We were given a chocolate factory case study to practice supply chain mapping as Halloween was just around the corner. Necanko, Inc. is a major chocolate producer headquartered in the United States. They made chocolates all year, with demand fluctuating. Karen Mazzoli, a buyer-scheduler at Necanko, examined sales demand and was unsure about the predictability of the forecast, why sales were increasing, and what actions she would take.
I began by noting the various processes and parties involved in delivering the chocolates to the end consumer. As we made the supply chain map with common conventions, I had experience with how to build a technical network architecture, and the example of supply chain mapping we looked at in class helped me see the different types of relationships and flows of resources (information, materials, and money) between supply chain actors in a way that was easy to understand. We created product flow but were unable to link it with information and financial flow since there was insufficient data. Concerns were required. It was challenging for me to map it with the product flow.
After mapping, I considered several reasons for the unexpected sales increase. First, the lack of upstream sales data suggests they relied on corporate and warehouse weekly sales and inventory reports. Karen can find out what candy brokers promised retailers and whether prices have changed or promotions have been implemented, which causes the bullwhip effect. Talking to the marketing department and brokers to determine if the demand change is real or fake. These relationships provide demand and capacity management data. Second, this is a company that has been changing its production schedule and laying off many employees. So, what effect will this increase in anticipated sales have? It could cause an overreaction to unexpected or unplanned changes in demand and prices.
This case study inspired me to consider various viewpoints from group discussions and helped me understand with supply chain mapping strategies. Discovering that the root causes of the bullwhip effect are miscommunication and a lack of coordination among supply chain participants. Karen was flooded with information from the case study, some of which may not even be pertinent. As a result, information filtering is crucial, and it is important to have access to real-time demand data.