Discuss about the Conference on Marketing and Business Development.
Exhibit 12 shows exceptional fluctuations that are really significant while considering the aggregate demand for pasta in the country of Italy. The instability in the weekly demands from the Northeast DC is resulted by various reasons. The first reason is the fluctuation in customer’s demand due to the seasonal changes (Morrone, Russo & Calace, 2015). These fluctuations are quite predictable. Secondly, the demand from the distributors differs for various factors like volume discounts, transportation and promotions, long time for lead (10 days), packing design and sizes, various types of products, no specific quantities for minimum and maximum order. Moreover, the suppliers do not have the system or tools for forecasting. They take the benefit of transportation or volume discount during the promotional period to stock the order in advance for weeks and in future weeks they order very less amount or nothing and use the stocked inventory. Another reason for fluctuation is the poor communication among the sales and marketing team, distributors, manufacturers, retailers (Tan, Hilmola & Binh, 2016).
The nature of the supply chain is of complex type. The distributors have various kinds of customers like small shops and supermarkets and they have various strategies. Many stages are involved in the supply chain between the factories and the end-use-customers. The demand is not predictable or not possible to keep track of sales from the stores and from the distributors. The fluctuation in demand lead to the “bullwhip effect” that is the enlarged variation in the demand pattern and involvement of more stages in the supply chain. This is the most evidential in exhibit 12 and it can be seen that there are 4-6 point in the orders and that is followed by the exceptional low order immediately after that (Brinkhoff, Özer & Sargut, 2015).
Barilla Spa is the largest manufacturer of pasta globally. The organization sells their pasta large number of retailers in Italy through the third party supplier and distributors towards the end of 1980 and they suffered cost penalties and growing inefficiencies in operations that caused due to the large variations in their week-to-week distribution pattern (Di Guardo & Castriotta, 2013).
The fluctuation effect put Barilla in a circumstance where the production is not sufficient or the finished goods production is in excess. This outcome reveals that either the company is holding large stock of inventories or is stocked out. The expenses are directly related to the loss of revenue as the cost of holding the inventory and competition respectively. Owing to the fluctuations, the logistic manufacturing operations are pressurised. Al the end of the distributor, the effect of the fluctuation leads to set up additional capability to hold the excess production of purchase any kind of promotion.
Stock outs are expensive as they lead to loss of sales because the customers are likely to buy the competitor’s product and it can be seen from exhibit 13 that the stock out level is around 5% or more than that. As the margins are diminishing, it would be advantageous for the operation to minimize the cost of the whole company. Moreover, the large scale of buffering in inventories requires cost expenses and is likely to conceal various issues in the procedures (Islam et al., 2013).
Brando Vitali, the ex-logistic director of Barilla suggested just-in-time distribution (JITD) tools for contradict the issues regarding the variation in demand. This tool needs the distributors to reveal the data with Barilla regarding sales and the company will forecast and supply exact quantity product at appropriate time to the distributors to meet the demand effectively. This was a drastic change from the traditional setup for the supply chain where the distributors were not used to share the data regarding sales with the company. However, the suggestion of Vital faces several criticisms from the distributors as well as from the own marketing and sales department of Barilla due to various reasons.
As under the JITD approach the products are supplies as when the demand is raised from the distributor, there is no need to stock the product on the warehouse on a large scale. Thereby the cost of storing the product is minimised. On the other hand, there is no need for excess production. Therefore, the level of expired products will be minimised. Thus, the JITD approach can be used as a measure for cost reduction (Seuring, 2013).
The system of JITD works through the cooperation between seller and distributor. The distributor must reveal their sales forecast to the seller and based on the forecast, the seller will provide the product to the distributor as and when the demand will be raised by the distributor. It is quite same like the collecting the point-of-sale information from the retailers, that is the seller will respond to the sell through data just one stage behind of the retailers. Actually, the seller will use the sell-through information from the retailer.
Barilla must go ahead to implement the JITD approach. The reason behind this is the JITD implementation is aligned with the business objectives of Barilla. JITD will allow the company to theoretically reduce the uncertain demand, which in turn, will maximize the uses of their assets and minimize the level of inventories and will increase its revenue through removing the stock-outs (Koz?owski, Gola & ?wi?, 2014).
From distributor: The distributor’s view is that they they require to reveal their sales figure or their warehouse to Barilla. Moreover, they can improve their service and inventory level on their own that will assist them to get the inventory faster as they prefer to place their order as and when necessary and Barilla is supposed to deliver the goods within 36 hours.
From marketing and sales department: They think that the sales level of the company will be flatten if the JITD approach is introduced and without any incentive they will not force the retailers to buy the product of Barilla. Moreover, they feel that if the space in the distributor’s warehouse freed up then they will stock the competitor’s product. Further, they are in the view that the distribution channel not ready yet to handle the sophisticated relationship of JITD.
Maggiali can persuade the customers to try the JITD approach through following:
Before the implementation of the JITD tool, Barilla must obtain the acceptance from their internal bodies to smoothen the distribution channel. Various internal departments are there who will be affected by the JITD approach. The marketing and sale department feel that they spend significant time with the distributor to assist them in preparing the weekly demand pattern and incorporating discounts and promotion into their strategies for sales. They feel that the JITD approach will eliminate the need of sales representative, which in turn, lead to cutting of jobs for the sales staffs.
The marketing strategy is also a crucial part of Barilla which will be affected with the implementation of the new procedure. The sales of the organization come from the promotional tools and discounts, on a large scale that are given as incentives to the distributor. However, without incentives they are less likely to take active part in the distribution. Another issue is that, if the JITD approach is implemented, it will leave a vacant space in the warehouse of the distributors and the company is in the view that the vacant space will be filled up by the competitor’s product which in turn, will reduce the sales level of Barilla. The total number of product that are dealt by Barilla is another factor of concern. With the SKU of 800 dry products, it is quite tough to adjust the distribution channel in accordance with the JITD approach (Lee & Prabhu, 2016).
The sales people of Barilla spend 90% of their time with the stores. They assist the company in setting up for the in-house promotions, merchandising the products of the company, taking note of the competitive data related to the stock outs, price, introduction of new product and the ordering approaches.
Additionally, they spend half day for weekly meetings held with the retailers, distributors, buyers and assist the distributor for estimating their weekly order and incorporation of discounts and promotions into the plan.
Moreover, they spend few times with the CDC to discuss about the new pricing strategies and new products, issues that were faced in the previous week’s deliveries and settlement if issues regarding the discount and deal structures. However, if the JITD system is incorporated, the sales people’s requirement will be decreased or there will be no need of the sales representatives. In such an circumstance, this is very obvious that the sales people will not be willing to accept the JITD approach (Khan, Khan & Sohail, 2014).
It is quite understandable that Barilla is only looking out for their own interest, however, they should not ignore the interest of the distributors completely. It is obvious that Barilla is not interested in allowing their distributors for taking the best possible decision for their organization as the present scenario costing them bigger hassle and money. One party must not control and take the decisions completely without taking consideration the view of other party. If Barilla is willing to offer the distributor the cost incentives like on bulk purchase, the distributors are more likely to accept the JTID approach (Zhong et al., 2013).
References:
Brinkhoff, A., Özer, Ö., & Sargut, G. (2015). All You Need Is Trust? An Examination of Inter?organizational Supply Chain Projects. Production and operations management, 24(2), 181-200. Available at https://onlinelibrary.wiley.com/doi/10.1111/poms.12234/full
Di Guardo, M. C., & Castriotta, M. (2013). The challenge and opportunities of crowdsourcing web communities: an Italian case study. International Journal of Electronic Commerce Studies, 4(1), 79. Available at https://search.proquest.com/openview/33ec8db3e8603c1890c7181a7ce1faa5/1?pq-origsite=gscholar&cbl=2030559
Islam, D. M. Z., Meier, J. F., Aditjandra, P. T., Zunder, T. H., & Pace, G. (2013). Logistics and supply chain management. Research in Transportation Economics, 41(1), 3-16. Available at https://www.sciencedirect.com/science/article/pii/S0739885912001606
Khan, S. N., Khan, M. A., & Sohail, R. (2014). The Bullwhip Effect in Different Manufacturing Paradigm: An Analysis. Economia. Seria Management, 17(1), 140-171. Available at https://mer.ase.ro/files/2014-1/11.pdf
Koz?owski, E., Gola, A., & ?wi?, A. (2014). Model of production control in just-in-time delivery system conditions. Advances in Manufacturing Science and Technology, 38(1). Available at https://yadda.icm.edu.pl/baztech/element/bwmeta1.element.baztech-48b4a37d-0b3b-4b36-8889-079fc81177bf
Lee, S., & Prabhu, V. V. (2016). Just-in-time delivery for green fleets: A feedback control approach. Transportation Research Part D: Transport and Environment, 46, 229-245. Available at https://www.sciencedirect.com/science/article/pii/S1361920916301833
Morrone, D., Russo, A., & Calace, D. (2015, November). Family Firms’ CSR Actions: the Case of Barilla. In International Conference on Marketing and Business Development (Vol. 1, No. 1, pp. 366-376). Bucharest University of Economic Studies Publishing House. Available at https://www.mbd.ase.ro/?p=193
Seuring, S. (2013). A review of modeling approaches for sustainable supply chain management. Decision support systems, 54(4), 1513-1520. Available at https://www.sciencedirect.com/science/article/pii/S0167923612001741
Tan, A., Hilmola, O. P., & Binh, D. H. (2016). Matching volatile demand with transportation services in Vietnam: A case study with Gemadept. Asia Pacific Journal of Marketing and Logistics, 28(1), 160-174. Available at https://www.emeraldinsight.com/doi/abs/10.1108/APJML-05-2015-0079
Wan, Y. L., Zhu, H. P., Mu, Y. P., & Yu, H. C. (2014). Research on iot-based material delivery system of the mixed-model assembly workshop. In Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013) (pp. 581-593). Springer Berlin Heidelberg. Available at https://link.springer.com/chapter/10.1007/978-3-642-40060-5_56
Wieland, A., & Handfield, R. B. (2016). Supply Chain Management. In 5th World Conference onProduction and Operations Management. P&OM 2016. Available at https://www.forskningsdatabasen.dk/en/catalog/2350919704
Zhong, R. Y., Dai, Q. Y., Qu, T., Hu, G. J., & Huang, G. Q. (2013). RFID-enabled real-time manufacturing execution system for mass-customization production. Robotics and Computer-Integrated Manufacturing, 29(2), 283-292. Available at https://www.sciencedirect.com/science/article/pii/S0736584512000956
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