Abstract
Supply chain planning is a crucial factor for operational excellence and competitive advantage. Related concepts and approaches were already designed in the last century and are now implemented by most firms in almost every industry sector. Advanced planning systems that provide decision-support for supply chain planning were conceptualized and developed several decades ago and are still in place and used by planners in their daily work. However, progress in information technology and megatrends of sustainability and digitalization as well as global crises and disasters considerably change the business environment in which companies and supply chains operate. Supply chain planning processes and systems must be extended, adapted, and amended to reflect these developments and transitions. This chapter summarizes the fundamental concepts of supply chain planning and advanced planning systems and outlines which changes and advancements are needed to ensure that processes and tools remain strong contributors to business success for firms and supply chains. Practitioners may gain insight about fundamental developments and trends in supply chain planning while scholars may find stimuli for further research and future studies on this topic.
This is a preview of subscription content, log in via an institution to check access.
References
Akçalı, E., & Çetinkaya, S. (2011). Quantitative models for inventory and production planning in closed-loop supply chains. International Journal of Production Research, 49(8), 2373–2407. https://doi.org/10.1080/00207541003692021
Almeder, C., Preusser, M., & Hartl, R. F. (2009). Simulation and optimization of supply chains: Alternative or complementary approaches? OR Spectrum, 31, 95–119. https://doi.org/10.1007/s00291-007-0118-z
APICS. (2017). SCOR – Supply chain operations reference model version 12.0. APICS.
Berning, G., Brandenburg, M., Gürsoy, K., Mehta, V., & Tölle, F. J. (2002). An integrated system solution for supply chain optimization in the chemical process industry. OR Spectrum, 24, 371–401. https://doi.org/10.1007/s00291-002-0104-4
Bigliardi, B., Filipelli, S., Petroni, A., & Tagliente, L. (2022). The digitalization of supply chain: A review. Procedia Computer Science, 200, 1806–1815. https://doi.org/10.1016/j.procs.2022.01.381
Boukherroub, T., Ruiz, A., Guinet, A., Fondrevelle, J. (2015). An integrated approach for sustainable supply chain planning. Computers & Operations Research, 54, 180–194. https://doi.org/10.1016/j.cor.2014.09.002
Brandenburg, M. (2013). Quantitative models for value-based supply chain management. Springer.
Brandenburg, M. (2015). Low carbon supply chain configuration for a new product – a goal programming approach. International Journal of Production Research, 53(21), 6588–6610. https://doi.org/10.1080/00207543.2015.1005761
Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2013). Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 233(2), 299–312. https://doi.org/10.1016/j.ejor.2013.09.032
Brandenburg, M., Kuhn, H., Schilling, R., & Seuring, S. (2014). Performance- and value-oriented decision support for supply chain configuration – A discrete-event simulation model and a case study of an FMCG manufacturer. Logistics Research, 7, 118. https://doi.org/10.1007/s12159-014-0118-8
Broz, D., Durand, G., Rossit, D., Tohmé, F., & Frutos, M. (2017). Strategic planning in a forest supply chain: A multigoal and multiproduct approach. Canadian Journal of Forest Research, 47(3), 297–307. https://doi.org/10.1139/cjfr-2016-0299
Broz, D., Vanzetti, N., Corsano, G., & Montagna, J. M. (2019). Goal programming application for the decision support in the daily production planning of sawmills. Forest Policy and Economics, 102, 29–40. https://doi.org/10.1016/j.forpol.2019.02.004
Calvete, H. I., Galé, C., & Polo, L. (2016). Integrated supply chain planning: A review. In R. León, M. J. Muñoz-Torres, & J. M. Moneva (Eds.), Modeling and simulation in engineering, economics and management (Lecture notes in business information processing) (Vol. 254, pp. 92–103). Springer International.
Chae, B. K., 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. https://doi.org/10.1080/00207543.2013.861616
Christopher, M. (2005). Logistics and supply chain management – Creating value-added networks (3rd ed.). Prentice Hall.
Das, K., & Posinasetti, N. R. (2015). Addressing environmental concerns in closed loop supply chain design and planning. International Journal of Production Economics, 163, 34–47. https://doi.org/10.1016/j.ijpe.2015.02.012
de Kok, T. G., & Fransoo, J. C. (2003). Planning supply chain operations: Definition and comparison of planning concepts. In A. G. de Kok & S. G. Graves (Eds.), Handbooks in operations research and management science (Vol. 11, pp. 597–675). Elsevier.
de Man, J. C., & Strandhagen, J. O. (2018). Spreadsheet application still dominates enterprise resource planning and advanced planning systems. IFAC PapersOnLine, 51(11), 1224–1229. https://doi.org/10.1016/j.ifacol.2018.08.423
Dougherty, J., & Gray, C. (2006). Sales and operations planning-best practices: Lessons learned from worldwide companies (3rd ed.). Trafford Publishing.
Durach, C. F., Wieland, A., & Machuca, J. A. D. (2015). Antecedents and dimensions of supply chain robustness: A systematic literature review. International Journal of Physical Distribution & Logistics Management, 45(1/2), 118–137. https://doi.org/10.1108/IJPDLM-05-2013-0133
Figueira, G., & Almada-Lobo, B. (2014). Hybrid simulation–optimization methods: A taxonomy and discussion. Simulation Modelling Practice and Theory, 46, 118–134. https://doi.org/10.1016/j.simpat.2014.03.007
Fildes, R., & Kingsman, B. (2011). Incorporating demand uncertainty and forecast error in supply chain planning models. Journal of the Operational Research Society, 62, 483–500. https://doi.org/10.1057/jors.2010.40
Fleischmann, B., Meyr, H., & Wagner, M. (2015). Advanced planning. In H. Stadtler, C. Kilger, & H. Meyr (Eds.), Supply chain management and advanced planning – Concepts, models, software and case studies (5th ed., pp. 71–95). Springer.
Ghadge, A., Wurtmann, H., & Seuring, S. (2020). Managing climate change risks in global supply chains: A review and research agenda. International Journal of Production Research, 58(1), 44–64. https://doi.org/10.1080/00207543.2019.1629670
Hahn, G. J., & Kuhn, H. (2012a). Designing decision support systems for value-based management: A survey and an architecture. Decision Support Systems, 53(3), 559–569. https://doi.org/10.1016/j.dss.2012.02.016
Hahn, G. J., & Kuhn, H. (2012b). Simultaneous investment, operations, and financial planning in supply chains: A value-based optimization approach. International Journal of Production Economics, 140(2), 559–569. https://doi.org/10.1016/j.ijpe.2012.02.018
Hahn, G. J., & Kuhn, H. (2012c). Value-based performance and risk management in supply chains: A robust optimization approach. International Journal of Production Economics, 139(1), 135–144. https://doi.org/10.1016/j.ijpe.2011.04.002
Haug, A., & Stentoft Arlbjørn, J. (2011). Barriers to master data quality. Journal of Enterprise Information Management, 24(3), 288–303. https://doi.org/10.1108/17410391111122862
Haulder, N., Kumar, A., & Shiwakoti, N. (2019). An analysis of core functions offered by software packages aimed at the supply chain management software market. Computers & Industrial Engineering, 138, 106116. https://doi.org/10.1016/j.cie.2019.106116
Hendricks, K. B., Singhal, V. R., & Stratman, J. K. (2007). The impact of enterprise systems on corporate performance: A study of ERP, SCM, and CRM system implementations. Journal of Operations Management, 25(1), 65–82. https://doi.org/10.1016/j.jom.2006.02.002
Hill, C. A., Zhang, G. P., Miller, & K. E. (2018). Collaborative planning, forecasting, and replenishment & firm performance: An empirical evaluation. International Journal of Production Economics, 196, 12–23. https://doi.org/10.1016/j.ijpe.2017.11.012
Ivanov, D. (2017). Simulation-based ripple effect modelling in the supply chain. International Journal of Production Research, 55(7), 2083–2101. https://doi.org/10.1080/00207543.2016.1275873
Ivanov, D., & Dolgui, A. (2020). Viability of intertwined supply networks: Extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. International Journal of Production Research, 58(10), 2904–2915. https://doi.org/10.1080/00207543.2020.1750727
Jonsson, P., Kjellsdotter, L., & Rudberg, M. (2007). Applying advanced planning systems for supply chain planning: Three case studies. International Journal of Physical Distribution & Logistics Management, 37(10), 816–834. https://doi.org/10.1108/09600030710848932
Jonsson, P., Rudberg, M., & Holmberg, S. (2013). Centralised supply chain planning at IKEA. Supply Chain Management: An International Journal, 18(3), 337–350. https://doi.org/10.1108/SCM-05-2012-0158
Kepczynski, R., Jandhyala, R., Sankaran, G., & Dimofte, A. (2018). Integrated business planning – How to integrate planning processes, organizational structures and capabilities, and leverage SAP IBP technology. Springer.
Kilpatrick, J. (2022). Supply chain implications of the Russia-Ukraine conflict. Deloitte Insights. Retrieved April 8, 2022, from https://www2.deloitte.com/xe/en/insights/focus/supply-chain/supply-chain-war-russia-ukraine.html
Knolmayer, G. F., Mertens, P., Zeier, A., & Dickersbach, J. T. (2009). Supply chain management based on SAP systems – Architecture and planning processes. Springer.
Kurbel, K. E. (2013). Enterprise resource planning and supply chain management – Functions, business processes and software for manufacturing companies. Springer.
Lainez, J. M., Puigjaner, L., & Reklaitis, G. V. (2009). Financial and financial engineering considerations in supply chain and product development pipeline management. Computers and Chemical Engineering, 33(12), 1999–2011. https://doi.org/10.1016/j.compchemeng.2009.06.025
Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1–25.
Meyr, H., Wagner, M., & Rohde, J. (2015). Structure of advanced planning systems. In H. Stadtler, C. Kilger, & H. Meyr (Eds.), Supply chain management and advanced planning – Concepts, models, software and case studies (5th ed., pp. 99–106). Springer.
Nagurney, A. (2021). Optimization of supply chain networks with inclusion of labor: Applications to COVID-19 pandemic disruptions. International Journal of Production Economics, 235, 108080. https://doi.org/10.1016/j.ijpe.2021.108080
Nikolopoulos, K., Punia, S., Schäfers, A., Tsinopoulos, C., & Vasilakis, C. (2021). Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions. European Journal of Operational Research, 290(1), 99–115. https://doi.org/10.1016/j.ejor.2020.08.001
Norrman, A., & Wieland, A. (2020). The development of supply chain risk management over time: Revisiting Ericsson. International Journal of Physical Distribution & Logistics Management, 50(6), 641–666. https://doi.org/10.1108/IJPDLM-07-2019-0219
Panahifar, F., Heavey, C., Byrne, P. J., & Fazlollahtabar, H. (2015). A framework for Collaborative Planning, Forecasting and Replenishment (CPFR) – State of the Art. Journal of Enterprise Information Management, 28(6), 838–871. https://doi.org/10.1108/JEIM-09-2014-0092
Peidro, D., Mula, J., Poler, R., & Lario, F. C. (2009). Quantitative models for supply chain planning under uncertainty: A review. The International Journal of Advanced Manufacturing Technology, 43, 400–420. https://doi.org/10.1007/s00170-008-1715-y
Pittman, P. H., & Atwater, J. B. (Eds.). (2019). APICS dictionary – The essential supply chain reference (16th ed.). Association for Supply Chain Management.
Reefke, H., & Sundaram, D. (2018). Sustainable supply chain management: Decision models for transformation and maturity. Decision Support Systems, 113, 56–72. https://doi.org/10.1016/j.dss.2018.07.002
Rodríguez, M. Á., Alemany, M. M. E., Boza, A., Cuenca, L., & Ortiz, Á. (2020). Artificial intelligence in supply chain operations planning: Collaboration and digital perspectives. In L. M. Camarinha-Matos, H. Afsarmanesh, & A. Ortiz (Eds.), Boosting collaborative networks 4.0. PRO-VE 2020. IFIP advances in information and communication technology (Vol. 598). Springer. https://doi.org/10.1007/978-3-030-62412-5_30
Rudberg, M., & Thulin, J. (2009). Centralised supply chain master planning employing advanced planning systems. Production Planning and Control, 20(2), 158–167. https://doi.org/10.1080/09537280802705047
Schlegel, A., Birkel, H. S., & Hartmann, E. (2021). Enabling integrated business planning through big data analytics: A case study on sales and operations planning. International Journal of Physical Distribution & Logistics Management, 51(6), 607–633. https://doi.org/10.1108/IJPDLM-05-2019-0156
Schmenner, R. W., & Swink, M. L. (1998). On theory in operations management. Journal of Operations Management, 17(1), 97–113. https://doi.org/10.1016/S0272-6963(98)00028-X
Seifert, D. (2003). Collaborative planning, forecasting, and replenishment: How to create a supply chain advantage. AMACOM.
Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699–1710. https://doi.org/10.1016/j.jclepro.2008.04.020
Shapiro, J. F. (2007). Modeling the supply chain (2nd ed.). Cengage Learning.
Sharma, R., Shishodia, A., Gunasekaran, A., Min, H., & Munim, Z. H. (2022). The role of artificial intelligence in supply chain management: Mapping the territory. International Journal of Production Research. https://doi.org/10.1080/00207543.2022.2029611
Shu, J., & Barton, R. (2012). Managing supply chain execution: Monitoring timeliness and correctness via individualized trace data. Production and Operations Management, 21(4), 715–729. https://doi.org/10.1111/j.1937-5956.2012.01353.x
Siebert, J. U., Brandenburg, M., & Siebert, J. (2020). Defining and aligning supply chain objectives before, during, and after the COVID-19 pandemic. IEEE Engineering Management Review, 48(4), 72–85. https://doi.org/10.1109/EMR.2020.3032369
Simchi-Levi, D., & Haren, P. (2022). How the war in Ukraine is further disrupting global supply chains. Harvard Business Review. Retrieved April 8, 2022, from https://hbr.org/2022/03/how-the-war-in-ukraine-is-further-disrupting-global-supply-chains
Stadtler, H. (2005). Supply chain management and advanced planning – Basics, overview and challenges. European Journal of Operational Research, 163(3), 575–588. https://doi.org/10.1016/j.ejor.2004.03.001
Stadtler, H. (2015). Supply chain management: An overview. In H. Stadtler, C. Kilger, & H. Meyr (Eds.), Supply chain management and advanced planning – Concepts, models, software and case studies (5th ed., pp. 3–28). Springer.
Stadtler, H., & Fleischmann, B. (2012). Hierarchical planning and the supply chain planning matrix. In H. Stadtler, B. Fleischmann, M. Grunow, H. Meyr, & C. Sürie (Eds.), Advanced planning in supply chains – Illustrating the concepts using and SAP® APO case study (pp. 21–34). Springer.
Stank, T. P., & Goldsby, T. J. (2000). A framework for transportation decision making in an integrated supply chain. Supply Chain Management – An International Journal, 5(2), 71–77. https://doi.org/10.1108/13598540010319984
Stindt, D. (2017). A generic planning approach for sustainable supply chain management – How to integrate concepts and methods to address the issues of sustainability? Journal of Cleaner Production, 153(1), 146–163. https://doi.org/10.1016/j.jclepro.2017.03.126
Stock, J. R., & Boyer, S. L. (2009). Developing a consensus definition of supply chain management: A qualitative study. International Journal of Physical Distribution & Logistics Management, 39(8), 690–711. https://doi.org/10.1108/09600030910996323
Tang, C. S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics, 103(2), 451–488. https://doi.org/10.1016/j.ijpe.2005.12.006
Terzi, S., & Cavalieri, S. (2004). Simulation in the supply chain context: A survey. Computers in Industry, 53(1), 3–16. https://doi.org/10.1016/S0166-3615(03)00104-0
Trkman, P., McCormack, K., Valadares de Olivia, M. P., & Bronzo Ladeira, M. (2010). The impact of business analytics on supply chain performance. Decision Support Systems, 49(3), 318–327. https://doi.org/10.1016/j.dss.2010.03.007
Turken, N., Cannataro, V., Geda, A., & Dixit, A. (2020). Nature inspired supply chain solutions: Definitions, analogies, and future research directions. International Journal of Production Research, 58(15), 4689–4715. https://doi.org/10.1080/00207543.2020.1778206
Willms, P., & Brandenburg, M. (2019). Emerging trends from advanced planning to integrated business planning. IFAC-PapersOnLine, 52(13), 2620–2625. https://doi.org/10.1016/j.ifacol.2019.11.602
Zhang, Z., & Awasthi, A. (2014). Modelling customer and technical requirements for sustainable supply chain planning. International Journal of Production Research, 52(17), 5131–5154. https://doi.org/10.1080/00207543.2014.899717
Zsidisin, G. A., Petkova, B. N., & Dam, L. (2016). Examining the influence of supply chain glitches on shareholder wealth: Does the reason matter? International Journal of Production Research, 54(1), 69–82.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive licence to Springer Nature Switzerland AG
About this entry
Cite this entry
Brandenburg, M. (2023). Operations and Supply Chain Planning. In: Sarkis, J. (eds) The Palgrave Handbook of Supply Chain Management. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-89822-9_94-1
Download citation
DOI: https://doi.org/10.1007/978-3-030-89822-9_94-1
Received:
Accepted:
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-030-89822-9
Online ISBN: 978-3-030-89822-9
eBook Packages: Springer Reference Business and ManagementReference Module Humanities and Social SciencesReference Module Business, Economics and Social Sciences