On managing business processes variants

Abstract

Variance in business process execution can be the result of several situations, such as disconnection between documented models and business operations, workarounds in spite of process execution engines, dynamic change and exception handling, flexible and ad-hoc requirements, and collaborative and/or knowledge intensive work. It is imperative that effective support for managing process variances be extended to organizations mature in their BPM (Business Process Management) uptake so that they can ensure organization wide consistency, promote reuse and capitalize on their BPM investments. This paper presents an approach for managing business processes that is conducive to dynamic change and the need for flexibility in execution. The approach is based on the notion of process constraints. It further provides a technique for effective utilization of the adaptations manifested in process variants. In particular, we will present a facility for discovery of preferred variants through effective search and retrieval based on the notion of process similarity, where multiple aspects of the process variants are compared according to specific query requirements. The advantage of this approach is the ability to provide a quantitative measure for the similarity between process variants, which further facilitates various BPM activities such as process reuse, analysis and discovery.

Generating optimized configurable business process models in scenarios subject to uncertainty

“…Furthermore, in contrast to related proposals [29,47,53,75,94], not only a single enactment plan but a set of optimized enactment plans are considered when generating the imperative model. This way, the flexibility of the resulting imperative model is not unnecessarily restricted.…”

“…In turn, related to BP, Hummer et al [40] provides a model-driven approach which produces an imperative process specification from a declarative specification. Unlike our approach, Hummer et al [40], Lu et al [53] and Rychkova et al [74] do not consider the optimization of any objective function. Furthermore, none of this approaches [40,47,53,60,63,74] considers the uncertainty of the scenario through stochastic attributes.…”

“…[29,40,47,53,60,63,64,75,94]). These proposals are based on generating a single execution plan which fulfills all the BP constraints starting with a constraint-based specification.…”

“…However, there exist some further proposals which could be extended in such direction [40,47,53,60,63,74]. Specifically, Pesic [63] proposes the generation of a non-deterministic finite state automaton from constraint-based specifications which represents exactly all traces that satisfy the constraints.…”

“…Although [47] presents a similar constraint-based approach, it misses dealing with multi-objective optimization, and does not support high level constraints. Moreover, in [53], a constraint formalization is proposed to generate variations of an ad-hoc BPMN sub-processes. In a similar way, Rychkova et al [74] proposes the specification of processes based on a first-order logic language and translates them to an imperative language.…”