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Chancen und Herausforderungen bei der Verwendung von Predictive Analytics im Talent Management aus Sicht von Mitarbeitenden
Abstract
Der digitale Wandel eröffnet Unternehmen in vielen Funktionsbereichen neue Möglichkeiten, wie beispielsweise dem Bereich des Human Resource Management (HRM). Predictive Analytics gewinnt in diesem Zusammenhang zunehmend an Bedeutung, wie beispielsweise im Rahmen des Talent Managements. Durch gezieltere Förderung und Bindung von Leistungsträgern können Wettbewerbsvorteile geschaffen werden. Während die Potenziale und Herausforderungen von Predictive Analytics aus unternehmerischer Sicht bereits vielfältig diskutiert werden, stellt die Sichtweise der Mitarbeitenden auf diese neuen Ansätze eine neue Forschungsperspektive dar. In einer qualitativen Studie mit 12 Interviews wurden die Sichtweisen von Mitarbeitenden auf das Thema Predictive Analytics im Talent Management näher betrachtet. Dabei zeigte sich, dass Mitarbeitende die vielfältigen Chancen für sich und das gesamte Unternehmen erkennen. Die wahrgenommenen Herausforderungen lassen sich in die vier Themenfelder Einfluss auf Beziehungen, Datenintegrität, Ethik und Funktionalität zusammenfassen. Die identifizierten Chancen und Herausforderungen deuten darauf hin, dass eine intakte Vertrauensbasis zwischen der Orga- nisation und den Mitarbeitenden eine fundamentale Voraussetzung für eine erfolgreiche Implementierung ist. Diese Befunde verknüpfen die aktuelle Diskussion zu Predictive Analytics mit der Forschung zu HRM-bezogenen Attributionen von Mitarbeitenden und organisationalem Vertrauen.
The main purpose of this study is to analyze the main challenges and opportunities in the context of the use of innovative technologies in the management of talent in small and medium-sized craft enterprises. The systematization of literary sources and approaches has shown that the complexities of talent management processes in the personnel management system are related to the consequences of socio-economic, demographic, and climatic changes in society, the activation of globalization processes, and the rapid development of information technologies. The article analyzes the impact of digitization on the talent management process, as well as identifies the main factors that impede the transition of small and medium-sized enterprises to the use of HR software solutions. The study used methods of bibliometric analysis and predictive analytics and selected the activity of small and medium-sized craft enterprises in Germany. Literature research has shown that in most small and medium-sized craft enterprises, the decision to use innovative technology approaches to the process of talent management in small and medium-sized enterprises is the sole responsibility of the company owner. The results of data analysis using software products play an important role in reducing the risk of making wrong decisions, especially in the talent management process. In the course of the research, it is established that the use of information technologies of data processing allows us to determine the level of qualification of employees, their psychophysiological parameters, as well as to monitor the dynamics of changes of certain professional characteristics. The main threats and challenges arising from the use of information systems with elements of artificial intelligence of data processing, when managing talents, are highlighted in the work. The results presented in this article may be useful for small and medium-sized business leaders to promote the practice of using innovative technology approaches in the enterprise talent management process. Keywords: skilled labor; digitization; human resources management; small and medium enterprises, talent management.
Despite the enormous interest in human capital analytics (HCA), organizations have struggled to move from operational reporting to HCA. This is mainly the result of the inability of analytics teams to establish credible internal HCA and demonstrate its value. In this research note, I stress the importance of conceptualizing HCA as an organizational capability and suggest a method for its operationalization. I argue that the development of HCA within an organization requires working with three dimensions of HCA: data quality, analytical competencies, and strategic ability to act. Moreover, such work must be undertaken on three levels: individual, process, and structure.
Human Resources Management (HRM) is part of the organizational functions that contribute to the effectiveness of a firm’s performance, and brings an organization a competitive advantage through the implementation of its Human Resources (HR) practices. HR practices adopted by management are perceived or attributed subjectively by individual employees, and can in turn affect the employees’ attitudes and behavior (e.g. Job satisfaction and turnover intention). The purpose of this study is to contribute to the process-based approach by investigating the effect of HR attributions on turnover intentions, with job satisfaction playing a mediating role. The analysis is on the individual level, with 454 respondents from various organizations within the Netherlands. The results show that HR attributions can affect the turnover intention, through the presence of job satisfaction. Thus, it can be said that it is important to always consider the employees’ attitudes and behavior when examining their perception of HR practices, and in predicting their intention to leave.
Zusammenfassung
Unternehmen verfügen mittlerweile über fortgeschrittene analytische Informationssysteme, die es erlauben die wachsenden Datenmengen nahezu automatisiert auszuwerten und Aussagen über zukünftige Entwicklungen zu treffen. Predictive Analytics befinden sie sich im Human Capital Management noch in den Anfängen. Datengetriebene Unternehmen wie Google oder Hewlett-Packard nutzen Predictive Analytics bereits, um Personalbeschaffung und -erhaltung zu verbessern. Obwohl jedoch die Personalbereiche über umfangreiche Daten verfügen, beschränkt sich deren Nutzung nach unserer Erfahrung und einer von uns durchgeführten Befragung in den meisten Fällen immer noch auf reaktives Excel-Reporting und einfachste Prognosen z. B. zur Personalanzahl. Data Mining-Verfahren werden hingegen selten genutzt, obwohl sich daraus für das Human Capital Management und andere Unternehmensbereiche Vorteile ergeben könnten. In diesem Beitrag stellen wir anhand von Praxisbeispielen und ausgewählter Fachliteratur Potentiale von Predictive Analytics im Human Capital Management vor, untersuchen die Verbreitung sowie die Einsatzmöglichkeiten von personalbezogenen Analysen und gehen auch auf die spezifischen Herausforderungen der Nutzung von Personaldaten ein.
a r t i c l e i n f o a b s t r a c t The ongoing confusion about the meaning of 'talent' within the world of work is hindering the establishment of widely accepted talent management theories and practices. The aim of this paper is to contribute to the literature on talent management by offering an in-depth review of the talent concept within the specific context of the world of work, and proposing a framework for its conceptualization. We group different theoretical approaches to talent into 'object' (i.e., talent as natural ability; talent as mastery; talent as commitment; talent as fit) versus 'subject' approaches (i.e., talent as all people; talent as some people) and identify dynamics existing within and between them, as well as implications for talent management theory and practice. Finally, we discuss different avenues for further research aimed at developing the talent—and consequently, the talent management—construct further.
Evaluation of applicants for middle- and upper-level managerial positions and recommended starting salaries were examined in a sample of 44 male and 24 female line and staff managers. We postulated hypotheses that (a) managers would use job-relevant and job-irrelevant variables in evaluation of applicants, (b) the managers' selection decision models would involve configural cue processing, (c) managers' demographic characteristics would affect their evaluations of applicants for managerial positions, and (d) applicant sex and race would affect starting salary recommendations, after controlling for human capital variables. Subjects viewed videotaped presentations by 16 applicants and evaluated them for the job for which they were applying. Variables of applicant age, sex, race, experience, education, and level of job for which applying were manipulated. The results supported four of the five hypotheses. Job-irrelevant variables were used heavily in selection decisions, and decision models were complex, with multiple interactions among the decision cues. Subject demographic characteristics were the strongest predictors of starting salary recommendations.
We propose a systemic, multilevel framework for understanding trust repair at the organizational level. Drawing on systems theory, we theorize how each component of an organization's system shapes employees' perceptions of the organization's trust-worthiness and can contribute to failures and effective trust repair. We distinguish the framework from prior work grounded in dyadic assumptions and propose underlying principles and a four-stage process for organizational trust repair. Finally, we explore the implications for research and practice.
The trust literature distinguishes trustworthiness (the ability, benevolence, and integrity of a trustee) and trust propensity (a dispositional willingness to rely on others) from trust (the intention to accept vulnerability to a trustee based on positive expectations of his or her actions). Although this distinction has clarified some confusion in the literature, it remains unclear (a) which trust antecedents have the strongest relationships with trust and (b) whether trust fully mediates the effects of trustworthiness and trust propensity on behavioral outcomes. Our meta-analysis of 132 independent samples summarized the relationships between the trust variables and both risk taking and job performance (task performance, citizenship behavior, counterproductive behavior). Meta-analytic structural equation modeling supported a partial mediation model wherein trustworthiness and trust propensity explained incremental variance in the behavioral outcomes when trust was controlled. Further analyses revealed that the trustworthiness dimensions also predicted affective commitment, which had unique relationships with the outcomes when controlling for trust. These results generalized across different types of trust measures (i.e., positive expectations measures, willingness-to-be-vulnerable measures, and direct measures) and different trust referents (i.e., leaders, coworkers).
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Dieses Fachbuch hilft Personalverantwortlichen sowie Führungskräften und Beratern anhand von wissenschaftlichen Beiträgen und ausführlichen Fallbeispielen, sich im Wettbewerb um die besten Köpfe gut zu positionieren. Aufgrund demografischer Entwicklungen sinkt die Zahl qualifizierter Berufseinsteiger. Daher gilt es für Unternehmen, die zentralen Bedürfnisse und Erwartungen von Talenten zu erkennen und das eigene Arbeitsumfeld entsprechend zu gestalten.
Die Praxisbeiträge aus international renommierten Top-Unternehmen zeigen auf, wie die für ein erfolgreiches Talent Management erforderlichen Prozesse und Strategien entwickelt und umgesetzt werden können. 20 Leitsätze fassen die wichtigsten Erkenntnisse zusammen. Die dritte Auflage enthält erstmalig aktuelle Beiträge aus der Karriereforschung und den Sportwissenschaften sowie vier vollständig neue Fallstudien.
Der Inhalt
• Talent Management aus Sicht der Wissenschaft
• Erwartungen junger Talente an ihre Arbeitgeber
• Talent Management in der Praxis: 11 Fallbeispiele
Die Herausgeber
Prof. Dr. Adrian Ritz ist Professor am Kompetenzzentrum für Public Management der Universität Bern sowie Vorsitzender der Wissenschaftlichen Kommission für öffentliche Betriebswirtschaftslehre des Verbands der Hochschullehrer für Betriebswirtschaftslehre.
Prof. Dr. em. Prof. h. c. Dr. h. c. mult. Norbert Thom war Direktor des Instituts für Organisation und Personal (IOP) der Universität Bern. Er verfügt über umfangreiche Beratungserfahrungen im öffentlichen und privaten Sektor.
Aufgrund demographischer Entwicklungen wird zukünftig die Zahl qualifizierter Berufseinsteiger sinken. Unternehmen müssen daher heute die richtigen Entscheidungen treffen, um in einigen Jahren im Wettbewerb um die besten Köpfe gut positioniert zu sein. „Talent Management“ enthält neben wissenschaftlichen Beiträgen 13 ausführliche Fallbeispiele aus Wirtschaft und Verwaltung. Die Autoren dieser Praxisbeiträge kommen aus international renommierten Top-Unternehmen wie ABB, Audi, Microsoft, Novartis, Swisscom etc. und zeigen auf, wie die für ein erfolgreiches Talent Management erforderlichen Prozesse und Strategien entwickelt und in der Praxis umgesetzt werden können. 18 Leitsätze fassen zusammen, was Sie über Talent Management für Ihren Führungsalltag wissen müssen. Für die zweite Auflage wurden alle Texte aktualisiert.
Der Inhalt
Talent Management aus Sicht der Wissenschaft
Erwartungen junger Talente an ihre Arbeitgeber
Talent Management in der Praxis: 13 Fallbeispiele
Kritische Reflexion von Talent Management
Die Zielgruppen
Personalverantwortliche in Privatwirtschaft, Non-Profit-Organisationen und öffentlichen Institutionen
Führungskräfte und Berater
Studenten und Dozenten der Betriebswirtschaftslehre, insbesondere mit dem Schwerpunkt Personal, an Universitäten, Fachhochschulen und Akademien
Die Herausgeber
Prof. Dr. Adrian Ritz ist Mitglied der Geschäftsleitung des Kompetenzzentrums für Public Management (KPM) der Universität Bern und berät öffentliche sowie private Organisationen.
Prof. Dr. Norbert Thom Prof. h. c. Dr. h. c. mult. ist Gründer und Direktor des Instituts für Organisation und Personal (IOP) der Universität Bern und hat umfangreiche Erfahrungen in der Beratung von Regierungen, Verwaltungen sowie Unternehmen gesammelt.
Sylke Piéch stellt dar, was unter internationaler Talententwicklung zu verstehen ist, wie die Einordnung in den gesamten Talent-Management-Prozess erfolgt und wie dieses relevante Aufgabengebiet erfolgreich in die Praxis umgesetzt werden kann. Durch das Aufzeigen von konkreten Maßnahmen, Handlungsempfehlungen und Praxisbeispielen kann dieses Werk wie ein Kompass für die nationale und internationale Talententwicklung genutzt werden.
Der Inhalt
• Internationales Talentmanagement
• Talententwicklung in der Praxis
• Maßnahmen zur internationalen Talententwicklung
• Talentbindung und Mitarbeitermotivation
• Talententwicklung in der öffentlichen Verwaltung
• Unternehmensrelevanz und Praxisbeispiele aus der Wirtschaft
Die Zielgruppen
• Entscheider und Verantwortliche, sowohl auf operativer als auch auf strategischer Ebene, die die Wettbewerbsfähigkeit und Zukunft ihres Unternehmens bzw. ihrer Organisationen durch eine gezielte Personal- und Talentförderung sichern wollen
• Dozenten und Studenten der Betriebswirtschaftslehre mit dem Schwerpunkt Human Resources Management
Die Autorin
Dr. Sylke Piéch ist Direktorin des Instituts für Leadership & Human Resources Management an der
Internationalen Akademie (INA) gGmbH der Freien Universität Berlin. Zudem ist sie Geschäftsführerin des Instituts für interkulturelle Forschung und Praxis (iifp). Ihre fachliche Expertise liegt in der Personal- und Führungskräfteentwicklung, internationaler Talententwicklung, Coaching und Teammanagement sowie Diversity Management.
This research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as well as methods for assessing predictive power. Predictive analytics not only assist in creating practically useful models, they also play an important role alongside explanatory modeling in theory building and theory testing. We describe six roles for predictive analytics: new theory generation, measurement development, comparison of competing theories, improvement of existing models, relevance assessment, and assessment of the predictability of empirical phenomena. Despite the importance of predictive analytics, we find that they are rare in the empirical IS literature. Extant IS literature relies nearly exclusively on explanatory statistical modeling, where statistical inference is used to test and evaluate the explanatory power of underlying causal models, and predictive power is assumed to follow automatically from the explanatory model. However, explanatory power does not imply predictive power and thus predictive analytics are necessary for assessing predictive power and for building empirical models that predict well. To show that predictive analytics and explanatory statistical modeling are fundamentally disparate, we show that they are different in each step of the modeling process. These differences translate into different final models, so that a pure explanatory statistical model is best tuned for testing causal hypotheses and a pure predictive model is best in terms of predictive power. We convert a well-known explanatory paper on TAM to a predictive context to illustrate these differences and show how predictive analytics can add theoretical and practical value to IS research.
Suggested as a strategic necessity, practice of HR analytics along with its potential business benefits for organisations abounds in popular press. However, the issue of how employees perceive the use of predictive analytics pertaining to themselves and the impact such perceptions may have on proximal employee outcomes has received little attention. The current research reports on the results of an exploratory study that attempts to shed light on how employees' attributions of organisations' use of HR analytics relate to their commitment to the organisation. Based on this evidence, the current research provides managerial implications related to potential employee concerns with HR analytics and their ramifications for organisations, and calls for future research to investigate these issues more thoroughly and systematically.
Beatrice Katharina Bruckner geht der Frage nach, wie eine Vertrauenskultur im Kontext einer zunehmend dynamischen Arbeitswelt entwickelt werden kann. Sie zeigt, dass Vertrauen nicht nur für die Arbeitszufriedenheit der Mitarbeiter erforderlich, sondern auch für den Erfolg von Unternehmen entscheidend ist. Organisationales Vertrauen entsteht nicht zufällig und unkontrolliert, sondern kann von Beginn einer Arbeitsbeziehung an aktiv gestaltet und gefördert werden. Die Autorin thematisiert umfassend die Determinanten der Mitarbeitereinschätzung organisationaler Vertrauenswürdigkeit in der frühen Beschäftigtenphase. Sie zeigt damit für die Unternehmenspraxis, wie sich die Vertrauensgenese gerade im Beziehungsaufbau mit neuen Organisationsmitgliedern konkret fördern lässt.
Der Inhalt
• Eine Einführung in die Vertrauenstheorie
• Intraorganisationales Vertrauen
• Mixed-Methods-Untersuchungsdesign
• Einflussfaktoren der Mitarbeitereinschätzung organisationaler Vertrauenswürdigkeit in der frühen Beschäftigtenphase
• In der Unternehmenspraxis Vertrauensbildung aktiv fördern
Die Zielgruppen
• Dozierende und Studierende der Wirtschaftswissenschaften
• Manager und Personalverantwortliche aus der Unternehmenspraxis
Die Autorin
Beatrice K. Bruckner promovierte bei Prof. Dr. Egbert Kahle an der Leuphana Universität Lüneburg.
We conduct an evidence-based review using an integrative synthesis of published peer-reviewed literature on Human Resource analytics (HR Analytics). Our search of several publication databases identified 60 articles on this topic, however only 14 articles were in quality peer-reviewed journals. Our review of these articles addresses the following 5 questions: (1) What is HR Analytics (how has the concept definition evolved)? (2) How does HR Analytics work (what are the processes)? (3) Why does HR Analytics work (what theories explain cause-effect relationships, antecedents, and consequences)? (4) What does HR Analytics produce (what are the outcomes)? (5) What is required for HR Analytics to succeed (what are the moderators of the analytics-outcome relationships)? We conclude that despite evidence linking the adoption of HR Analytics to organizational performance that adoption of HR Analytics is very low and academic research, and therefore, evidence on this topic is sparse. We offer potential explanations for this paradox and suggest avenues for future research.
In this study, the authors examined the findings and implications of the research on trust in leadership that has been conducted during the past 4 decades. First, the study provides estimates of the primary relationships between trust in leadership and key outcomes, antecedents, and correlates (k = 106). Second, the study explores how specifying the construct with alternative leadership referents (direct leaders vs. organizational leadership) and definitions (types of trust) results in systematically different relationships between trust in leadership and outcomes and antecedents. Direct leaders (e.g., supervisors) appear to be a particularly important referent of trust. Last, a theoretical framework is offered to provide parsimony to the expansive literature and to clarify the different perspectives on the construct of trust in leadership and its operation.
A considerable amount of research has examined trust since our 1995 publication. We revisit some of the critical issues that we addressed and provide clarifications and extensions of the topics of levels of analysis, time, control systems, reciprocity, and measurement. We also recognize recent research in new areas of trust, such as affect, emotion, violation and repair, distrust, international and cross-cultural issues, and context-specific models, and we identify promising avenues for future research.
This research essay highlights the need to integrate predictive analytics into information systems (IS) research, and shows several concrete ways in which this can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as well as methods for assessing predictive power. Predictive analytics not only assist in creating practically useful models, they also play an important role alongside explanatory modeling in theory building and theory testing. We describe six roles for predictive analytics: new theory generation, measurement development, comparison of competing theories, improvement of existing models, relevance assessment, and assessment of the predictability of empirical phenomena. Despite the importance of predictive analytics, we find that they are rare in the empirical IS literature. The latter relies nearly exclusively on explanatory statistical modeling, where statistical inference is used to test and evaluate the explanatory power of underlying causal models. However, explanatory power does not imply predictive power and thus predictive analytics are necessary for assessing predictive power and for building empirical models that predict well. To show the distinction between predictive analytics and explanatory statistical modeling, we present differences that arise in the modeling process of each type. These differences translate into different final models, so that a pure explanatory statistical model is best tuned for testing causal hypotheses and a pure empirical predictive model is best in terms of predictive power. We “convert” a well-known explanatory paper on TAM to a predictive context to illustrate these differences and show how predictive analytics can add theoretical and practical value to IS research.
The construct of Human Resource (HR) Attributions is introduced. We argue that the attributions that employees make about the reasons why management adopts the HR practices that it does have consequences for their attitudes and behaviors, and ultimately, unit performance. Drawing on the strategic HR literature, we propose a typology of five HR-Attribution dimensions. Utilizing data collected from a service firm, we show that employees make varying attributions for the same HR practices, and that these attributions are differentially associated with commitment and satisfaction. In turn, we show that these attitudes become shared within units and that they are related to unit-level organizational citizenship behaviors and customer satisfaction. Findings and implications are discussed.
In this study, the authors examined the findings and implications of the research on trust in leadership that has been conducted during the past 4 decades. First, the study provides estimates of the primary relationships between trust in leadership and key outcomes, antecedents, and correlates (k = 106). Second, the study explores how specifying the construct with alternative leadership referents (direct leaders vs. organizational leadership) and definitions (types of trust) results in systematically different relationships between trust in leadership and outcomes and antecedents. Direct leaders (e.g., supervisors) appear to be a particularly important referent of trust. Last, a theoretical framework is offered to provide parsimony to the expansive literature and to clarify the different perspectives on the construct of trust in leadership and its operation.
Strategisches Talent-Management. Talente systematisch finden, entwickeln und binden
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