Applying Six Sigma methodology to improve performance in organizations

Fahimi, K.; Amirabadi, M.

doi:10.22034/IJHCUM.2024.03.12

Articles in Press

Document Type : ORIGINAL RESEARCH ARTICLE

Authors

Planning, Human capital development and Council Affairs department, Tehran municipality, Tehran, Iran

https://doi.org/10.22034/IJHCUM.2024.03.12

Abstract

BACKGROUND AND OBJECTIVES: The six sigma is a common methodology that has applied successfully in many organizations leading to sustainable performance improvements in products and services. However, the applied methodologies have not pay attention to Multi Criteria Decision Making models, clustering algorithm and Balance scorecard model. The purpose of this model is to apply the six-sigma methodology in Tehran Municipality and show how the Balance scorecard model, clustering algorithm, Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution can be applied in the methodology.
METHODS: Define, Measure, Analysis, Improvement and Control as a common methodology of six sigma is applied in Tehran Municipality. Several unique elements that are exist in Tehran Municipality are identified and categorized based on the Balance scorecard model into indexes, goals and perspectives. Also, Analytic Hierarchy Process for weight extraction and Technique for Order of Preference by Similarity to Ideal Solution for ranking are applied. The improvement strategies are created based on the six sigma tolerances.
FINDINGS: The findings show that the methodology can be elevated by Balance scorecard, Analytic Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution. This formulation is done and applied in Tehran Municipality and can be used in other organizations for conducting improvement strategies. Based on the arbitrary data, the best district of Tehran city is district 9 by 89.75% and the worst is district 18 by 10.12% score. Also, Wards and K-mean clustering algorithms and six sigma control limits are used to cluster the districts into superior, somehow superior, moderate, somehow inferior and inferior clusters based on their performance.
CONCLUSION: This manuscript helps to understand the way of integration the methodology, Balance scorecard, Analytic Hierarchy Process, Technique for Order of Preference by Similarity to Ideal Solution and six sigma tolerances for sustainable improvement of Tehran Municipality. The proposed formulation can be used in any organization to reach to sustainable improvement.

Graphical Abstract

Keywords

Main Subjects

Human capital in urban management

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Tehran Urban Research and Planning Center: Tehran Municipality

References

Azar, A.; Olfat, L.; Khosravani, F.; Jalali, R., (2011). A BSC method for supplier selection strategy using TOPSIS and VIKOR: a case study of part maker industry. Manag. Sci. Lett., 1(4): 559–568 (10 pages).

Araujo, C. A. S.; Wanke, P.; Siqueira, M. M., (2018). A performance analysis of Brazilian public health: TOPSIS and neural networks application. Int. J. Product. Perform., 67(9): 1526–1549 (23 pages).

Afshari, A.; Mojahed, M.; Yusuff, R. M., (2010). Simple additive weighting approach to personnel selection problem. IJIMT., 1(5): 511-515 (5 pages).

Al-Harbi, K. M. A. S., (2001). Application of the AHP in project management. Int. J. Proj. Manag., 19(1): 19-27 (9 pages).

Behzadian, M.; Otaghsara, S. K.; Yazdani, M.; Ignatius, J., (2012). A state-of the-art survey of TOPSIS applications. Expert Syst. Appl., 39(17): 13051-13069 (18 pages).

Chakrabarty, A.; Chuan Tan, K., (2007). The current state of six sigma application in services. Manag. Serv. Qual., 17(2): 194-208 (14 pages).

Chou, S. Y.; Chang, Y. H.; Shen, C. Y., (2008). A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes. Eur. J. Oper. Res., 189(1): 132-145 (13 pages).

Chu, T. C., (2002). Selecting plant location via a fuzzy TOPSIS approach. Int. J. Adv. Manuf. Technol., 20(11): 859-864 (15 pages).

European Foundation for Quality Management, (2019). The EFQM model - EFQM.

Esfandiari, M.; Rizvandi, M., (2014). An application of TOPSIS method for ranking different strategic planning methodology. Manag. Sci. Lett., 4(7): 1445-1448 (3 pages).

Fong, P. S. W.; Choi, S. K. Y., (2000). Final contractor selection using the analytical hierarchy process. Constr. Manag. Econ., 18(5): 547-557 (10 pages).

Goh, T. N., (2002). A strategic assessment of Six Sigma. Qual. Reliab. Eng. Int., 18(5): 403-410 (7 pages).

Handfield, R.; Walton, S. V.; Sroufe, R.; Melnyk, S. A., (2002). Applying environmental criteria to supplier assessment: A study in the application of the Analytical Hierarchy Process. Eur. J. Oper. Res., 141(1): 70-87 (18 pages).

Hastie, T.; Tibshirani, R.; Friedman, J. H.; Friedman, J. H., (2009). The elements of statistical learning: data mining, inference, and prediction New York: springer.

Hwang, C. L.; Yoon, K., (1981). Methods for multiple attribute decision making. In Multiple attribute decision making (pp. 58-191). Springer, Berlin, Heidelberg.

Jabbarzadeh, A., (2018). Application of the AHP and TOPSIS in project management. J. Proj. Manag., 3(2): 125-130 (5 pages).

Kaliszewski, I.; Podkopaev, D., (2016). Simple additive weighting—A metamodel for multiple criteria decision analysis methods. Expert Syst. Appl., 54: 155-161 (7 pages).

Kaplan, R.S.; Norton, D.P., (1992). The balanced scorecard: measures that drive performance. 83: Harvard Business Review.

KPIs, (2019). Microsoft Research. Key Performance Indicators in Power Pivot.

Kumar, R.; Singh, K.; Jain, S. K., (2020). A combined AHP and TOPSIS approach for prioritizing the attributes for successful implementation of agile manufacturing. Int. J. Product. Perform., 69(7): 1395–1417 (20 pages).

Kwak, Y. H.; Anbari, F. T., (2006). Benefits, obstacles, and future of six sigma approach. Technovation. 26(5-6): 708-715 (7 pages).

Lantz, B., (2019). Machine learning with R: expert techniques for predictive modeling. Packt publishing ltd.

Lin, M. C.; Wang, C. C.; Chen, M. S.; Chang, C. A., (2008). Using AHP and TOPSIS approaches in customer-driven product design process. Comput. Ind., 59(1): 17-31 (14 pages).

Meshram, S. G.; Alvandi, E.; Meshram, C.; Kahya, E.; Al-Quraishi, A. M. F., (2020). Application of SAW and TOPSIS in prioritizing watersheds. Water Resour. Manage., 34(2): 715-732 (17 pages).

Mirfakhredini, H.; Peymanfar, M. H.; Khatibi Oghada, A.; Alimohammadi, H., (2013). Performance assessment of sports organization with BSC--Topsis integrated model. J. Sport Manag., 5(16): 77–96. (19 pages). (In Persian)

Murtagh, F.; Legendre, P., (2014). Ward’s hierarchical agglomerative clustering method: which algorithms implement Ward’s criterion? J. Classif., 31: 274-295 (21 pages).

Nurmalini, N.; Rahim, R., (2017). Study approach of simple additive weighting for decision support system. Int. J. Sci. Res. Sci. Technol., 3(3): 541-544 (3 pages).

Partovi, F. Y.; Burton, J.; Banerjee, A., (1990). Application of analytical hierarchy process in operations management. Int. J. Oper. Prod. Manag., 10(3): 5-19 (14 pages).

Palcic, I.; Lalic, B., (2009). Analytical Hierarchy Process as a tool for selecting and evaluating projects. Int. J. Simul. Model., 8(1): 16-26 (10 pages).

Saaty, R. W., (1987). The analytic hierarchy process-what it is and how it is used. Math. Model., 9(3–5): 161–176 (15 pages).

Sahir, S. H.; Rosmawati, R.; Minan, K., (2017). Simple additive weighting method to determining employee salary increase rate. Int. J. Sci. Res. Sci. Technol., 3(8): 42-48 (6 pages).

Sehhat, S.; Taheri, M.; Sadeh, D. H., (2015). Ranking of insurance companies in Iran using AHP and TOPSIS techniques. Am. J. Res. Commun., 3(1): 51–60 (9 pages).

Rathi, R.; Khanduja, D.; Sharma, S., (2015). Six Sigma project selection using fuzzy TOPSIS decision making approach. Manag. Sci. Lett., 5(5): 447-456 (9 pages).

Triantaphyllou, E., (2000). Multi-criteria decision-making methods. In Multi-criteria decision-making methods: A comparative study (pp. 5-21)., Springer, Boston, MA.

Yadav, G.; Seth, D.; Desai, T. N., (2018). Prioritizing solutions for Lean Six Sigma adoption barriers through fuzzy AHP-modified TOPSIS framework Int. J. Lean Six Sigma., 9(3): 270-300 (30 pages).

Wang, T. C.; Chang, T. H., (2007). Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Syst. Appl., 33(4): 870-880 (10 pages).

Wang, J. W.; Cheng, C. H.; Huang, K. C., (2009). Fuzzy hierarchical TOPSIS for supplier selection. Appl. Soft Comput., 9(1): 377-386 (9 pages).

Witten, D.; James, G., (2013). An introduction to statistical learning with applications in R. springer publication.

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International Journal of Human Capital in Urban Management

Applying Six Sigma methodology to improve performance in organizations

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References

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Articles in Press, Accepted Manuscript
Available Online from 29 March 2024

Applying Six Sigma methodology to improve performance in organizations

References

References

Send comment about this article

Articles in Press, Accepted Manuscript Available Online from 29 March 2024

Articles in Press, Accepted Manuscript
Available Online from 29 March 2024