Forecasting on Product Chain
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Forecasting
Organizations concentrate on forecasting for their management and decision-making processes for planning and appropriate control to boost the firm performance and reduce risks (Chase, & Jacobs, 2014). Manufacturers rely on a forecast to design and produce new goods and services, compensations and decision making relevant to the section. The Periodic decisions concerning key supplier choice, process selection, planning, and layout as well as continuous decision within the supply chain process also rely on forecasting. There are different forecast approaches that companies can use to suit their needs depending on the demand analysis engaged.
Businesses can forecast on demand trends to either a particular year, or how they expect to meet the demand for their group of products or product line (Chase, & Jacobs, 2014). The video under review on forecasting is a presentation by Professor Vaidy Jayaraman on basics of supply chain management (Jayaraman, 2015). The presentation focuses on business analytics presenting details surrounding a company supply chain and on how data is critical for the process. It is, therefore, important to understand that supply chain forecasting requires data, and the appropriate use of data collected. Prediction is a universal concept that people use everywhere, countering the high degree of uncertainty about what will happen within a period.
Jayaraman presents that the supply chain consist of five major entities and forecasting is critical to those entities. The five objects play a crucial role in the supply chain, and suppliers play a key role necessary for the process (Jayaraman, 2015). Manufacturers source for suppliers depending on their products and response to the demands. Procurement department has a responsibility of determining the purchase and supply of materials, critical supplier base for the company, the quantity and time in which a supplier will deliver materials.
Production is also significant in putting the units together in a condition that meets the consumer needs. Distribution then ensures delivery to the final point (Jayaraman, 2015). The primary entities integration is essential in the understanding share of customer demand and in balancing supply and demand. Companies have since evolved to be consumer demand driven, where customer dictate every process of the supply chain. Uncertainty cannot be eliminated, but good forecast reduces the risk of change (Jayaraman, 2015).
An estimate is significant if the probability of prediction is likely to happen. Therefore, appropriate data and monitoring of trends are essential in establishing uncertainty and possible risks within the system. Choosing a forecast tool will depend on its appropriateness to the task performed by the company and type of product on the dealing. Jayraman (2015) explains that forecasting is always wrong. However, it is essential in using the tool as starting point for a manufacturer and the supply chain process. The data collected and its time series is an influential factor. Forecasting is appropriate on product aggregation and matching a product within a short period (Jayaraman, 2015).
Time series is essential to the influence of appropriateness of forecasting. Therefore, the shorter forecast has lesser error estimates as compared to longer period predictions (Jayaraman, 2015). With the presentation giving critical aspects of forecasting, it does not go to the end and leaves the audience in a dilemma. The major basic to understand the video presentation is that prediction is important and need to be carried out with the relevant data. The period should be dependent on the type of product on the play and its demand market.