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The purpose of this paper is to explore the key ingredients that people analytics teams require to contribute to organizational performance. As the information that is currently available is fragmented, it is difficult for organizations to understand what it takes to execute people analytics successfully.

To identify the key ingredients, a narrative literature review was conducted using both traditional people analytics and broader business intelligence literature. The findings were summarized in the People Analytics Effectiveness Wheel.

The People Analytics Effectiveness Wheel identifies four categories of ingredients that a people analytics team requires to be effective. These are enabling resources, products, stakeholder management and governance structure. Under each category, multiple sub-themes are discussed, such as data and infrastructure; senior management support; and knowledge, skills, abilities and other characteristics (KSAOs) (enablers).

Many organizations are still trying to set up their people analytics teams, and many others are struggling to improve decision-making by using people analytics. For these companies, this paper provides a comprehensive overview of the current literature and describes what it takes to contribute to organizational performance using people analytics.

This paper is designed to provide organizations and researchers with a comprehensive understanding of what it takes to execute people analytics successfully. By using the People Analytics Effectiveness Wheel as a guideline, scholars are now better equipped to research the processes that are required for the ingredients to be truly effective.

The purpose of this paper is to describe a range of innovative (for public library performance measurement and impact assessment) methods and tools developed by country teams as part of the Global Libraries (GL) initiative. Short reports are provided on: a return on investment study, a simplified data processing system for library managers and an online reporting system for public libraries in Ukraine; a study of the public image of Polish libraries in print mass media, two approaches to sustainability of performance measurement and impact assessment in Romania, through tools to conduct pop-up surveys and use of agricultural subsidies support data, assessments of changes in public library managers’ planning efforts in Poland and of their perceptions of libraries and their own role, using Modified Delphi forecasting, in Lithuania, two ways of focussing on the world of public library users by engaging non-profit organizations in library research in Poland and conducting impact studies in virtual environments in Chile.

A range of methods and tools and their uses are described.

No specific research findings are reported.

All of these tools and methods have been (or are being) trialed in national public library contexts; some have been developed over several years.

Useful for people in other (non-GL) countries who may be contemplating public library evaluation at regional, national or local level or who are interested in performance measurement and impact evaluation.

This paper is part of a GL effort to share what participants have learnt about impact planning and assessment in public libraries with the wider international libraries community.

The impact planning and assessment program of GL has been the largest sustained international public library evaluation program so far attempted. This paper reports on the more innovative evaluation activities undertaken at country level through this program.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

Teamwork has long featured in social science research. Further, with research increasingly “cross-national,” communication becomes more complex, for instance, involving different cultures, languages and modes of communication. Yet, studies examining team communicative processes that can facilitate or constrain collaboration are rare. As a cross-national European team representing varied disciplines, experiences, languages and ethnicities, we undertook to examine our communication processes with the aim to promote better qualitative research practices.

Viewing reflection as a tool for enhancing workplace practices, we undertook a structured reflection. We developed an empirically derived framework about team communication, then used it to analyse our interaction practices and their relative effectiveness.

The results highlighted two under-examined influences, the use of different modes of communication for different purposes and the need for face-to-face communication to address a particularly challenging aspect of research, negotiating a shared coding scheme to analyse diverse cultural and linguistic qualitative data.

The study offers a procedure and concepts that others could use to examine their team communication.

The communicative processes that can constrain and facilitate effective cross-national research team collaboration are rarely examined. The results emphasise the need for careful negotiations around language, epistemologies, cultures and goals from the moment collaboration begins in formulating a project, through applying for grant funds, to when the last paper is published – timely in a context in which such work is increasingly expected.

A leader plays an important role in the growth of an organization. The leader is a person who influences the standards, structure, culture and behaviour of the individuals employed in the organization. A leader also has effects on the result and productivity of teams. The purpose of this paper is to analyze the effect of transformational leadership style on team performance. This paper will also analyze the existence of a relationship between transformational leadership style and team performance.

For this study, the researcher collected the data from 354 individuals employed in IT organizations in Pune. The team members answered questions asked about the transformational leadership style, and the team leaders answered questions related to team performance. The data has been analyzed using the latest available version of Statistical Product and Service Solutions.

The results of this examination suggest that there is strong and positive relationship between the transformational leadership style and team performance. Further, it was also found that transformational leader helps in a great way in improving team performance which in turn increases the organization’s productivity.

Few limitations of this research work are that the data collected for this research work is non-cognitive in nature and simultaneously respondents may incline to evaluate the positive facets of opinion poll more propitiously than negative facets. Secondly, the data have been collected only from companies located in Pune.

This research study provides empirical data that will be helpful for human resources department of an organization, as it can help them in the development of policies and practices. It will also provide help leaders to support employees who are seeking effective ways to support struggling employees in context to their team performance.

The present study can be differentiated from past studies, as it thinks over an ensemble of transformational leadership style as an essential antecedent of team performance and also enhances the knowledge of the researchers and practitioners about the leadership style that upshot to the team performance. This will also help the managers, researchers, organizational development specialist and employees who are seeking effective ways to support struggling employees in context to their team performance.

The purpose of this paper is to reference academic publications and semi-structured interviews with management experts employing a coaching style within their teams to create a platform for evaluating specific coaching mechanisms, evolving insights to the characteristics required of a manager applying coaching to deal with team challenge. A practical perspective led by managers using critical incidents to explore and highlight areas of experience and expertise in dealing with team challenge.

This qualitative assessment was derived from 30 semi-structured interviews which were recorded, transcribed and thematically analysed to assist in added insight for work-based management of dealing with team challenge. Data from 30 interviews were collected via Skype, FaceTime or Zoom to create the necessary rapport and capture the experience of dealing with team challenge. An audio record of each interview was captured to create a synchronised, fully indexed transcript from which characteristics and mechanisms could be identified.

Findings illustrated that the characteristics of the work-based manager themselves is an essential part of the mix when dealing with team challenge, the application of a coaching style accentuated the competencies and characteristics required of the manager to successfully address team challenge, demanding a specific coaching mindset. The starting point is the manager themselves knowing all the details before they intervene by utilising the traditional competencies of a professional coach.

Only one sample of 30 interviewees contributed to this research, a wider sample would be advisable, including a wider cultural base to assess characteristics in a variety of contexts. There was a wide sector representation in this research (public, private and third sector), but specific sector analysis would also be interesting to assess validity of results more rigorously.

The practical outputs from this research of the manager’s self-assessment can be used by managers as a check list when dealing with team challenge or by HR managers as an assessment tool to decide which managers to invest in coaching training. The characteristics may be a means of deciphering the skills of the managers. Finally the self-assessment could be used as a training tool to support work-based learning or coach training on how to address team challenge and offer a discussion prompt around these elements as being essential.

Coaching dialogue is a social interaction and this research contributes to enhancing the quality and purpose of social interactions in the workplace. By employing a coaching style of listening, questioning and reflecting managers can utliise a standard framework for solving issues in the workplace.

Dealing with challenge in teams through the analysis of the coaching style applied by 30 managers is unique, the value added through this research has been an enhanced appreciation of the manager as coach role and an appreciation to the established team models of Fleishman, Katzenbach and Smith, Hackman and Edmondson. This added layer enabling managers to deal with team challenge associated with our ever changing work environment.

To date, little research has been undertaken to test the effectiveness of team coaching, with past work focusing on models, frameworks and competencies. This study aimed to examine the effectiveness of team coaching within real world organizational teams and its impact on individual perceptions of team cohesion and psychological safety.

A randomized control trial (RCT) using the comparable interventions: (1) team coaching (intervention) and (2) team facilitation (control) was employed with multiple teams and multiple facilitators, measuring the impact on team cohesion and psychological safety.

The data indicate participants engaging in the team coaching intervention made greater gains in terms of their individual perceptions of psychological safety and team cohesion than individuals who received the team facilitation intervention (T1–T2).

Facilitators should apply a team coaching approach when seeking to address issues of cohesion and psychological safety within workplace teams.

This study provides the first evidence, using an RCT method, of the effectiveness of team coaching as a workplace intervention for enhancing individual perceptions of psychological safety and team cohesion.

Data science promises new opportunities for organizational decision-making. Data scientists arguably play an important role in this regard and one can even observe a certain “buzz” around this nascent occupation. This paper enquires into how data scientists construct their occupational identity and the challenges they experience when enacting it.

Based on semi-structured interviews with data scientists working in different industries, the authors explore how these actors draw on their educational background, work experiences and perception of the contemporary digitalization discourse to craft their occupational identities.

The authors identify three main components of data scientists’ occupational identity: a scientific mindset, an interest in sophisticated forms of data work and a problem-solving attitude. The authors demonstrate how enacting this identity is sometimes challenged through what data scientists perceive as either too low or too high expectations that managers form towards them. To address those expectations, they engage in outward-facing identity work by carrying out educational work within the organization and (paradoxically) stressing both prestigious and non-prestigious parts of their work to “tame” the ambiguity and hype they perceive in managers’ expectations. In addition, they act upon themselves to better appreciate managers’ perspectives and expectations.

This study contributes to research on data scientists as well as the accounting literature that often refers to data scientists as new competitors for accountants. It cautions scholars and practitioners alike to be careful when discussing the possibilities and limitations of data science concerning advancements in accounting and control.

Analytics technologies are profoundly changing the way in which organizations generate economic and social value from data. Consequently, the professional roles of data scientists and data analysts are in high demand in the labor market. Although the technical competencies expected for these roles are well known, their behavioral competencies have not been thoroughly investigated. Drawing on the competency-based theoretical framework, this study aims to address this gap, providing evidence of the emotional, social and cognitive competencies that data scientists and data analysts most frequently demonstrate when they effectively perform their jobs, and identifying those competencies that distinguish them.

This study is exploratory in nature and adopts the competency-based methodology through the analysis of in-depth behavioral event interviews collected from a sample of 24 Italian data scientists and data analysts.

The findings empirically enrich the extant literature on the intangible dimensions of human capital that are relevant in analytics roles. Specifically, the results show that, in comparison to data analysts, data scientists more frequently use certain competencies related to self-awareness, teamwork, networking, flexibility, system thinking and lateral thinking.

The study was conducted in a small sample and in a specific geographical area, and this may reduce the analytic generalizability of the findings.

The skills shortages that characterize these roles need to be addressed in a way that also considers the intangible dimensions of human capital. Educational institutions can design better curricula for entry-level data scientists and analysts who encompass the development of behavioral competencies. Organizations can effectively orient the recruitment and the training processes toward the most relevant competencies for those analytics roles.

This exploratory study advances our understanding of the competencies required by professionals who mostly contribute to the performance of data science teams. This article proposes a competency framework that can be adopted to assess a broader portfolio of the behaviors of big data professionals.

A literature review of 28 data literacy, education articles from 2010 to 2018 was conducted to gain a better understanding of the current state of data literacy research.

A systematic literature review of ERIC, Education Source, and JSTOR was conducted. Articles were included in this literature review if they focused on “data literacy” for K-12 teachers or leaders.

Results demonstrated that the concept of data literacy has become more concrete, but there is still disagreement about the parameters of the construct. While data literacy was shown to be gaining in importance, training from schools of education were focused heavily on assessment literacy. Four recommendations are made as follows: (1) create skill-focused educator prep programs, (2) encourage opportunities for collaboration, (3) model data use from both quantitative and qualitative sources and (4) investigate the role of technology and big data on data literacy.

The scope of this literature review was very narrow and, as such, does not fully encapsulate data-driven decision-making in K-12 education overall.

Data literacy is important for both teachers and leaders, as educational environments strive to better understand individual learners and improve learning outcomes. This literature review looks to pull together the current status of data literacy research with hopes of inspiring more targeted research that influences training practices for both teachers and leaders.