Role of a Strategic Management Team in Conflict Resolution: A Case Study of IKEA

The thesis looked into and investigated the topic at hand as a case study of IKEA's strategic management team in dispute resolution. Organizational operations changes have a cascade effect on marketing and human resource management, undermining efforts at standardization and localization. Workplace disagreement can jeopardise organizational goals, leading to dysfunction and excessive competition. Workplace conflict must be addressed before it has a detrimental impact on team productivity and leads businesses to lose money. However, workplace disagreements can lead to the formation of positive relationships, peer learning, enhanced communication, new ideas, and increased motivation. We used transformational leadership theory to look at how senior account managers deal with conflict at work for this study. The thesis looked at IKEA's marketing techniques for forming a strategic management team to handle conflicts, and it was based on extensive research and accurate data.

New Digital Well Construction Planning Solution: Improving Efficiency & Quality of Well Design through Collaboration and Automation

Drilling wells with minimum risk and optimizing well placement with the least possible cost are key goals that companies strive to achieve. The major contributor to the successful execution of the well is the quality of the drilling program. Well design is a complex process, which requires full collaboration of multiple domain roles & expertise working together to integrate various well-planning data. Many design challenges will be encountered, such as risk assessments, domain-specific workflows, geological concerns, technology selections, cost & time estimation, environmental and safety concerns. Design process efficiency depends on effective communication between parties, quickly adapting to any changes, reducing the number of changes, and reducing complicated & manual processes. Current existing workflow and tools are not promoting an excellent collaborative environment among the different roles involved. Engineers utilize multiple engineering applications, which involved many manual data transfers and inputs. The different party is still working in a silo and sharing the design via email or other manual data transfer. Any changes to the design cause manual rework, leading to inconsistency, incoherency, slow decision & optimization process, and failure to identify all potential risks, increasing the well planning time. The new digital planning solution based on cloud technology allows the design team to maximize the results by giving them access to all the data and science they need in a single, standard system. It's a radical new way of working that gives engineers quicker and better-quality drilling programs by automating repetitive tasks and validation workflows to ensure the entire plan is coherent. This new planning solution allows multiple roles & domain collaboration to break down silos, increase team productivity through tasks assignment, and share all data. An automated trajectory design changes the way engineers design trajectory from manually connecting the path from a surface location to the target reservoir location to automatically calculate & propose multiple options with various KPIs allowing the engineer to select the best trajectory option. The system reinforces drilling program quality through auto engineering analysis, which provides quick feedback for any design changes and provides an integrated workflow from the trajectory design to operational activity planning and AFE. The automation of repetitive tasks, such as multiple manual inputs, frees domain experts to have more time to focus on creating new engineering insights while still maintaining design traceability to review updates over the life of the projects and see how the design changes have optimized the drilling program. This new solution solves some of the significant challenges in the current well-planning workflow.

Continuous Integration for Machine Learning Experiments Reproducibility: a Practical Study

The development of a Machine Learning (ML) model depends on many variables in its training. Both model architecture-related variables, such as initial weights and hyperparameters, and general variables, like datasets and framework versions, might impact model metrics and experiment reproducibility. An application cannot be trustworthy if it produces good results only in a specific environment. Therefore, in order to avoid reproducibility issues, some good practices need to be adopted. This paper aims to report a practical experience in developing a machine learning application adopting a workflow that assures the reproducibility of the experiments and, consequently, its reliability, improving the team productivity.

Tool for Measuring Productivity in Software Development Teams

Despite efforts to define productivity, there is no consensus in the software industry regarding what the term productivity means and, instead of having only one metric or factor that describes productivity, it is defined by a set of aspects. Our objective is to develop a tool that supports the productivity measurement of software development teams according to the factors found in the literature. We divided these factors into four groups: People, Product, Organization, and Open Source Software Projects. We developed a web system containing the factors that influence productivity identified in this work, called Productive, to support software development teams in measuring their productivity. After developed the tool, we monitored its use over eight weeks with two small software development teams. From the results, we found that software development companies can use the system to support monitoring team productivity. The results also point to an improvement in productivity while using the system, and a survey applied to users demonstrates the users’ positive perception regarding the results obtained. In future work, we will monitor the use of the tool and investigate the users’ perceptions in other project contexts.

“No, We’re Not!” the Classification and Impact of Blocking Behavior in Design Team Meetings

This paper proposes a framework through which emergent disagreements during design team meetings may be classified by their tendency to reinforce or challenge the status quo. We investigate the use of the framework in measuring the effects of these disagreements on team productivity. The Interaction Dynamics Notation (IDN) [1] provides the basis for identifying disagreements through blocking behavior. Kirton’s Adaption-Innovation (A-I) Theory [2] is used to classify the style of a Block as Adaptive (status quo-preserving) or Innovative (status quo-challenging). Emergent disagreements like Blocks are potentially risky during team meetings, because they obstruct the flow of discussion. However, certain styles of Blocks, as classified using A-I Theory, may be better suited to idea generation and thus, be worth the risk. This paper addresses the following questions: (1) Can IDN Blocks be reliably classified using A-I Theory constructs? (2) How do different styles of Blocks impact productivity (e.g., the generation of ideas) during design meetings? A set of 104 Blocks observed in 14 academic teams during design ideation sessions was coded using the proposed framework and reliably determined to be Adaptive, Innovative, or Neither. Blocks were not entirely inhibitory and led to new design ideas under certain conditions. Neither Adaptive nor Innovative Blocks led to more efficient generation of ideas. Innovative Block sequences had greater variance in length than Adaptive Block sequences, while Deflected Blocks more frequently led to idea generation than Overcome or Unresolved Blocks. This research has implications for the productivity of design teams in their problem solving and decision making across settings in academia and industry.

A case for increasing exemplary followership in organizations

Purpose In today’s rapidly changing workforce environment, organizations seek ways to increase productivity to remain competitive. The central human capital strategy is to attract the best talent and increase individual and team productivity to reach its strategic goals. Human Resources (HR) Professionals are required to attract, retain, train and develop employees to exhibit critical citizenship behaviours. The purpose of this paper is to present organizational-based research on why exemplary followers are considered valuable, as well as contribute to the understanding and discourse of the important role “exemplary followers” have for organizations. Extant followership constructs will be linked to key HR processes to illustrate how organizations can select, develop and retain “exemplary followership” to safeguard organizational sustainability. Design/methodology/approach A brief overview of HR systems and processes to enhance exemplary followership in employees is presented for training and development purposes. A range of research and practitioner papers are reviewed with the aim of illustrating the importance of and the key constructs for exemplary followership and to suggest practical applications for its development within organizations’ HR processes. Findings By understanding the importance and implications of exemplary followership development, the author will suggest practical HR tools that may be adopted, whole or in part, thus improving organizational sustainability. Practical implications Providing ways for HR to increase exemplary followership through learning and growth might help to expand practical followership development programmes in organizations at all levels. Originality/value This paper has drawn on limited followership organizational performance research done in the USA and Ghana and overall research in this area. It has discussed the Followership Continuum Model as a prescriptive tool for organizations to use. All Followership research has simply provided foundational constructs to be used in the original work the author developed for increasing exemplary followership in organizations through HR processes. There is no research like this to the author’s knowledge.

A Statistical Model to Assess the Team's Productivity in Agile Software Teams

Agile methods promise to achieve high productivity and provide high-quality software. Agile software development is the most important approach that has spread through the world of software development over the past decade. Software team productivity measurement is essential in agile teams to increase the performance of software development. Due to the prevalence of agile methodologies and increasing competition of software development companies, software team productivity has become one of the crucial challenges for agile software companies and teams. Awareness of the level of team productivity can help them to achieve better estimation results on the time and cost of the projects. However, to measure software productivity, there is no definitive solution or approach whether in traditional and agile software development teams that lead to the occurrence of many problems in achieving a reliable definition of software productivity. Hence, this study aims to propose a statistical model to assess the team’s productivity in agile teams. A survey was conducted with forty software companies and measured the impact of six factors of the team on productivity in these companies. The results show that team effectiveness factors including inter-team relationship, quality conformance by the team, team vision, team leader, and requirements handled by the team had a significant impact on the team’s productivity. Moreover, the results also state that inter-team relations affect the most on software teams’ productivity. Finally, the model fit test showed that 80% of productivity depends on team effectiveness factors.

The Mediating Effect of Teams Cohesion in the Relationship between Internal Recruitment and Teams Effectiveness at Jordanians Industrial Shareholding Companies

It was proved by research that teamwork in manufacturing organizations increases productivity, enhances organizations efficiency and guarantees quality of outputs. In this context, synergy, cooperation, strong relationships and coordination are essential to achieve the expected yield of teamwork. It is difficult to attain the required level of cohesiveness in the short run and among new employees. So that this study aims to find out the impact that internal recruitment has on both teams effectiveness in terms of (team productivity and quality of performance) and also on teams cohesion as a mediator between internal recruitment and teams effectiveness. The “Jordanian industrial shareholding companies” formed the population of the study, (43) Companies of these agreed to be part of the study, 260 questionnaires were distributed targeted production managers and supervisors. The results confirmed the cause and effect relationships between the three variables with the implication that internal recruitment has several benefits not only on teams’ effectiveness and teams’ cohesion, but also on job satisfaction and job commitment. Based on the results it is recommended to instill the teamwork spirit and cooperation culture within organizations. Lately this organizational unity became crucial for reducing the negative consequences of the COVID-19 pandemic.

An Instrument for Measuring Perception about Social and Human Factors that Influence Software Development Productivity

In terms of productivity in software development, there is specific interest in identifying its influencing factors. For this purpose, several classification approaches have been previously used, which have already recognized technical factors, organizational factors, product factors, project factors, and personal factors. However, these approaches often focus on technical factors over social and human factors (SHFs). Nevertheless, in addition to the obvious technical aspects, the software development process involves problem-solving skills and cognitive aspects and social interaction. In this sense, determining SHFs can lead to software organizations designing strategies for improving team productivity. In this study, we first conducted a preliminary classification of the SHFs identified in the literature. Because this study seeks to assess the factors from the standpoint of software development professionals, we developed and validated an instrument to measure the perception of software development team members about SHFs that may be affecting their productivity. For this purpose, the first four stages of survey-based research were followed: objective definition, survey design, instrument construction, instrument validity, and reliability assessment. The instrument included 79 items assessing 13 different SHFs. After assessing both their validity and reliability, the results demonstrated that the instrument is a valid and reliable tool for measuring SHFs perception among software development team members.