The benefits of data warehousing: why some organizations realize exceptional payoffs
Introduction
Data warehousing is one of the key developments in the information system (IS) field. Only 10 years ago, warehousing initiatives were just beginning in a few visionary firms. Today, virtually all large organizations have warehouses and many are moving to later generations of warehouses [3]. The Palo Alto Management Group provides figures about the size and growth of the data warehousing market. They estimate that the sale of systems, software, services, and in-house expenditures will grow from a US$ 8.8 billion market in 1996 to a US$ 113.5 billion market in 2002—a 51% growth rate.
The fundamental business driver behind data warehousing is the desire to improve decision making and organizational performance [6]. It involves extracting data from source systems (e.g. legacy, external), cleaning (e.g. eliminating inconsistencies) and transforming the data (e.g. applying business rules, summarizing), and loading it to a data store (e.g. relational database). It also includes the actual tools (e.g. SQL) and applications that end-users apply to access and analyze the data.
Data warehousing projects are high risk/high return initiatives. In a 1996 study, International Data Corporation studied 62 data warehouses and found an average 3 years ROI of 401% [9]. While precise figures are not available, it is believed that the initial failure rate for these projects is as high as 50%, although many organizations succeed with later efforts [11]. With their average cost of over US$ 1 million, failures are costly to organizations in which they occur [18].
Nearly all of the current literature on data warehousing is written by practitioners who draw on their experience. In order to provide an academic perspective, we began a program of research. Among our projects has been a set of case studies that focus attention on organizational benefits.
In the process of conducting the case studies, it became clear that some organizations are receiving more significant returns than others. This caused us to ask ‘why?’ A compelling explanation is provided by Kotter’s [13] eight-step model for transforming an organization. Companies that use a warehouse as a facilitator for organizational transformation potentially receive exceptional payoffs.
Section snippets
A framework for benefits
Data warehousing supports a variety of decision support applications that can lead to benefits for organizations, however, as early as the 1960s, researchers realized that the benefits are difficult to define and measure [10]. The difficulty exists because the benefits include intangible impacts. In one study, the Fleetmanager DSS led to a rich blend of qualitative and quantitative benefits, including a reduction in labor time, more effective and efficient decisions, and higher morale among
Kotter’s model for organizational transformation
Data warehouses have the potential to support significant changes in how an organization is structured and carries out its business. Knowingly or not, organizational design and the design of work processes is shaped by the amount and type of information required in a given environment and the organization’s information processing capability [4], [16]. Because a data warehouse can provide more detailed, integrated, accessible, and historically complete information, it should be possible for an
Three data warehousing case studies
We selected three companies from diverse industries and sectors. While all have been successful with their data warehousing efforts, some are providing a more significant payoff than others. In each organization we spent 1–2 days in face-to-face interviewing of employees, conducting phone interviews, and examining documents and video tapes of key events. Interviews included senior management, middle management, implementers and users. All interviews were taped and transcribed.
Discussion
All three of the initiatives are successful—all organizations are receiving important benefits. However, the extent of the benefits differs from organization to organization.
The first step in Kotter’s model is to create a sense of urgency. At FSC this was easy to do; the company was facing failure. There was also a sense of urgency at the IRS, though not as severe. The sense of urgency at LMC was not as great: a warehouse was needed to facilitate the building of several important IS, but this
Conclusion
There is a striking contrast between FSC and the IRS on the one hand, and LMC on the other. In neither FSC nor the IRS is the data warehousing effort seen as anything other than a means to a strategic end. In both of these organizations, the strategic vision for changing the organization came first, and was followed by recognition of the importance of an appropriate IT infrastructure. In both, the effort was driven by the business side of the house. However, LMC has occasionally been mentioned
Hugh J. Watson is a Professor of MIS and a holder of a C. Herman and Mary Virginia Terry Chair of Business Administration in the Terry College of Business at the University of Georgia. Hugh is the author of 22 books and over 100 articles. He is currently specializing in data warehousing and is the Senior Editor of the Journal of Data Warehousing and is a Fellow of The Data Warehousing Institute.
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Hugh J. Watson is a Professor of MIS and a holder of a C. Herman and Mary Virginia Terry Chair of Business Administration in the Terry College of Business at the University of Georgia. Hugh is the author of 22 books and over 100 articles. He is currently specializing in data warehousing and is the Senior Editor of the Journal of Data Warehousing and is a Fellow of The Data Warehousing Institute.
Dale L. Goodhue is an Associate Professor of MIS at the University of Georgia’s Terry College of Business. He received his PhD in MIS from MIT, and has published in Management Science, MIS Quarterly, Decision Sciences, Sloan Management Review and other journals. His research interests include measuring the impact of information systems, the impact of task–technology fit on individual performance, and the management of data and other IS infrastructures/resources.
Barbara H. Wixom is an Assistant Professor of Commerce at the University of Virginia’s McIntire School of Commerce, and she received her PhD in MIS from the University of Georgia. Dr. Wixom was made a Fellow of The Data Warehousing Institute for her research in data warehousing, and she has published in journals that include MIS Quarterly, Information Systems Research, Communications of the ACM, Journal of Data Warehousing, and Information Systems Management. Dr. Wixom’s research interests include the use of IT to support organizational decision making, IS success, and the benefits of IT.