從ERP 交易資料發掘供應商績效評估指標
並考慮查詢構面

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姓名

吳佩蓉(Pei-Jung Wu) 查詢紙本館藏

畢業系所

工業管理研究所

論文名稱

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 Criteriafrom ERP Transactional Data withConsideration of Query Dimension )

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摘要(中)

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。

摘要(英)

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.

關鍵字(中)

★ 建立績效評估指標
★ 二元表示樹
★ ontology

關鍵字(英)

★ ontology
★ building indexes
★ binary expression tree

論文目次

摘要................................................................................................................................ I
Abstract.......................................................................................................................II
Table of Content ..........................................................................................................IV
List of Figures..............................................................................................................V
List of Tables.............................................................................................................. VI
Chapter 1 Introduction................................................................................................1
1.1 Introduction and motivation.........................................................................1
1.2 Problem definition .........................................................................................3
1.3 Research objective .........................................................................................3
1.4 Research framework......................................................................................4
Chapter 2 Literature review .......................................................................................5
2.1 Review the process of procurement..............................................................5
2.2 Schemas of data warehouse...........................................................................7
2.3 Class diagram of entity relationship diagram .............................................9
Chapter 3 Methodology.............................................................................................13
3.1 Constructing ontology of ERP data and key figures and queries in SAP
BW.......................................................................................................................14
3.1.1 Preprocessing.....................................................................................16
3.1.2 Categorizing and merging................................................................20
3.1.3 Segmentation .....................................................................................26
3.2 Constructing the structures of formula .....................................................30
3.3 Generating KPIs...........................................................................................35
3.4 Building the dimensional model .................................................................37
3.4.1 Finding out dimensions.....................................................................38
3.4.2 Constructing the fact table and dimension table of procurement
dimensional model .....................................................................................38
Chapter 4 Application................................................................................................40
4.1 Generated KPIs of data type of Quantity and compare with the indexes
in BW...................................................................................................................40
4.2 Apply the methodology to data type of Currency .....................................43
Chapter 5 Conclusion ................................................................................................53
5.1 Contribution of our research ......................................................................53
5.2 Limitation of our research...........................................................................53
5.3 Further research...........................................................................................54
Reference ....................................................................................................................55
Appendix A. InfoCubes of procurement process in SAP........................................57
IV
Appendix B. Queries of procurement ......................................................................72
Appendix C. Some InfoCubes of quality management and inventory management
.....................................................................................................................................90
Appendix D. Queries of quality and inventory management ..............................106
Appendix E Generated KPIs of data type of Quantity (source of data element is
from SAP R/3 system)..............................................................................................130
Appendix F Generated KPIs of Currency (source of data elements is from SAP
R/3 system)................................................................................................................137
Appendix G Generated KPIs of data type of QUAN (source of data element is
from key figures and queries) .................................................................................143
Appendix H Generated KPIs of CURR (source of data element is from key figures
and queries) ..............................................................................................................165

參考文獻

1. Kent Bauer, “KPI Identification With fishbone enlightenment”, DM Review,
Mar2005, Vol. 15 Issue 3, p12
2. Gulay Barbarosoglu, Tulin Yazgac, “An Application of the Analytic Hierarchy
Process to the Supplier Selection Problem”, Production and Inventory
Management Journal, First Quarter 1997, 14-21.
3. Howard Winkler, “Developing KPIs at Southern company”, Strategic HR Review,
MayJun2005, Vol. 4 Issue 4, p28
4. Jane Griffin, “Developing strategic KPIs for your BPM system”, DM Review,
Oct2004, Vol. 14 Issue 10, p70
5. Sui-Ming Lin, “Discovering Supplier Performance Criteria from ERP
transactional data”, national central university
6. Surajit Chaudhuri, Umeshwar Dayal, “An Overview of Data Warehousing and
OLAP Technology”, SIGMOD Record 26, 1(March 1997), p65-74
7. Peter Verdaasdonk, “An object-oriented model for ex ante accounting
information”, Journal of Information Systems, Spring 2003, Vol. 17, No. 1, p43-61
8. Kai-Ying Chen and Shui-Shong Lu, “A Petri-net and entity-relationship diagram
based object-oriented design method for manufacturing systems control”,
Computer Integrated Manufacturing, 1997, Vol. 10, No. 1-4, p17-28
9. Peretz Shoval, Revital Danoch and Mira Balabam, “Hierarchical
entity-relationship diagrams: the model, method of creation and experimental
evaluation”, Requirements Eng, 2004, Vol. 9, p217-228
10. Srinivas Tallurly and Joseph Sarkis, “A model for performance monitoring of
suppliers”, International Journal of Production Research, 2002, Vol.40, No. 16,
p4257-4269
11. Clyde W. Holsapple and K.D. Joshi, “A collaborative approach to ontology
design”, Communications of the ACM, 2002, Vol.45, No.2, p42-47
12. John O. Everett, Daniel G. Bobrow, Reinhard Stolle, Richard Crouch, Valeria De
Paiva, Cleo Condoravdi, Martin Van Den Berg, and Livia Polanyi, “Making
ontologies work for resolving redundancies across documents”, Communications
of the ACM, 2002, Vol.45, No.2, p55-60
13. Bowen Hui, Eric Yu, “Extracting conceptual relationships from specialized
documents”, Data & Knowledge Engineering, 2005, Vol 54, p29-55
1. Toby J. Teorey, Database Modeling & Design, Third Edition, Morgan Kaufmann
Publishers, Inc., San Francisco, California
2. Ralph Kimball Willey, the Data warehouse Lifecycle toolkit
3. Yedidyah Langsam, Moshe J Augenstein, Aaron M. Tenenbaum, Data Structures
56
Using C and C++, 2nd Edition, Prentice Hall
4. David Hoyle, Automotive Quality Systems Handbook: New International
Standards Requirements, Elsevier, 2000
Website
1. http://help.sap.com
2. http://www.oracle.com

指導教授

沈國基(Gwo-Ji Sheen)

審核日期

2006-7-11

推文