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International Journal of Approximate Reasoning
Advances in statistical decision theory and applications
Advances in statistical decision theory and applications
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Journal of Systems and Software - Special issue on invited articles on top systems and software engineering scholars
Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
A Framework of Software Measurement
A Framework of Software Measurement
Software Metrics: A Rigorous and Practical Approach
Software Metrics: A Rigorous and Practical Approach
Making Sense of Measurement for Small Organizations
IEEE Software
Measurement Programs in Software Development: Determinants of Success
IEEE Transactions on Software Engineering
AIMQ: a methodology for information quality assessment
Information and Management
Measurement Modeling Technology
IEEE Software
Lessons from Implementing a Software Metrics Program
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METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
Cranfield: Corporate Performance Management
Cranfield: Corporate Performance Management
The Art and Science of Software Release Planning
IEEE Software
The Profit Impact of Business Intelligence
The Profit Impact of Business Intelligence
Decision Support Systems
A framework for developing measurement systems and its industrial evaluation
Information and Software Technology
What's up with software metrics? - A preliminary mapping study
Journal of Systems and Software
Ensuring Reliability of Information Provided by Measurement Systems
IWSM '09 /Mensura '09 Proceedings of the International Conferences on Software Process and Product Measurement
Using Models to Develop Measurement Systems: A Method and Its Industrial Use
IWSM '09 /Mensura '09 Proceedings of the International Conferences on Software Process and Product Measurement
Information and Software Technology
Information and Software Technology
Developing measurement systems: an industrial case study
Journal of Software Maintenance and Evolution: Research and Practice
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Ontology management and evolution for business intelligence
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Context: Today, many software development organizations struggle to establish measurement programs to monitor their projects, products and units. After overcoming the initial threshold of establishing the measurement program organizations stand before the questions of which measures should be collected in order to lead to actions or at least effectively trigger decision processes. Objective: The objective of this paper is to investigate how to use measures in an effective way in decision processes. This dependency is examined through a case study - Ericsson in Sweden. Two models of these dependencies are recognized a priori - metrics-push and metric-pull - and in the study the models are used to describe how measures affect decisions and vice versa. Method: The research method is a case study of the measurement program of one of the product development units of Ericsson in Sweden. The participants are carefully selected from the management teams at different levels of organizations. The objects are measures and decisions at these management levels. The instruments are interviews and observations. The results obtained at Ericsson are validated through interviews at another company - RUAG Space. Results: The results show that effective use of measures as evidence for decision processes does not require a large number of measures (ca. 20 at the top management level). It was found that there are four types of measures which are used in different ways in the context of decision formulation and implementation (which we call decision-measures dependency model). The critical aspects of effective measures in decision-making context are completeness, reliability and providing early warnings. It was also found that the time between the decision and when its results can be observed via measures (length of the feedback loop) is a crucial aspect determining at which organizational level a measure should be placed. Conclusions: After overcoming the initial threshold of establishing measurement programs the organizations demand non-functional properties from the measures. These non-functional properties like completeness, providing early-warning or trust determine whether decision processes are triggered by measures or not.