Decisions are used by organizations to manage and execute their coordinated, value-adding decision-making and are thereby among an organization’s most important assets. To be able to manage deci-sions and underlying business rules, Decision Management (DM) and Business Rules Management (BRM) are increasingly being applied at organisations. One of the latest developments related to the domain of DM and BRM is the introduction of the Decision Model and Notation (DMN) in September 2015 by the Object Management Group (OMG). The goal of this technical paper is to provide students with a case to practice the specification, verification, validation, deployment, execution, monitoring and governance of business rules in practice.
Proper decision-making is one of the most important capabilities of an organization. Therefore, it is important to have a clear understanding and overview of the decisions an organization makes. A means to understanding and modeling decisions is the Decision Model and Notation (DMN) standard published by the Object Management Group in 2015. In this standard, it is possible to design and specify how a decision should be taken. However, DMN lacks elements to specify the actors that fulfil different roles in the decision-making process as well as not taking into account the autonomy of machines. In this paper, we re-address and-present our earlier work [1] that focuses on the construction of a framework that takes into account different roles in the decision-making process, and also includes the extent of the autonomy when machines are involved in the decision-making processes. Yet, we extended our previous research with more detailed discussion of the related literature, running cases, and results, which provides a grounded basis from which further research on the governance of (semi) automated decision-making can be conducted. The contributions of this paper are twofold; 1) a framework that combines both autonomy and separation of concerns aspects for decision-making in practice while 2) the proposed theory forms a grounded argument to enrich the current DMN standard.
In 2015, the Object Management Group published the Decision Model and Notation with the goal to structure and connect business processes, decisions and underlying business logic. Practice shows that several vendors adopted the DMN standard and (started to) integrate the standard with their tooling. However, practice also shows that there are vendors who (consciously) deviate from the DMN standard while still trying to achieve the goal DMN is set out to reach. This research aims to 1) analyze and benchmark available tooling and their accompanied languages according to the DMN-standard and 2) understand the different approaches to modeling decisions and underlying business logic of these vendor specific languages. We achieved the above by analyzing secondary data. In total, 22 decision modelling tools together with their languages were analyzed. The results of this study reveal six propositions with regards to the adoption of DMN with regards to the sample of tools. These results could be utilized to improve the tools as well as the DMN standard itself to improve adoption. Possible future research directions comprise the improvement of the generalizability of the results by including more tools available and utilizing different methods for the data collection and analysis as well as deeper analysis into the generation of DMN directly from tool-native languages.
