To research the management of risk and cost in the cladding industry, this work has evaluated current practice and deficiencies, concentrating on the lack of integration or standardisation resulting in inaccurate cost estimates, unacceptable risks and loss of profit in cladding manufacture. The research presents an approach for integrating process- and technology-orientated improvements into a knowledge-based model to improve a cladding manufacturing SME’s performance. The research also presents a management method for the selection, integration, control and implementation of this approach. Controlling data transfer between systems produces a knowledge-based model, allowing cladding industry designers and estimators to take more accurate decisions, with the objective of reducing risk and improving company profitability. This model, with the addition of external supply chain elements, is a management framework, which can be termed an agile manufacturing system. The development of this framework has raised the following data certainty questions: • What is the measured uncertainty of that data? • How can the industry control and structure high data volumes transferred between systems to produce more accurate cost models? The answers to these questions were found by applying a structured methodology for the selection, integration and control of technology in the cladding industry, but involving the human factor. In this approach, the principle of entropy was adopted to measure data uncertainty. The structured methodology was made possible by a new categorisation into Innovative, Standard and Semi-Standard cladding projects. The research applied this structured methodology, combining qualitative and quantitative methods for validating assumptions, to a cladding industry SME case-study. The case-study investigated the validity of real cost and project data and calculated data uncertainty for specific projects, categorised as described, using a risk factor percentage predicted on entropy principles, based on historical data fed back from the SME’s ERP system. This risk factor approach was similar to that previously used in the insurance and banking industries. The risk percentage formulae used were based on assumptions extracted from qualitative and quantitative methods applied to the SME, its partner companies and industry specialists. Assumptions about the gross margins for UK metal cladding projects formed part of the risk percentage formulae. The results of this case-study found that gross margins varied from 5% in standard projects to 40% in the Innovative projects. An entropy scale was proposed as a basis for comparing risk calculation results, with the highest entropy equalling 100%, signifying the highest risk possible. It was found that risk rises in the case-study were from 23% for Standard to 93% for Innovative projects. This principle of a risk factor percentage was tested in the UK cladding manufacturer SME case-study and its value to the SME was demonstrated.

This thesis establishes a framework for understanding the role of a supplier within the context of a business ecosystem. Suppliers typically define their business in terms of capturing value by meeting the demands of direct customers. However, the framework recognises the importance of understanding how a supplier captures indirect value by meeting the demands of indirect customers. These indirect customers increasingly use a supplier’s products and services over time in combination with those of other suppliers. This type of indirect demand is difficult for the supplier to anticipate because it is asymmetric to their own definition of demand. Customers pay the costs of aligning products and services to their particular needs by expending time and effort, for example, to link disparate social technologies or to coordinate healthcare services to address their particular condition. The accelerating tempo of variation in individual needs increases the costs of aligning products and services for customers. A supplier’s ability to reduce its indirect customers’ costs of alignment represents an opportunity to capture indirect value. The hypothesis is that modelling the supplier's relationship to indirect demands improves the supplier’s ability to identify opportunities for capturing indirect value. The framework supports the construction and analysis of such models. It enables the description of the distinct forms of competitive advantage that satisfy a given variety of indirect demands, and of the agility of business platforms supporting that variety of indirect demands. Models constructed using this framework are ‘triply-articulated’ in that they articulate the relationships among three sub-models: (i) the technical behaviours generating products and services, (ii) the social entities managing their supply, and (iii) the organisation of value defined by indirect customers’ demands. The framework enables the derivation from such a model of a layered analysis of the risks to which the capture of indirect value exposes the supplier, and provides the basis for an economic valuation of the agility of the supporting platform architectures. The interdisciplinary research underlying the thesis is based on the use of tools and methods developed by the author in support of his consulting practice within large and complex organisations. The hypothesis is tested by an implementation of the modeling approach applied to suppliers within their ecosystems in three cases: (a) UK Unmanned Airborne Systems, (b) NATO Airborne Warning and Control Systems, both within their respective theatres of operation, and (c) Orthotics Services within the UK's National Health Service. These cases use this implementation of the modeling approach to analyse the value of platforms, their architectural design choices, and the risks suppliers face in their use. The thesis has implications for the forms of leadership involved in managing such platform-based strategies, and for the economic impact such strategies can have on their larger ecosystem. It informs the design of suppliers’ platforms as system-of-system infrastructures supporting collaborations within larger ecosystems. And the ‘triple-articulation’ of the modelling approach makes new demands on the mathematics of systems modeling.

Five case studies are analysed in depth and other investigations are carried out in order to answer questions concerned with: (i) the nature of the distributions which are output from risk evaluation models; (ii) the important features of the distributions which are input to risk evaluation models; (iii) the accuracy with which different methods for assessing subjective probability distributions are capable of providing the inputs to risk evaluation models; (iv) the way in which dependencies should be dealt with in risk evaluation models; (v) the extent to which it is possible to distinguish important probability assessments from unimportant probability assessments in risk evaluation models.

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