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What were the major obstacles that delayed the adoption of rule-based systems as a mainstream technology for the first 15 years of it existence ?

• Lack of consistent focus on the problem domain - particularly lack of business focus the application was an example of technology rather than catriona

• Lack a rigorous methodology -

• Poor performance - they could run very very slowly on pre-Pentium and early-Pentium computers.

• High complexity - a more fundamental reason, was the sheer complexity of building and maintaining a large rule-based system. A rule base of three or four thousand rules required a massive, highly-trained staff to maintain, a hundred people or more in the case of the Digital Equipment product configurator, XCON.

• High cost of entry - early implementations of rule based systems became too tied down with a particular technology. The cost of entry into a new computer language environment ( such has LISP or Scheme ) was very high. The alternative was to use a commercial "expert system" packages, in a time when standards for exchange of rule-base information were non-existent.

• Lack of standards - the company was locked into proprietary technology and packages, often within a workstation-only technical infrastructure . This situation was not unique to rule based systems - there were no standards for metadata interchange between data modeling and CASE tools until the 1990s.

• Islands of automation - after succeeding in overcoming the barriers listed above, the "expert system" was often doomed to remain an island of automation in the corporate firmament.

In short, the entire approach was too demanding, too technical and too 'computery' for practical use in business situations.

The business rules approach succeeded in changing the focus from knowledge-intensive business processes, such as product configuration, to enterprise-level business rules, effectively rising above the parochialism of early implementations. In fact, business rules technology grew in tandem with CASE and modeling tools extended for modeling business rules. The UML modeling standard and Rational Rose modeling tools are prime examples.