Enhancing Process-Adaptation Capabilities with Web- Based Corporate Radar Technologies Prateek Jain 2 , Peter Z. Yeh 1 , Kunal Verma 1 , Alex Kass 1 , Amit Sheth 2 1 Accenture Tech. Labs 2 Knoesis Center 50 West Fernando Street Wright State University San Jose, CA 95113 Dayton, OH 45435 +1 408 817 2113 +1 770 910 4416 {peter.z.yeh, k.verma, alex.kass}@accenture.com {prateek, amit}@knoesis.org ABSTRACT Dynamic business processes are capable of adapting themselves to internal events but lack the ability to adapt to external events. Corporate radars are capable of mining the Web for external events of interest to produce structured representations of these events but are not capable of adapting themselves based on these events. In this position paper, we advocate and propose a system that integrates these two approaches to enhance the capability of process-adaptation engines, greatly increasing the scope of events they can respond to. Categories and Subject Descriptors H.3.5 [Online Information Services]: Web-based services General Terms Algorithms, Design, Experimentation Keywords Dynamic business process, Corporate Radars, Dynamic process adaptation 1. INTRODUCTION Systems that can automatically adapt an enterprise’s business process to changes in the external environment will enable the enterprise to be more agile and responsive to potential risks and opportunities. The creation of such systems requires a mechanism to dynamically adapt business processes and a separate mechanism to provide various types of context–awareness on which adaptation decisions can be based. The first mechanism can be provided by the WS-BPEL specification and various engines that support its execution. In previous research [2], we have begun to lay the groundwork for dynamic process adaptation. This system employs a process management layer, distinct from the process execution engine, capable of adapting business processes based on service-generated events, such as delivery delays or failures. However, this first generation adaptation system is limited to events generated by the system’s services. Hence, there are several important kinds of dynamic adaptation that are beyond its capabilities such as: 1. The ability to react to events that are entirely external to the system, such as changes in a supplier’s economic circumstances. 2. The ability to shape the business process based on informed inferences regarding the likely external cause of service-based events. The second mechanism can be provided by systems that detect and interpret external events of interest to support business decisions. In other previously unrelated work, we have been developing prototype systems that do just that. These “corporate radar” systems [1][4] automatically mine the Web to: 1) detect business-relevant events occurring in the competitive eco-system outside the enterprise; and 2) map those events to a model of the business dynamics in which the user’s organization operates to infer the potential implications of these events. These corporate radar systems suggest techniques that can be used to detect and interpret events for process adaptation, and hence address the limitations with the existing process-adaptation framework described above. However, corporate radar systems up to now have been designed to populate executive decision-support dashboards or generate news feeds as decision support for human managers. They have not been used to provide guidance to other automated systems such as a process-adaptation engine. In this paper, we propose a system that combines corporate radars with a business-process adaptation engine, resulting in a context- aware adaptation system. This context-aware adaptation system will be capable of taking a much broader context into account when determining the best process to execute. This broader awareness will enable enterprises to be more agile and responsive to potential threats and opportunities in two important ways: 1. Adapting proactively in response to early detection of external events: Consider a supply chain process where a computer manufacturer has a single supplier for its motherboards. Given the dependence of the manufacturer on this supplier, it is important to become aware of possible disruptions in the supply of motherboards before they happen to proactively adopt the process model. We can use corporate radars to mine the Web for indicators that the supplier will fail to Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. OBI 2008 October 27, 2008, Karlsruhe, Germany Copyright 2008 ACM 978-1-60558-219-1/08/0010…$5.00.