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Demand forecasting is a crucial aspect because it largely contributes to efficient decision-making in terms of different organizational operations, particularly in the case of manufacturing companies. In this regard, forecasting is a fundamental process in demand management and other related activities. Forecasting accuracy, for instance, is associated with increased operational performance, in terms of delivery and cost performance. For instance, the company in Hangzhou, China location faces issues pertaining to poor deliveries due to lack of a demand plan, and more so, a forecasting process.
This indicates the need for the plastic company to establish a comprehensive demand plan, which includes forecasting techniques.
There are different forecasting methods or techniques, which companies can use to establish a demand plan. Murphy and Knemeyer (2014) identify three major forecasting methods, judgmental, time series, and cause and effect. Judgmental forecasting involves the use of judgment or intuition and is mainly used in situations where there exists no historical data. For instance, judgment forecasting is employed in cases where a new product has been introduced.
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Some of the methods used in judgement forecasting include surveys and the analogue technique. The former requires a deep understanding of the survey design and sampling methodologies, while the latter involves identifying a similar item with the one being forecasted, then using the demand history of this item to establish a relevant forecast.
The second forecast method is time series, which focuses on forecasting future demand based on the past demand. Among the forecasting techniques under the time series method, include weighted moving averages and simple moving averages.
The weighted moving average technique uses more recent data when making future demand. On the other hand, the simple moving technique uses data from different time periods to make forecasts. Therefore, there is a possibility of failing to detect recent changes in demand.
The third forecasting method is cause and effect. It looks into how different factors influence demand, thus making forecasts. Some of the forecasting techniques under this method include simple and multiple regression. Simple regression identifies demand based on one variable, while multiple regression makes demand based on more than one variable.
In my view, the plastic company should consider the time series forecasting method. This recommendation is based on the view that the company has made sales in the past, thus it is possible to evaluate the trends of past demand and predict the future. In this case, it is advisable to employ both simple moving averages and weighted moving averages techniques. A combination of these techniques will enable the company to make informed decisions in terms of the technique that leads to accurate demand forecasts.
It is important for both manufacturing and service companies to establish forecasting and inventory strategies because they lead to improved performance, among other benefits. For instance, effective forecasting and inventory strategies help a manufacturing company achieve supplier and customer satisfaction due to smooth supply chain management. It is rarely to face issues of cancellations or rush orders. Furthermore, customer orders are delivered on time, as there are cases of out of stock and late deliveries notices. In the case of service companies, accurate forecasting strategies ensure that customer expectations are met, in terms of service delivery.
If the company in China uses the time series method, the company in China will establish an effective way of managing its supply chain. The company will be in a position to achieve customer and supplier satisfaction, leading to ultimate organizational performance. This is due to proper demand management. In additional, the organization will be in a position to establish a string financial structure. This occurs due to successful inventory management; thereby an organization is less likely to incur costs associated with excess inventory.
Evidently, demand forecasting is an important element of an organization because it plays a key role in planning and control of the supply chain. Forecasting ensures that an organization is able to stock relevant units without having excess inventory. Consequently, it is possible to prevent unnecessary costs. Therefore, in order for the plastic manufacturing company to make on-time deliveries, there is need to engage in demand and inventory management.
An Importance Of Demand Forecasting. (2024, Feb 10). Retrieved from https://studymoose.com/an-importance-of-demand-forecasting-essay
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