1 / 22

Learning Supply Chain Management Through Use Of A Business Game

Learning Supply Chain Management Through Use Of A Business Game. Navonil Mustafee Korina Katsaliaki n.mustafee@ swansea.ac.uk | k.katsaliaki@ihu .edu.gr. Facilitating the Analysis of a UK NBS Chain ( Mustafee et al . 2009; Katsaliaki and Brailsford 2007 ).

felton
Download Presentation

Learning Supply Chain Management Through Use Of A Business Game

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Learning Supply Chain Management Through Use Of A Business Game Navonil Mustafee KorinaKatsaliaki n.mustafee@swansea.ac.uk | k.katsaliaki@ihu.edu.gr

  2. Facilitating the Analysis of a UK NBS Chain (Mustafee et al. 2009; Katsaliaki and Brailsford 2007) Beer Game (Sterman, 1984; 1989); Mortgage Service Game (Anderson and Morrice, 2000) • The Blood Supply Game • Mimics supply chain of blood from donors to patients • Models material and information flow • Perishable product • Limited collection/production Sterman, J. (1984), “Instructions for Running the Beer Distribution Game (D-3679), “Sloan School of Management, MIT. Sterman, J. (1989), “Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment,” Management Science, 35, 3, 321–339. Anderson Jr.E.G. and Morrice D.J. A simulation game for teaching service-oriented supply chain management: Does Information Sharing Help Managers with Service Capacity Decisions? Production and Operations Management, 2000, 9 (1): 40-55. Mustafee, N., Taylor, S.J.E., Katsaliaki, K. and Brailsford, S. (2009). Facilitating the Analysis of a UK NBS Chain Using the HLA. SIMULATION: Transactions of the Society of Modelling and Simulation International.Vol 85(2):113-128. Katsaliaki, K., and S. C. Brailsford. 2007. Using Simulation to Improve the U.K. Blood Supply Chain. Journal of the Operational Research Society, 58(2):219-227.

  3. Outdate Katsaliaki, K., and S. C. Brailsford. 2007. Using Simulation to Improve the U.K. Blood Supply Chain. Journal of the Operational Research Society, 58(2):219-227. (adapted from) Mustafee, N., Taylor, S.J.E., Katsaliaki, K. and Brailsford, S. (2009). Facilitating the Analysis of a UK NBS Chain Using the HLA. SIMULATION: Transactions of the Society of Modelling and Simulation International. Vol 85(2):113-128.

  4. The Supplier:The donors who provide the raw material (the unprocessed blood); • The Manufacturer:The National Blood Service (NBS) centre which tests, processes and transforms blood into blood products ready for use; • The Distributor:The NBS also plays the role of the distributor who has the responsibility to store the product and to transport it to the receiver when an order is placed; • Wholesalers:The hospital blood banks which place orders with the NBS, receive products from the NBS, and handle the blood stocks issued to them; • Retailers:The doctors at each hospital who place orders for blood products to hospital blood banks (wholesalers) to satisfy the needs of the patients. • End Users:The patients (end-user) in need for transfusion.

  5. The pedagogic purpose of the Blood Supply Game is fourfold: • To improve understanding of certain aspects of supply chains, such as variant supply and demand and distribution options; • To evaluate the overall impact of these principles which is different from the sum of the impact of each one of them; • Place the user in the position of managers who have to make real decisions; • Familiarisation with a graphical, business-oriented model. • The aim of the player is to make such decisions that maximise the ‘profit’ of the NBS; this is related with satisfying as many hospital patients and satisfying as many hospital orders as possible and careful control of NBS stock.

  6. 1 3 3 4 2 2 3 3 3 3 2 4

  7. Weekdays Time Day Max game play: 28 days Click to increment days

  8. STDEV= sqr(905)2: random number from the Normal distribution which is defined by the mean value of 905. Doctors’ orders will vary from week to week. STDEV= sqr(coll)1: random number from the Normal distribution which is defined by the mean value of the player’s choice. PTI weekly collections will vary from week to week. STDEV= sqr(508)3: random number from the Normal distribution which is defined by the mean value of 508. PTI weekly orders will vary from week to week.

  9. Scenario 1 – Assign Stock on Demand

  10. Scenario 1 – Assign Stock on Demand NBS profit calculation (scenario 1)

  11. Scenario 2 – Assign Stock on Demand with Adjusted Collections

  12. Scenario 2 – Assign Stock on Demand with Adjusted Collections NBS profit calculation (scenario 2)

  13. Scenario 3 – Assign Stock Collectively with Adjusted Collections

  14. Scenario 3 – Assign Stock Collectively with Adjusted Collections NBS profit calculation (scenario 3)

  15. Future Work • Multi-player version • More strategies • One day tutorial session

  16. Acknowledgements • Mr. Sebastian Kitching • Students of EBRM00 • HEA (Travel Grant)

  17. Questions

More Related