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Decision-making is a core competence of organizational management (Laudon and Laudon, 2016) to formulate full-informed decisions. It encompasses the responsibility of optimizing the business processes and is traditionally supported on a PDCA cycle (Shewart, 1980): (1) the intelligence to discover the organizational problem, then (2) the design of potential solutions, afterward (3) choose the best solution, and finally, (4) implement the solution and check if it fulfills the desired goals.
An informed decision-making process augments the capability of the organizational actors to understand their surroundings constraints and then to decide upon the best action to be enacted. Moreover, to execute decision-making processes, the information offered by business metrics (Jones & Bonsignour, 2012), e.g., turn-over or sales target, are not enough to decide.
Enterprise Ontology (EO) (Dietz, 2006) and the emerging field of Enterprise Engineering (EE) (Dietz, Hoogervorst, Albani, Babkin, & Barjis, 2013) are followed, in this paper, to support the understanding of the business processes dynamics and to understand workarounds.
In the core of the business process dynamics are the concepts of business transaction and business transaction compliance. On the one hand, a business transaction model is the result of designing the constraints that are desired for an organizational reality (Hoogervorst, 2009), that is valid within a well-defined timeframe, and including who is responsible for each part of the business transaction and the comprehensive definition of system's state and transition (Guerreiro & Tribolet, 2013). On the other hand, business transaction compliance aims at verifying and correcting if the prescribed business transactions models are being respected throughout run-time operation (Sadiq, Governatori, & Namiri, 2007). Herein, a problem may occur, organizational actors perform workarounds while they perform their daily tasks, meaning that the a priori business transaction prescriptions do not assure that actors perform them accordingly. The theory of workarounds is about how agents with some degree of behavioral discretion decide whether to follow established practices and what to do when exceptions, anomalies and mishaps occur (Alter, 2014).
In this extent, an informed control cycle aids the managers to take informed steering actions at operational time, as previously presented by Guerreiro (2013). Figure 1 describes a steering cycle of observation, assessing the environment, designing the potential solutions and choosing the best solution. These steps recall to the management competences and are mainly human based. Nevertheless, this paper argues and shows how automatic tools deliver support to the managers, aiding at some point in their decision-making steps.
Figure 1. The organizational steering cycle
The business processes optimization issue relates with the following three approaches. Firstly, the Kaizen approach (Masaaki, 1986) allowing small incremental changes to actor’s operational environment but only in the scope of their assigned work tasks. Kaizen approach is able to local optimization but not suitable for business processes global optimization. Moreover, the knowledge about the local optimization is lost if the business process is significantly altered or the team is disbanded.
Secondly, from the industry, the Capability Maturity Model Integration (CMMI, 2016) aiming the optimization of processes, from any kind of organization and business. It delivers a set of recommendations and formalization to identify the organizational problems and then it prescribes solution to improve the efficiency. However, it does not detail how to deal with the stratification of the organization neither with issues such as verification and measurement.