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

Poor data quality (DQ) can have substantial social and economic impacts. Although firms are improving data quality with practical approaches and tools, their improvement efforts tend to focus narrowly on accuracy. We believe that data consumers have a much broader data quality conceptualization than IS professionals realize. The purpose of this paper is to develop a framework that captures the aspects of data quality that are important to data consumers.A two-stage survey and a two-phase sorting study were conducted to develop a hierarchical framework for organizing data quality dimensions. This framework captures dimensions of data quality that are important to data consumers. Intrinsic DQ denotes that data have quality in their own right. Contextual DQ highlights the requirement that data quality must be considered within the context of the task at hand. Representational DQ and accessibility DQ emphasize the importance of the role of systems. These findings are consistent with our understanding that high-quality data should be intrinsically good, contextually appropriate for the task, clearly represented, and accessible to the data consumer.Our framework has been used effectively in industry and government. Using this framework, IS managers were able to better understand and meet their data consumers' data quality needs. The salient feature of this research study is that quality attributes of data are collected from data consumers instead of being defined theoretically or based on researchers' experience. Although exploratory, this research provides a basis for future studies that measure data quality along the dimensions of this framework.

https://courses.washington.edu/geog482/resource/14_Beyond_Accuracy.pdf

Beyond accuracy: what data quality means to data consumers

Vendor selection criteria and methods

Everybody knows that digital technology has revolutionized our economy and our lifestyles. But how many of us really understand the drivers behind the technology – the significance of going digital; the miniaturization of electronic devices; the role of venture capital in financing the revolution; the importance of research and development? How many of us understand what it takes to make money from innovative technologies? Should we worry about manufacturing going offshore? What is the role of India and China in the digital economy? Drawing on a lifetime’s experience in the industry, as an engineer, a senior manager, and as a partner in a global venture capital firm, Henry Kressel offers an expert personalized answer to all these questions. He explains how the technology works, why it matters, how it is financed, and what the key lessons are for public policy.

Competing for the Future

https://isiarticles.com/bundles/Article/pre/pdf/19101.pdf

A review of methods supporting supplier selection

Spreadsheet programs and microcomputers have revolutionizedinformation processing in organizations. Users have adoptedspreadsheets to solve problems and circumvent the longdelays encountered in dealing with the traditionalinformation services department. A significant number ofserious errors have been reported through the misuse ofspreadsheet technology. This paper discusses severaldifferent contexts for the development of spreadsheet modelsand presents structured design techniques for these models.The recommended approach to spreadsheet analysis and designencourages the use of a block structure format for theworksheet and introduces Spreadsheet Flow Diagrams as asystems design tool. The objective of this design approachis to reduce the probability and severity of spreadsheeterrors, improve auditability and promote greater longevityfor spreadsheet models.

Spreadsheet Analysis and Design

Although spreadsheet programs and microcomputers have revolutionized information processing in organizations, a significant number of serious errors have been reported through the misuse of this technology. This article discusses several different contexts for the development of spreadsheet models and presents structured design techniques for these models.

Spreadsheet analysis and design

Despite the problems involved in its use, SWOT (strengths-weaknesses-opportunities-threats) analysis remains a major strategic tool for listing the strengths and weaknesses of an organisation, for recording the major strengths and translating them into value. This paper presents a straightforward methodology for making a structured analysis of strengths and weaknesses, based on an analysis of important value-creating events and the strengths and weaknesses that caused these events. The focused SWOT methodology distils the strengths and weaknesses into core competences and core problems, by using the core-competence tree and the current-reality tree. The core competences and core problems are then linked into a plan of action aimed at preserving and leveraging the organisation's core competences, while defending against exposure to core problems. Applications of the methodology are presented and it is demonstrated in a detailed case study.

Focused SWOT: diagnosing critical strengths and weaknesses

Synchronized manufacturing as in OPT: from practice to theory

This paper describes a model based Decision Support System (DSS) for purchasing materials and components for large projects. The DSS may be used under two scenarios. Under the first scenario, we have a project to execute, and we are looking for a good way to manage the purchasing to minimize the expected costs. The decisions under our control are when and from whom to order each item. Under the other scenario, we are bidding for the project, and wish to assess the costs associated with the purchasing decisions which we should consider before making our bid. In both cases, we take into account expected out of pocket costs as well as lateness and/or expediting penalties. The DSS is designed to help choose the best supplier for each item and schedule the placement of the orders—decisions which are very difficult to make well without such a model based DSS.

/pdf/a-decision-support-system-for-purchasing-management-of-large-2ygs7yyjk9.pdf

Boaz Ronen

Papers

Spreadsheet Analysis and Design

Spreadsheet analysis and design

Focused SWOT: diagnosing critical strengths and weaknesses

Synchronized manufacturing as in OPT: from practice to theory

A decision support system for purchasing management of large projects