Supply Chain Analysis: FastGood

Supply Chain Revisited 

FastGood, being a multinational FMCG company, has been maintaining a dispersed and wide supply chain network across South-East Asia. Currently, FastGood owns 3 factories, 5 suppliers and 13 distribution centers in Thailand, Malaysia and Indonesia. The company is selling 4 top performing products to its 440 customers disperse in the operation areas. However, the recent issues faced by FastGood include its products’ demand being shifted to the competitors due to the fluctuation of demand in all regions. As the demand is fluctuating, the company has to consider established the new DCs across the region.

Based on the given case study, the new DCs have been added to the current supply chain of FastGood. An upgraded supply chain network will build up the strength between the customers and company (Lutz & Ritter, 2009). The map above shows some new changes in the distribution center. The green color reflects the suppliers of FastGood while the three factories are shown in yellow. The fourteen distributions have been shown in orange color. The density of customers is shown in blue color. Almost all the distribution centers have been relocated and new have been added. The demand is highest in Indonesia (approximately 3 times as much as Malaysia and 4 times as compared to Thailand). It has been analyzed that there is a shortage of distribution centers in Indonesia. Only 9 distribution centers were previously present in the supply chain in Indonesia, however the new supply chain contains 11 distribution centers. The new distribution centers are constructed after analyzing the density of the customers in Indonesia. The new 2 distribution centers are added at the areas where the customers’ density is highest. Moreover, the current distribution centers are relocated in Indonesia at the areas where customers are the most. It has been analyzed that the most demand is originated in Jakarta, Indonesia. Previously, there were only 2 distribution centers in Jakarta, now new supply chain contains 4 distribution centers in Jakarta region. 1 new distribution center is added in Papua New Guinea to meet potential future demand from customers across the region. 

There were two distribution centers in Thailand, however it seems that the customers are concentrated in Bangkok. Due to this, one new distribution center is added there. Moreover, one distribution center was added in Malaysia as well because there were only two DCs in Malaysia. The factories will remain same. With these additions, there are now total 17 DCs spread in three countries. The new DCs are now present at more concentrated areas where the demand for products is more and customers are present (Nozick & Turnquist, 2001). This new supply chain will aid FastGood in being responsive enough towards fluctuating demand and meeting the needs of customers. As the company was facing issues in terms of lacking number of DCs at key locations, the new DCs will cover the demand of certain regions. The new DCs are added for satiating the needs of customers efficiently by identifying the areas where demand is certain (Andreoli, et al., 2010). By adding new DCs at concentrated areas and removing DCs from non-concentrated areas, FastGood will be able to reduce inventory holding costs and meet fluctuating demand.

When the DCs will be located near the high demanding market like Jakarta, the company will be able to fulfill the demand of its customers disperse in the highly concentrated area. By having DCs nearby, the transportation cost will also reduce and the company will also be able to reduce the risk of losing customers (Zhou, et al., 2002). As identified, the customers expect lead time of delivery to be less than 24 hours, this means that with new DCs, the company will be able to transit goods as soon as possible and the customers will get their goods in less than 24 hours. 

Moving Averages Analysis

Out of several forecasting methods, the prediction analysis of demand holds prime importance for FCMG companies. The demand forecasting is described as a process through which the customer demands for a good or service can be predicted over the next time period based on the historical data. In the given case, the demand for facial creams will be predicted by using the moving averages. The moving average is a method through which the trend line and future movement of values can be predicted efficiently (Khosroshahi, et al., 2016). By using this technique, the firms tend to minimize the overall noise in the short-term movement in the data. The name of “moving average” is given owing to the process of adding new demanded quantity at each progressive time period.