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The purpose of this study is to identify the specific skills and abilities within the broad category of data analytics that current business professionals believe are most important for accounting graduates. Data analytics knowledge is clearly important, but this category is broad. Therefore, this study identifies the specific skills and abilities that are most important for accounting graduates so that faculty can create classroom materials most beneficial for the future accounting graduates. In 2013, the Association to Advance Collegiate Schools of Business developed new standards for accounting programs, including standard A7, related to information technology and analytics. The intent of the standard clearly focuses on increasing the level of technology and analytics studied within the accounting curriculum. However, the specific details and methods for achieving the intent of A7 remain an open question. This chapter uses prior research focused on business analytics education to identify potential analytic skills, tools, techniques, and management issues of concern within the accounting profession. A survey of 342 accounting professionals identifies suggested areas of analytic competencies for accounting graduates. Specifically, the authors find preferences for skills related to data interpretation and communication over any individual technical skills or statistical knowledge. These skills suggest a role for accountants as intermediaries who may need to translate analytic activities into business language. Post hoc, the authors examine the survey results for differences based on respondent characteristics. Interestingly, female respondents report lower beliefs about the importance of analytic skills. The authors also find some differences when examining different demographics within the respondents.

Building information modelling (BIM) is an innovative, collaborative process underpinned by digital technologies introduced to improve project performance in the architecture, engineering and construction (AEC). Growth in industry demands has necessitated BIM inclusion into the higher education (HE) curricula as both a pedagogic and practical objective to prepare and develop aspiring built environment (BE) professionals with the required competence for contemporary practice. However, comprehension of BIM concepts and subsequent development of the skill set required for its application remains overwhelming for students. In mitigating this challenge, adopting appropriate learner-centred strategies has been advocated. Problem-based learning (PBL) is becoming a widespread strategy to address concerns associated with authentic practices.

This paper evaluates the impact of the PBL strategy on students' accelerated learning of BIM based on a case study of 53 undergraduate students in a BIM module. The network analysis and centrality measures were employed in understudying the most applicable BIM skills.

From the analyses, PBL benefits students' knowledge acquisition (cognitive and affective) of BIM concept and development of transferable skills (academic and disciplinary), equipping them with capabilities to become BIM competent and workplace ready for the AEC industry.

The BIM pedagogy evolves, and new skillsets emerge. Analytical, communications and collaboration skills remain sacrosanct to delivering BIM modules. These skills mentioned above are essential in getting undergraduate students ready to apply BIM in the AEC sector.

The study objective was to understand what components of organizational culture and capability combined with analytic skillsets are needed to allow organizations to exploit real-time analytic technologies to create supply chain performance improvements.

The authors relied on information processing theory to support a hypothesized model, which is empirically tested using an ordinary least squares equation model, and survey data from a sample of 208 supply chain executives across multiple industries.

The authors found strong support for the concept that real-time analytics will require specialized analytical skills for the managers who use them in their daily work, as well as an analytics-focused organizational culture that promotes data visibility and fact-based decision-making.

Based on the study model, the authors found that a cultural bias to embrace analytics and a strong background in statistical fluency can produce decision-makers who can make sense of a sea of data, and derive significant supply chain performance improvements.

The research was initiated through five workshops and presentations with supply chain executives leading real-time analytics initiatives within their organizations, which were then mapped onto survey items and tested. The authors complement our findings with direct observations from managers that lend unique insights into the field.

Because analytics are increasingly becoming a key source of competitive advantage, attracting, engaging and retaining analytical talent and building an organizations' analytical capability is now a key skill top management needs to learn. This paper aims to investigate this issue.

Given that analytics is a relatively new management discipline and that only a few leading companies manage the talent it requires as a strategic resource, the authors collected their best practices.

The paper specifies the four main practices that top executives need to follow to create and develop a talent‐powered analytical organization.

The authors offer anecdotal research on leading companies.

What distinguishes talent‐powered analytical organizations is their ability to unleash their analysts' talents to maximize and continually expand the company's analytical capabilities.

By building and aligning the four key talent management capabilities revealed in this paper, organizations can maximize the strategic impact of their analytical talent and continually expand the organization's collective analytical capabilities.

There has been an increasing amount of research on personnel selection in many business disciplines (Hough & Oswald, 2000; Breaugh & Starke, 2000). Research on internal auditor selection, however, has had limited exposure in the auditing literature (Bailey, Gramling, & Ramamoorti, 2003). Recently, Seol and Sarkis (2005) introduced an analytic hierarchy process (AHP) model that used a decision hierarchy based on the CFIA (competency framework for internal auditing) framework. A limitation of AHP, however, is the assumption of strict hierarchical relationship that needs to exist among factors.

The purpose of this paper is an introduction of a more robust model, the analytical network process (ANP), which relaxes the strict hierarchical and decomposition levels of the hierarchy and incorporates possible interrelationships and interdependencies of various personnel selection criteria, factors, and alternatives. In illustrating the application, we return to the CFIA model framework, describe how and where interdependencies exist amongst the CFIA factors/attributes, and how ANP is used in the internal auditor selection process. The illustration will also describe some sensitivity analysis for the ANP approach. The tool is not without its limitations that include the potential for geometrically more questions and information elicitation from the decision makers. Finally managerial and research implications associated with the technique and results are described.

In the realm of education, there has been an increasing emphasis on developing analytical thinking (AT) in the past few years. This systematic review focuses on an analysis of journal publications that have explored AT within the context of science, technology, engineering and mathematics (STEM) education. This analysis investigated four primary issues: (1) the operational definition that was used; (2) the types of theories that were used; (3) the interventions that were implemented to enhance AT skills; and (4) the research designs that were used.

To ensure a comprehensive and thorough review, we used the guidelines of preferred reporting items for systematic reviews and meta-analysis.

A comprehensive review of 28 pertinent scholarly articles reveals that scholars frequently rely on the concepts proposed by Anderson (2002), Marzano and Kendall (2008), Rodrangsee and Tuntiwongwanich (2021) and Suyatman et al. (2021) to establish a framework for delineating the competencies associated with analytical thinking (AT). Quasi-experimental designs were the most frequently used research designs in the studies analysed, followed by research and development approaches and then correlational designs. Most researchers have focused on investigating the effectiveness of problem-based learning as an intervention for improving AT skills. However, most research indicates that the theories or theoretical frameworks used to guide the research must be evident.

To the extent the authors know, this study represents the initial comprehensive examination of analytical thinking in STEM education. It presents a consolidated summary of the available evidence, assessing its quality and bringing it together in a single resource.

This study aims to enhance the understanding of competency requirements of supply chain planners and analysts (SCP&As) and identify different personal preferences of hiring managers toward job candidates’ competency profiles.

A total of 243 supply chain managers with hiring experience participated in an adaptive choice-based conjoint experiment to uncover the relative importance of six competency attributes, namely, analytical and problem-solving ability, interpersonal skills, general management skills, computer/IT skills, supply chain management (SCM) knowledge and industry experience.

SCM knowledge and analytical and problem-solving ability were identified as the most important competencies and were considered three times more important than general management skills. Based on convergent cluster and ensemble analysis, two types of hiring managers were identified. The first group is characterized by a pronounced preference for job candidates with extensive SCM knowledge. In contrast, the second group’s members prefer candidates with a more balanced competency profile.

The authors’ findings help companies to facilitate a better person–job fit, a key determinant of employee performance and job satisfaction.

This study aims to explore the emergence of the human resource (HR) analyst role. The job posts on LinkedIn display the industry demand and skills required by the organizations. This study identifies the different knowledge, skills and abilities (KSA) required for an HR analyst role in different stages of professional growth (i.e. entry-level, middle-senior level and top-level) across different industries/sectors as applicable to the crisis.

A total of 80 job posts were extracted from LinkedIn. Details such as industry, job levels, qualifications, job experience, job functions, job descriptions (JDs) and job skills (JS) were collected. Further, 30 videos were extracted from YouTube and converted into text. Text analysis was conducted using NVivo software to analyze JDs, JS and job functions. Using NVivo, word frequency, word cloud, word tree and treemap were created to visualize the data. Finally, ten in-depth interviews were conducted with senior HRA managers based in India to understand the essential competencies required for the HR analyst role and the strategies to develop them.

The findings indicate that not only technical skills are needed, but business and communication skills are particularly important for all job levels during a crisis. The JD word cloud showed words, such as data, business, support and management, and the word tree depicted HR data and change agents as important words with many related sentences as branches. General JS included analytical, communication, problem-solving and management. Technical JS were the most widely used and included structure query language, system applications & products in data processing, human capital management, TABLEAU, management information system and PYTHON. Strategies to develop these competencies included case studies, live projects, internships on HR analytics (HRAs) assignments and mentoring by senior HRA professionals.

The sample used was small, as the study included 80 job posts available on LinkedIn restricted to India. The study was restricted to qualitative approach and text analytics was used. Survey methods and a quantitative approach can be used to collect data from HR recruiters, job holders and senior leaders to understand the role of HRAs in the job market and then these variables can be tested empirically.

Based on the McCartney et al.’s (2020) competency model for the HR Analyst role, this study has explored the KSA framework using data visualization techniques and used text analytics to analyze LinkedIn job posts for different levels, videos from YouTube and in-depth interviews. It also mapped the KSA for the HR analyst role to the various stages of crisis system management given by Mitroff (2005). The use of social media analytics, such as analyzing LinkedIn data and YouTube videos, are highlighted.

Three categories of managerial skills are described as essential for effectiveness of senior managers: task, people and analytical and self‐development skills. Argues that managers at the lower level of the hierarchy value task‐related skills whereas self‐development and people‐ related skills are perceived as essential by the top management team. Suggests that although the above categories of managerial skills are somewhat broadly grouped in the literature there may exist distinct meaningful patterns of interrelationships among them which have several implications for the effective management training and development of senior managers.

Most of the studies carried out on human factor in software development concentrate primarily on personality traits. However, soft skills which largely help in determining personality traits have been given comparatively little attention by researchers. The purpose of this paper is to find out whether employers' soft skills requirements, as advertised in job postings, within different roles of software development, are similar across different cultures.

The authors review the literature relating to soft skills before describing a study based on 500 job advertisements posted on well‐known recruitment sites from a range of geographical locations, including North America, Europe, Asia and Australia. The study makes use of nine defined soft skills to assess the level of demand for each of these skills related to individual job roles within the software industry.

It was found that in the cases of designer, programmer and tester, substantial similarity exists for the requirements of soft skills, whereas only in the case of system analyst is dissimilarity present across different cultures. It was concluded that cultural difference does not have a major impact on the choice of soft skills requirements in hiring new employee in the case of the software development profession.

Specific studies concerning soft skills and software development have been sporadic and often incidental, which highlights the originality of this work. Moreover, no concrete work has been reported in the area of soft skills and their demand as a part of job requirement sets in diverse cultures, which increases the value of this paper.