Demand forecasting is an essential process due to the usage of crucial data to influence the future, which stands to benefit customers and businesses. The issued scenario offers a platform to exercise the technique leading to recommendations that are considerable to meet the estimated surge in demand for the sale. It equally conceptualizes other elements regarding the supply chain that are considerable.
Demand forecasting informs a significant aspect of businesses considering the rational target of acquiring the highest returns from goods and services sold. According to Song et al. (2019), demand forecasting is “a field of predictive analytics which tries to understand and predict customer demand to optimize supply decisions by corporate supply chain and business management.” It contextualizes the importance of assessment of data to predict the future with the technique factoring utilization of the instrument. Historical sales are a significant key performing indicator assessed with demand forecasting equally focusing on test markets’ statistical techniques. The predictive analytic approach is applicable in “production planning, inventory management, and at times in assessing future capacity requirements, or in making decisions on whether to enter a new market” (Arias & Bae, 2016). It magnifies the essentialness of the technique with positive future effects when adequately and efficiently utilized to meet market needs while concurrently improving business performance. The issued scenario is a perfect example of applying demand forecasting with the given data essential in making decisions for the retail sector.
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The scenario requires management to upscale by offering incentives for the sale of the good with the trajectory informing the necessity for additional stock. The issued case has one sect deciding to give a customer substantial discounts during the peak season using inventory at hand. The underlying reason for the move is the release of an emerging product in the market to cope up with the competition. Leadership should release at hand by releasing inventory left in the stock, which magnifies the need to go beyond the usual and offer an incentive like a significant discount on the product’s price. It would see an increase in the good’s sale. The demand forecast graph posits that during the seasonal demand of a product, it is advisable to hold more stock. Considering the situation whereby management opts to release a new good, the ideal option to take would involve getting rid of old product stock then going ahead with the target. Therefore, I would recommend efficient engagement and offering incentives as illustrated.
Elements of the supply chain that are considerable in the planning for the increase in demand is the processes which involve planning, developing, making, and conveying. The first stage consists of a program regarding the manner the administration would address clients’ issues (Şahin & Topal, 2019). For the scenario, there is a need to ponder on establishing a profitable inventory system. The second stage involves creating a framework for a stable relationship, considering the issuers of unpolished resources (Şahin & Topal, 2019). For the scenario, there is a need for consideration of any significant provider and positioning essential techniques for transportation, transference, and instalment. The third stage is the accumulating step. For the scenario, some considerable elements include inventory linkage directors planning for group training with the scene offering the platform to avoid missing on substantial product yield. The final stage involves coordination. For the scenario, its consideration would enhance the organization and transmission of stock accompanied by meeting the needs of clients. Therefore, considering the mentioned elements of the supply chain when preparing for the increase in demand would meet the market needs.
I would recommend selling existing stock before releasing the new product, which may require offering incentives as a mode of preparing for the estimated surge in demand for the sale. The supply chain process which factors planning, developing, making, and conveying are other considerable elements to prepare for the increment. The scenario magnifies the advantage of demand forecasting, which factors historical sales data for meeting customer and business needs.
References
Arias, M. B., & Bae, S. (2016). Electric vehicle charging demand forecasting model based on big data technologies. Applied energy , 183 , 327-339.
Şahin, H., & Topal, B. (2019). Examination of effect of information sharing on businesses performance in the supply chain process. International Journal of Production Research , 57 (3), 815-828.
Song, H., Qiu, R. T., & Park, J. (2019). A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting. Annals of Tourism Research , 75 , 338-362.
