Service identification through value chain analysis and prioritization

In a resource constrained business world, strategic choices must be made on process improvement and service delivery. There are calls for more agile forms of enterprises and much effort is being directed at moving organizations from a complex landscape of disparate application systems to that of an integrated and flexible enterprise accessing complex systems landscapes through service oriented architecture (SOA). This paper describes the deconstruction of an enterprise into business services using value chain analysis as each element in the value chain can be rendered as a business service in the SOA. These business services are explicitly linked to the attainment of specific organizational strategies and their contribution to the attainment of strategy is assessed and recorded. This contribution is then used to provide a rank order of business service to strategy. This information facilitates executive decision making on which business service to develop into the SOA. The paper describes an application of this Critical Service Identification Methodology (CSIM) to a case study.

Student focus and prioritization of design parameters in first-year engineering design projects

BACKGROUND Research on engineering design is a core area of concern within engineering education and a fundamental understanding of how engineering students approach and undertake design is necessary in order to develop effective design models and pedagogies. Understanding the factors related to design experiences in education and how they affect student practice can help educators as well as designers to leverage these factors as part of the design process. PURPOSE This study investigated the design practices of first-year engineering students’ and their experiences with a first-year engineering course design project. The research questions that guided the investigation were: 1. From a student perspective, what design parameters or criteria are most important? 2. How does this perspective impact subsequent student design practice throughout the design process? DESIGN/METHOD The authors employed qualitative multi-case study methods (Miles & Huberman, 1994) in order to the answer the research questions. Participant teams were observed and video recorded during team design meetings in which they researched the background for the design problem, brainstormed and sketched possible solutions, as well as built prototypes and final models of their design solutions as part of a course design project. Analysis focused on explanation building (Yin, 2009) and utilized within-case and cross-case analysis (Miles & Huberman, 1994). RESULTS We found that students focused disproportionally on the functional parameter, i.e. the physical implementation of their solution, and the possible/applicable parameter, i.e. a possible and applicable solution that benefited the user, in comparison to other given parameters such as safety and innovativeness. In addition, we found that individual teams focused on the functional and possible/ applicable parameters in early design phases such as brainstorming/ ideation and sketching. When prompted to discuss these non-salient parameters (from the student perspective) in the final design report, student design teams often used a post-hoc justification to support how the final designs fit the parameters that they did not initially consider. CONCLUSIONS This study suggests is that student design teams become fixated on (and consequently prioritize) certain parameters they interpret as important because they feel these parameters were described more explicitly in terms how they were met and assessed. Students fail to consider other parameters, perceived to be less directly assessable, unless prompted to do so. Failure to consider other parameters in the early design phases subsequently affects their approach in design phases as well. Case studies examining students’ study strategies within three Australian Universities illustrate similarities with some student approaches to design.

A decision support framework for prioritization of engineering asset management activities under uncertainty

Engineers and asset managers must often make decisions on how to best allocate limited resources amongst different interrelated activities, including repair, renewal, inspection, and procurement of new assets. The presence of project interdependencies and the lack of sufficient information on the true value of an activity often produce complex problems and leave the decision maker guessing about the quality and robustness of their decision. In this paper, a decision support framework for uncertain interrelated activities is presented. The framework employs a methodology for multi-criteria ranking in the presence of uncertainty, detailing the effect that uncertain valuations may have on the priority of a particular activity. The framework employs employing semi-quantitative risk measures that can be tailored to an organisation and enable a transparent and simple-to-use uncertainty specification by the decision maker. The framework is then demonstrated on a real world project set from a major Australian utility provider.

Species-based and community-level approaches to conservation prioritization

One major reason for the global decline of biodiversity is habitat loss and fragmentation. Conservation areas can be designed to reduce biodiversity loss, but as resources are limited, conservation efforts need to be prioritized in order to achieve best possible outcomes. The field of systematic conservation planning developed as a response to opportunistic approaches to conservation that often resulted in biased representation of biological diversity. The last two decades have seen the development of increasingly sophisticated methods that account for information about biodiversity conservation goals (benefits), economical considerations (costs) and socio-political constraints. In this thesis I focus on two general topics related to systematic conservation planning. First, I address two aspects of the question about how biodiversity features should be valued. (i) I investigate the extremely important but often neglected issue of differential prioritization of species for conservation. Species prioritization can be based on various criteria, and is always goal-dependent, but can also be implemented in a scientifically more rigorous way than what is the usual practice. (ii) I introduce a novel framework for conservation prioritization, which is based on continuous benefit functions that convert increasing levels of biodiversity feature representation to increasing conservation value using the principle that more is better. Traditional target-based systematic conservation planning is a special case of this approach, in which a step function is used for the benefit function. We have further expanded the benefit function framework for area prioritization to address issues such as protected area size and habitat vulnerability. In the second part of the thesis I address the application of community level modelling strategies to conservation prioritization. One of the most serious issues in systematic conservation planning currently is not the deficiency of methodology for selection and design, but simply the lack of data. Community level modelling offers a surrogate strategy that makes conservation planning more feasible in data poor regions. We have reviewed the available community-level approaches to conservation planning. These range from simplistic classification techniques to sophisticated modelling and selection strategies. We have also developed a general and novel community level approach to conservation prioritization that significantly improves on methods that were available before. This thesis introduces further degrees of realism into conservation planning methodology. The benefit function -based conservation prioritization framework largely circumvents the problematic phase of target setting, and allowing for trade-offs between species representation provides a more flexible and hopefully more attractive approach to conservation practitioners. The community-level approach seems highly promising and should prove valuable for conservation planning especially in data poor regions. Future work should focus on integrating prioritization methods to deal with multiple aspects in combination influencing the prioritization process, and further testing and refining the community level strategies using real, large datasets.

Establishing National Ocean Service Priorities for Estuarine, Coastal, and Ocean Modeling: Capabilities, Gaps, and Preliminary Prioritization Factors

This report was developed to help establish National Ocean Service priorities and chart new directions for research and development of models for estuarine, coastal and ocean ecosystems based on user-driven requirements and supportive of sound coastal management, stewardship, and an ecosystem approach to management. (PDF contains 63 pages)

Prioritization of candidate cancer genes-an aid to oncogenomic studies

The development of techniques for oncogenomic analyses such as array comparative genomic hybridization, messenger RNA expression arrays and mutational screens have come to the fore in modern cancer research. Studies utilizing these techniques are able to highlight panels of genes that are altered in cancer. However, these candidate cancer genes must then be scrutinized to reveal whether they contribute to oncogenesis or are coincidental and non-causative. We present a computational method for the prioritization of candidate (i) proto-oncogenes and (ii) tumour suppressor genes from oncogenomic experiments. We constructed computational classifiers using different combinations of sequence and functional data including sequence conservation, protein domains and interactions, and regulatory data. We found that these classifiers are able to distinguish between known cancer genes and other human genes. Furthermore, the classifiers also discriminate candidate cancer genes from a recent mutational screen from other human genes. We provide a web-based facility through which cancer biologists may access our results and we propose computational cancer gene classification as a useful method of prioritizing candidate cancer genes identified in oncogenomic studies.

Prioritization of knowledge needs for sustainable aquaculture: a national and global perspective

Aquaculture is currently the fastest expanding global animal food production sector and is a key future contributor to food security. An increase in food security will be dependent upon the development and improvement of sustainable practices. A prioritization exercise was undertaken, focusing on the future knowledge needs to underpin UK sustainable aquaculture (both domestic and imported products) using a ‘task force’ group of 36 ‘practitioners’ and 12 ‘research scientists’ who have an active interest in sustainable aquaculture. A long list of 264 knowledge needs related to sustainable aquaculture was developed in conjunction with the task force. The long list was further refined through a three stage process of voting and scoring, including discussions of each knowledge need. The top 25 knowledge needs are presented, as scored separately by ‘practitioners’ or ‘research scientists’. There was similar agreement in priorities identified by these two groups. The priority knowledge needs will provide guidance to structure ongoing work to make science accessible to practitioners and help to prioritize future science policy needs and funding. The process of knowledge exchange, and the mechanisms by which this can be achieved, effectively emerged as the top priority for sustainable aquaculture. Viable alternatives to wild fish-based aquaculture feeds, resource constraints that will potentially limit expansion of aquaculture, sustainable offshore aquaculture and the treatment of sea lice also emerged as strong priorities. Although the exercise was focused on UK needs for sustainable aquaculture, many of the emergent issues are considered to have global application.

Task prioritization in aging: effects of sensory information on concurrent posture and memory performance

In older adults, cognitive resources play a key role in maintaining postural stability. In the present study, we evaluated whether increasing postural instability using sway referencing induces changes in resource allocation in dual-task performance leading older adults to prioritize the more age-salient posture task over a cognitive task. Young and older adults participated in the study which comprised two sessions. In the first session, three posture tasks (stable, sway reference visual, sway reference somatosensory) and a working memory task (n-back) were examined. In the second session, single- and dual-task performance of posture and memory were assessed. Postural stability improved with session. Participants were more unstable in the sway reference conditions, and pronounced age differences were observed in the somatosensory sway reference condition. In dual-task performance on the stable surface, older adults showed an almost 40% increase in instability compared to single-task. However, in the sway reference somatosensory condition, stability was the same in single- and dual-task performance, whereas pronounced (15%) costs emerged for cognition. These results show that during dual-tasking while standing on a stable surface, older adults have the flexibility to allow an increase in instability to accommodate cognitive task performance. However, when instability increases by means of compromising somatosensory information, levels of postural control are kept similar in single- and dual-task, by utilizing resources otherwise allocated to the cognitive task. This evidence emphasizes the flexible nature of resource allocation, developed over the life-span to compensate for age-related decline in sensorimotor and cognitive processing.

Association Study of 167 Candidate Genes for Schizophrenia Selected by a Multi-Domain Evidence-Based Prioritization Algorithm and Neurodevelopmental Hypothesis

Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n = 3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this
ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.

An experimental approach to project risk identification and prioritization

One of the aims of a broad ethnographic study into how the apportionment of risk influences pricing levels of contactors was to ascertain the significant risks affecting contractors in Ghana, and their impact on prices. To do this, in the context of contractors, the difference between expected and realized return on a project is the key dependent variable examined using documentary analyses and semi-structured interviews. Most work in this has focused on identifying and prioritising risks using relative importance indices generated from the analysis of questionnaire survey responses. However, this approach may be argued to constitute perceptions rather than direct measures of the project risk. Here, instead, project risk is investigated by examining two measures of the same quantity; one ‘before’ and one ‘after’ construction of a project has taken place. Risks events are identified by ascertaining the independent variables causing deviations between expected and actual rates of return. Risk impact is then measured by ascertaining additions or reductions to expected costs due to the occurrence of risk events. So far, data from eight substantially complete building projects indicates that consultants’ inefficiency, payment delays, subcontractor-related problems and changes in macroeconomic factors are significant risks affecting contractors in Ghana.

Modeling and illustrating requirement prioritization in public e-service development from a value-based perspective

A major problem in e-service development is the prioritization of the requirements of different stakeholders. The main stakeholders are governments and their citizens, all of whom have different and sometimes conflicting requirements. In this paper, the prioritization problem is addressed by combining a value-based approach with an illustration technique. This paper examines the following research question: How can multiple stakeholder requirements be illustrated from a value-based perspective in order to be prioritizable? We used an e-service development case taken from a Swedish municipality to elaborate on our approach. Our contributions are: 1) a model of the relevant domains for requirement prioritization for government, citizens, technology, finances and laws and regulations; and 2) a requirement fulfillment analysis tool (RFA) that consists of a requirement-goal-value matrix (RGV), and a calculation and illustration module (CIM). The model reduces cognitive load, helps developers to focus on value fulfillment in e-service development and supports them in the formulation of requirements. It also offers an input to public policy makers, should they aim to target values in the design of e-services.