François Marmier

A risk oriented model to assess strategic decisions in new product development projects

The project management team has to respect contractual commitments, in terms of deadlines and budgets, that are often two antagonistic objectives. At the same time, the market becomes more and more demanding as far as costs and delays are concerned while expecting a high quality level. Then, the project management team has to continuously consider novelty and a risk management strategy in order to determine the best balance between benefits and risks. Based on the principles of a synchronized process between risk management and project management, and on the concepts of risk scenario, we propose a decision-making tool to help the project manager choose the best way to improve project success rate while controlling the level of risks. As a finding, the project manager would be able to evaluate and compare different novelties or development strategies taking into account their repercussions on potential risks and risk treatment strategies. Finally, a case study in the aerospace industry and specifically on satellite integration and tests is developed to validate this approach. We model risk scenario and influence on project planning.We compare different innovations or development strategies according to potential risks and risk treatment strategies.We calculate global risk level for each project development strategy.

Scheduling rules to minimize total tardiness in a parallel machine problem with setup and calendar constraints

Quality control lead times are one of most significant causes of loss of time in the pharmaceutical and cosmetics industries. This is partly due to the organization of laboratories that feature parallel multipurpose machines for chromatographic analyses. The testing process requires long setup times and operators are needed to launch the process. The various controls are non-preemptive and are characterized by a release date, a due date and available routings. These quality processes lead to significant delays, and we therefore evaluate the total tardiness criterion. Previous heuristics were defined for the total tardiness criterion, parallel machines, and setup such as apparent tardiness cost (ATC) and ATC with setups (ATCS). We propose new rules and a simulated annealing procedure in order to minimize total tardiness.

Strategic decision-making in NPD projects according to risk: Application to satellites design projects

Abstract In this paper we present a method for making strategic decisions in New Product Development (NPD) projects based on risks. In NPD the complexity of the process depends both on the nature of the design problem and the difficulties associated with managing the project (activities, risks). To design a complex product several different teams, having different competencies, work on the project. Not one among them controls the entire process. The interactions between product subsystems in NPD often lead to technological arbitration between alternative solutions. In selecting one solution over another, the risk management concerns and the overall project plan are affected. Therefore, the objective is to give the project manager the means to evaluate the effects of strategic decisions, including those that influence the selection of technological solutions for the project plan as well as those for risk treatment strategies. We propose an integrated process that comprises design, project management and risk management. It takes into consideration the design activities and risk activities to generate a design project planning where design activities and risk activities are folded into the overall design project plan. During the process of project design two different types of strategies are required: one relates to the problem design, the other to the assessment of project risks. Each strategy leads to different possible scenarios. We present a decision tree that shows the decision steps and possible project scenarios. A generic decision support system is proposed. We demonstrate its applicability by applying it to a satellite design project.

Structuring and integrating human knowledge in demand forecasting: a judgemental adjustment approach

Demand forecasting consists of using data of the past demand to obtain an approximation of the future demand. Mathematical approaches can lead to reliable forecasts in deterministic context through extrapolating regular patterns in time-series. However, unpredictable events that do not appear in the historical data can make the forecasts obsolete. Since forecasters have a partial knowledge of the context and of the future events (such as strikes, promotions) with some probability, the idea presented in this work is on structuring the implicit and the explicit knowledge in order to easily and fully integrate it in final forecasts. This article presents a judgemental-based approach in forecasting where mathematical forecasts are considered as a basis and the structured knowledge of the experts is provided to adjust the initial forecasts. This is achieved using the identification and classification of four factors characterising events that could not be considered in the initial forecasts. Validation of the approach is provided with two case studies developed with forecasters from a plastic bag manufacturer and a distributor acting in the food market. The results show that structuring the expert knowledge through the identification of factor-related events leads to high improvements of forecast accuracy.

A model driven engineering approach for business continuity management in e-Health systems

Nowadays e-Health systems recognize the benefits of new Information and Communication Technology (ICT) in the delivery of healthcare services. While these modern technologies have enhanced practices in the healthcare sector, the potential of failures to interrupt a process is still important. This risk of system downtime may induce significant impacts on patient safety. Thus, ensuring business resilience has proven to be increasingly challenging as the healthcare field employs more ICT applications and all signs for the future point to even more reliance on digital data. In this context, we propose an approach based on Business Continuity Management (BCM) to ensure the ability to operate in spite of unforeseen events and to quickly recover from any type of business interruption. The basic purpose of this paper is to define a formal description of a Business Continuity Plan (BCP), following an approach grounded in Model-Driven Engineering (MDE).

Human and organisational factors in planning and control

Reference EPFL-ARTICLE-182028doi:10.1080/09537280903453786View record in Web of Science Record created on 2012-11-01, modified on 2016-08-09

Improvement of the planning reliability by the integration of human skills in project risk management

To make the project more profitable, the actors that are the more adequate to perform the tasks have to be selected and decisions about how to deal with risks during the project have to be made. In this paper, the resource management is integrated into a project risk management approach. A decision support system is proposed to help the project manager decide which risk treatment strategy to develop and which assignments to plan to be the more efficient as well as less sensitive to the risks. Finally, a case study based on a weather forecasting station project is developed to validate this approach.

A new structured adjustment approach for demand forecasting

Demand forecasting consists of using data of the past demand to obtain an approximation of the future demand. Mathematical approaches can lead to reliable forecasts in deterministic context, extrapolating regular patterns in series. However unpredictable events that do not appear in the historical data can make the forecasts obsolete. As forecasters have a partial knowledge of the context and probable future events (such as strikes, promotions), this work investigates structuring the implicit as well as the explicit knowledge in order to be easily and fully integrated into final forecasts. This paper presents a judgmental-based approach in forecasting where mathematical forecasts are considered as a basis and the structured knowledge of the experts is provided to adjust the initial forecasts. This is achieved using the identification of four factors characterizing specific events that could not have been considered in the initial forecasts. The validation of this approach has been conducted on 2 industrial case studies, a plastic bag manufacturer and a distributor on the food market. The results show that structuring the expert knowledge could lead not only to high improvements of forecasts accuracy but also to a better initial data cleaning and outlier identifications.

Project risk management conceptual model

The realization of most complex infrastructures requires project formalism. The main observation in the project management field is the cost and delay overrun. This situation is due to the difficulty to predict risks that can occur during realization phase. There is a need of a model to formalize risks and projects attributes for a relevant analyze. A conceptual framework is the first step for this purpose. The objective of this paper is then to propose a conceptual model for project management process in risk situation. Our proposal is a base that can be use to assess the project risk indicator, the analysis of its variants, the determination of risky critical path etc.

Software Cost and Duration Estimation Based on Distributed Project Data: A General Framework

Effort estimation is one of the most challenging tasks in the process of software project management. Enhancing the accuracy of effort estimation remains a serious problem for software professionals. Accurate estimation is difficult to achieve. The main difficulty is to collect distributed knowledge as data and information are often dispersed over different services, departments or organisations. Other main difficulty is to propose a model representative enough of this multi-partner behaviour. The objective of this study is to propose a general framework of the estimation starting from the analysis of the available projects database, the choice and establishment of estimation model, up to the use of this model to make estimation for new projects. In this paper, a comparative study between regression models and neural network models is performed. The proposed study is applied on a dataset of an automotive company.