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Stakeholder Ontology and Mining for Improving Complex Services

Stakeholder Ontology and Mining for Improving Complex Services

Jay Ramanathan, Rajiv Ramnath
Copyright: © 2013 |Volume: 5 |Issue: 2 |Pages: 15
ISSN: 1935-5688|EISSN: 1935-5696|EISBN13: 9781466632981|DOI: 10.4018/jisss.2013040105
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MLA

Ramanathan, Jay, and Rajiv Ramnath. "Stakeholder Ontology and Mining for Improving Complex Services." IJISSS vol.5, no.2 2013: pp.65-79. http://doi.org/10.4018/jisss.2013040105

APA

Ramanathan, J. & Ramnath, R. (2013). Stakeholder Ontology and Mining for Improving Complex Services. International Journal of Information Systems in the Service Sector (IJISSS), 5(2), 65-79. http://doi.org/10.4018/jisss.2013040105

Chicago

Ramanathan, Jay, and Rajiv Ramnath. "Stakeholder Ontology and Mining for Improving Complex Services," International Journal of Information Systems in the Service Sector (IJISSS) 5, no.2: 65-79. http://doi.org/10.4018/jisss.2013040105

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Abstract

Complex service-oriented organizations (such as IT customer service or the hospital emergency) deal with many challenges due to incoming request types that we characterize as non-routine. Each such request reflects significant variations in the environment and consequently requirements, which drives discovery of processing needs. At the same time such organizations are often challenged with sharing high-cost resources and satisfying multiple stakeholders with different expectations. Performance improvement in this context is particularly challenging and requires new methods. To address this, the authors present an ontology designed for highly dynamic service organizations where traceable workflow data is difficult to obtain and there are many stakeholders. The ontology provides the contextual framework by with useful knowledge can be successfully extracted from mined performance data obtained from scattered sources. Specifically the service ontology 1) obtains tacit knowledge as explicit in-the-micro feedback from workers performing Roles, 2) provides the structure for organizing in-the-small execution data from evolving process and instances, and 3) aggregates process instances metrics into a performance and decision-making facility to align to in-the-large goals of stakeholders. Using actual customer service requests they illustrate the benefits of the ontology for relating aggregated goals to feedback from individual roles of workers. The authors also illustrate the benefits in terms of identifying actionable improvement targets.

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