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Over the past few years, developments in business analytics have provided strategic planners with promising instruments for dealing with turbulent environments. This study…
Over the past few years, developments in business analytics have provided strategic planners with promising instruments for dealing with turbulent environments. This study aims to reveal whether or not the application of business analytics in strategic planning contributes to better company performance, and to formulate recommendations on how to integrate business analytics in companies' performance management systems.
Based on a survey conducted with 89 respondents from high‐technology firms, a group comparison between firms with strong performance and those with weak performance reveals significant differences between the two groups' strategic planning processes and application of business analytics.
The empirical survey's results show that better‐performing companies are characterized by a more sophisticated analytical planning process. Lower‐performing firms acknowledge this competitive advantage. Based on these findings, the authors develop recommendations on how to integrate business analytics in performance management contexts.
The empirical study's results are limited to high‐technology industries in the cultural setting of Germany.
The empirical results emphasize the competitive advantage gained by applying business analytics. The recommendations concerning analytical performance management should help managers to sensibly integrate the analytical toolbox in performance management contexts.
This paper combines insights on the best usage of business analytics from the perspective of strategic planning experts, with recommendations for the integration of business analytics into the performance management framework from an academic perspective.
The purpose of this article is to explore the importance of workplace learning in the context of performance measurement on an organisational level. It shows how workplace…
The purpose of this article is to explore the importance of workplace learning in the context of performance measurement on an organisational level. It shows how workplace learning analytics can be grounded on professional identity transformation theory and integrated into performance measurement approaches to understand its organisation-wide impact.
In a conceptual approach, a framework to measure the organisation-wide impact of workplace learning interventions has been developed. As a basis for the description of the framework, related research on relevant concepts in the field of performance measurement approaches, workplace learning, professional identity transformation, workplace and social learning analytics are discussed. A case study in a European Public Employment Service is presented. The framework is validated by qualitative evaluation data from three case studies. Finally, theoretical as well as practical implications are discussed.
Professional identity transformation theory provides a suitable theoretical framework to gain new insights into various dimensions of workplace learning. Workplace learning analytics can reasonably be combined with classical performance management approaches to demonstrate its organisation-wide impact. A holistic and streamlined framework is perceived as beneficial by practitioners from several European Public Employment Services.
Empirical data originates from three case studies in the non-profit sector only. The presented framework needs to be further evaluated in different organisations and settings.
The presented framework enables non-profit organisations to integrate workplace learning analytics in their organisation-wide performance measurement, which raises awareness for the importance of social learning at the workplace.
The paper enriches the scarce research base about workplace learning analytics and its potential links to organisation-wide performance measurement approaches. In contrast to most previous literature, a thorough conceptualisation of workplace learning as a process of professional identity transformation is used.