Authors :
Benjamin Yaw Kokroko; Joseph Kobi; Edmund Kofi Yeboah
Volume/Issue :
Volume 10 - 2025, Issue 10 - October
Google Scholar :
https://tinyurl.com/ye9bbfx7
Scribd :
https://tinyurl.com/bdfvfbff
DOI :
https://doi.org/10.38124/ijisrt/25oct1433
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
The optimization of order fulfillment performance and its measurement in the context of the modern supply chain
management have become a crucial factor that defines the competitive advantage and customer satisfaction. This study
explores the model of integrating customer service level agreements (SLAs) and real-time analytics dashboard to gauge the
rate of order fulfillment and delivery performance in complex supply chain networks. By taking a mixed-methodology with
contingency theory and configuration analysis, the proposed study investigates how businesses can use business intelligence
platforms and specifically, Microsoft power BI, strategically to work with operational data to convert them into performance
management insights. The studies examine the information of various manufacturing companies in various geographical
settings and industrial industries to create a complete model of the performance measurement through dashboard. Based
on hierarchical regression analysis and cluster analysis techniques, the study determines five different types of analytics
dashboard implementation, which span between the fundamental operation monitoring to sophisticated predictive analytics
implementation. The results indicate that when the organizations have an extreme integration of internal processes,
customer relationship, and supplier coordination, the best level of order fulfillment performance is attained when assisted
by the ability to provide real-time analytics. Moreover, the study proves that with the appropriate combination of customer
service level agreements and dashboard analytics, alignment of operation execution and strategic goals occurs, which leads
to quantifiable results in the rate of on-time delivery, accurateness of orders, and the customer satisfaction metrics. The
paper can add to the existing body of research on supply chain management by offering empirical information about the
connection between performance measurement based on SLA and operational performance and presenting the practitioner
with an empirically tested model of implementing real-time analytics dashboards.
Keywords :
Order Fulfillment Performance, Delivery Performance Measurement, Real-Time Analytics Dashboards, Business Intelligence Systems, Supply Chain Integration, Supply Chain Visibility, Performance Management Systems, Digital Transformation, Supply Chain Analytics.
References :
- Kaplan, R. S., & Norton, D. P. (1996). Using the balanced scorecard as a strategic management system. Harvard Business Review, 74(1), 75–85. https://www.academia.edu/31849238/Evaluating_the_Performance_of_Order_Fulfillment_Process_in_Supply_Chain
- Pettersson, A. I. (2008). Supply chain performance measurement systems in Swedish companies. Linköping University Electronic Press. https://www.diva-portal.org/smash/get/diva2:1235617/FULLTEXT01.pdf
- Rodríguez, R. R., Saiz, J. J. A., & Bas, A. O. (2009). Quantitative relationships between key performance indicators for supporting decision-making processes. Computers in Industry, 60(2), 104–113. https://www.researchgate.net/publication/229521412_Improving_Supply_Chain_Performance_Using_Order_Fulfillment_Metrics
- Croxton, K. L. (2003). The order fulfillment process. The International Journal of Logistics Management, 14(1), 19–32. https://www.semanticscholar.org/paper/The-Order-Fulfillment-Process-Croxton/182fb7c9a6cecd0ac2cd6bd9d45c49f71326dcc1
- Slack, N., Brandon-Jones, A., Johnston, R., & Betts, A. (2015). Operations and process management: Principles and practice for strategic impact (4th ed.). Pearson Education. https://www.diva-portal.org/smash/get/diva2:1235617/FULLTEXT01.pdf
- Striteska, M., & Spickova, M. (2012). Review and comparison of performance measurement systems. Journal of Organizational Management Studies, 2012, 1–13. https://www.academia.edu/31849238/Evaluating_the_Performance_of_Order_Fulfillment_Process_in_Supply_Chain
- Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations & Production Management, 21(1/2), 71–87. https://www.researchgate.net/publication/235267228_The_Order_Fulfillment_Process
- Jackson, T. W. (2016). Business intelligence and dashboards: A research perspective. Journal of Systems and Information Technology, 18(3), 228–244. https://www.gooddata.com/blog/supply-chain-dashboard-examples/
- Baroudi, F. (2010). Key performance indicators for supply chain management. International Journal of Productivity and Performance Management, 59(3), 226–240. https://www.diva-portal.org/smash/get/diva2:1235617/FULLTEXT01.pdf
- Neely, A., Mills, J., Platts, K., Richards, H., Gregory, M., Bourne, M., & Kennerley, M. (2000). Performance measurement system design: Developing and testing a process-based approach. International Journal of Operations & Production Management, 20(10), 1119–1145. https://www.semanticscholar.org/paper/The-Order-Fulfillment-Process-Croxton/182fb7c9a6cecd0ac2cd6bd9d45c49f71326dcc1
- Swaminathan, J. M. (2001). Enabling customization using standard operations. California Management Review, 43(3), 125–135. https://www.researchgate.net/publication/235267228_The_Order_Fulfillment_Process
- Mattsson, S. A. (2012). Logistik i försörjningskedjor (2nd ed.). Studentlitteratur. https://www.diva-portal.org/smash/get/diva2:1235617/FULLTEXT01.pdf
- Sundström, P., & Tollmar, K. (2018). Measuring performance of an order-to-delivery process: A study at Scania CV AB. KTH Royal Institute of Technology. https://www.diva-portal.org/smash/get/diva2:1235617/FULLTEXT01.pdf
- Bolstorff, P., & Rosenbaum, R. (2012). Supply chain excellence: A handbook for dramatic improvement using the SCOR model (3rd ed.). AMACOM. https://www.researchgate.net/publication/235267228_The_Order_Fulfillment_Process
- Rohm, H., & Nisbet, J. (2017). Developing meaningful key performance indicators. Balanced Scorecard Institute. https://www.researchgate.net/publication/389525612_Improvement_of_an_Order_Fulfillment_Process_A_Case_Study_in_a_Vietnamese_Distributor
- Gunasekaran, A., Patel, C., & McGaughey, R. E. (2004). A framework for supply chain performance measurement. International Journal of Production Economics, 87(3), 333–347. https://www.researchgate.net/publication/229521412_Improving_Supply_Chain_Performance_Using_Order_Fulfillment_Metrics
- Toni, A. D., & Tonchia, S. (2001). Performance measurement systems: Models, characteristics and measures. International Journal of Operations & Production Management, 21(1/2), 46–71. https://www.researchgate.net/publication/308904558_Consumer_Behaviour_and_Order_Fulfilment_in_Online_Retailing_A_Systematic_Review
- Harrison, A., & van Hoek, R. (2014). Logistics management and strategy: Competing through the supply chain (5th ed.). Pearson Education. https://www.researchgate.net/publication/308904558_Consumer_Behaviour_and_Order_Fulfilment_in_Online_Retailing_A_Systematic_Review
- Eckerson, W. W. (2009). Performance management strategies: How to create and deploy effective metrics. Business Intelligence Journal, 14(1), 24–27. https://www.gooddata.com/blog/supply-chain-dashboard-examples/
- Urciuoli, L., Mohanty, S., Hintsa, J., & Boekesteijn, E. G. (2014). The resilience of energy supply chains: A multiple case study approach on oil and gas supply chains to Europe. Supply Chain Management, 19(1), 46–63. https://www.researchgate.net/publication/229521412_Improving_Supply_Chain_Performance_Using_Order_Fulfillment_Metrics
- Parmenter, D. (2015). Key performance indicators: Developing, implementing, and using winning KPIs (3rd ed.). John Wiley & Sons. https://www.researchgate.net/publication/308904558_Consumer_Behaviour_and_Order_Fulfilment_in_Online_Retailing_A_Systematic_Review
- Nolan, B., & Andersson, P. (2015). Leading and lagging indicators in performance measurement. International Journal of Performance Management, 6(2), 103–117. https://www.researchgate.net/publication/229521412_Improving_Supply_Chain_Performance_Using_Order_Fulfillment_Metrics
- Brabazon, P. G., & MacCarthy, B. (2017). Understanding variability in automotive supply chain lead times. Journal of Manufacturing Technology Management, 28(3), 347–371. https://www.researchgate.net/publication/389525612_Improvement_of_an_Order_Fulfillment_Process_A_Case_Study_in_a_Vietnamese_Distributor
- Forslund, H., Jonsson, P., & Mattsson, S. A. (2008). Order-to-delivery process performance in delivery scheduling environments. International Journal of Productivity and Performance Management, 57(8), 579–596. https://www.researchgate.net/publication/235267228_The_Order_Fulfillment_Process
- Stewart, G. (1995). Supply chain performance benchmarking study reveals keys to supply chain excellence. Logistics Information Management, 8(2), 38–44. https://www.diva-portal.org/smash/get/diva2:1235617/FULLTEXT01.pdf
- Savkin, A. (2017). The difference between balanced scorecard and dashboard explained. BSC Designer. https://www.academia.edu/31849238/Evaluating_the_Performance_of_Order_Fulfillment_Process_in_Supply_Chain
- Busi, M., & Bititci, U. S. (2007). Collaborative performance management: Present gaps and future research. International Journal of Productivity and Performance Management, 55(1), 7–25. https://www.researchgate.net/publication/389525612_Improvement_of_an_Order_Fulfillment_Process_A_Case_Study_in_a_Vietnamese_Distributor
- Keebler, J. S., & Plank, R. E. (2009). Logistics performance measurement in the supply chain: A benchmark. Benchmarking: An International Journal, 16(6), 785–798. https://www.researchgate.net/publication/308904558_Consumer_Behaviour_and_Order_Fulfilment_in_Online_Retailing_A_Systematic_Review
- Neely, A., Gregory, M., & Platts, K. (1995). Performance measurement system design: A literature review and research agenda. International Journal of Operations & Production Management, 15(4), 80–116. https://www.semanticscholar.org/paper/The-Order-Fulfillment-Process-Croxton/182fb7c9a6cecd0ac2cd6bd9d45c49f71326dcc1
- Wang, G., Huang, S. H., & Dismukes, J. P. (2004). Product-driven supply chain selection using integrated multi-criteria decision-making methodology. International Journal of Production Economics, 91(1), 1–15. https://www.researchgate.net/publication/389525612_Improvement_of_an_Order_Fulfillment_Process_A_Case_Study_in_a_Vietnamese_Distributor
- Bourne, M., Mills, J., Wilcox, M., Neely, A., & Platts, K. (2000). Designing, implementing and updating performance measurement systems. International Journal of Operations & Production Management, 20(7), 754–771. https://www.academia.edu/31849238/Evaluating_the_Performance_of_Order_Fulfillment_Process_in_Supply_Chain
- APICS. (2017). Supply chain operations reference model (SCOR) version 12.0. APICS Supply Chain Council. https://www.researchgate.net/publication/229521412_Improving_Supply_Chain_Performance_Using_Order_Fulfillment_Metrics
- Hausman, W. H. (2002). Supply chain performance metrics. Stanford Global Supply Chain Management Forum, 1–19. https://www.researchgate.net/publication/235267228_The_Order_Fulfillment_Process
- Fraser, J., Manrodt, K. B., & Vitasek, K. (2008). Global logistics and supply chain strategies for the 2008–2013 period. Establish Supply Chain Management Review, 12(7), 54–61. https://www.researchgate.net/publication/229521412_Improving_Supply_Chain_Performance_Using_Order_Fulfillment_Metrics
- Badawy, M., El-Aziz, A. A., Idress, A. M., Hefny, H., & Hossam, S. (2016). A survey on exploring key performance indicators. Future Computing and Informatics Journal, 1(1–2), 47–52. https://www.researchgate.net/publication/308904558_Consumer_Behaviour_and_Order_Fulfilment_in_Online_Retailing_A_Systematic_Review
The optimization of order fulfillment performance and its measurement in the context of the modern supply chain
management have become a crucial factor that defines the competitive advantage and customer satisfaction. This study
explores the model of integrating customer service level agreements (SLAs) and real-time analytics dashboard to gauge the
rate of order fulfillment and delivery performance in complex supply chain networks. By taking a mixed-methodology with
contingency theory and configuration analysis, the proposed study investigates how businesses can use business intelligence
platforms and specifically, Microsoft power BI, strategically to work with operational data to convert them into performance
management insights. The studies examine the information of various manufacturing companies in various geographical
settings and industrial industries to create a complete model of the performance measurement through dashboard. Based
on hierarchical regression analysis and cluster analysis techniques, the study determines five different types of analytics
dashboard implementation, which span between the fundamental operation monitoring to sophisticated predictive analytics
implementation. The results indicate that when the organizations have an extreme integration of internal processes,
customer relationship, and supplier coordination, the best level of order fulfillment performance is attained when assisted
by the ability to provide real-time analytics. Moreover, the study proves that with the appropriate combination of customer
service level agreements and dashboard analytics, alignment of operation execution and strategic goals occurs, which leads
to quantifiable results in the rate of on-time delivery, accurateness of orders, and the customer satisfaction metrics. The
paper can add to the existing body of research on supply chain management by offering empirical information about the
connection between performance measurement based on SLA and operational performance and presenting the practitioner
with an empirically tested model of implementing real-time analytics dashboards.
Keywords :
Order Fulfillment Performance, Delivery Performance Measurement, Real-Time Analytics Dashboards, Business Intelligence Systems, Supply Chain Integration, Supply Chain Visibility, Performance Management Systems, Digital Transformation, Supply Chain Analytics.