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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.

This paper aims to set out key steps in the development, engagement and retention of analytical leaders, showing why they are such a core resource, highlighting the key types of analytical talent and focusing on the core skills needed to attain analytical proficiency.

The research is based on a comprehensive survey of 799 analytical professionals employed by large US companies across a range of industries carried out in July 2008, as well as on the book Analytics at Work by Thomas Davenport, Jeanne Harris and Robert Morison, which was published in 2010.

The research identified the core skills requirements for each of the four main types of analytical talent, highlighting the skill set needed by analytical leaders. Where developing and retaining this vital resource is concerned, it was found that analysts who understood their roles were six times more likely to be engaged than those who did not.

Organizations need to take steps to develop, care for and retain their analytical talent. This is a prerequisite for establishing analytical leadership in a recruitment market where competition for analytics talent is increasing all the time.

As well as drawing on exclusive research, the paper shows that Accenture uses case studies based on in‐depth interviews and thought leadership to demonstrate analytical leaders' unique qualities.

Opportunities for professional development in online teaching are abundant. However, when the online teacher is geographically and professionally isolated from others with an interest in online teaching, use of insider research to identify areas of good online teaching practice, and those areas that require further development, affords an opportunity for self-directed professional development. Despite a plethora of methodological interpretations of autoethnography, autonetnography has until now remained no more than a methodological ideal. With my background as a registered nurse and teacher of health and social care, shifting from face-to-face teaching towards teaching online, I claim value in developing autonetnography as an insider researcher self-study, to inform my online teacher professional development needs. This chapter has two main aims: (1) to share my theoretical development of analytic autonetnography as an emerging e-research methodology and (2) to evaluate my experience of employing analytic autonetnography to research my recent online teaching practice. I will claim that whilst I have found analytic autonetnography methodologically beneficial to research my online teaching practice, I was also the author who laid the foundations, constructed and evaluated an analytic autonetnography model to test its value. Therefore, the relevance of my findings in the context of the value of analytic autonetnography as an emerging e-research methodology will remain open to debate until other researchers in the digitally mediated field experience, critique, challenge and enhance analytic autonetnography theoretically.

We have designed this in-class exercise to benefit undergraduate or graduate students enrolled in courses in auditing. This in-class exercise involves six short independent analytical procedures scenarios, two each for three different accounts: Payroll Expense; Depreciation Expense; and Interest Expense. The scenarios require students to perform substantive analytical procedures for each of the financial statement accounts. Students must use their accounting knowledge, analytical thinking skills, and problem-solving ability in order to compute an estimated expectation for an account balance. Following computing an estimate of the expected balance, students must then compare the result to the client-recorded balance and determine if the difference is within tolerable limits established for the audit. The primary learning objectives for the in-class analytical procedures exercise involve the following:

1. Understanding when it might be appropriate for the auditor to perform substantive analytical procedures,

2. Understanding how to form an expectation of an account balance when performing analytical procedures, and

3. Understanding how to evaluate the results of a substantive analytical procedure.

Understanding when it might be appropriate for the auditor to perform substantive analytical procedures,

Understanding how to form an expectation of an account balance when performing analytical procedures, and

Understanding how to evaluate the results of a substantive analytical procedure.

In cooperation with KPMG, we believe that the analytical procedures exercise gives students a better understanding of performing substantive analytical procedures. ¹ As identified by Auditing Standard AU-C 520, PCAOB Standard AS 2305, and in the academic literature (e.g., Hirst & Koonce, 1996), analytical procedures are an important part of the audit process. Understanding when and how to perform substantive analytical procedures, combined with how to evaluate the results, will aid in student knowledge of the audit process.

Over the past decade, international business and international management researchers have utilized meta-analytic approaches to synthesizing findings in the extant literature. This chapter reviews the studies published in the top five international business and management journals from 2004 to 2012. The review investigates major problems in the published meta-analyses by evaluating their overall analyses as well as the approaches utilized. The findings of this review reveal differences among the journals and improvements in the approaches applied in recent years. The chapter ends by discussing why and how international business and management researchers need to focus more on methodological fundamentals in their applications of meta-analysis.

All researchers have a self, but how many understand how their self informs their identity and world view? The use of self is vital in relationships, especially where helping others to learn is central to the role. Many occupations, such as teaching and health care, require the individual to engage in reflective practices to inform how individuals give of themselves in professional practice. Despite the potential power of analytic autoethnography, there is an absence of clear examples which clarify how the theory and method are linked. From my background as a lecturer and mental health nurse I argue the value of analytic autoethnography as research-based self-study to assist self-development. This chapter has two main aims: (i) to provide an example as to how the theory and method within analytic autoethnography articulate into a research design; and (ii) to forewarn researchers as to the areas which require early consideration when constructing an analytic autoethnography to safeguard the researcher’s psychological wellbeing. My experiences draw parallels between the cognitive reflective skills required within the research methods to review values and beliefs held within memories and mental health cognitive therapies. The potential for cathartic insights increases the researcher’s empathy to shape appropriate responses to assist others to learn.

The purpose of this manuscript is to provide a step-by-step primer on systematic and meta-analytic reviews across the service field, to systematically analyze the quality of meta-analytic reporting in the service domain, to provide detailed protocols authors may follow when conducting and reporting these analyses and to offer recommendations for future service meta-analyses.

Eligible frontline service-related meta-analyses published through May 2021 were identified for inclusion (k = 33) through a systematic search of Academic Search Complete, PsycINFO, Business Source Complete, Web of Science, Google Scholar and specific service journals using search terms related to service and meta-analyses.

An analysis of the existing meta-analyses within the service field, while often providing high-quality results, revealed that the quality of the reporting can be improved in several ways to enhance the replicability of published meta-analyses in the service domain.

This research employs a question-and-answer approach to provide a substantive guide for both properly conducting and properly reporting high-quality meta-analytic research in the service field for scholars at various levels of experience.

This work aggregates best practices from diverse disciplines to create a comprehensive checklist of protocols for conducting and reporting high-quality service meta-analyses while providing additional resources for further exploration.

This study aims to identify the appropriate combination of attributes that must be present to deliver value in a new product for a pharmaceutical enterprise.

The application object was the Metronidazole analytical standard, using choice experiments to product attributes and price.

The practical results indicate that consumer value anticipation allows entry into the market with higher competitiveness.

Conceptually, it uses a value delivery approach, generally applied to large companies, in a case aimed at enterprises. In practice, for the enterprise studied, the value anticipation by the consumer allows entry into the market with higher competitiveness.

Lean healthcare (LHC) applies lean philosophy in the healthcare sector to promote a culture of continuous improvement through the elimination of non-value-added activities. Studies on the subject can be classified as conceptual (theoretical) or analytical (applied). Therefore, this research compares bibliometric indicators between conceptual and analytical articles on LHC.

For data collection, the PRISMA Protocol was employed, and 488 articles published from 2009 to 2021, indexed in the Scopus and WoS databases, were retrieved.

This study reveals how conceptual and analytical LHC studies are organized in terms of the most relevant journals, articles, institutions, countries, the total number of citations, collaboration networks (co-authorship, international collaboration network and institutional collaboration network) and main co-words.

Only four papers conducting bibliometric analysis on LHC studies were identified in the Scopus and Web of Science databases. In addition, none of these papers compared conceptual and analytical bibliometric indicators to reveal the evolution, organization and trends of each category. Therefore, this work is not only the first to make this comparison but also the first to analyze the collaboration between authors, institutions and countries in relation to studies on LHC. The analyses performed in this work allow one new possible understanding, by researchers and health professionals, of the literature behavior in this field of study.

The purpose of this paper is to propose an effective knowledge elicitation method and representation scheme that empowers humanitarian assistance/disaster relief (HA/DR) analysts and experts to create analytic models without the aid of data scientists and methodologists while addressing the issues of complexity, collaboration, and emerging technology across a diverse global network of HA/DR organizations.

The paper used a mixed-methods research approach, with qualitative research and analysis to select the model elicitation method, followed by quantitative data collection and evaluation to test the representation scheme. A simplified analytic modeling approach was created based on emerging activity-based intelligence (ABI) analytic methods.

Using open source data on the Syrian humanitarian crisis as the reference mission, ABI analytic models were proven capable in modeling HA/DR scenarios of physical systems, nonphysical systems, and thinking.

As a data-agnostic approach to develop object and network knowledge, ABI aligns with the objectives of modeling within multiple HA/DR organizations.

Using an analytic method as the basis for model creation allows for immediate adoption by analysts and removes the need for data scientists and methodologists in the elicitation phase. Applying this highly effective cross-domain ABI data fusion technique should also supplant the accuracy weaknesses created by traditional simplified analytic models.