Knowledge management applied to enterprise risk management

Risk and knowledge are two concepts and components of business management which have so far been studied almost independently. This is especially true where risk management (RM) is conceived mainly in financial terms, as for example, in the financial institutions sector. Financial institutions are affected by internal and external changes with the consequent accommodation to new business models, new regulations and new global competition that includes new big players. These changes induce financial institutions to develop different methodologies for managing risk, such as the enterprise risk management (ERM) approach, in order to adopt a holistic view of risk management and, consequently, to deal with different types of risk, levels of risk appetite, and policies in risk management. However, the methodologies for analysing risk do not explicitly include knowledge management (KM). This research examines the potential relationships between KM and two RM concepts: perceived quality of risk control and perceived value of ERM. To fulfill the objective of identifying how KM concepts can have a positive influence on some RM concepts, a literature review of KM and its processes and RM and its processes was performed. From this literature review eight hypotheses were analysed using a classification into people, process and technology variables. The data for this research was gathered from a survey applied to risk management employees in financial institutions and 121 answers were analysed. The analysis of the data was based on multivariate techniques, more specifically stepwise regression analysis. The results showed that the perceived quality of risk control is significantly associated with the variables: perceived quality of risk knowledge sharing, perceived quality of communication among people, web channel functionality, and risk management information system functionality. However, the relationships of the KM variables to the perceived value of ERM are not identified because of the low performance of the models describing these relationships. The analysis reveals important insights into the potential KM support to RM such as: the better adoption of KM people and technology actions, the better the perceived quality of risk control. Equally, the results suggest that the quality of risk control and the benefits of ERM follow different patterns given that there is no correlation between both concepts and the distinct influence of the KM variables in each concept. The ERM scenario is different from that of risk control because ERM, as an answer to RM failures and adaptation to new regulation in financial institutions, has led organizations to adopt new processes, technologies, and governance models. Thus, the search for factors influencing the perceived value of ERM implementation needs additional analysis because what is improved in RM processes individually is not having the same effect on the perceived value of ERM. Based on these model results and the literature review the basis of the ERKMAS (Enterprise Risk Knowledge Management System) is presented.

Designing a safety management support system using open architecture databases: the requirements of information representation in the support of managers' risk-related decision-making

This research was conducted at the Space Research and Technology Centre o the European Space Agency at Noordvijk in the Netherlands. ESA is an international organisation that brings together a range of scientists, engineers and managers from 14 European member states. The motivation for the work was to enable decision-makers, in a culturally and technologically diverse organisation, to share information for the purpose of making decisions that are well informed about the risk-related aspects of the situations they seek to address. The research examined the use of decision support system DSS) technology to facilitate decision-making of this type. This involved identifying the technology available and its application to risk management. Decision-making is a complex activity that does not lend itself to exact measurement or precise understanding at a detailed level. In view of this, a prototype DSS was developed through which to understand the practical issues to be accommodated and to evaluate alternative approaches to supporting decision-making of this type. The problem of measuring the effect upon the quality of decisions has been approached through expert evaluation of the software developed. The practical orientation of this work was informed by a review of the relevant literature in decision-making, risk management, decision support and information technology. Communication and information technology unite the major the,es of this work. This allows correlation of the interests of the research with European public policy. The principles of communication were also considered in the topic of information visualisation - this emerging technology exploits flexible modes of human computer interaction (HCI) to improve the cognition of complex data. Risk management is itself an area characterised by complexity and risk visualisation is advocated for application in this field of endeavour. The thesis provides recommendations for future work in the fields of decision=making, DSS technology and risk management.

Cervicovaginal vascular endothelial growth factor (VEGF) and risk of preterm birth (PTB)

Objective - During pregnancy, the human cervix undergoes angiogenic transformations. VEGF is expressed in cervical stroma and is proposed to play key roles in the process of cervical ripening and dilation. This study was conducted to evaluate whether cervical secretion of VEGF can be of clinical value in predicting impending PTB. Study Design - In an observational prospective cohort study, we analyzed cervical fluid samples from 103 pregnant women (GA: median [IQR]: 28 [25-31] wks) who presented for either a routine prenatal visit (n=61) or for evaluation of threatened preterm labor (n=42). Cervical secretions were collected under a standard protocol which was followed in all cases. Cervical length (CL) was assessed by transvaginal ultrasound using well-established criteria. Dilation was evaluated by digital exam performed only after collection of the biological samples. VEGF levels were immunoassayed by investigators unaware of the clinical outcome. Main exclusion criteria were ruptured membranes, active labor, vaginal bleeding, vaginal exam or intercourse within 24h. Results were analyzed with and without normalization for total protein. Results - 1) Clinical characteristics of the cohort are presented in Table;2) VEGF was detectable in all specimens, with no correlation between its levels, CL, twins or GA at collection; 3) There was an inverse correlation between VEGF and cervical dilation (R=-0.646, P=0.003); 4) Women with cervical dilation =1 cm had lower VEGF compared to those with a closed cervix (P=0.003); 5) Women who experienced PTB within 14 days (n=11) had lower VEGF (P=0.003); 6) A free VEGF level of =600 pg/mL had a sensitivity, specificity, +LR and -LR of 70%, 95%, 13.5 and 0.3, respectively in predicting PTB within 14 days. Conclusions - Low VEGF levels in the cervicovaginal secretions of pregnant women are associated with an increased risk of PTB within 2 weeks of collection. Active engagement of VEGF in the process of cervical ripening and dilatation and/or increased affinity of extracellular matrix components for VEGF may provide explanation for our findings.

Handling varying amounts of missing data when classifying mental-health risk levels

One of the main challenges of classifying clinical data is determining how to handle missing features. Most research favours imputing of missing values or neglecting records that include missing data, both of which can degrade accuracy when missing values exceed a certain level. In this research we propose a methodology to handle data sets with a large percentage of missing values and with high variability in which particular data are missing. Feature selection is effected by picking variables sequentially in order of maximum correlation with the dependent variable and minimum correlation with variables already selected. Classification models are generated individually for each test case based on its particular feature set and the matching data values available in the training population. The method was applied to real patients' anonymous mental-health data where the task was to predict the suicide risk judgement clinicians would give for each patient's data, with eleven possible outcome classes: zero to ten, representing no risk to maximum risk. The results compare favourably with alternative methods and have the advantage of ensuring explanations of risk are based only on the data given, not imputed data. This is important for clinical decision support systems using human expertise for modelling and explaining predictions.

The complements towards developing a new risk management framework and Its applicability to the Nigerian power sector

The availability of regular supply has been identified as one of the major stimulants for the growth and development of any nation and is thus important for the economic well-being of a nation. The problems of the Nigerian power sector stems from a lot of factors culminating in her slow developmental growth and inability to meet the power demands of her citizens regardless of the abundance of human and natural resources prevalent in the nation. The research therefore had the main aim of investigating the importance and contributions of risk management to the success of projects specific to the power sector. To achieve this aim it was pertinent to examine the efficacy of risk management process in practice and elucidate the various risks typically associated with projects (Construction, Contractual, Political, Financial, Design, Human resource and Environmental risk factors) in the power sector as well as determine the current situation of risk management practice in Nigeria. To address this factors inhibiting the proficiency of the overarching and prevailing issue which have only been subject to limited in-depth academic research, a rigorous mixed research method was adopted (quantitative and qualitative data analysis). A review of the Nigeria power sector was also carried out as a precursor to the data collection stage. Using purposive sampling technique, respondents were identified and a questionnaire survey was administered. The research hypotheses were tested using inferential statistics (Pearson correlation, Chi-square test, t-test and ANOVA technique) and the findings revealed the need for the development of a new risk management implementation Framework. The proposed Framework was tested within a company project, for interpreting the dynamism and essential benefits of risk management with the aim of improving the project performances (time), reducing the level of fragmentation (quality) and improving profitability (cost) within the Nigerian power sector in order to bridge a gap between theory and practice. It was concluded that Nigeria’s poor risk management practices have prevented it from experiencing strong growth and development. The study however, concludes that the successful implementation of the developed risk management framework may help it to attain this status by enabling it to become more prepared and flexible, to face challenges that previously led to project failures, and thus contributing to its prosperity. The research study provides an original contribution theoretically, methodologically and practically which adds to the project risk management body of knowledge and to the Nigerian power sector.