Management Tools for RetD Project Portfolios in Complex Organizations – the case of an international pharmaceutical firm

Project Portfolio Management (PPM) is a growing issue in both professional and academic circles. The typology of Cooper et al. (1998) has pictured the variety of PPM formalized approaches into four types (financial, strategic, scoring and “bubble diagram”). While the use of formalized methods by top performers is clearly attested, the choice of a specific approach and the precise benefits and limits of different instruments are still in debate. The present paper formalizes more precise contingency hypotheses between PPM practices and organizational variables such as R&D strategy, the structure and history of a firm's development, partnership policy and learning track in the project domain. Where managerial implications are concerned, the paper puts forward an analytical framework for the adjustment of portfolio instruments to fit specific situations and develops the conclusions of that framework for an international pharmaceutical group, Merck Lipha. The research underlying this paper adopts an interactive and experimental case-based methodology which has been on-going since 1997.Project; portfolios; pharmaceuticals; decision; processes; interactive research

An SEA Guide for Identifying Evidence-Based Interventions for School Improvement

The Every Student Succeeds Act (ESSA) is the most recent reauthorization of the Elementary and Secondary Education Act and replaces the No Child Left Behind Act (NCLB). The law focuses on using research evidence to improve teaching and learning and at the same time passes considerable authority from federal to state policymakers. This means that responsibility largely falls on states and localities to effectively make sense of and use research evidence in their decisions around school improvement, teacher preparation, principal recruitment, and family engagement. With support from the Annie E. Casey Foundation, Overdeck Family Foundation, and the William T. Grant Foundation, the Florida Center for Reading Research (FCRR) has developed Guides for Identifying Evidence-Based Interventions for School Improvement

Ensemble of Example-Dependent Cost-Sensitive Decision Trees

Several real-world classification problems are example-dependent cost-sensitive in nature, where the costs due to misclassification vary between examples and not only within classes. However, standard classification methods do not take these costs into account, and assume a constant cost of misclassification errors. In previous works, some methods that take into account the financial costs into the training of different algorithms have been proposed, with the example-dependent cost-sensitive decision tree algorithm being the one that gives the highest savings. In this paper we propose a new framework of ensembles of example-dependent cost-sensitive decision-trees. The framework consists in creating different example-dependent cost-sensitive decision trees on random subsamples of the training set, and then combining them using three different combination approaches. Moreover, we propose two new cost-sensitive combination approaches; cost-sensitive weighted voting and cost-sensitive stacking, the latter being based on the cost-sensitive logistic regression method. Finally, using five different databases, from four real-world applications: credit card fraud detection, churn modeling, credit scoring and direct marketing, we evaluate the proposed method against state-of-the-art example-dependent cost-sensitive techniques, namely, cost-proportionate sampling, Bayes minimum risk and cost-sensitive decision trees. The results show that the proposed algorithms have better results for all databases, in the sense of higher savings.Comment: 13 pages, 6 figures, Submitted for possible publicatio

A systems approach to evaluate One Health initiatives

Challenges calling for integrated approaches to health, such as the One Health (OH) approach, typically arise from the intertwined spheres of humans, animals, and ecosystems constituting their environment. Initiatives addressing such wicked problems commonly consist of complex structures and dynamics. As a result of the EU COST Action (TD 1404) “Network for Evaluation of One Health” (NEOH), we propose an evaluation framework anchored in systems theory to address the intrinsic complexity of OH initiatives and regard them as subsystems of the context within which they operate. Typically, they intend to influence a system with a view to improve human, animal, and environmental health. The NEOH evaluation framework consists of four overarching elements, namely: (1) the definition of the initiative and its context, (2) the description of the theory of change with an assessment of expected and unexpected outcomes, (3) the process evaluation of operational and supporting infrastructures (the “OH-ness”), and (4) an assessment of the association(s) between the process evaluation and the outcomes produced. It relies on a mixed methods approach by combining a descriptive and qualitative assessment with a semi-quantitative scoring for the evaluation of the degree and structural balance of “OH-ness” (summarised in an OH-index and OH-ratio, respectively) and conventional metrics for different outcomes in a multi-criteria-decision-analysis. Here, we focus on the methodology for Elements (1) and (3) including ready-to-use Microsoft Excel spreadsheets for the assessment of the “OH-ness”. We also provide an overview of Element (2), and refer to the NEOH handbook for further details, also regarding Element (4) (http://neoh.onehealthglobal.net). The presented approach helps researchers, practitioners, and evaluators to conceptualise and conduct evaluations of integrated approaches to health and facilitates comparison and learning across different OH activities thereby facilitating decisions on resource allocation. The application of the framework has been described in eight case studies in the same Frontiers research topic and provides first data on OH-index and OH-ratio, which is an important step towards their validation and the creation of a dataset for future benchmarking, and to demonstrate under which circumstances OH initiatives provide added value compared to disciplinary or conventional health initiatives