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AI Models for Business Process Reengineering
August 1996 (vol. 11 no. 4)
pp. 16-23

Most models fail to capture the rationale behind processes, making business reengineering less effective. The authors describe their i* framework, which views organizations as collections of actors with strategic interests, and interdependencies involving goals, tasks, and resources. The authors also describe the ConGolog framework, which supports reasoning about the dynamics of processes under incomplete knowledge.

Competitive pressures, customer demands, and ever-changing regulatory conditions are forcing many companies to rethink the way they do business. A fundamental part of this rethinking process is to link production procedures and organizational services to business goals and objectives. At present, there is little formal support for this kind of reasoning. Business process design is usually done informally, and individual design decisions are hard to relate to business objectives.

Traditional modeling techniques--structured analysis, dataflow diagrams, and entity-relationship diagrams--describe what a business process is, but they cannot express the why of the process--the motivations, intents, and rationales behind the activities and entities. This is a serious drawback. A central argument in business process reengineering is that if you don't understand why things are done the way they are, you are likely to automate outdated processes (leading to the proverbial "paving of the cow path") and miss the opportunity to innovate the process itself. In choosing among alternative business processes, analysts must be able both to describe relationships and to propose and argue about solutions from strategic perspectives. Artificial intelligence in general and knowledge representation in particular can help in modeling organizations and in analyzing alternatives. Recognizing the value of AI in this area, we developed a framework for modeling and analyzing organizations in support of several applications, including business process reengineering. The i* framework (i* stands for distributed intentionality) views processes as involving social actors who depend on one another for goals to be achieved, tasks to be performed, and resources to be furnished. The i* framework includes two models: Strategic Dependency Model, which describes the network of relationships among actors. Strategic Rationale Model, which describes and supports the reasoning that each actor has about its relationships with other actors. We have formally represented these models in the conceptual modeling language Telos and have based their semantics on intentional concepts--goal, belief, ability, and commitment--studied in work by Philip Cohen and Hector Levesque. To complement the i* framework's strategic level of reasoning, we use a logic-based framework, ConGolog, to model the detailed dynamics of the business environment and processes being redesigned. The framework supports the validation and verification of business processes using simulation and automated reasoning techniques. Users can reason about processes even with only a partial description of the world state. In this article, we show how the i* models and ConGolog aid the redesign of claims processing in an automobile insurance company. We also describe a toolset that aids analysis using these models, which we are currently developing at the University of Toronto. The models and their associated tools incorporate a number of AI techniques, including means-ends analysis, qualitative reasoning, agent modeling, and theories of action.
Citation:
Eric S.K. Yu, John Mylopoulos, Yves Lespérance, "AI Models for Business Process Reengineering," IEEE Intelligent Systems, vol. 11, no. 4, pp. 16-23, Aug. 1996, doi:10.1109/64.511773
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