The data mining process: At a cricical crossroads in development
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Kenneth A. Saban is an assistant professor of marketing at the A.J. Palumbo School of Business Administration, Duquesne University. His research interests include competitive intelligence, organisational learning, electronic commerce and new product development. As a former Fortune 500 executive, he is well versed in the challenges associated with building large customer databases to improve corporate decision making and marketing products and services on a global basis.
Abstract This paper makes a case for the balanced management of data mining (DM). En route to making this case, the paper reviews: 1) the drivers of DM growth, ie rapid market change, falling cost of electronic data collection; 2) the pros and cons of DM, including the privacy issues; 3) the ethical framework of DM and the degree of stakeholder concerns; 4) different DM management approaches; 5) myths about DM leading to mismanagement, anatomy and shortcomings of industry DM self-regulation; and 6) benefits of balanced DM management.
Dr Kenneth A. Saban Assistant Professor of Marketing, AJ Palumbo School of Business, Duquesne University, 801 Rockwell Hall, Pittsburg PA 15282, USA. Tel: ⫹1 (412) 396 5152; Fax: ⫹1 (412) 396 4764; e-mail: [email protected]
INTRODUCTION Data mining (DM) is fast becoming one of the most sought after decisionsupport tools with spending for hardware, software and services projected to be US$73bn by the year 2001, up from the US$10bn in 1998.1 Broadly defined, DM is the efficient discovery of relevant information from large customer databases to improve corporate decisionmaking. When new data are uncovered from customer interfaces, they are quickly incorporated into the company’s decision support system, which in turn helps managers make more informed decisions. The forces that have contributed to the expanded use of DM process in the USA include: — marketplace dynamics are changing at such a rapid pace, that decision-making data are quickly obsolete2,3
䉷 Henry Stewart Publications 1350-2328 (2001)
Vol. 8, 2, 157–167
— advances in data storage and data processing technology — declining costs of electronic communications — emergence of new DM products4,5 — the need to be more knowledgeable about the nuances of new customers, lost customers, and retained customers6 — the electronic commerce revolution is not only changing business models, but also the information requirements to make timely business decisions. Companies that are able to manage this transformation effectively ‘stand to achieve substantial gains in productivity and operating efficiency, improvements in end-user and customer satisfaction — which ultimately affects the top line — and greater flexibility to respond to new business opportunities’.7 Companies that are not informed could be blind-sided by unforeseen market forces.
Journal of Database Marketing
157
Saban
While data miners are busy mining for customer gold, a growing number of privacy advocates are questioning current DM practices, ie the creation, use and potential sale of customer profiles in
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