ARPHA Conference Abstracts : Conference Abstract
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Conference Abstract
Leveraging Technology and data Analytics in Performance Management- An Exploratory Study on its Evolution: the when, now, and hereafter
expand article info Rosemary Isioma Obi
‡ College De Paris, La Défense, Paris, France
Open Access

Abstract

In the words of Douglas Conant of the Campbell Soup Company, "To win in the marketplace, you must first win the workplace." Embedding performance management as a cultural cornerstone is imperative for any organization aspiring to succeed in the marketplace. Campbell's theory of performance (Campbell 1990) defines performance as behaviors or actions relevant to the organization's goals and measurable in terms of contribution to those goals. These behaviors are distinguished from effectiveness, which is the impact of behaviors on outcomes. Performance management ensures efficiency, effectiveness, and productivity by facilitating planning, monitoring, and evaluating individual and organizational performance to achieve strategic goals. Performance management involves goal setting, feedback, coaching, and evaluation to align employee efforts with strategic goals and foster accountability and continuous improvement. Historically criticized for its rigidity and lack of timeliness, performance management has evolved, propelled by technological advancements and data analytics (Swan 2015). 

This abstract summarizes the critical role of technology and data analytics in transforming performance management systems. It highlights the shift from traditional methods to modern, agile, and data-driven practices, emphasizing the potential of emerging technologies to revolutionize the field further. The study spotlights the importance of adopting these innovations to enhance managerial effectiveness, employee satisfaction, and organizational competitiveness in the digital age. Despite their limitations, the traditional performance management methods laid the foundation for modern performance management systems.

The evolution of performance management from criticized models lacking flexibility to agile, data-driven systems has been facilitated by technology, enabling organizations to access real-time performance data and sophisticated analytics tools for proactive decision-making and personalized feedback (Pulakos et al. 2015). This shift marks a departure from static evaluations to adaptive practices empowered by technological advancements (Buckingham and Goodall 2015). Integrating technology and data analytics has revolutionized performance management, leveraging AI and machine learning to analyze vast datasets and uncover patterns in employee performance (Buckingham and Goodall 2015). These advancements have led to the emergence of performance management software, data analytics tools, real-time feedback platforms, and mobile applications, streamlining processes and fostering continuous improvement (Mone et al. 1998Stone et al. 2009Pulakos et al. 2015Davenport and Harris 2007Garris et al. 2002). These innovations enable organizations to adopt agile, data-driven, and employee-centric approaches to drive better performance outcomes and gain a competitive advantage in the digital age.

Organizations worldwide increasingly turn to digital solutions to streamline processes, improve transparency, and enhance effectiveness in the current performance management landscape. For instance, IBM offers an employee feedback and review application that facilitates 360-degree feedback, allowing employees to provide input to their peers, managers, and subordinates. Airbnb utilizes employee performance management software to facilitate feedback and reviews, fostering a culture of open communication and collaboration. Amazon's performance management philosophy, "radical candor," emphasizes the importance of open, honest, and transparent communication between managers and employees, promoting a workplace performance management culture.

The future of performance management holds exciting possibilities with the advent of innovative technologies such as neurotechnology and brain-computer interfaces (BCIs) for real-time feedback on cognitive performance, predictive analytics, and machine learning algorithms for forecasting performance trends, genetic testing, and personalized medicine for tailored wellness programs, virtual reality (VR) training simulations for immersive learning experiences, blockchain technology for transparent record-keeping, and quantum computing for complex data analysis. This exploratory study would employ a mixed-methods approach to investigate the impact of technology and data analytics on performance management. Recommendations include adopting performance management as a culture, investing in performance management software, data analytics tools, and real-time feedback platforms, prioritizing data-driven decision-making, and fostering a culture of innovation and agility.

"By integrating performance management as a cultural cornerstone, organizations can leverage digital innovations to refine and amplify their practices, thus fostering organizational success in an ever-evolving digital landscape."

Keywords

Performance management, technology, data analytics, organizational success, evolution, traditional organizational practices, digital age, agility, real-time feedback

Presenting author

Rosemary Isioma Obi

Presented at

The Art and Science of Managing Performance” symposium, held on February 29th 2024, co-organized by Ascencia Center for Applied Business & Management Research (CABMR - France) and Gisma University for Applied Sciences (Germany), in collaboration with the Association for University Business & Economic Research (AUBER, United States).

Acknowledgements

I want to express my gratitude to College De (Paris, France), Ascencia Center for Applied Business and Management Research – CABMR (France), Gisma University of Applied Sciences (Germany), and the Association for University Business & Economic Research – AUBER (USA) for organizing The Art & Science of Managing Performance Symposium. My gratitude also goes to the HR professionals and employees of some organizations who generously shared their insights and expertise during the interviews conducted for this study. I also extend my appreciation to the few participants who took the time to complete the surveys, providing invaluable quantitative data for the research. Finally, I acknowledge the support and guidance of my academic advisors, whose expertise and encouragement have been instrumental in shaping this exploratory study. 

Hosting institution

Ascencia Business School, Collège de Paris, International Campus, Paris - La Défense.

Conflicts of interest

The authors have declared that no competing interests exist.

References

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