Leveraging Information for High Level-of-abstraction Organizational Processes

Leveraging Information for High Level-of-abstraction Organizational Processes

J.L. Dalmau-Espert F. Llorens-Largo P. Compañ-Rosique R. Satorre-Cuerda R. Molina-Carmona 

Department of Computer Science and Artificial Intelligence, University of Alicante, Spain

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Nowadays, Big Data techniques have made possible to obtain interesting low-level information from large amounts of data. However, the information is often difficult to be enriched enough to aid in high-level organizational processes. The objective of this work is to define a model to allow the use of available information for the design and implementation of high level-of-abstraction processes that take place in the organizations. Particularly, this paper is focused on the strategic planning (SP) process, one of the most complex and abstract processes in any company. So far, there are very few successful attempts to automate this process, which is usually based on manual tasks. At the most, the results from the automatic data analysis are generated and used as reports and are not integrated in the process. A further step is proposed, posing a SP model based on a multi-agent system with a blackboard, which is used as a means of communication and storage of the generated information. The information is described using ontology to formalize both the SP process and the information used in each step. The combination of these elements enables the participation, interaction and sharing of information and knowledge of the participants in the process. The accumulated knowledge allows the use of previous experience to automate the process and improve the decision making. In short, the proposed model is a formal, comprehensive, agile and flexible solution to perform the process of SP in organizations today leveraging of the enormous amount of available data and the gathered experience.


multi-agent system, ontology, organizational process, strategic planning.


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