Suggestions for Integrated BSC-DEA Implementation in the Industry 4.0 Company
Abstract
Purpose: The implementation of the integrated BSC-DEA model in an Industry 4.0 company involves leveraging advanced technologies to enhance its performance measurement. This approach enables real-time monitoring of KPIs, optimising operational efficiency while ensuring continuous improvement in a rapidly evolving digital environment. By integrating BSC-DEA with Industry 4.0 principles, companies can achieve a more agile and data-driven decision-making process, securing a sustainable competitive advantage.
Methodology/Approach: The integration uses BSC to identify KPIs, which are then applied in the DEA model. This allows an Industry 4.0 company to benchmark performance and optimise resource use through targeted improvements.
Findings: This research overview presents a structured approach to understanding the proposal for applying the integrated BSC-DEA model in an Industry 4.0 company. Continuous feedback, data validation, and periodic reviews ensure that the model facilitates sustainable performance improvement.
Research Limitation/implication: The proposed implementation process requires a substantial commitment of time and resources, along with support from all levels of the Industry 4.0 company.
Originality/Value of paper: The research presented in this paper introduces novel concepts, methodologies, and findings that advance the current state of knowledge. The originality of this work is demonstrated through innovative approaches to existing problems, as well as the analysis and synthesis of diverse ideas to develop new theoretical processes, models, and practical implications.
References
Amado, C.A.F., Santos, S.P. and Marques, P.M., 2012. Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment. The International Journal of Management Science, 40(3), pp. 390–403. https://doi.org/10.1016/j.omega.2011.06.006.
Aryanezhad, M.B., Najafi, E. and Farkousha, S.B., 2011. A BSC-DEA approach to measure the relative efficiency of the service industry: A case study of the banking sector. International Journal of Industrial Engineering Computations, 2, pp. 273–282. Available at: http://growingscience.com/ijiec/Vol2/IJIEC_2010_20.pdf.
Asosheh, A., Nalchigar, S. and Jamporazmey, M., 2010. Information technology project evaluation: An integrated data envelopment analysis and balanced scorecard approach. Expert Systems with Applications: An International Journal, 37(8), pp. 5931–5938. https://doi.org/10.1016/j.eswa.2010.02.012.
Bain & Company, 2023. Management tools and trends 2023. [Online] Available at: https://www.bain.com/insights/management-tools-balanced-scorecard/.
Banker, D.R., Potter, M. and Srinivasan, M., 2004. A Balanced Scorecard analysis of performance metrics. European Journal of Operational Research, 154(2), pp. 423–436. https://doi.org/10.1016/S0377-2217(03)00179-6.
Braglia, M., Gabbrielli, R., Marrazzini, L. and Padellini, L., 2022. Key Performance Indicators and Industry 4.0 – A structured approach for monitoring the implementation of digital technologies. Procedia Computer Science, 200, pp.1626-1635. https://doi.org/10.1016/j.procs.2022.01.363.
Eilat, H., Golany, B. and Shtub, A., 2006. Constructing and evaluating balanced portfolios of R&D projects with interactions: a DEA-based methodology. European Journal of Operational Research, 172, pp. 1018–1039. https://doi.org/10.1016/j.ejor.2004.12.001. ISSN 0377-2217.
Eilat, H., Golany, B. and Shtub, A., 2008. R&D project evaluation: An integrated DEA and balanced scorecard approach. Omega: The International Journal of Management Science, 36(5), pp. 895–912. https://doi.org/10.1016/j.omega.2006.05.002.
Excitant, 2024. The Fourth Generation Balanced Scorecard Approach. Available at: http://www.excitant.co.uk/resources/white-papers/the-fourth-generation-balanced-scorecard-approach.
Frederico, G.F., Garza-Reyes, J.A., Kumar, A. and Kumar, V., 2021. Performance measurement for supply chains in the Industry 4.0 era: a balanced scorecard approach. International Journal of Productivity and Performance Management, 70(4), pp.789-807. https://doi.org/10.1108/IJPPM-08-2019-0400.
Garcia-Valderrama, T., Muleno-Mendigirri, E. and Revuelta-Bordoy, D., 2009. Relating the perspectives of the Balanced Scorecard for R&D by means of DEA. European Journal of Operational Research, 196, pp. 1177–1189. https://doi.org/10.1016/j.ejor.2008.05.015.
Hassan, N., Mohaghegh Tabar, M. and Shabanzade, P., 2010. Resolving multi-objectives resource allocation problem based on inputs and outputs using data envelopment analysis method. Australian Journal of Basic and Applied Sciences, 4(10), pp. 5320–5325.
Hofmann, E. and Rüsch, M., 2017. Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 89, pp.23-34. https://doi.org/10.1016/j.compind.2017.04.002.
Chaharlang, Y., Soleimani, H., Mehdizadeh, E. and Alinezhad, A., 2023. Introduction of an integrated system for measuring the BSC and DEA-based performance of social systems using uncontrollable factors: A case study of Shahriar municipalities. Buildings, 13(1), pp. 242.
Chen, T.Y. and Chen, L.H., 2007. DEA performance evaluation based on BSC indicators incorporated: the case of the semiconductor industry. International Journal of Productivity and Performance Management, 56(4), pp. 335–357.https://doi.org/10.1108/17410400710745333.
Chen, T.Y., Chen, C.B. and Peng, S.Y., 2008. Firm operation performance analysis using data envelopment analysis and Balanced Scorecard: a case study of a credit cooperative bank. International Journal of Productivity and Performance Management, 57(7), pp. 523–539. https://doi.org/10.1108/17410400810904010.
Chiang, C.Y. and Lin, B., 2009. An integration of Balanced Scorecards and data envelopment analysis for firm's benchmarking management. Total Quality Management & Business Excellence, 20(11), pp. 1153–1172. https://doi.org/10.1080/14783360903248286.
Kádárová, J., Mihok, J. and Turisová, R., 2023. Proposal of performance assessment by integration of two management tools. Quality Innovation Prosperity, 17(1), pp. 26–39. https://doi.org/10.12776/qip.v17i1.143.
Kumar, J., Prince, N. and Baker, H.K., 2022. Balanced Scorecard: A Systematic Literature Review and Future Research Issues. FIIB Business Review, 11(2), pp.147-161. https://doi.org/10.1177/23197145211049625.
Kumar, S., Lim, W.M. and Sureka, R. et al., 2024. Balanced scorecard: trends, developments, and future directions. Review of Management Science, 18, pp.2397–2439. https://doi.org/10.1007/s11846-023-00700-6.
Min, H., Min, H. and Joo, S., 2008. A data envelopment analysis-based balanced scorecard for measuring the comparative efficiency of Korean luxury hotels. International Journal of Quality & Reliability Management, 25(4), pp. 349–365. https://doi.org/10.1108/02656710810865249.
Niknazar, P., 2010. Evaluating the use of BSC-DEA method in measuring organisation's efficiency: Master's thesis in Informatics. University of Borås, School of Business and Informatics. http://bada.hb.se/bitstream/2320/7976/1/2010MI09.pdf.
Rouse, P., Putterill, M. and Ryan, D., 2002. Integrated performance measurement design: insights from an application in aircraft maintenance. Management Accounting Research, 13(2), pp. 229–248.
Sardjono, W., Johan, G.N., Utomo, H., Sukardi, S. and Rahmasari, A., 2021. Supply Chain Measurement in the Industry 4.0 Using Balanced Scorecard. In Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City.
Shafiee, M., Hosseinzadeh Lotfi, F. and Saleh, H., 2014. Supply chain performance evaluation with data envelopment analysis and balanced scorecard approach. Applied Mathematical Modelling, 38(21–22), pp. 5092–5112. https://doi.org/10.1016/j.apm.2014.03.023.
Sutoova, A., Zgodavova, K., Lajczykova, M., 2018. Quality and Effectiveness Evaluation of the Geological Services Using CEDAC Method. Acta Montanistica Slovaca 23(1), 18-25.
Tawse, A. and Tabesh, P., 2023. Thirty years with the balanced scorecard: What we have learned. Business Horizons, 66(1), pp.123-132. https://doi.org/10.1016/j.bushor.2022.03.005.
Vitezić, N. and Petrlić, A., 2020. An analytical-predictive model for measuring the efficiency and effectiveness of public health services. The Open Public Health Journal, [online] 13, pp. 20-23. https://doi.org/10.2174/1874944502013010203.
Zhu, J., 2009. Quantitative models for performance evaluation and benchmarking: Data envelopment analysis with spreadsheets. New York: Springer Science + Business Media, LLC.
Zgodavová, K., Šolc, M., Petrík, J., 2013. Principles, Concepts and Standards of Quality Management: Quality, Metrology, Information Security. LAP Lambert Academic Publishing, Saarbrucken, Germany.
Authors
Copyright (c) 2024 Michaela Kočišová, Milan Fiľo, Jaroslava Kádárová
This work is licensed under a Creative Commons Attribution 4.0 International License.
This is an open access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access. This journal is licensed under a Creative Commons Attribution 4.0 License - http://creativecommons.org/licenses/by/4.0.
Authors who publish with the Quality Innovation Prosperity agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
