Hugh J. Watson

An empirical investigation of the factors affecting data warehousing success

The IT implementation literature suggests that various implementation factors play critical roles in the success of an information system; however, there is little empirical research about the implementation of data warehousing projects. Data warehousing has unique characteristics that may impact the importance of factors that apply to it. In this study, a cross-sectional survey investigated a model of data warehousing success. Data warehousing managers and data suppliers from 111 organizations completed paired mail questionnaires on implementation factors and the success of the warehouse. The results from a Partial Least Squares analysis of the data identified significant relationships between the system quality and data quality factors and perceived net benefits. It was found that management support and resources help to address organizational issues that arise during warehouse implementations; resources, user participation, and highly-skilled project team members increase the likelihood that warehousing projects will finish on-time, on-budget, with the right functionality; and diverse, unstandardized source systems and poor development technology will increase the technical issues that project teams must overcome. The implementations success with organizational and project issues, in turn, influence the system quality of the data warehouse; however, data quality is best explained by factors not included in the research model.

The Current State of Business Intelligence

Business intelligence (BI) is now widely used, especially in the world of practice, to describe analytic applications. BI is currently the top-most priority of many chief information officers. BI has become a strategic initiative and is now recognized by CIOs and business leaders as instrumental in driving business effectiveness and innovation. BI is a process that includes two primary activities: getting data in and getting data out. Getting data in, traditionally referred to as data warehousing, involves moving data from a set of source systems into an integrated data warehouse. Getting data in delivers limited value to an enterprise; only when users and applications access the data and use it to make decisions does the organization realize the full value from its data warehouse. Thus, getting data out receives most attention from organizations. This second activity, which is commonly referred to as BI, consists of business users and applications accessing data from the data warehouse to perform enterprise reporting, OLAP, querying, and predictive analytics.

Data warehousing supports corporate strategy at first American corporation 1,2

From 1990 through 1998, First American Corporation (FAC) changed its corporate strategy from a traditional banking approach to a customer relationship-oriented strategy that placed FAC.s customers at the center of all aspects of the companys operations. The transformation made FACs an innovative leader in the financial services industry. This case study describes FACs transformation and the way in which a data warehouse called VISION helped make it happen. FACs experiences suggest lessons for managers who plan to use technology to support changes that are designed to significantly improve organizational performance. In addition, they raise interesting questions about the means by which information technology can be used to gain competitive advantage.

The BI-Based Organization

Business intelligence (BI) is an umbrella term that is commonly used to describe the technologies, applications, and processes for gathering, storing, accessing, and analyzing data to help users make better decisions. For BI-based firms, BI is a prerequisite for competing in the marketplace. Though there are several possible BI targets, it is important to understand how they differ in terms of strategic vision, level of sponsorship, required resources, impact on people and processes, and benefits. Some companies like Harrah’s Entertainment, Continental Airlines, Norfolk Southern, and Blue Cross and Blue Shield of North Carolina are exemplars of BI best practices. Despite the progress made with BI, there are still many opportunities for academic research.

Determining information requirements for an EIS

Executive information systems (EISs) are challenging applications to develop, and many organizations are unsuccessful in their efforts. A major problem is determining the information requirements for the system. A multi-stage study was conducted to explore (1) methods used to determine the information requirements for the initial and ongoing version of an EIS; (2) how frequently the methods are used; (3) how useful the methods are; and (4) in what situations the methods are useful or not useful. Telephone interviews identified 16 methods used to determine information requirements and provided insights into what makes the methods useful or not useful. Survey questionnaires revealed how frequently the methods are used and how useful they are. The use of the 16 methods for the initial and ongoing versions of an EIS are discussed as are suggestions for further research.

Critical success factors for information center managers

A stage hypothesis for information centers (ICs) is proposed and 26 critical success factors (CSFs) for IC managements are investigated. Based on 311 responses from IC managers, support is found for the proposed stages and information is provided about the importance of the CSFs. A principal components analysis is performed on the 26 CSFs which identifies five composite CSFs: (1) commitment to the IC concept; (2) quality of IC support services; (3) facilitation of end-user computing; (4) role clarity; and (5) coordination of end-user computing. Statistical tests show that the importance of these composite CSFs tend to vary among themselves but is relatively constant individually across the IC stages.

Executive information system: a framework for development and a survey of current practices

Executive information systems (EIS) are now successfully providing computer support for senior executives in a growing number of organizations. Previous attempts to support senior executives are discussed with a focus on why these attempts failed and what was learned that should be incorporated in future efforts. An EIS development framework is presented that includes a structural perspective of the elements and their interaction, the development process, and the dialog between the user and the system. Survey data from 50 firms having an EIS are presented and discussed in the context of the development framework. While most of the findings confirm conventional EIS wisdom, others are somewhat surprising, such as the significant role that information systems management often play sin initiating the development of an EIS or serving as its operational sponsor. The findings lead to additional suggestions for EIS research opportunities, as well as predictions about the future nature of EIS.

The Keys to Executive Information System Success

Abstract:Executive information systems (EIS) are high-risk/high-return systems, largely because the clientele these systems serve are not only influential in the firm, but have information needs that are very difficult to provide through computer-based information systems. As a result, it is important to understand the keys to successful EIS development and ongoing operation. This two-phase study first interviewed executives, EIS professionals, and vendors and consultants to elicit keys to success. The findings of the first phase rank-ordered the keys to successful EIS development and the keys to successful ongoing EIS operation. The first phase also indicated differences among the constituencies regarding the relative importance of the keys. The second phase of the research surveyed a large sample of EIS professionals to further examine the keys obtained from the interviews. These findings showed underlying dimensions of the two sets of keys, which in turn were used to produce a model of successful EIS d...

Real-Time Business Intelligence: Best Practices at Continental Airlines

Abstract Data management for decision support has moved through three generations, with the latest being real-time data warehousing. This latest generation is significant because of its potential for affecting tactical decision making and business processes. Continental Airlines is a leader in real-time business intelligence, and much can be learned from how they have implemented it.

The benefits of data warehousing: why some organizations realize exceptional payoffs

Data warehousing is one of the key developments in the information systems (IS) field. While its benefits are plentiful, some organizations are receiving more significant returns than others. The types of returns can vary in the impact they have on the organization and the ease in which they can be quantified and measured. This article presents a framework that shows how data warehouses can transform an organization; it also offers a compelling explanation for why differences in impact exist. Case studies of data warehousing initiatives at a large manufacturing company (LMC), the Internal Revenue Service, and a financial services company (FSC) are presented and discussed within the context of the framework. The analysis shows that the benefits that each company received can be tied to the way in which it conforms to the framework.