決策支援系統應用於傳統供應鏈管理時，雖然可以提供需求預測，分配製造資源來滿足客戶需求，也可以告知客戶交貨時間，但無法及時搜集整體供應鏈的資訊做整合性分析，因此所做的分析可能失去時效性。而網格供應鏈則是能利用其異構、適應性、共同分享特性，能夠及時取得整體供應商與客戶資訊。
因此本研究應用決策支援系統於網格供應鏈環境時，使用「指數平滑」與「迴歸分析」兩項預測方法，以協助供應鏈中之製造商進行銷售預測、原物料需求規劃，準確的銷售預測，可使整體生產程序從原料取得至出貨的時間大為提前，提昇客戶服務品質。
根據實作模擬結果，製造商預測追加訂購量與客戶實際追加訂購量之平均誤差值為43、誤差百分比為4.9%、準確率為95.1%、平均縮短4.9天的交貨時間。
Basically, applying Decision Support Systems to the traditional Supply Chain Management although can provide demand forecasting, distribute manufactory resources efficiently and inform clients of the delivery schedule. Nevertheless, it fails to collect overall data of supply chain in time for the integrated analysis which may result in invalidity. Grid Supply Chain is tailor-made to take a good advantage of configuration, adaptability, mutual sharing character to access all data of suppliers and customers.
This research emphasizes on applying a decision support system into the supply chain grid. Exponential smoothing and regression analysis methods are constructed in the system to assist the manufacturer on the supply chain grid to conduct sales forecasting and raw material demand planning. Time of the entire production process from material acquirement to product delivery can be ahead based on accurate sales forecasting and customer service is then enhanced.
Based on the actual stimulation result, the average odds between the extra order prediction from the manufacturers and the actual additional order amount from the clients are 43, equivalent to the margin for error around 4.9%, i.e. the precision ratio of 95.1%. The average delivery time is shortened by 4.9 days.
