Technology And Policy In Decision Support Systems

Data warehousing, data marting, online analytical processing (OLAP) – these terms dominate discussions of enterprise decision support systems (DSS). At the same time, it is becoming increasingly clear that none of these product categories has a particularly stellar track record for improving the quality or quantity of commercial decisions. This is so because none of the technological answers to the commercial decision-making problem focuses on decision-making processes themselves -on the entirety of the decision-making problem – which are as much matters of policy as they are of technology. This white paper discusses the evolution of the data warehousing marketplace from data infrastructure to enterprise decision support systems, focusing on the decision-making process as the design center for effective DSS environments. Technology and Policy In Decision Support Systems Revision 8 10/12/98 Page 2 of 14 98010033.8 Copyright © 1996-8 by DP Applications, Inc. All rights reserved. www.dpapplications.com Introduction: Plumbers Or Decision Process Designers? Examining the terms a community uses to describe its work can tell us a great deal about what that community believes about its mission, focus and objectives. Consider the “data warehousing market,” now estimated at between $6 and $8 billion a year worldwide. In 1994, a survey of key terms used in well over 75,000 articles from approximately 150 IT trade press publications revealed the following statistics for that database: Term Occurrences June 94-May 95 Average/Month data warehouse 251 21 data warehousing 244 20 decision support 797 66 DSS 148 12 OLAP 84 7 multidimensional 284 24 A similar analysis, run on the same fundamental article database more recently, reveals different statistics. Term June 94-May 95 Average/Month Dec 96-Dec97 Average/Month % Growth data warehouse 251 21 869 72 246% data warehousing 244 2