Enterprise Information System and Data Mining

2012 ◽  
pp. 228-235
Author(s):  
Kenneth D. Lawrence ◽  
Dinesh R. Pai ◽  
Ronald Klimberg ◽  
Sheila M. Lawrence
Keyword(s):  
Data Mining ◽  
Supply Chain ◽  
Information Systems ◽  
Business Intelligence ◽  
Large Data ◽  
Customer Relationship ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Competitive Edge ◽  
Organizational Functions

The advent of information technology and the consequent proliferation of information systems have lead to generation of vast amounts of data, both within the organization and across its supply chain. Enterprise information systems (EIS) have added to organizational complexity, and at the same time, created opportunities for enhancing its competitive advantage by utilizing this data for business intelligence purposes. Various data mining tools have been used to gain a competitive edge through these large data bases. In this paper, the authors discuss EIS-aided business intelligence and data mining as applicable to organizational functions, such as supply chain management (SCM), marketing, and customer relationship management (CRM) in the context of EIS.

Enterprise Information System and Data Mining

2010 ◽  
Vol 1 (3) ◽  
pp. 34-41 ◽  
Author(s):  
Kenneth D. Lawrence ◽  
Dinesh R. Pai ◽  
Ronald Klimberg ◽  
Sheila M. Lawrence
Keyword(s):  
Data Mining ◽  
Supply Chain ◽  
Information Systems ◽  
Business Intelligence ◽  
Large Data ◽  
Customer Relationship ◽  
Enterprise Information System ◽  
Enterprise Information ◽  
Competitive Edge ◽  
Organizational Functions

The advent of information technology and the consequent proliferation of information systems have lead to generation of vast amounts of data, both within the organization and across its supply chain. Enterprise information systems (EIS) have added to organizational complexity, and at the same time, created opportunities for enhancing its competitive advantage by utilizing this data for business intelligence purposes. Various data mining tools have been used to gain a competitive edge through these large data bases. In this paper, the authors discuss EIS-aided business intelligence and data mining as applicable to organizational functions, such as supply chain management (SCM), marketing, and customer relationship management (CRM) in the context of EIS.

Customer Relationship Management (CRM) Metrics - What's the Holdup?

2011 ◽  
pp. 1679-1685
Author(s):  
Timothy Shea ◽  
Ahern Brown ◽  
D. Steven White ◽  
Catherine Curran-Kelly ◽  
Michael Griffin
Keyword(s):  
Information Systems ◽  
Enterprise Resource Planning ◽  
Business Strategy ◽  
Relationship Management ◽  
Resource Planning ◽  
Customer Relationship ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Industry Standard ◽  
Development Application

Adopting a focus on CRM has been an industry standard for nearly two decades. While evidence suggests that a majority of the attempts to implement CRM systems fail, no single reason for the failures has been identified. Assuming that CRM implementation is an extension of a customer-oriented business strategy and assuming successful integration with Enterprise Information Systems such as Enterprise Resource Planning (ERP) systems, the authors contend that the lack of valid and reliable CRM metrics leads to the perception of failed CRM implementation. Only through the development, application, and use of CRM metrics can organizations hope to achieve their CRM goals.

Customer Relationship Management (CRM) Metrics

2009 ◽  
pp. 311-317
Author(s):  
Timothy Shea ◽  
Ahern Brown ◽  
D. Steven White ◽  
Catharine Curran-Kelly ◽  
Michael Griffin
Keyword(s):  
Information Systems ◽  
Enterprise Resource Planning ◽  
Business Strategy ◽  
Relationship Management ◽  
Resource Planning ◽  
Customer Relationship ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Industry Standard ◽  
Development Application

Adopting a focus on CRM has been an industry standard for nearly two decades. While evidence suggests that a majority of the attempts to implement CRM systems fail, no single reason for the failures has been identified. Assuming that CRM implementation is an extension of a customeroriented business strategy and assuming successful integration with Enterprise Information Systems such as Enterprise Resource Planning (ERP) systems, the authors contend that the lack of valid and reliable CRM metrics leads to the perception of failed CRM implementation. Only through the development, application, and use of CRM metrics can organizations hope to achieve their CRM goals.

Implementation Management of an E-Commerce-Enabled Enterprise Information Systems

2011 ◽  
pp. 32-47
Author(s):  
R. P. Sundarraj ◽  
Joseph Sarkis
Keyword(s):  
Information Technology ◽  
Supply Chain ◽  
Information Systems ◽  
Erp Implementation ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Erp System ◽  
Market Needs ◽  
Implementation Management

This chapter presents a case study of an overview of the efforts of Texas Instrument’s (TI’s) internal and external ERP implementation, with a focus on linking its ERP system in a global e-commerce setting. This linkage is especially important since it had been stated in TI’s strategic plan as an objective of this project to provide visibility of the ERP system to external constituents via Web linkages along with the objective of standardizing internal processes and important information technology systems to support market needs. Thus, its ERP system is central to managing its supply chain and B2B e-commerce linkages from both a customer and supplier perspective. Issues faced by TI are clearly outlined with future questions also posed in the final section.

Customer Relationship Management (CRM) Metrics

2011 ◽  
pp. 2345-2351
Author(s):  
Timothy Shea ◽  
Ahern Brown ◽  
D. Steven White ◽  
Catherine Curran-Kelly ◽  
Michael Griffin
Keyword(s):  
Information Systems ◽  
Enterprise Resource Planning ◽  
Business Strategy ◽  
Relationship Management ◽  
Resource Planning ◽  
Customer Relationship ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Industry Standard ◽  
Development Application

Adopting a focus on CRM has been an industry standard for nearly two decades. While evidence suggests that a majority of the attempts to implement CRM systems fail, no single reason for the failures has been identified. Assuming that CRM implementation is an extension of a customeroriented business strategy and assuming successful integration with Enterprise Information Systems such as Enterprise Resource Planning (ERP) systems, the authors contend that the lack of valid and reliable CRM metrics leads to the perception of failed CRM implementation. Only through the development, application, and use of CRM metrics can organizations hope to achieve their CRM goals.

Business Intelligence Enterprise Solution at Abu Dhabi Finance

2013 ◽  
pp. 310-323
Author(s):  
Salam Abdallah
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Strategic Planning ◽  
Business Intelligence ◽  
Abu Dhabi ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Knowledge Based ◽  
Transaction Processing Systems ◽  
Support Decision Making

The challenge of transforming data and information in enterprise information systems into knowledge that can be rolled up and presented to management as key performance indicators is business-critical. The implementation of a business intelligence layer on top of the transaction processing systems and management information systems is viewed as an opportunity to move up a level to promote knowledge-based decision-making and strategic planning. This chapter attempts to examine the issues and challenges associated with the initiative by Abu Dhabi Finance to implement business intelligence solutions that extract information from the enterprise information systems, present them as KPIs for senior management, and produce knowledge that can be used to support decision-making and strategic planning.

Business Intelligence Enterprise Solution at Abu Dhabi Finance

2014 ◽  
pp. 1046-1055
Author(s):  
Salam Abdallah
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Strategic Planning ◽  
Business Intelligence ◽  
Abu Dhabi ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Knowledge Based ◽  
Transaction Processing Systems ◽  
Support Decision Making

The challenge of transforming data and information in enterprise information systems into knowledge that can be rolled up and presented to management as key performance indicators is business-critical. The implementation of a business intelligence layer on top of the transaction processing systems and management information systems is viewed as an opportunity to move up a level to promote knowledge-based decision-making and strategic planning. This chapter attempts to examine the issues and challenges associated with the initiative by Abu Dhabi Finance to implement business intelligence solutions that extract information from the enterprise information systems, present them as KPIs for senior management, and produce knowledge that can be used to support decision-making and strategic planning.

Contemporary Issues in Enterprise Information Systems

2017 ◽  
pp. 120-136 ◽  
Author(s):  
Ebru E. Saygili ◽  
Arikan Tarik Saygili
Keyword(s):  
Information Systems ◽  
Enterprise Resource Planning ◽  
Success Factors ◽  
Resource Planning ◽  
Customer Relationship ◽  
Enterprise Information ◽  
Chain Management ◽  
Enterprise Information Systems ◽  
Critical Success ◽  
Business Functions

The widespread usage of enterprise information systems (EIS) by various companies operating in different countries has led to digitalization of inter and intra-organizational business functions like customer relationship management (CRM) and supply chain management (SCM). This study considers current issues in EIS implementations in the context of enterprise resource planning (ERP) systems in different countries, industries and companies. Due to the increasing demands and varying needs of different parties, ERP implementations are getting more complex, which means considering a greater number and variety of critical success factors (CSFs). This study therefore reviews the current literature related to CSFs and their classifications before introducing a new conceptual model of 40 CSFs for successful EIS implementations.

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