Evaluation of the Effectiveness of Statistical Management Tools in Improving the Performance of Business Organisations

Authors

  • Kresnawidiansyah Agustian Universitas Islam Jakarta
  • Choiril Maksum Universitas Islam Jakarta
  • Agustian Zen Universitas Islam Jakarta
  • Ratih Ayu Sekarini Universitas Islam Jakarta
  • Aulia Januar Malik Institut Bisnis Muhammadiyah Bekasi

DOI:

https://doi.org/10.61100/adman.v1i2.56

Keywords:

Business Organisation Performance, Effectiveness, Statistical Management Tools

Abstract

In an era of globalisation and intensifying business competition, business organisations must constantly strive to improve their operational effectiveness in order to survive and thrive. One tool that has been used by many organisations in this effort is statistical management. Statistical management is a data-driven approach that enables organisations to make better decisions, identify improvement opportunities, and better manage risks. This literature review aims to present an in-depth understanding of the use of statistical management in the context of business organisations. This research is a literature review that adopts a qualitative method approach, which means it will analyse and interpret data by relying on information and text from various sources. The study results show that evaluating the effectiveness of Statistical Management tools in improving the performance of business organisations is an important step in maintaining competitiveness and long-term success. Statistical Management provides a robust framework for collecting, analysing, and interpreting statistical data, which in turn helps organisations make better decisions, improve product or service quality, and optimise operational processes.

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Published

2023-10-03

How to Cite

Agustian, K., Maksum, C., Zen, A., Sekarini, R. A., & Malik, A. J. (2023). Evaluation of the Effectiveness of Statistical Management Tools in Improving the Performance of Business Organisations. Journal of Contemporary Administration and Management (ADMAN), 1(2), 118–127. https://doi.org/10.61100/adman.v1i2.56

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