StarTech is a manufacturer and the distributor of hard-to-find technology products. During the preceding four years, its revenues increased by more than $70 million. This increase made the operation of the company more complicated and revealed the necessity to improve the supply chain. Currently, StarTechs products are sold either through distributors, online direct marketers, value-added resellers, and direct sales to end-consumers. Most of StarTechs products are manufactured in Asia and then shipped to warehouses in Canada, the United States, and the United Kingdom via marine or airfreight. To find a way on how to keep the rate of sales growing faster than the rate of the companys investment in inventory, it might be recommended to have different demand forecasting process for products in different life cycles and restructure demand forecasting based on anchor product relationships.
The First Recommendation
The advice to implement different demand forecasting process for products in different life cycles seems to be an effective strategy that would contribute to the reduction of high transportation costs and investments in inventory. Apparently, during the entire life cycle of the product, the demand for it is different. This means that at the stage of growth, maturity, and decline, the number of units sold per week would vary greatly. Demand forecasting allows predicting future sales through the analysis of historical sales data. The precise forecast of sales assists to estimate the necessary rate of investment in inventory and, therefore, to avoid wastes related to the excessive spending. The given case study shows that currently, StarTechs demand forecasting process does not differ during the entire life cycle. The implementation of the suggested strategy is expected to help the company keep its sales growth without increasing the rate of inventory investments.
For example, the demand forecasting for the products that are in the stage of maturity and of growth should be different. That is because, at the stage of maturity, the demand increases less dramatically in comparison with the demand at the stage of growth. The more precise prediction of demand that takes into account the stage of a products life cycle allows to better predict the needed supply and reduce the costs connected with manufacturing and storage of the excessive goods.
The Second Recommendation
The second recommendation suggests the restructuring demand forecasting based on anchor product relationships. To some extent, this advice is closely connected to the previously mentioned one since it argues that the objective of StarTechs administration could be achieved through the more accurate demand forecasting. The difference lies in the fact that the demand forecast should include not only the stages of life cycle but also relations between the anchor products. In other words, it is suggested to take into consideration the fact that the growing demand for one product might turn into increasing demand for a supplementary product or a lower demand for a substitutional product.
More precisely, the growing demand for portable batteries might lead to a higher need for specific cables. At the same time, the appearance of wireless batteries that charge devices via Bluetooth connection would lead to lower demand for the traditional portable batteries and wires. The given case study reveals that StarTech offers a wide range of various cables. Therefore, demand forecasting should be restructured so that it would take into consideration the changes in demand for other products, the utilization of which requires cables.
