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

http://traits-dgs.nceas.ucsb.edu/workspace/readings/Rao82TPB.pdf/attachment_download/file

Diversity and dissimilarity coefficients: A unified approach☆

Growing evidence suggests that thrombophilia is associated with venous thromboembolism (VTE) and adverse pregnancy outcomes. However, methodological limitations have made it difficult to obtain a clear overview of the overall risks. We conducted a systematic review to determine the risk of VTE and adverse pregnancy outcomes associated with thrombophilia in pregnancy. The effectiveness of prophylactic interventions during pregnancy was also evaluated. Major electronic databases were searched, relevant data abstracted and study quality assessed by two independent reviewers. Odds ratios (ORs) stratified by thrombophilia type were calculated for each outcome. A total of 79 studies were included in our review. The risks for individual thrombophilic defects were determined for VTE (ORs, 0.74-34.40); early pregnancy loss (ORs, 1.40-6.25); late pregnancy loss (ORs, 1.31-20.09); pre-eclampsia (ORs, 1.37-3.49); placental abruption (ORs, 1.42-7.71) and intrauterine growth restriction (ORs, 1.24-2.92). Low-dose aspirin plus heparin was the most effective in preventing pregnancy loss in thrombophilic women (OR, 1.62). Our findings confirm that women with thrombophilia are at risk of developing VTE and complications in pregnancy. However, despite the increase in relative risk, the absolute risk of VTE and adverse outcomes remains low. There is also a lack of controlled trials of antithrombotic intervention to prevent pregnancy complications. Thus, at present, universal screening for thrombophilia in pregnancy cannot be justified clinically.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2141.2005.05847.x

Thrombophilia in pregnancy: a systematic review

The statistical analysis of compositional data

Revolutionizing product development

This paper discusses the management of learning for achieving deep understanding of concepts and techniques for the analysis of conceptual situations Our goal is to to teach not only “how” but also “why” Conceptual understanding is a critical component of evidence-based management The paper presents Meaning Equivalence Reusable Learning Objects (MERLO), a novel methodology for evaluating and enhancing deep comprehension of the essence of multidimensional, complex conceptual situations, often embedded in mixed data-sets We take a broad view of conceptual understanding and use training of applied statisticians, architecture students, and Continuous Medical Education programs as examples The next sections provide background to the evidence based management of learning; an introduction to MERLO; a concept mapping of information quality (InfoQ); and discussion and directions for future research BACKGROUND Management decisions are usually based on two major inputs: Available evidence and decision making criteria Managers’ decisions are ostensibly based on objective evaluation of the evidence presented to them What does ‘objective’ mean? Often ‘objective’ means circumstantial evidence: A combination of reliable personal/economical/engineering and market details relevant to the situation Is there anything missing? There may be no missing data, as ‘evidence’ is often interpreted to include ‘all relevant facts’; which leaves a substantive issue with respect to the nature of the managerial decision making criteria This issue arises from the statistical - nondeterministic – nature of the processes driving modern markets: Supply uncertainties; variable material and production costs; customer psychology and behavior; etc In other words: No formulas are available for making ‘evidence based’, data-driven decisions; rather, interpretation of the data plays an important, often critical, role in making management decisions The issue becomes critical in view of managers’ often lack of understanding and appropriate interpretation of patterns of variations in the data, versus memorizing particular facts In order to make rational ‘evidence based’ decisions, managers’ decisions must be based not only on ‘evidence’ but, critically, also on conceptual understanding of the issues involved in the interpretation of the evidence Listening to conversations among managers and practitioners in different professional fields, reveal a common trend to clarify statements by repeatedly re-formulating the issue under discussion from alternative points-of-view that share equivalence-of-meaning These spontaneously and flexibly formulated statements are often encoded in alternative representations of complex issues in different sign systems: a conversation that began with a casual spoken dialog may evolve to include explicit references to numerical data; diagrams; and quotations of written statements in technical reports; that illustrate different aspects of the conceptual situation under discussion We use the term ‘conceptual thinking’ to describe ways of thinking that explore patterns of equivalence-of-meaning and associations among ideas, relations, and underlying issues Managers who are conceptual thinkers engage in creative discovery of hidden, but potentially viable, relations among concepts, thus testing and extending such patterns of associations that may not be obvious or easily identified Conceptual thinking also requires the ability, knowledge, and experience to generate novel ideas through alternative representations of

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The evidence-based management of learning: diagnosis and development of conceptual thinking with meaning equivalence reusable learning objects (merlo)

Modelling cause and effect relationships has been a major challenge for statisticians in a wide range of application areas. Bayesian Networks (BN) combine graphical analysis with Bayesian analysis to represent causality maps linking measured and target variables. Such maps can be used for diagnostics and predictive analytics. The paper presents an introduction to Bayesian Networks and various applications such as the impact of management style on statistical efficiency (Kenett1), studies of web site usability (Kenett2), operational risks (Kenett3), biotechnology (Peterson4), customer satisfaction surveys (Kenett5), healthcare systems (Kenett6) and the testing of web services (Bai7). Following the presentation of these case studies, a general section discusses various properties of Bayesian Networks. Some references to software programs used to construct BNs are also provided. A concluding section lists some possible directions for future research.

Applications of Bayesian Networks

. Association rules are one of the most popular unsupervised data mining methods. Once obtained, the list of association rules extractable from a given dataset is compared in order to evaluate their importance level. The measures commonly used to assess the strength of an association rule are the indexes of support, confidence, and lift. Relative Linkage Disequilibrium (RLD) was proposed in as an approach to analyse both quantitatively and graphically association rules RLD can be considered an adaptation of the lift measure with the advantage that it presents more effectively the deviation of the support of the whole rule from the support expected under independence. Moreover RLD can be interpreted graphically using a simplex representation leading to powerful graphical display of association relationships. In this paper we demonstrate the strength of RLD by applying it to two large data sets. One data set consists of 2008 aircraft accident and incident occurrences recorded in the FAA data base. The other data set consists of operational risks captured by a large financial institution operating under Basel II regulations.

Relative Linkage Disequilibrium Applications to Aircraft Accidents and Operational Risks

This work is about integrated analysis of data collected as official statistics with administrative data from operational systems in order to increase the quality of information. Information quality, or InfoQ, is ‘the potential of a data set to achieve a specific goal by using a given empirical analysis method’. InfoQ is based on the identification of four interacting components: the analysis goal, the data, the data analysis and the utility, and it is assessed through eight dimensions: data resolution, data structure, data integration, temporal relevance, generalizability, chronology of data and goal, construct operationalization and communication. The paper illustrates, through case studies, a novel strategy to increase InfoQ based on the integration of official statistics with administrative data using copulas and Bayesian Networks. Official statistics are extraordinary sources of information. However, because of temporal relevance and chronology of data and goals, these fundamental sources of information are often not properly leveraged resulting in a poor level of InfoQ in the use of official statistics. This leads to low valued statistical analyses and to the lack of sufficiently informative results. By improving temporal relevance and chronology of data and goals, the use of Bayesian Networks allows us to calibrate official with administrative data, thus strengthening the quality of the information derived from official surveys, and, overall, enhancing InfoQ. We show, with examples, how to design and implement such a calibration strategy. Copyright © 2015 John Wiley & Sons, Ltd.

/pdf/official-statistics-data-integration-for-enhanced-6obpsy9mv1.pdf

Official Statistics Data Integration for Enhanced Information Quality

The idea of adding a practical perspective to the mathematical definition of statistical efficiency is based on a suggestion by Churchill Eisenhart who, years ago gave, in an informal ‘Beer and Statistics’ seminar, a new definition of statistical efficiency. Later Bruce Hoadley from Bell Laboratories picked up where Eisenhart left off and added his version nicknamed ‘Vador’. Blan Godfrey, former CEO of the Juran Institute, more or less used Hoadley's idea during his Youden Address at the Fall Technical Conference of the American Society for Quality Control. We expand on this idea adding an additional component, the value of the data actually collected, which we believe is critical to the overall idea. The concept of Practical Statistical Efficiency (PSE) derived from these developments is introduced and demonstrated using five case studies. We suggest that PSE be considered before, during and after undertaking any quality improvement projects. Copyright © 2003 John Wiley & Sons, Ltd.

Ron S. Kenett

Papers

The evidence-based management of learning: diagnosis and development of conceptual thinking with meaning equivalence reusable learning objects (merlo)

Applications of Bayesian Networks

Relative Linkage Disequilibrium Applications to Aircraft Accidents and Operational Risks

Official Statistics Data Integration for Enhanced Information Quality

Statistical efficiency: The practical perspective