New product development resource forecasting

Forecasting resource requirements for new product development (NPD) projects is essential for both strategic and tactical planning. Sophisticated, elegant planning tools to present data and inform decision-making do exist. However, in NPD, such tools run on unreliable, estimation-based resource information derived through undefined processes. This paper establishes that existing methods do not provide transparent, consistent, timely or accurate resource planning information, highlighting the need for a new approach to resource forecasting, specifically in the field of NPD. The gap between the practical issues and available methods highlights the possibility of developing a novel design of experiments approach to create resource forecasting models

An investigation of constraint-based risk management for collaborative design

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In the context of internationally challenging economic, design has been regarded as a key factor in assisting design and manufacturing companies to survive. By using up-to-date computer-supported technology, the global design collaboration based on multidisciplinary and distributed environment is becoming a mainstream to new product development (NPD). However, during the process of collaborative design, risk is rarely mentioned. In particular, due to the complexity of design process and lack of efficient design decision-making, there have been some design collaboration failures across multiple companies. Some design projects cannot deliver the benefits as companies have expected through the collaboration. Moreover, a number of stakeholders, managers and designers expressed their disappointment at not seeing the projected savings in cost and time, which critically discredited the value of design collaboration. Many studies in academia and commercial cases have suggested that risk assessment can be applied as an effective means in the realm of design. Nevertheless, few of them conducted risk management research associated with design constraints under a collaborative environment from both theoretical and practical perspectives. In current risk practice, many risk practitioners simply report key risks to their management teams and no further analysis, which might subsequently result in confusion with excessive discussions. Consequently, to prevent the failure of design collaboration and perform a satisfactory risk assessment, it is important to perform risk management with an upstream perspective and at an operational level. An approach, called constraint-based design risk management (DRM) where a conceptual framework has been proposed on the basis of collaborative design features, risk management process and Theory of Constraints (TOC). Moreover, a DRM matrix has been developed to map, measure and mitigate collaborative design risk through evaluating the critical design constraints, and then specified design risk variables in the light of risk criteria. Design constraints are quantitative parameters that frequently affect main design processes and decisions. The combination of design constraints and risk criteria can be accessible and applicable by designers and design mangers. In addition, a Bayesian weighting method based on Bayesian theorem has been developed to measure collaborative design risk in a more efficient manner. Ultimately, a DRM tool has been created as a simulated scenario prototype, which incorporated with three case-study evaluations, to demonstrate the importance and effectiveness of using TOC and risk theory in the realm of design collaboration

The Impact of Service Complexity on New Service Development – A Contingency Approach

This dissertation explores the limitations and impact on performance of applying formalised NPD processes in service innovation. Hypotheses build on a structural framework of organisational factors, which have been linked to successful product innovation but have not been consistently supported in a service context. Evidence is presented for a moderating influence of service complexity on the relationship between factors relating to NSD process organisation and new service performance. The findings create a link between product and service innovation and demonstrate that whereas complex new services benefit from formalised development processes and structure, services with lower complexity do not

Project Risk Management : a study on the risk management approach utilized by ConocoPhillips Capital Projects

Master's thesis in Risk managementThe oil and gas industry on the Norwegian continental shelf is currently experiencing a record-breaking activity level and optimism fueled by high oil prices and major new discoveries made during 2011. The total investments have been at an all-time high the last couple of years and it will most likely continue to rise due to the amount of modification and redevelopment projects, as well as new field developments. However, with every great opportunity there are normally accompanying threats that need to be managed in order to ensure success. In such a heated climate as experienced in the oil and gas industry, there are many potential pitfalls related to infrastructure development projects, which are best exemplified by the reported cost overruns and delays affecting the Yme-redevelopment project. This report asks the question whether the current risk management system utilized by ConocoPhillips is providing value in the execution of major projects by assisting the projects in steering clear of threats with the potential to cause serious cost overruns and schedule delays. To answer the question, a common background of knowledge related to project and risk management is outlined, before introducing ConocoPhillips as a company, the worldwide project organization and the Norwegian business unit. With the context set, an overview of the project development process is given before going more into the details on the risk management process, the risk analysis modeling and the way risk management is tied into the overall development process. Based on analysis of current practices, processes and internal requirements, it becomes clear that ConocoPhillips has an extensive and rigorous system set up in order to gradually mature projects until they are ready to be implemented. Risk management plays a key part in the development process where a lot of focus and resources are used to build highly advanced integrated cost and schedule risk models generating P50 values of both project cost and completion dates that are used for project sanction. The report comes to a conditional positive conclusion, where the risk management system in light of the overall development process is deemed to create value in its contribution of providing predictability in terms of project cost and schedule compared to the project premise. However, although predictability has an inherent value for the project owners and government, the full benefits of risk management are not being realized. To unlock the full potential of risk management at ConocoPhillips, this report makes recommendations intended to shift the focus of risk management from the current reporting and verification role, to promoting the use of risk analysis in the early concept-screening phase and in the wider context of value based decision-making that must take into account more than just cost and schedule uncertainty

Embedding risk management within new product and service development of an innovation and risk management framework and supporting risk processes, for effective risk mitigation : an action research study within the Information and Communication Technology (ICT) Sector

At first glance, innovation and risk management seem like two opposing disciplines with diverse objectives. The former seeks to be flexible and encourages enhanced solutions and new ideas, while the latter can be seen as stifling such innovative thinking. Since there is a failure rate of as many as eight out of every ten products launched, it is perhaps necessary for organisations to consider applying more structured approaches to innovation, in order to better manage risks and to increase the chances of delivering improved goods and services. A risk management approach is well suited to address the challenge of failure, as it focuses not only on the negative impact of risks but also on the opportunities they present. It aligns these with the strategic objectives of the organisation to increase the chances of its success. The research objective of this study was to establish how to embed risk management within the innovation divisions of an organisation to ensure that more efficient products and services are delivered to customers. To achieve this end, action research was conducted in a large organisation operating in a high-technology environment that launches many diverse products and services and rapidly expanding service offerings to other industries. The study took four years to complete and delivered multiple interventions that successfully embedded risk management within the organisation, leading to changed behaviours and double-loop learning. Two main knowledge contributions are offered by the study. Firstly, a generic and empirically validated integrated Innovation and Risk Management Framework (IRMF) is developed and guides new product and service development by considering both best practices and risks. Secondly, a risk dashboard is designed as a design science artefact within the action research cycles, which consolidates all the knowledge that was generated during the study. This is ultimately a visual interface to support stage-gate decision making. Since the context of the study was broad, extensive and complicated, the use of mixed-method research complemented and expanded on the findings by providing another layer of support and validation. This thesis highlights the complexity of innovation and presents the need for an organising framework that will encourage innovation but is sufficiently flexible to cater for diverse needs and risks. The study delivers several other, valuable contributions regarding what, how and why incidents occur within the real-world context of new product and service development. Several generic artefacts, such as risk processes and maturity frameworks, are also developed, which can guide risk and new product and service development practitioners to deliver more efficient product and services. This study offers several novel approaches to evaluating risks and provides practical support and recommendations, addressing shortcomings of fragmented research in similar, but smaller-scale studies that have been conducted in information systems. It is the premise of this research that a much wider number of risks need to be managed as new products and services are developed, than was noted in previous studies. Effective risk management in new product and service development could lead to competitive advantage for organisations by increasing knowledge and facilitating sustainable, informed risk decision-making

Proceedings of the 18th International Conference on Engineering Design (ICED11):Book of Abstracts

The ICED series of conferences is the Design Society's "flagship" event. ICED11 took place on August 15-18, 2011, at the campus of the Danish Technical University in Lyngby/Copenhagen, Denmark. The Proceedings of the conference are published in 10 individual volumes, arranged according to topics. All volumes of the Proceedings may be purchased individually through Amazon and other on-line booksellers. For members of the Design Society, all papers are available on this website. The Programme and Abstract Book is publically available for download

Opportunity Identification for New Product Planning: Ontological Semantic Patent Classification

Intelligence tools have been developed and applied widely in many different areas in engineering, business and management. Many commercialized tools for business intelligence are available in the market. However, no practically useful tools for technology intelligence are available at this time, and very little academic research in technology intelligence methods has been conducted to date. Patent databases are the most important data source for technology intelligence tools, but patents inherently contain unstructured data. Consequently, extracting text data from patent databases, converting that data to meaningful information and generating useful knowledge from this information become complex tasks. These tasks are currently being performed very ineffectively, inefficiently and unreliably by human experts. This deficiency is particularly vexing in product planning, where awareness of market needs and technological capabilities is critical for identifying opportunities for new products and services. Total nescience of the text of patents, as well as inadequate, unreliable and untimely knowledge derived from these patents, may consequently result in missed opportunities that could lead to severe competitive disadvantage and potentially catastrophic loss of revenue. The research performed in this dissertation tries to correct the abovementioned deficiency with an approach called patent mining. The research is conducted at Finex, an iron casting company that produces traditional kitchen skillets. To \u27mine\u27 pertinent patents, experts in new product development at Finex modeled one ontology for the required product features and another for the attributes of requisite metallurgical enabling technologies from which new product opportunities for skillets are identified by applying natural language processing, information retrieval, and machine learning (classification) to the text of patents in the USPTO database. Three main scenarios are examined in my research. Regular classification (RC) relies on keywords that are extracted directly from a group of USPTO patents. Ontological classification (OC) relies on keywords that result from an ontology developed by Finex experts, which is evaluated and improved by a panel of external experts. Ontological semantic classification (OSC) uses these ontological keywords and their synonyms, which are extracted from the WordNet database. For each scenario, I evaluate the performance of three classifiers: k-Nearest Neighbor (k-NN), random forest, and Support Vector Machine (SVM). My research shows that OSC is the best scenario and SVM is the best classifier for identifying product planning opportunities, because this combination yields the highest score in metrics that are generally used to measure classification performance in machine learning (e.g., ROC-AUC and F-score). My method also significantly outperforms current practice, because I demonstrate in an experiment that neither the experts at Finex nor the panel of external experts are able to search for and judge relevant patents with any degree of effectiveness, efficiency or reliability. This dissertation provides the rudiments of a theoretical foundation for patent mining, which has yielded a machine learning method that is deployed successfully in a new product planning setting (Finex). Further development of this method could make a significant contribution to management practice by identifying opportunities for new product development that have been missed by the approaches that have been deployed to date

Multi-criteria decision-making in whole process design

PhD ThesisIn recent years, the chemical and pharmaceutical industries have faced increased development times and costs with fewer novel chemicals being discovered. This has resulted in many companies focusing on innovative research and development as they consider this key to business success. In particular, a number of leading industrial organisations have adopted the principles of Whole Process Design (WPD). WPD considers the optimisation of the entire product development process, from raw materials to end product, rather than focusing on each individual unit operation. The complexity involved in the implementation of WPD requires rationalised decision-making, often with limited or uncertain information. This thesis assesses the most widely applied methods in Multi-Criteria Decision Analysis (MCDA) in conjunction with the results of two interviews and two questionnaires that identified the industrial requirements for decision-making during WPD. From the findings of this work, a novel decision-making methodology was proposed, the outcome of which allows a decision-maker to visually interpret their decision results with associated levels of uncertainty. To validate the proposed methodology, a software framework was developed that incorporates two other decision-making approaches, the Analytical Hierarchy Process (AHP) and ELimination Et Choix Traduisant la REalité trois (ELECTRE III). The framework was then applied to a number of industrial case studies to validate the application of the proposed methodology.Engineering and Physical Sciences Research Council (EPSRC) and Chemistry Innovatio