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Enterprise Architecture for Information System Analysis: Modeling and assessing data accuracy, availability, performance and application usage
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
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 [en]
Enterprise Architecture, Metamodeling, Decision-making, Data Accuracy, Service Availability, Service Performance, Technology Acceptance Model, Task Technology Fit
National Category
Information Systems
Identifiers
URN: urn:nbn:se:kth:diva-101494ISBN: 978-91-7501-444-9 (print)OAI: oai:DiVA.org:kth-101494DiVA: diva2:552047
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
List of papers
1. Data accuracy assessment using enterprise architecture
Open this publication in new window or tab >>Data accuracy assessment using enterprise architecture
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2011 (English)In: Enterprise Information Systems, ISSN 1751-7575, E-ISSN 1751-7583, Vol. 5, no 1, 37-58 p.Article in journal (Refereed) Published
Abstract [en]

Errors in business processes result in poor data accuracy. This article proposes an architecture analysis method which utilises ArchiMate and the Probabilistic Relational Model formalism to model and analyse data accuracy. Since the resources available for architecture analysis are usually quite scarce, the method advocates interviews as the primary data collection technique. A case study demonstrates that the method yields correct data accuracy estimates and is more resource-efficient than a competing sampling-based data accuracy estimation method.

Keyword
accuracy, data quality, enterprise architecture, probabilistic relational models, architecture analysis
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-39358 (URN)10.1080/17517575.2010.507878 (DOI)000285351400003 ()2-s2.0-78650276572 (Scopus ID)
Note

QC 20110908

Available from: 2011-09-09 Created: 2011-09-09 Last updated: 2017-12-08Bibliographically approved
2. Enterprise Architecture Availability Analysis Using Fault Trees and Stakeholder Interviews
Open this publication in new window or tab >>Enterprise Architecture Availability Analysis Using Fault Trees and Stakeholder Interviews
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2014 (English)In: Enterprise Information Systems, ISSN 1751-7575, E-ISSN 1751-7583, Vol. 8, no 1, 1-25 p.Article in journal (Refereed) Published
Abstract [en]

The availability of enterprise information systems is a key concern for many organisations. This article describes a method for availability analysis based on Fault Tree Analysis and constructs from the ArchiMate enterprise architecture (EA) language. To test the quality of the method, several case-studies within the banking and electrical utility industries were performed. Input data were collected through stakeholder interviews. The results from the case studies were compared with availability of log data to determine the accuracy of the method's predictions. In the five cases where accurate log data were available, the yearly downtime estimates were within eight hours from the actual downtimes. The cost of performing the analysis was low; no case study required more than 20 man-hours of work, making the method ideal for practitioners with an interest in obtaining rapid availability estimates of their enterprise information systems.

Keyword
availability, enterprise architecture, probabilistic relational models, architecture analysis, fault tree analysis, stakeholder elicitation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-79641 (URN)10.1080/17517575.2011.647092 (DOI)000328473200001 ()2-s2.0-84890611982 (Scopus ID)
Note

QC 20140122

Available from: 2012-02-09 Created: 2012-02-09 Last updated: 2017-12-07Bibliographically approved
3. Using enterprise architecture analysis and interview data to estimate service response time
Open this publication in new window or tab >>Using enterprise architecture analysis and interview data to estimate service response time
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.

Keyword
Enterprise Architecture, Performance, Design Science, Quality of Service, Service Management, Service Engineering
National Category
Information Systems
Identifiers
urn:nbn:se:kth:diva-102189 (URN)10.1016/j.jsis.2012.10.002 (DOI)000317162600006 ()2-s2.0-84875269195 (Scopus ID)
Note

QC 20130506

Available from: 2012-09-12 Created: 2012-09-10 Last updated: 2017-12-07Bibliographically approved
4. Using enterprise architecture and technology adoption models to predict application usage
Open this publication in new window or tab >>Using enterprise architecture and technology adoption models to predict application usage
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2012 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 85, no 8, 1953-1967 p.Article in journal (Refereed) Published
Abstract [en]

Application usage is an important parameter to consider in application portfolio management. This paper presents an enterprise architecture analysis framework which can be used to assess application usage. The framework, in the form of an architecture metamodel, incorporates variables from the previously published Technology Acceptance Model (TAM) and the Task-Technology Fit (TTF) model. The paper describes how the metamodel has been tailored for a specific domain, viz, industry maintenance management. The metamodel was tested in the maintenance management domain through a survey with 55 respondents at five companies. Data collected in the survey showed that the domain-specific metamodel is able to explain variations in maintenance management application usage. Integrating the TAM and TTF variables with an architecture metamodel allows architects to reuse research results smoothly, thereby aiding them in producing good application portfolio decision-support.

Keyword
Enterprise architecture, Architecture analysis, Technology Acceptance Model, Task-Technology Fit, Maintenance management, Computerized Maintenance Management Systems, Metamodel, Application portfolio management
National Category
Computer Systems Software Engineering
Identifiers
urn:nbn:se:kth:diva-98916 (URN)10.1016/j.jss.2012.02.035 (DOI)000305109300018 ()2-s2.0-84861346426 (Scopus ID)
Note
QC 20120712Available from: 2012-07-12 Created: 2012-07-05 Last updated: 2017-12-07Bibliographically approved
5. An enterprise architecture framework for multi-attribute information systems analysis
Open this publication in new window or tab >>An enterprise architecture framework for multi-attribute information systems analysis
2014 (English)In: Journal of Software and Systems Modeling (online), ISSN 1619-1366, E-ISSN 1619-1374, Vol. 13, no 3, 1085-1116 p.Article in journal (Refereed) Published
Abstract [en]

Enterprise architecture is a model-based IT and business management discipline. Enterprise architecture analysis concerns using enterprise architecture models for analysis of selected properties to provide decision support. This paper presents a framework based on the ArchiMate metamodel for the assessment of four properties, viz., application usage, system availability, service response time and data accuracy. The framework integrates four existing metamodels into one and implements these in a tool for enterprise architecture analysis. The paper presents the overall metamodel and four viewpoints, one for each property. The underlying theory and formalization of the four viewpoints is presented. In addition to the tool implementation, a running example as well as guidelines for usage makes the viewpoints easily applicable.

Keyword
Enterprise architecture, Enterprise architecture analysis, Enterprise architecture tool, Data accuracy, Technology usage, Service availability, Service response time
National Category
Computer and Information Science
Identifiers
urn:nbn:se:kth:diva-102187 (URN)10.1007/s10270-012-0288-2 (DOI)000338502600010 ()2-s2.0-84903448926 (Scopus ID)
Note

QC 20140813. Updated from manuscript to article in journal.

Available from: 2012-09-12 Created: 2012-09-10 Last updated: 2017-12-07Bibliographically approved

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