planning.

2021 ◽  
Vol 157 (A1) ◽  
M Nordin

This paper presents a new method for operational analysis (OA) as a tool in simulation based design (SBD) for Naval Integrated Complex Systems (NICS), here applied to the submarine domain. An operational analysis model is developed and described. The first step of the design process is to identify and collect the needs from the customer and stakeholders, from which requirements can be deduced and designed in an organized way, i.e. requirement elucidation. It is important to evaluate the benefits or penalties of each requirement on the design as early as possible during initial design. Thus the OA-model must be able to evaluate requirements aggregated in synthesised ships such as initial concepts, i.e. Play-Cards, as representations of a submarine concept in the functions domain where the first set of requirements are designed, and establish their Measure of Capability (MoC) and Measure of Effectiveness (MoE). The work has resulted in an OA-model for submarine design that can be used during the development and for evaluation during the life cycle of a submarine system. The purpose of integrating OA in the design process is to explore the design space and evaluate not only technical solutions and cost but also the system effect in the early phases and thereby find and describe a suitable design room. This will generate a more rapid knowledge growth compared to the classic basic ship design procedures which focus on technical performance and cost. It is expected that we not only reach a higher level of knowledge about the design object but also achieve higher precision in the compliance to needs and deduced and designed requirements by the use of an OA-model as an integrated tool during initial design. This approach also invites customer participation within the framework of integrated project teams.

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Hamidreza Abbasianjahromi ◽  
Mehdi Aghakarimi

PurposeUnsafe behavior accounts for a major part of high accident rates in construction projects. The awareness of unsafe circumstances can help modify unsafe behaviors. To improve awareness in project teams, the present study proposes a framework for predicting safety performance before the implementation of projects.Design/methodology/approachThe machine learning approach was adopted in this work. The proposed framework consists of two major phases: (1) data collection and (2) model development. The first phase involved several steps, including the identification of safety performance criteria, using a questionnaire to collect data, and converting the data into useful information. The second phase, on the other hand, included the use of the decision tree algorithm coupled with the k-Nearest Neighbors algorithm as the predictive tool along with the proposing modification strategies.FindingsA total of nine safety performance criteria were identified. The results showed that safety employees, training, rule adherence and management commitment were key criteria for safety performance prediction. It was also found that the decision tree algorithm is capable of predicting safety performance.Originality/valueThe main novelty of the present study is developing an integrated model to propose strategies for the safety enhancement of projects in the case of incorrect predictions.

2021 ◽  
Fakhriya Shuaibi ◽  
Mohammed Harthi ◽  
Samantha Large ◽  
Jane-Frances Obilaja ◽  
Mohammed Senani ◽  

Abstract PDO is in the process of transforming its well and urban planning by adopting digital technologies and Artificial Intelligence (AI) to improve organizational efficiency and maximize business value through faster quality decision. In 2020, PDO collaborated with a third-party contractor to provide a novel solution to an industry-wide problem: "how to effectively plan 100's of wells in a congested brownfield setting?". This paper describes an innovative AI-assisted well planning method that is a game-changer for well planning in mature fields, providing efficiency in urban and well trajectory planning. It was applied in one of PDO's most congested fields with a targeted infill of 43m well spacing. The novel well planning method automatically designs and optimizes well trajectories for 100-200 new wells while considering surface, subsurface and well design constraints. Existing manual workflows in the industry are extremely time consuming and sequential (multiple man-months of work) - particularly for fields with a congested subsurface (350+ existing wells in this case) and surface (limited options for new well pads). These conventional and sequential ways of working are therefore likely to leave value on the table because it is difficult to find 100+ feasible well trajectories, and optimize the development in an efficient manner. The implemented workflow has the potential to enable step change in improvements in time and value for brownfield well and urban planning for all future PDO developments. The innovative AI assisted workflow, an industry first for an infill development of this size, evaluates, generates and optimizes from thousands of drillable trajectories to an optimized set for the field development plan (based on ranked value drivers, in this case, competitive value, cost and UR). The workflow provides a range of drillable trajectories with multi-scenario targets and surface locations, allowing ranking, selection and optimization to be driven by selected metrics (well length, landing point and/or surface locations). The approach leads to a step change reduction in cycle time for well and urban planning in a complex brownfield with 100-200 infill targets, from many months to just a few weeks. It provides potential game-changing digital solutions to the industry, enabling improved performance, much shorter cycle times and robust, unbiased well plans. The real footprint and innovation from this AI-assisted workflow is the use of state-of-the-art AI to enhance team collaboration and integration, supporting much faster and higher quality field development decisions. This paper describes a novel solution to integrated well planning. This is a tangible example of real digital transformation of a complex, integrated and multi-disciplinary problem (geologists, well engineers, geomatics, concept engineers and reservoir engineers), and only one of very few applied use cases in the industry. This application also gives an example of "augmented intelligence", i.e. how AI can be used to truly support integrated project teams, while the teams remain fully in control of the ultimate decisions. The success of this approach leans on the integrated teamwork across multiple technical disciplines, not only involving PDO's resources, but also WhiteSpace Energy as a 3rd party service provider. The enhanced collaboration allowed all parties to highlight their constraints in an integrated way from the start, strengthening the technical discussion between disciplines and learning from each constraint impact and dependencies. (e.g. dog leg severity). In summary, the change in process flow moving from a sequential well planning and urban planning method to an iterative and fast AI solution – including all technical considerations from beginning represented for PDO an added value of over 6 months of direct cycle time HC acceleration.

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8235
Nataliia Dotsenko ◽  
Dmytro Chumachenko ◽  
Igor Chumachenko ◽  
Andrii Galkin ◽  
Tomasz Lis ◽  

The paper examines the impact of the COVID-19 pandemic on human resource management processes in project-oriented companies. It is proposed to use formal transformations on groups of performers. The use of formal transformations will reduce the influence of the subjective factor and improve the quality of sustainability management decisions made when forming a project team. The formalization of the selection process of applicants and the distribution of work among the performers have been considered. The existing methods of forming a project team with functional redundancy are approximate. Methodological support for the process of forming a project team with functional redundancy, based on a logical-combinatorial approach, and allowing to form project teams under given constraints, is proposed. A method of forming a functionally redundant project team based on formal transformations of groups of performers has been developed. The use of the apparatus of symbolic sequences for the formation of a project team with functional redundancy is proposed. An example of using the proposed method when forming a command with functional redundancy is considered. It is shown that the use of this methodological support makes it possible to select the composition of the project team with the minimum number and the minimum value of the characteristic.

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