A Substantive Response

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ASubstantive Response

ASubstantive Response

BMaddressed one of the critical topics that are of a major concern tothe stakeholders, especially those who are responsible for themanagement of the supply chain. The topic of the Bullwhip effect hasgained popularity following an increase in the uncertainties thathave increased the difficulty of forecasting the required inventorywith accuracy. BM holds suggests that the process of managing thebullwhip effect should start with an effective analysis of internalas well as external causes of the effect. Although this argument iscorrect, these causes are classified into behavioral and operationalcauses in order to help the stakeholder design strategy that addresseach of the cause depending on their respective nature (Dadar,Sammidi &amp Gardner, 2014). A better understanding of the causes ofthe bullwhip effect is critical because studies have shown that someinterventions (such as exponential smoothing) that are taken beforeanalyzing the underlying causes can make thing worse by introducingthe bullwhip behavior in the organization. Therefore, BM’s findingsare consistent with the findings reported by Dadar, Sammidi andGardner.

Anotherchallenge that BM highlights as the key limitation to the process ofmanaging the bullwhip effect is the difficulty of determining thesustainability of a spike in sales. This is a correct observationbecause it would be difficult to manage inefficiencies in the supplychain if the stakeholders cannot determine the stability of thecurrent demand. According to Singhal Agarwal &amp Mittal (2011) theincrease in demand uncertainties, which can be attributed to regularchanges in customer behaviors and a stiff competition in the markethave complicated the process of managing the supply chain.

BMalso proposes the use of fuzzy forecast as an effective method ofpredicting product demand. Although there is no single formula thathas been identified as a perfect determinant of the future demand forany product in the modern market, the use of fuzzy estimate approachhelp the stakeholders reduce the level of uncertainties by reducinginformation variability between different stages along the supplychain (Tozan &amp Vayvay, 2008). For example, the fuzzy forecastapproach allows the stakeholders to use statistical strategies (suchas fuzzy regression, Neuro-fuzzy models, and time series), whichincrease the accuracy of predicting product demand (Tozan &ampVayvay, 2008).

BMsuggests that the just-in-time (JIT) strategy can be used to managethe bullwhip effect without giving the detailed explanation of howthe system works, which creates the need for additional information.JIT is considered as a pull system that applies the principle of leanproduction in the management of inventory. For example, the JIT pullsystem requires organizations to buy stock and manufacture when anorder has been placed (Dadar, Sammidi &amp Gardner, 2014). This isaccomplished when the form established effective methods of sharinginformation between the management, suppliers, and buyers. Effectivesharing of information ensures that the supply brings the exactquantity of stock that is required and the company produces the exactinventory of what customers need, thus helping the company avoid thecost of overstocking (Dadar, Sammidi &amp Gardner, 2014).

Inconclusion, BM addressed the critical elements (including the causes,effects, and mitigation strategies) of bullwhip effect. Mostimportantly, the emphasis on the analysis of specific causes of thebullwhip effect before developing solutions is important becauseexisting strategies are not one-size-fit all remedies. This impliesthat different solutions may address the different causes of theeffect and fail to resolve some.


Dadar,M., Sammidi, S. &amp Gardner, L. (2014). Reducing the bullwhipeffect in the supply chain: A study of different ordering strategies.TheJournal of Technology Studies,1, 52-63.

Singhal,P., Agarwal, G. &amp Mittal, M. (2011). Supply chain riskmanagement: Review, classification and future research directions.InternationalJournal of Business Science and Applied Management,6 (3), 1-28.

Tozan,H. &amp Vayvay, O. (2008). Fuzzy and neuro-fuzzy forecastingapproaches to whiplash effect in supply chains. Journalof Naval Science and Engineering,4 (1), 27-42.

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