Introduction
Seasonal demand affects the inventory therefore it is important to manage inventory because it helps in resource planning and supply chains management. For an origination that needs to maintain its competitive advantage, it should manage effectively its inventory and supplies.
Inventory plan and supply chain for seasonal shopping
Drop shipping
This is a method for supply plan for seasonal shopping. Because seasonal products are time-specific, medium and small retailers may take the drop shipping adage instead of the seasonal items manufacturing. Such a method involves using the third-party suppliers in holding inventory as well as fulfilling customer orders (Li et al, 2019). Therefore, such a process ensures that the seller involved never gets in touch with that product in any case. Even though the order is fulfilled through the worshipper, the customer only places the order from the shop. This method proves to be a good one in management of the inventory and freeing up the warehouse space. It hampers down the hassles of managing inventory and operations.
Demand Analysis
In order to plan for inventory of seasonal shopping, it is important to plan for demand analysis. This would help in acquiring the right product for the right time to be sold during the season pick. One way of doing demand analysis to come up with social media analysis where the anticipated demand for such items would be determined. The trending of products at Google searches as well as social media would help in coming up with the right decisions on replenishing the inventory and planning for supplies (Agarwal, 2018). They can give cues on modifying the efforts while competing with others. Also, the understanding of trending products may be a huge advantage which the seller would have since it would give the glimpse of which products are safe in stock and at what quantities are required. Hence, it helps in avoiding unpredictable demand or supply fluctuations.
Past historical data analysis
This is an important supply chain and inventory management plan. Looking for the historical purchase data and sales data is important to come up with a good shopping plan for the inventory and suppliers (Kilimci et al, 2019). Taking a close analysis on the monthly sales volume and during holidays or events when seasonal products sales are at pick would help in determining what products volumes are at demand during such events. Therefore, it would help in effective management of inventory by giving a detailed and real data on past sales and supplies management.
Technological plan for Supply and Inventory planning
It would be an appropriate thing for an organization to come up with technological solutions that would help in planning of the sales of seasonal products. Acquisition or development of demand planning application would be a better thing to automate and project supply and inventory. A reliable forecast may be based on effective mathematics algorithms which would help in planning on holiday rush and sales of seasonal products (Xu et al, 2019. Through the use of intelligent forecasting resources, inventory manages may be able to develop efficient supply chain plan that can be used in in achieving optimal planning. Seasonal trends like Black Friday may be used to automatically project the forecast of demand. Also, it may help in planning for inventory and restocking of the warehouse. Therefore, a manageable quantity of the seasonal products would usually be kept at the inventory and it would facilitate the better management of products with reduced losses due to excess inventory and off-peak emergence. Such intelligent systems may be used on holidays such as Christmas to determine the planning of seasonal products in inventory and in supply chain. It helps in coming up with the customer knowledge, market trends, planner experience and current events which would affect the demand and supply of such seasonal products.
Categorization of seasonal product
Another step towards the management of supply chain and inventory of seasonal products is through categorization of the seasonal products. Based on this section of plan, the following categorization can be followed;
- Product lifecycle – these products are usually having both traits of off-season and on-season. For instance, products like Halloween decorations have in-season while products such as candy have been sold on year-round and still show seasonal peaks (Saros, 2018).
- Season length – this determines the extreme at which it would respond to the actual demand during in-season. During short season, one needs to deliver the expected total demand quantities in storage before the commence of a season. For the longer seasons, replenishing of the stores and inventory would need to be done several times while the season is on (Soysal et al, 2019).
- Lead time of purchase – such products would determine whether one would need to acquire full quantity purchase ahead of a season or obtaining additional stock while in-season when necessary. Lead time dictates the lead time risk associated to purchases during pre-season (Smaros, 2018).
Conclusion
This supply chain and inventory plan has demonstrated ways through which a company would manage seasonal products. When such a plan is implemented, there would be a minimized risk on inventory as well as prevention of lost opportunities at supply chain.
References
Agarwal, K. (2018). Seasonal Inventory Management Made Easy. Retrieved from https://www.orderhive.com/smart-tips-dont-be-fazed-by-seasonal-inventory
Li, G., Zhang, X., & Liu, M. (2019). E-tailer’s procurement strategies for drop-shipping: Simultaneous vs. sequential approach to two manufacturers. Transportation Research Part E: Logistics and Transportation Review, 130, 108-127.
Smaros, J. (2018). Seasonal Inventory Management – Planning for Halloween. Retrieved from https://www.relexsolutions.com/seasonal-inventory-management-planning-for-halloween/
Soysal, G., & Chintagunta, P. K. (2019). What Explains Price Declines in Seasonal Goods Markets? An Empirical Examination. An Empirical Examination (January 10, 2019).
Kilimci, Z. H., Akyuz, A. O., Uysal, M., Akyokus, S., Uysal, M. O., Atak Bulbul, B., & Ekmis, M. A. (2019). An Improved Demand Forecasting Model Using Deep Learning Approach and Proposed Decision Integration Strategy for Supply Chain. Complexity, 2019.
Xu, G., Feng, J., Chen, F., Wang, H., & Wang, Z. (2019). Simulation-based optimization of control policy on multi-echelon inventory system for fresh agricultural products. International Journal of Agricultural and Biological Engineering, 12(2), 184-194.