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

Evidence Based Informed Consent for Caesarean Section Using MERLO - Meaning Equivalence Reusable Learning Objects

Numbers are not data and data analysis does not necessarily produce information and knowledge. Statistics, data mining, and artificial intelligence are disciplines focused on extracting knowledge from data. They provide tools for testing hypotheses, predicting new observations, quantifying population effects, and summarizing data efficiently. In these fields, measurable data is used to derive knowledge. However, a clean, exact and complete dataset, which is analyzed professionally, might contain no useful information for the problem under investigation. The term Information Quality (InfoQ) was coined by Ref. [15] as the potential of a dataset to achieve a specific (scientific or practical) goal using a given data analysis method. InfoQ is a function of goal, data, data analysis, and utility. Eight dimensions that relate to these components help assess InfoQ: Data Resolution, Data Structure, Data Integration, Temporal Relevance, Generalizability, Chronology of Data and Goal, Construct Operationalization, and Communication. The eight dimensions can be used for developing streamlined evaluation metrics of InfoQ. We describe two studies where InfoQ was integrated into research methods courses, guiding students in evaluating InfoQ of prospective and retrospective studies. The results and feedback indicate the importance and usefulness of InfoQ and its eight dimensions for evaluating empirical studies.

https://www.galitshmueli.com/system/files/InfoQ_IDAM_2013_0.pdf

An Information Quality (InfoQ) Framework for Ex-Ante and Ex-Post Evaluation of Empirical Studies

Open source software (OSS) has increasingly played a leading role in current information technology practices. Its pervasive adoption is not without risks for an industry that has experienced significant failures in product quality, timelines and delivery costs. Inadequate risk management has been identified among the top deficiencies when implementing OSS-based solutions. A crucial aspect in managing and mitigating OSS adoption risks is that of deeply understanding the behavior and dynamics of the OSS communities that provide the software components. This can be achieved via the analysis of big amounts of data related, for example, to community activeness, reliability, or capacity of managing the OSS component maintenance and evolution. The objective of this chapter is to present a risk management method and platform for managing OSS risks. Our approach integrates different data sources that represent different aspects of OSS communities in the context of a business-oriented decision-making framework. This way, we aim to support placing technical OSS adoption and deployment decisions into organizational, business strategy as well as the broader OSS community context and as a result, reduce the gap between the concerns of companies and institutions using OSS and the possible risk of business and technical failures in adopting it.

Community Data for OSS Adoption Risk Management

Operational risk management: an overview

The response to the COVID-19 pandemic has been highly variable. Governments have applied different mitigation policies with varying effect on social and economic measures, over time. This article presents a methodology for examining the effect of mobility restriction measures and the association between health and population activity data. As case studies, we refer to the pre-vaccination experience in Italy and Israel. Facing the pandemic, Israel and Italy implemented different policy measures and experienced different population behavioral patterns. Data from these countries are used to demonstrate the proposed methodology. The analysis we introduce in this paper is a staged approach using Bayesian Networks and Structural Equations Models. The goal is to assess the impact of pandemic management and mitigation policies on pandemic spread and population activity. The proposed methodology models data from health registries and Google mobility data and then shows how decision makers can conduct scenario analyses to help design adequate pandemic management policies.

/pdf/integrated-analysis-of-behavioural-and-health-covid-19-data-18gjssra.pdf

Ron S. Kenett

Papers

Evidence Based Informed Consent for Caesarean Section Using MERLO - Meaning Equivalence Reusable Learning Objects

An Information Quality (InfoQ) Framework for Ex-Ante and Ex-Post Evaluation of Empirical Studies

Community Data for OSS Adoption Risk Management

Operational risk management: an overview

Integrated Analysis of Behavioural and Health COVID-19 Data Combining Bayesian Networks and Structural Equation Models