Knowledge Driven Behavioural Analysis in Process Intelligence

InthispaperweillustratehowtheknowledgedrivenBehaviourAnal- ysis, which has been used in the KITE.it process management framework, can support the evolution of analytics from descriptive to predictive. We describe how the methodology uses an iterative three-step process: first the descriptive knowledge is collected, querying the knowledge base, then the prescriptive and predictive knowledge phases allow us to evaluate business rules and objectives, extract unexpected business patterns, and screen exceptions. The procedure is iterative since this novel knowledge drives the definition of new descriptive an- alytics that can be combined with business rules and objectives to increase our level of knowledge on the combination between process behaviour and contex- tual information

Knowledge and business intelligence technologies in cross-enterprise environments for italian advanced mechanical industry

Today\u2019s industry is pushed by the competitive pressure to revise the business model by opening the organizational boundaries to suppliers, clients and partners. As a side effect, knowledge sharing within the market increases and organizations may lose control on strategical knowledge that can be exploited by competitors. For this reason process monitoring today cannot fail in controlling the collaboration activities established inside and outside the organization. KITE.it is a project, founded by the italian Ministry of Economic Development, aimed at proposing a methodological and technological framework to support the italian mechanical industry in adopting advanced business network approached.1 The Kite framework is aimed at driving the management process in the identification of the business values creating the network and in supporting the strategical analysis by monitoring both the operational and collaborative processes. The metric system was designed to integrate in a unified analysis metrics insisting on the strategical, operational and collaborative level. From the technological point of view this is achieved by decoupling the monitoring format from the execution logs that can be integrated in the Kite model from heterogeneous data sources

Knowledge and business intelligence technologies in cross-enterprise environments for italian advanced mechanical industry

The internetworking and the outsourcing of business activities have become essential in the short term to maintain competitiveness in the market, as it allows to significantly reduce time and cost of core business processes. However, outsourcing, increasing the level of information sharing, imposes new precautions to maintain, in the medium and long-term, strategic control over the knowledge produced and exchanged, both in terms of "know-how" and "know-that". Especially for SMEs, his implies substantial risk of a technological nature, in that it requires complex and extremely expensive technological framework. KITE.it aims to develop a methodological and technological framework to support the transition of the advanced mechanical supply chains towards Value Network models able to guarantee: - interoperability and cooperation between firms and individuals in the network; - the management and securing of the intellectual capital; - measurement and performance optimization