| dc.description.abstract | The goal of the current thesis is to study how sales forecasts can predict and contributes to the improvement of business performance, and the data accuracy of sales forecasts relating to the overall efficiency of the its supply chain. The Z company integrates and manages various process activities within the supply chain through a reliable forecasting source, which can reduce the Bullwhip Effect brought by the supply chain, and makes the supply chain data more flexible and synergizing between production and market sales. The aim is to achieve a level of service that is satisfactory to the customer.
This research is based on Z company as the research subject. Using the regression analysis under the quantitative method which is used to define the most significant independent correlation variable and establishing its regression model from the sales forecast of insulating coating products, and then make a significant verification of the overall regression model. Utilizing significant test, collinearity test, ANOVA and residual analysis to conclude a predictive model.
The results of the study, can be seen that the cost side factor has no significant impact, but in the economic index ＂Taiwan Index of Producer’s shipment for Manufacturing＂; the Manufacturing purchasing manager′s index (PMI), ＂Employment Index＂, ＂ Material Price Index” and “New Order Export Index”; the downstream application market factor “The sales of Enamelled Wires” is significant. Based on the analysis of the regression model, the above five variables have a significant impact on the sales volume for the insulating coating products.
Keywords: insulating coating, sales forecast, regression analysis
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