Improve forecast accuracy of sales opportunities Using Case Based Reasoning

• Main Authors: Chien-Jung Tsai, 蔡千嶸
• Other Authors: Chen-Shu Wang
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/f5mmwj

碩士 === 國立臺北科技大學 === 管理學院資訊與財金管理EMBA專班 === 103 === Estimation of Sales opportunities is the most key important performance measures of sales representative , and an important part to project the revenue for sales manager, therefore the accuracy of sales opportunities forecast directly affect the behavior patterns of sales, while the existing estimated methodologies are most like self-estimated by sales person, or define sales funnel by the sales stage, somewhat lose inaccurate on reliability. To solve accuracy problem of sales opportunities forecasting, this study proposes a case-based recommending system (Case-Based Reasoning CBR), based on historical data to proposed a recommend chance of orders , which is supported by data mining , analyzing data relationship, exploring data, and providing weighting for relevant attribute to reinforce for all the data accuracy. The results found that the CBR system for inexperienced or junior sales person are indeed able to provide effective reference data, and then convert existing data into knowledge, to achieve heritage purposes. Leverage CBR systems is helping knowledge transfer by using legacy data, while currently the weightage should be judge and analysis by domain expert, and request regularly review for the fitment, therefore automatic adjust for specific characteristic can be a research in the future.