從ERP 交易資料發掘供應商績效評估指標 並考慮查詢構面;Discovering Supplier Performance Criteria from ERP Transactional Data with Consideration of Query Dimension

NCUIR > School of Management at National Central University > Graduate Institute of Industrial Management > Electronic Thesis & Dissertation > Item 987654321/11187

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/11187

Title:	從ERP 交易資料發掘供應商績效評估指標並考慮查詢構面;Discovering Supplier Performance Criteria from ERP Transactional Data with Consideration of Query Dimension
Authors:	吳佩蓉;Pei-Jung Wu
Contributors:	工業管理研究所
Keywords:	建立績效評估指標;二元表示樹;ontology;ontology;building indexes;binary expression tree
Date:	2006-06-28
Issue Date:	2009-09-22 14:15:51 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	現今DW (一OLAP 系統) 以多緯度分析，提供績效評估指標給各管理階層人員使用，它將ERP 系統所包含的豐富資料顯示出來。但在實務上，由原始資料產生出現有的有限績效評估指標中，我們想要了解還有哪些更多的評估指標可供使用。基於這原因，引發我們做此研究的動機。藉由討論ERP 系統中，原始資料的資料屬性與DW 裡現有的公式結構，我們將找出一個機制來自動產生績效評估指標。在此研究裡，有三個子問題：分類ERP 系統裡原始資料的機制是什麼；由DW 裡可發現什麼樣的公式結構與運算子的分類(operator class)；如何結合ERP 系統的原始資料與運算子的分類。我們將由企業流程的角度做切入，使用ERP 的原始資料作發展指標的研究。為了產生更多指標，我們研究BW 的InfoCube 並蒐集裡面的key figure 與query。為了分類key figure 與query，我們用ontology 的方式作呈現。之後我們用二元表示樹(binary expression tree)來呈現公式的結構。再更進一步，由公式結構試著找出運算子的分類，並將它運用於ERP 的原始資料中。有了ERP 原始資料與運算子的分類，我們可以產生更多的績效評估指標。我們使用SAP 的BW 作比較基準。BW 裡關於數量(quantity)資料型態的績效評估指標有三十七個，關於貨幣(currency)資料型態的有二十三個。我們利用 ERP 原始資料產生出來有意義的績效評估指標，分別對數量與貨幣的資料型態各有四十八與三十八個。從產生出來的結果可以證明，使用我們發展出的機制的確可以產生更多的績效評估指標。 Recently, DW (one OLAP system) provides KPIs for managers to use. DW provides multi-dimensional analysis to display the abundant information which is carried by ERP systems. But in practice, calculating from existing raw data, the indexes are definite. Under limited number of off-the-rack KPIs in DW, we want to know what more indexes we can use. Our research is inspired by demand of finding out a method to develop more KPIs. By discussing the attribute of raw data in ERP systems and formula structures in DW, we will find out the mechanism and possibility of generating KPIs automatically. In this problem, there are three sub-problems: the mechanism of classifying raw data in ERP systems; what the formula structures found in DW and the operator class; the linkage of raw data in ERP system and operator class. We will use data in one of ERP systems to develop indexes. Our cutting point is from business process point of view. To generate more indexes, we will collect key figures of InfoCubes and queries. To represent the classification of key figures and queries, we use ontology to represent them. After we classify key figures and queries, we use binary expression tree to construct formula structures by means of formulas found in InfoCubes and queries. Further, from formula structures, we try to find out operator class that can also apply to the data in ERP system. With operator class and data of ERP system, we generate possible KPI candidates. We take SAP BW for comparing base. There are thirty-seven indexes and twenty-three indexes individually for data type of quantity and currency. Our generating meaningful KPIs from ERP data for quantity and currency are forty-eight and thirty-eight. From our results of generating KPIs, we find that we exactly can generate more KPIs than indexes existing in ERP system by using our methodology.
Appears in Collections:	[Graduate Institute of Industrial Management] Electronic Thesis & Dissertation

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