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A topic currently receiving significant academic and practitioner attention is called evidence-based management. The purpose of this paper is to suggest that this approach is sometimes over-sold and may be a fad. Additionally, evidence-based management fails to fully recognize the importance of tacit knowledge, what Kahneman calls system 1. Evidence-based management does provide tools to better use what Kahneman calls system 2, rationality. Decision-makers need to take advantage of both rational and beyond rational processes.

This is an essay, it is not a report of a study. At this point in time, this paper needs thinking, reflection, pondering, more than a data-based study.

Advocates promote evidence-based management in part to help avoid fads, yet evidence-based management itself has many of the characteristics of a fad. Evidence-based management is based on an objective rational view of the world and suggests highly rational methods of decision-making. However, a rational fact-based might not give sufficient credit to instinct and feelings. Decision-makers should take into account facts, evidence, when making decisions, but not ignore intuition, hunches and feelings. This study is learning that decisions use a galaxy of approaches, with both cognitive and affective flexibility.

As with any opinion-based paper, this lacks empirical support. Proponents ask us to believe in evidence-based management. Neither we, the authors of this paper, nor the proponents of evidence-based management can empirically support the ideas offered. An additional limitation is that the paper is written in one language, English. Translation into another language might yield different meanings.

There are advantages for scholars and practitioners to look at the best available evidence. There can be disadvantages in overlooking non-quantifiable factors.

Those who use evidence-based management should also take into account feelings, ethics, aesthetics, creativity, for the betterment of society. To solve wicked problems one needs more than facts and rational analysis.

The overwhelming majority of those writing about evidence-based management are supporters. This study offers a different view. This paper brings new ideas and new thinking to both the extensive fad literature and the huge evidence-based management literature. Evidence-based management is discussed widely. Google Scholar lists more than two million papers in 2019, 2020 and 2021 on evidence-based management. Readers of this journal should critically evaluate this popular set of ideas.

The coronavirus disease 2019 (COVID-19) pandemic highlighted the necessity of practicing Evidence-based Management (EBMgt) as an approach to decision-making in hospital settings. The literature, however, provides limited insight into the process of EBMgt and its contextual nuances. Such insight is critical for better leveraging EBMgt in practice. Therefore, the authors' aim was to integrate the literature on the process of EBMgt in hospital settings, identify the gaps in knowledge and delineate areas for future research.

The authors conducted a systematic scoping review using an innovative methodology that involved two systematic searches. First using EBMgt terminology and second using terminology associated with the EBMgt concept, which the authors derived from the first search.

The authors identified 218 relevant articles, which using content analysis, they mapped onto the grounded model of the EBMgt process; a novel model of the EBMgt process developed by Sahakian and colleagues. The authors found that the English language literature provides limited insight into the role of managers' perceptions and motives in EBMgt, the practice of EBMgt in Global South countries, and the outcomes of EBMgt. Overall, this study’s findings indicated that aspects of the decision-maker, context and outcomes have been neglected in EBMgt.

The authors contributed to the EBMgt literature by identifying these gaps and proposing future research areas and to the systematic review literature by developing a novel scoping review method.

The purpose of this study is to demonstrate that Strategic Enterprise Management (SEM) and Business Intelligence (BI) have the potential to integrate management decisions vertically through an organization’s hierarchy. This study also aims to present a design theory framework and build a model dimension using eight principles serving as mid-range theories.

This study uses a design science perspective to posit how organizations can successfully implement SEMBI (a union of SEM and BI). This study then completes the design theory by building the method dimension using two principles. Finally, the study presents testable hypotheses for the theory and an evaluation using stakeholder attitudes and judgments as proxies for objective measures.

In the search for a prescription for SEMBI success, this study finds that the notion of the Capability Maturity Model (CMM) is a good artifact with which to organize the principles the authors are seeking. CMM has since been adapted to suit different contexts by incorporating relevant principles from those domains. Hereafter, this study refers to SEMBI–CMM as the adapted solution for SEMBI's success.

This study coins and uses the term SEMBI to represent the union of SEM and BI. This term retains its distinct identities and principles and forms a holistic and integrated view of SEM and BI implementation strategies. In an effort to advance this line of research, this study employs a design science perspective to address the question of how an organization can successfully implement SEMBI.

This paper investigated the organizational adoption of big data analytics (BDA) in the context of supply chain planning (SCP) to conceptualize how resources are orchestrated for organizational BDA adoption and to elucidate how resources and capabilities intervene with the resource management process during BDA adoption.

This research elaborated on the resource orchestration theory and technology innovation adoption literature to shed light on BDA adoption with multiple case studies.

A framework for the resource orchestration process in BDA adoption is presented. The authors associated the development and deployment of relevant individual, technological and organizational resources and capabilities with the phases of organizational BDA adoption and implementation. The authors highlighted that organizational BDA adoption can be initiated before consolidating the full resource portfolio. Resource acquisition, capability development and internalization of competences can take place alongside BDA adoption through structured processes and governance mechanisms.

A relevant discussion identifying the capability gap and provides insight into potential paths of organizational BDA adoption is presented.

The authors call for attention from policymakers and academics to reflect on the changes in the expected capabilities of supply chain planners to facilitate industry-wide BDA transition.

This study opens the black box of organizational BDA adoption by emphasizing and scrutinizing the role of resource management actions.

The purpose of this study is to target utilizing Human resources (HRs) data analytics that may enhance strategic business, but little study has examined how it affects components. Data analytics, HRM and strategic business require empirical investigations and how to over come HR data analytics implementation issues.

A semi-systematic methodology for its evaluation allows for a more complete examination of the literature that emerges theoretical framework and a structured survey questionnaire for quantitative data collection from IT sector personnel. SPSS analyses data.

Future research is essential for organisations to exploit HR data analytics’ performance-enhancing potential. Data analytics should complement human judgment, not replace it. This paper details these transitions, the important contributions to theory and practice and future research.

Data analytics has grown rapidly and might make HRM practices faster, more efficient and data-driven. HR data analytics may improve strategic business. HR data analytics on employee retention, engagement and organisational success is insufficient. HR data analytics may boost performance, but there is limited proof. The authors do not know how HRM data analytics influences firms and employees.

Data analytics offers HRM new opportunities, along with technical and ethical challenges. This study makes a significant contribution to HR data analytics, evidence-based practice and strategic business literature. In addition to estimating turnover risk, identifying engagement factors and planning interventions to increase retention and engagement, HR data analytics can also estimate the risk of employee attrition.

The purpose of the paper is to explore the meaning of Human Resources (HR) analytics and introduce the HR analytics cycle as a proactive and systematic process for ethically gathering, analyzing, communicating and using evidence-based HR research and analytical insights to help organizations achieve their strategic objectives.

Conceptual review of the current state and meaning of HR analytics. Using the HR analytics cycle as a framework, the authors describe a seven-step process for building evidence-based and ethical HR analytics capabilities.

HR analytics is a nascent discipline and there are a multitude of monikers and competing definitions. With few exceptions, these definitions lack emphasis on evidence-based practice (i.e. the use of scientific research findings in adopting HR practices), ethical practice (i.e. ethically gathering and using HR data and insights) and the role of broader HR research and experimentation. More importantly, there are no practical models or frameworks available to help guide HR leaders and practitioners in doing HR analytics work.

The HR analytics cycle encompasses a broader range of HR analytics practices and data sources including HR research and experimentation in the context of social, behavioral and organizational science.

This paper introduces the HR analytics cycle as a practical seven-step approach for making HR analytics work in organizations.

Sharing a practitioner perspective on the current value, challenges and future direction of HR analytics, from experience in a Fortune 500 company, to contribute to the development of the field in practice and academia. The paper aims to discuss this issue.

Perspective/position paper with practical findings.

HR analytics – i.e., applied management/OE science – clearly adds value when a number of pre-conditions are met. The value goes beyond talent outcomes, and applies to profits, cyber security, safety, and other outcomes.

HR/OE practitioners and academia should continue to work together, and consider both clear monetary value and change management when working toward evidence-based HR and evidence-based management.

The approach increases the impact of for- and non-profit organizations, giving higher impact at lower cost, via more efficient and effective use of human capital and also removes biases present in approaches that are not evidence-based.

Few very large companies have shared their experiences building up HR analytics, and this paper does exactly that from a large company that has invested heavily in HR analytics and is considered a front-runner globally (Shell). This showcases to practitioners and researchers what HR analytics can be, provided proper investments are made, and practitioners and researchers work together – i.e., what the impact of HR analytics is and what the challenges and pitfalls are.