According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

[서평]「The Unified Modeling Language User Guide」

Metrics and Models in Software Quality Engineering

This paper summarizes the current state of the art and recent trends in software engineering economics. It provides an overview of economic analysis techniques and their applicability to software engineering and management. It surveys the field of software cost estimation, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.

Software engineering economics

The Fourth Uncertainty in Artificial Intelligence workshop was held 19-21 August 1988. The workshop featured significant developments in application of theories of representation and reasoning under uncertainty. A recurring idea at the workshop was the need to examine uncertainty calculi in the context of choosing representation, inference, and control methodologies. The effectiveness of these choices in AI systems tends to be best considered in terms of specific problem areas. These areas include automated planning, temporal reasoning, computer vision, medical diagnosis, fault detection, text analysis, distributed systems, and behavior of nonlinear systems. Influence diagrams are emerging as a unifying representation, enabling tool development. Interest and results in uncertainty in AI are growing beyond the capacity of a workshop format.

/pdf/uncertainty-in-artificial-intelligence-5bwjag3cna.pdf

Uncertainty in artificial intelligence

Enterprise architecture (EA) models can be used in order to increase the general understanding of enterprise systems and to perform various kinds of analysis. This paper presents instantiated architectural models based on a metamodel for enterprise systems modifiability analysis, i.e. for assessing the cost of making changes to enterprise-wide systems. The instantiated architectural models detailed are based on 21 software change projects conducted at four large Nordic companies. Probabilistic relational models (PRMs) are used for formalizing the EA analysis approach. PRMs enable the combination of regular entity-relationship modeling aspects with means to perform enterprise architecture analysis under uncertainty. The modifiability metamodel employed in the analysis is validated with survey and workshop data (in total 110 experts were surveyed) and with the data collected in the 21 software change projects. Validation indicates that the modifiability metamodel contains the appropriate set of elements. It also indicates that the metamodel produces estimates within a 75% accuracy in 87% of the time and has a mean accuracy of 88% (when considering projects of 2000 man-hours or more).

Architecture analysis of enterprise systems modifiability - Models, analysis, and validation

Using enterprise architecture and technology adoption models to predict application usage

This paper presents a framework for analysis of how IT systems add business value by causally affecting the structure of organizations. The well established theory of organizational behavior developed by Mintzberg combined with more recent research on business value of IT is used to develop a quantitative theoretical framework showing which business values are affected by IT in relation to the organizational structure. This framework, which is based upon a qualitative equivalent developed in an earlier paper, describes relationships in an Extended Influence Diagram for quantified conditional probability tables and open up for an empirical appliance. Hence obtained data can be mathematically expressed for more sound assessments. The intention is to create a fully functioning tool for analyses of what kind of IT system should be used by an organization with a given structure to maximize its business value.

/pdf/quantifying-it-impacts-on-organizational-structure-and-2433a9h0k7.pdf

Quantifying IT Impacts on Organizational Structure and Business Value with Extended Influence Diagrams

Software Change Project Cost Estimation - A Bayesian Network and a Method for Expert Elicitation

The impact IT systems have on organizations is widely debated, both in academia and industry. This paper describes a quantitative framework for analyzing organizational impact from IT systems. The framework consists of an abstract model that is a metamodel suitable for expressing organizational structure incorporated with an extended influence diagram for analysis. The purpose is to create enterprise architecture (EA) models that can be used for analysis of the enterprise. The framework has been validated through a case study where the framework has been used to analyze the changes in organizational structure after the introduction of an IT system.

Modeling the IT Impact on Organizational Structure

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