Enriching Business Process Models with Decision Rules

Abstract

Abstract. Making the right decisions in time is one of the key tasks in every business. In this context, decision theory fosters decision-making based on well-defined decision rules. The latter evaluate a given set of input parameters and utilize evidenced data in order to determine an optimal alternative out of a given set of choices. In particular, decision rules are relevant in the context business processes as well. Contemporary process modeling languages, however, have not incorporated decision theory yet, but mainly consider rather simple, guard-based decisions that refer to process-relevant data. To remedy this drawback, this paper introduces an approach that allows embedding decision problems in business process models and applying decision rules to deal with them. As a major benefit, it becomes possible to automatically determine optimal execution paths during run time.

Formal Model of Business Processes Integrated with Business Rules

“…In this approach, the decisions are automatically revealed and translated to DMN what improves process executions regarding such issues as process duration or costs. Catalkaya et al (2013) proposed the method for applying decision theory to process models and extend the current standard with rule-based XOR-split gateway (the so called r-gateway). In order to take a decision the method utilize key performance indicators, such as cost of performing an activity.…”

A Process Mining Based Approach to Support Decision Making

“…This technique is implemented as a tool named Branch Miner 4 . In [13], authors propose a technique that embeds decision rules into process models by transforming the Xor gateway into a rule-based Xor gateway that automatically determines the optimal alternative in terms of performance (cost, time) during runtime. This technique is still not yet implemented.…”

Decision Mining Revisited - Discovering Overlapping Rules

“…There are several approaches for decision mining given an event log with historical data about the process [1,3,5,6,15,16,17,18,19]. In all of these approaches, the decision mining problem is translated into a classification problem, and solved using classification analysis techniques such as C4.5 [7].…”