Forecasting and risk analysis applied to management planning and control

The aim of this research was to improve the quantitative support to project planning and control principally through the use of more accurate forecasting for which new techniques were developed. This study arose from the observation that in most cases construction project forecasts were based on a methodology (c.1980) which relied on the DHSS cumulative cubic cost model and network based risk analysis (PERT). The former of these, in particular, imposes severe limitations which this study overcomes. Three areas of study were identified, namely growth curve forecasting, risk analysis and the interface of these quantitative techniques with project management. These fields have been used as a basis for the research programme. In order to give a sound basis for the research, industrial support was sought. This resulted in both the acquisition of cost profiles for a large number of projects and the opportunity to validate practical implementation. The outcome of this research project was deemed successful both in theory and practice. The new forecasting theory was shown to give major reductions in projection errors. The integration of the new predictive and risk analysis technologies with management principles, allowed the development of a viable software management aid which fills an acknowledged gap in current technology.

Exploring the digital supply chain:implications and models for online software distribution

As a discipline, supply chain management (SCM) has traditionally been primarily concerned with the procurement, processing, movement and sale of physical goods. However an important class of products has emerged - digital products - which cannot be described as physical as they do not obey commonly understood physical laws. They do not possess mass or volume, and they require no energy in their manufacture or distribution. With the Internet, they can be distributed at speeds unimaginable in the physical world, and every copy produced is a 100% perfect duplicate of the original version. Furthermore, the ease with which digital products can be replicated has few analogues in the physical world. This paper assesses the effect of non-physicality on one such product – software – in relation to the practice of SCM. It explores the challenges that arise when managing the software supply chain and how practitioners are addressing these challenges. Using a two-pronged exploratory approach that examines the literature around software management as well as direct interviews with software distribution practitioners, a number of key challenges associated with software supply chains are uncovered, along with responses to these challenges. This paper proposes a new model for software supply chains that takes into account the non-physicality of the product being delivered. Central to this model is the replacement of physical flows with flows of intellectual property, the growing importance of innovation over duplication and the increased centrality of the customer in the entire process. Hybrid physical / digital supply chains are discussed and a framework for practitioners concerned with software supply chains is presented.

The value of proprietary health and safety software to proactive health and safety management

There has been little research in health and safety management concernmg the application of information technology to the field. This thesis attempts to stimulate interest in this area by analysing the value of proprietary health and safety software to proactive health and safety management. The thesis is based upon the detailed software evaluation of seven pieces of proprietary health and safety software. It features a discussion concerning the development of information technology and health and safety management, a review of the key issues identified during the software evaluations, an analysis of the commercial market for this type of software, and a consideration of the broader issues which surround the use of this software. It also includes practical guidance for the evaluation, selection, implementation and maintenance of all health and safety management software. This includes a comprehensive software evaluation chart. The implications of the research are considered for proprietary health and safety software, the application of information technology to health and safety management, and for future research.

Introduction to performance improvement management software (PIM-DEA)

This chapter provides information on the use of Performance Improvement Management Software (PIMDEA). This advanced DEA software enables users to make the best possible analysis of the data, using the latest theoretical developments in Data Envelopment Analysis (DEA). PIM-DEA software gives full capacity to assess efficiency and productivity, set targets, identify benchmarks, and much more, allowing users to truly manage the performance of organizational units. PIM-DEA is easy to use and powerful, and it has an extensive range of the most up-to-date DEA models and which can handle large sets of data.

Sensor and software use for the glycaemic management of insulin-treated type 1 and type 2 diabetes patients

Lowering glucose levels, while avoiding hypoglycaemia, can be challenging in insulin-treated patients with diabetes. We evaluated the role of ambulatory glucose profile in optimising glycaemic control in this population. Insulin-treated patients with type 1 and type 2 diabetes were recruited into a prospective, multicentre, 100-day study and randomised to control (n = 28) or intervention (n = 59) groups. The intervention group used ambulatory glucose profile, generated by continuous glucose monitoring, to assess daily glucose levels, whereas the controls relied on capillary glucose testing. Patients were reviewed at days 30 and 45 by the health care professional to adjust insulin therapy. Comparing first and last 2 weeks of the study, ambulatory glucose profile-monitored type 2 diabetes patients (n = 28) showed increased time in euglycaemia (mean ± standard deviation) by 1.4 ± 3.5 h/day (p = 0.0427) associated with reduction in HbA1c from 77 ± 15 to 67 ± 13 mmol/mol (p = 0.0002) without increased hypoglycaemia. Type 1 diabetes patients (n = 25) showed reduction in hypoglycaemia from 1.4 ± 1.7 to 0.8 ± 0.8 h/day (p = 0.0472) associated with a marginal HbA1c decrease from 75 ± 10 to 72 ± 8 mmol/mol (p = 0.0508). Largely similar findings were observed comparing intervention and control groups at end of study. In conclusion, ambulatory glucose profile helps glycaemic management in insulin-treated diabetes patients by increasing time spent in euglycaemia and decreasing HbA1c in type 2 diabetes patients, while reducing hypoglycaemia in type 1 diabetes patients.

CloudMPL:a domain specific language for describing management policies for an autonomic cloud infrastructure

To benefit from the advantages that Cloud Computing brings to the IT industry, management policies must be implemented as a part of the operation of the Cloud. Among others, for example, the specification of policies can be used for the management of energy to reduce the cost of running the IT system or also for security policies while handling privacy issues of users. As cloud platforms are large, manual enforcement of policies is not scalable. Hence, autonomic approaches for management policies have recently received a considerable attention. These approaches allow specification of rules that are executed via rule-engines. The process of rules creation starts by the interpretation of the policies drafted by high-rank managers. Then, technical IT staff translate such policies to operational activities to implement them. Such process can start from a textual declarative description and after numerous steps terminates in a set of rules to be executed on a rule engine. To simplify the steps and to bridge the considerable gap between the declarative policies and executable rules, we propose a domain-specific language called CloudMPL. We also design a method of automated transformation of the rules captured in CloudMPL to the popular rule-engine Drools. As the policies are changed over time, code generation will reduce the time required for the implementation of the policies. In addition, using a declarative language for writing the specifications is expected to make the authoring of rules easier. We demonstrate the use of the CloudMPL language into a running example extracted from a management energy consumption case study.