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Using enterprise architecture analysis and interview data to estimate service response time
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0003-3922-9606
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0002-6590-6634
2013 (English)In: Journal of strategic information systems, ISSN 0963-8687, E-ISSN 1873-1198, Vol. 22, no 1, 70-85 p.Article in journal (Refereed) Published
Abstract [en]

Insights into service response time is important for service-oriented architectures and service management. However, directly measuring the service response time is not always feasible or can be very costly. This paper extends an analytical modeling method which uses enterprise architecture modeling to support the analysis. The extensions consist of (i) a formalization using the Hybrid Probabilistic Relational Model formalism, (ii) an implementation in an analysis tool for enterprise architecture and (iii) a data collection approach using expert assessments collected via interviews and questionnaires. The accuracy and cost effectiveness of the method was tested empirically by comparing it with direct performance measurements of five services of a geographical information system at a Swedish utility company. The tests indicate that the proposed method can be a viable option for rapid service response time estimates when a moderate accuracy within 15% is sufficient.

Place, publisher, year, edition, pages
2013. Vol. 22, no 1, 70-85 p.
Keyword [en]
Enterprise Architecture, Performance, Design Science, Quality of Service, Service Management, Service Engineering
National Category
Information Systems
Identifiers
URN: urn:nbn:se:kth:diva-102189DOI: 10.1016/j.jsis.2012.10.002ISI: 000317162600006Scopus ID: 2-s2.0-84875269195OAI: oai:DiVA.org:kth-102189DiVA: diva2:551325
Note

QC 20130506

Available from: 2012-09-12 Created: 2012-09-10 Last updated: 2017-12-07Bibliographically approved
In thesis
1. Enterprise Architecture for Information System Analysis: Modeling and assessing data accuracy, availability, performance and application usage
Open this publication in new window or tab >>Enterprise Architecture for Information System Analysis: Modeling and assessing data accuracy, availability, performance and application usage
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Decisions concerning IT systems are often made without adequate decision-support. This has led to unnecessary IT costs and failures to realize business benefits. The present thesis presents a framework for analysis of four information systems properties relevant to IT decision-making. The work is founded on enterprise architecture, a model-based IT and business management discipline. Based on the existing ArchiMate framework, a new enterprise architecture framework has been developed and implemented in a software tool. The framework supports modeling and analysis of data accuracy, service performance, service availability and application usage. To analyze data accuracy, data flows are modeled, the service availability analysis uses fault tree analysis, the performance analysis employs queuing networks and the application usage analysis combines the Technology Acceptance Model and Task-Technology Fit model. The accuracy of the framework's estimates was empirically tested. Data accuracy and service performance were evaluated in studies at the same power utility. Service availability was tested in multiple studies at banks and power utilities. Data was collected through interviews with system development or maintenance staff. The application usage model was tested in the maintenance management domain. Here, data was collected by means of a survey answered by 55 respondents from three power utilities, one manufacturing company and one nuclear power plant. The service availability studies provided estimates that were accurate within a few hours of logged yearly downtime. The data accuracy estimate was correct within a percentage point when compared to a sample of data objects. Deviations for four out of five service performance estimates were within 15 % from measured values. The application usage analysis explained a high degree of variation in application usage when applied to the maintenance management domain. During the studies of data accuracy, service performance and service availability, records were kept concerning the required modeling and analysis effort. The estimates were obtained with a total effort of about 20 man-hours per estimate. In summary the framework should be useful for IT decision-makers requiring fairly accurate, but not too expensive, estimates of the four properties.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xiii, 41 p.
Series
Trita-EE, ISSN 1653-5146 ; 2012:035
Keyword
Enterprise Architecture, Metamodeling, Decision-making, Data Accuracy, Service Availability, Service Performance, Technology Acceptance Model, Task Technology Fit
National Category
Information Systems
Identifiers
urn:nbn:se:kth:diva-101494 (URN)978-91-7501-444-9 (ISBN)
Public defence
2012-09-17, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20120912

Available from: 2012-09-12 Created: 2012-08-29 Last updated: 2013-01-28Bibliographically approved

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Ekstedt, MathiasHoneth, Nicholas

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