Yüksel YURTAY, Murat AYANOĞLU, Tuba KARAGÜL YILDIZ

GÖSTERGE PANELİNİN ÜRETİM BAĞLAMINDAKİ KARAR SÜREÇLERİNE ETKİSİ ÜZERİNE BİR AMPİRİK ÇALIŞMA

Üretim sistemleri daha fazla ve daha hızlı üretmeyi hedeflerken, yöneticileri de daha hızlı ve doğru karar almaya zorluyor. Bu zorunluluklar her seviyeden yöneticiyi, karar almada destek olabilecek, yeni arayışlara yönlendirmiştir. Bilim ve teknolojideki hızlı gelişmeler, tedarik zinciri sürecindeki yöneticilerin, bilgiye duyulan ihtiyacını arttırmıştır. Aynı zamanda bilgiye hızlı ve doğru şekilde erişimini de gündeme getirmiştir. Bu noktada İşletmelerde, biriken veriye odaklanılarak doğru sistem alt yapısı ve veri analizi yaklaşımıyla, bilgiye duyulan ihtiyaçlar çözümlenebilir. Sonuçlar, gösterge paneli disiplini ile görselleştirilerek, karar vericilerin ihtiyaçları karşılanabilir. Bu makale veri madenciliği tekniği ve gösterge paneli aracı ile tedarikçi izleme sürecini kontrol ederek, yöneticilere tedarikçi izleme karar destek sistemi sunar. Uygulamada k-means algoritması ve anahtar performans ölçütleri ile veriler analiz edilerek, mevcut veriler yapılandırılır. İşletmenin her seviyesinden yöneticiye tedarikçi izleme aşamalarında, gösterge paneli ile karar süreçlerinde destek verir.

Anahtar Kelimeler:

Gösterge Paneli, Veri Madenciliği, Tedarik Zinciri Yönetimi

PDF

___

Banerjee, A., Bandyopadhyay, T., Acharya, P. (2013). “Data analytics: Hyped up aspirations or true potential?”. The Journal for Decision Makers, 38(4), 1-11.
Chaudhuri, S., Dayal, U., Ganti, V. (2001) “Database technology for decision support systems”. IEEE Transactions on Automation Science and Engineering, 34(12), 48-55.
Chae, B., Olson, D., Sheu, C. (2014). “The impact of supply chain analytics on operational performance: A resource- based view”. International Journal of Production Research, 52(16),4695-4710.
Choudhary, A.K., Harding, J.A., Lin, H.K., Tiwari, M.K., Shankar, R. (2011). “Knowledge discovery and data mining integrated (KOATING) Moderators for collaborative projects”. International Journal of Production Research, 49(23), 7029-7057.
Chopra,S., Meindl, P. (2007). “Supply Chain Management: Strategy, Planning & Operations(6)”. Pearson Education, Inc., Upper Saddle River, New Jersey, Usa.
Collins, J.D., Worthington, W.J., Reyes, P.M., Romero, M. (2010). “Knowledge management, supply chain technologies, and firm performance”. Management Research Review, 33(10), 947-960.
Gröger, C., Stach, C., Mitschang, B., Westkämper, E. (2016). “A mobile dashboard for analytics-based information provisioning on the shop floor”. International Journal of Computer Integrated Manufacturing, 29(12), 1335-1354.
Fahad, A., Alshatri, N., Tari, Z., Alamri, A., Khalil, I., Zomaya, A.Y. (2014). “A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis”. IEEE Transactions on Emerging Topics in Computing, 2(3), 267-279.
Faliu, Y.F., Moon, I. (2013). “Extended K-Means Algorithm”. 5th International Conference on Intelligent Human-Machine Systems and Cybernetics, 26-27 August, Hangzhou, ,China.
James, T. (2012). “Smart Factories.”. Engineering & Technology, 7(6), 64–67.
Jun, T., Kai, C., Yu, F., Gang, T. (2009). “The Research & Application of ETL Tool in Business Intelligence Project”. International Forum on Information Technology and Applications, Chengdu, China.
Lau, H.C.W., Ho, G.T.S., Zhao, Y. Chung, N.S.H. (2009). “Development of a process mining system for supporting knowledge discovery in a supply chain network”. International Journal of Production Economics, 122(1), 176-187.Lempinen,H. (2012). “Constructing a Design Framework for Performance Dashboards”. Nordic Contributions in IS Research, SCIS, 109-130.
Liu, L. (2010). “Supply Chain Integration through Business Intelligence”. International Conference on Management and Service Science, Wuhan, China.
Olson, D.L. (2015). “A Review of Supply Chain Data Mining Publications”. Journal of Supply Chain Management Science, 1(1), 215.955.
Olson, D.L., Shi, Y. (2006). Introduction to Business Data Mining,1nd ed. London England, McGraw Hill Higher Education, Usa.
Pattnaik, S., Sutar, M.K., Govindan, K. (2009). “Supply Chain Integration in relation to Manufacturing Industries”. IEEE International Conference on Computers & Industrial Engineering, Troyes, France.
Peral,J., Mate, A., Macro, M. (2017). “Application of Data Mining techniques to identify relevant Key Performance Indicators”. Computer Standards & Interfaces, 54(2), 76-85.
Ren, C., Liu, Y., Guo, Y. (2014). “Fuzzy evaluation on supply chain competitiveness based on membership degree transformation new algorithm”. Journal of Chemical and Pharmaceutical Research, 6(2), 139-144.
Rivera, D.S., Shanks, G. (2015). “A Dashboard to Support Management of Business Analytics Capabilities“. Jounal of decision systems, 24(1), 76-84.
Tokolaa, H., Grögerb, C., Järvenpääc, E., Niemi, E. (2011). “Designing manufacturing dashboards on the basis of a Key Performance Indicator survey”. 49th CIRP Conference on Manufacturing Systems, Budapest, Hungary.
Vincent, O.R., Makinde, A.S., Salako, O.S., Oluwafemi, O.D. (2018). “A self-adaptive k-means classifier for business incentive in a fashion design environment”. Applied computing and informatics, 14(1), 88-97.
Yigitbasioglu, O.M., Velcu, O. (2011). “A review of dashboards in performance management: Implications for design and research.”. International Journal of Accounting Information Systems, 13(1), 41-59.