Applying Business Architecture Principles with Domain-Specific Ontology for ACM Modelling: A Building Construction Project Example

Adaptive Case Management (ACM) empowers knowledge workers of any industry by utilizing their experience in the execution of business cases. It is designed to handle non-repetitive processes, where the course of actions has to be decided for each case individually, based on the assessment of the current situation. ACM uses domain-specific data and the analysis of rules to provide the relevant information at the right time to the business users. This supports their actions and decision making but does not dictate predefined workflows that are difficult or even impossible to define for knowledge-intensive work and prevent users from efficiently achieving their goals. Solutions for ACM implementations need to focus on business requirements to support business users rather than limit them by extending existing tools such as content management systems, BPM-based software suites, or collaboration tools with ad hoc development that all lack the ability to adapt flexibly to business level changes without requiring significant IT development efforts. To tackle these challenges, this paper proposes a novel approach by applying business architecture concepts for the definition of ACM applications in combination with domain-specific ontologies and business rules. Business domain analysts describe with the domain-specific ontology the complete value stream with its goals, activities and rules which use a formalized natural business language. The resulting business information model is mapped to an underlying data model and instantly enacted during case execution so that adaptations get immediately available to the business users. The behavioral business rules guide business users to guarantee case compliance which facilitates an easy and rapid adaptation of business applications. We apply this approach to a real life example from the construction industry where several parties from different trades have to collaborate in heterogeneous environments.