Change Management System (CMS) Evaluation: A Case Study in a Multinational Manufacturing Company in Malaysia

  • S. Sarifah Radiah Shariff Malaysia Institute of Transport (MITRANS), Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia and Centre for Statistics and Decision Science, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malysia
  • K. N. M. Nasir Nasir Malaysia Institute of Transport (MITRANS), Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia
  • Noor Asiah Ramli Centre for Statistics and Decision Science, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malysia
  • Siti Meriam Zahari Centre for Statistics and Decision Science, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malysia
Keywords: Change management analysis, ideal cycle time, Monte Carlo simulation

Abstract

Changes can be defined as modification of the form, fit or function of an object such as a process or a product. Changes can be positive or negative but in general, making changes show that a company is progressing and improving. A company can choose to take initiative to change or just wait for external forces depending on its necessity or requirement. In some cases, change is not favourable unless it is really necessary as it involves time and money as well as other resources. Due to this, a good change management is necessary so that changes can be monitored effectively. A dynamic and timely change management is important in order to ensure that the company does not fall behind in being competitive in the industry. This study focuses on the evaluation of the change management system in a manufacturing company. Focus is given to the measurement of the change process which has been agreed to be due to cycle time in which an ideal cycle time for the change process is simulated. Based on Monte Carlo simulation, it is figured that the overall cycle time can be improved by 35%. At the same time, other effectiveness measure is also identified to improve the management system of the company.

Author Biographies

S. Sarifah Radiah Shariff, Malaysia Institute of Transport (MITRANS), Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia and Centre for Statistics and Decision Science, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malysia

S. Sarifah Radiah Shariff. She is a Senior Lecturer in Centre of Statistics and Decision Science Studies in Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam. Her expertise is in Supply Chain and Logistics Modelling. Currently she is attached to Malaysia Institute of Transport, UiTM as the Head of Postgraduate Studies. She graduated from Purdue University, West Lafayette, IN, USA with BSc in Statistics and Mathematics, and pursued her MSc in Information Technology in Universiti Teknologi MARA, Shah Alam, Malaysia. Her PhD is in Operations Research from University of Malaya, Kuala Lumpur, Malaysia. Before joining the academic line, she was a logistics practitioner in Procter & Gamble (M) Sdn Bhd, BHP (Transport) Malaysia, Convenience Shopping Sdn Bhd, that entitled her as a Profesional Technologist (Ts) in Transport and Logistics.

K. N. M. Nasir Nasir, Malaysia Institute of Transport (MITRANS), Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia

K. N. M. Nasir received her B.Sc. in Chemical Engineering from Clarkson University, N.Y. She pursued her M. Sc. Quantitative Science in University Technology MARA, Malaysia while being employed as a quality manager in Western Digital (M) Sdn. Bhd, and American-based Hard Disk Manufacturing company. She started working as engineer in 1995 with Panasonic Electronic Devices (M) Sdn. Bhd., before she joined Western Digital (M) Sdn. Bhd in 2006. Kartika has a solid experience in Total Quality Management, Reliability Engineering and Change Management. She is currently a Corporate Quality Manager of Uzma Engineering Sdn. Bhd, a local Oil and Gas Service company, since 2019.

Noor Asiah Ramli, Centre for Statistics and Decision Science, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malysia

Noor Asiah Ramli is a Senior Lecturer at the Statistical and Decision Sciences Department, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Malaysia. She teaches quantitative business analysis as well as operational research. She obtained her PhD in Decision Science from Universiti Malaya in 2013. Her main research interests are efficiency and productivity measurement using Data Envelopment Analysis technique.

Siti Meriam Zahari, Centre for Statistics and Decision Science, Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, Malysia

Siti Meriam Zahari received her first degree in Bachelor of Applied Science, with specialization in Mathematics and Economics, and her second degree in Master of Economic Management from Universiti Sains Malaysia in 2003 and 2004, respectively. She received a PhD degree from Universiti Teknologi MARA in 2009. Since 2009, she has been with the Centre for Statistical and Decision Science Studies, Universiti Teknologi MARA as a senior lecturer. Her current research interest includes, time series econometrics, statistical outliers, decision analysis and forecasting.

References

Anees, M. M., Mohamed, H. E., & Abdel Razek, M. E. (2013). Evaluation of change management efficiency of construction contractors. HBRC Journal, 9(1), 77–85.

Bruno, G. (2016). A Support System to Manage Product and Process Changes in Manufacturing. IFAC-PapersOnLine, 49(12), 1080–1085.

Cichos, D., & Aurich, J. C. (2016). Support of Engineering Changes in Manufacturing Systems by Production Planning and Control Methods. Procedia CIRP, 41, 165–170.

Cunningham, A., Wang, W., Zio, E., Wall, A., Allanson, D., & Wang, J. (2011). Application of delay-time analysis via Monte Carlo simulation. Journal of Marine Engineering & Technology, 10(3), 57-72.

Thomas, O.O. (2014). Change Management and its Effects on Organizational Performance of Nigerian Telecoms Industries: Empirical Insight from Airtel Nigeria. International Journal of Humanities Social Sciences and Education, 1(11), 170–179.

Koch, J., Gritsch, A., & Reinhart, G. (2016). Process design for the management of changes in manufacturing: Toward a Manufacturing Change Management process. CIRP Journal of Manufacturing Science and Technology, 14, 10–19.

Levovnik, D., & Gerbec, M. (2018). Operational readiness for the integrated management of changes in the industrial organizations – Assessment approach and results. Safety Science, 107(April), 119–129.

Li, F., Zhu, Q., Chen, Z., & Xue, H. (2018). A balanced data envelopment analysis cross-efficiency evaluation approach. Expert Systems with Applications, 106, 154–168.

Mahdavi, M. M. M., & Mahdavi, M. (2014). Stochastic lead time demand estimation via monte carlo simulation technique in supply chain planning. Sains Malaysiana, 43(4), 629-636.

Paris, A. S., Tanase, I., Tarcolea, C., & Dragomirescu, C. (2012). Applications of the Monte Carlo method in manufacturing processes. Proceedings in Manufacturing Systems, 7(4), 253-25.

Plehn, C., Stein, F., De Neufville, R., & Reinhart, G. (2016). Assessing the Impact of Changes and their Knock-on Effects in Manufacturing Systems. Procedia CIRP, 57, 479–486.

Raineri, A. B. (2011). Change management practices: Impact on perceived change results. Journal of Business Research, 64(3), 266–272.

Stasis, A., Whyte, J., & Dentten, R. (2013). A critical examination of change control processes. Procedia CIRP, 11, 177–182.

Sujova, A., & Rajnoha, R. (2012). The Management Model of Strategic Change based on Process Principles. Procedia - Social and Behavioral Sciences, 62, 1286–1291.

Wilberg, J., Elezi, F., Tommelein, I. D., & Lindemann, U. (2015). Using a Systemic Perspective to Support Engineering Change Management. Procedia Computer Science, 61, 287–292.

Yin, L., Tang, D., Ullah, I., Wang, Q., Zhang, H., & Zhu, H. (2017). Analyzing engineering change of aircraft assembly tooling considering both duration and resource consumption. Advanced Engineering Informatics, 33, 44-59.

Published
2020-08-31
Section
Articles