Data quality and processing for decision making: divergence between corporate strategy and manufacturing processes

Ronald D. McNeil; Renato Miele; Dennis Shaul

doi:10.1117/12.403681

13 October 2000 Data quality and processing for decision making: divergence between corporate strategy and manufacturing processes

Ronald D. McNeil, Renato Miele, Dennis Shaul

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Proceedings Volume 4192, Intelligent Systems in Design and Manufacturing III; (2000) https://doi.org/10.1117/12.403681
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States

Abstract

Information technology is driving improvements in manufacturing systems. Results are higher productivity and quality. However, corporate strategy is driven by a number of factors and includes data and pressure from multiple stakeholders, which includes employees, managers, executives, stockholders, boards, suppliers and customers. It is also driven by information about competitors and emerging technology. Much information is based on processing of data and the resulting biases of the processors. Thus, stakeholders can base inputs on faulty perceptions, which are not reality based. Prior to processing, data used may be inaccurate. Sources of data and information may include demographic reports, statistical analyses, intelligence reports (e.g., marketing data), technology and primary data collection. The reliability and validity of data as well as the management of sources and information is critical element to strategy formulation. The paper explores data collection, processing and analyses from secondary and primary sources, information generation and report presentation for strategy formulation and contrast this with data and information utilized to drive internal process such as manufacturing. The hypothesis is that internal process, such as manufacturing, are subordinate to corporate strategies. The impact of possible divergence in quality of decisions at the corporate level on IT driven, quality-manufacturing processes based on measurable outcomes is significant. Recommendations for IT improvements at the corporate strategy level are given.

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Ronald D. McNeil, Renato Miele, and Dennis Shaul "Data quality and processing for decision making: divergence between corporate strategy and manufacturing processes", Proc. SPIE 4192, Intelligent Systems in Design and Manufacturing III, (13 October 2000); https://doi.org/10.1117/12.403681

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KEYWORDS

Manufacturing

Oceanography

Databases

Data modeling

Data processing

Information technology

Feedback loops

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