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Enterprise Cockpit for Business Operation Management

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3288))

Abstract

The area of business operations monitoring and management is rapidly gaining impor-tance both in the industry and in the academia. This is demonstrated by the large number of performance reporting tools that have been developed. Such tools essen-tially leverage system monitoring and data warehousing applications to perform online analysis of business operations and produce fancy charts, from which users can get the feeling of what is happening in the system. While this provides value, there is still a huge gap between what is available today and what users would ideally like to have:

  • Business analysts tend to think of the way business operations are performed in terms of high level business processes, that we will call abstract in the following. There is no way today for analyst to draw such abstract processes and use them as a metaphor for analyzing business operations.

  • Defining metrics of interest and reporting against these metrics requires a signifi-cant coding effort. No system provides, out of the box, the facility for easily defin-ing metrics over process execution data, for providing users with explanations for why a metric has a certain value, and for predicting the future value for a metric.

  • There is no automated support for identifying optimal configurations of the busi-ness processes to improve critical metrics.

  • There is no support for understanding the business impact of system failures.

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© 2004 Springer-Verlag Berlin Heidelberg

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Casati, F., Castellanos, M., Shan, MC. (2004). Enterprise Cockpit for Business Operation Management. In: Atzeni, P., Chu, W., Lu, H., Zhou, S., Ling, TW. (eds) Conceptual Modeling – ER 2004. ER 2004. Lecture Notes in Computer Science, vol 3288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30464-7_61

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  • DOI: https://doi.org/10.1007/978-3-540-30464-7_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23723-5

  • Online ISBN: 978-3-540-30464-7

  • eBook Packages: Springer Book Archive

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