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Bidding Process Improvment: Development of specific methodology to formalize bids and project risks

Started on : 01/11/2016
Research Axis : 
  • Axis 1 : ORKID
Supervision : 

This subject aims at defining a methodology to formalize and exploit knowledge and experience in decision support during the bidding process. The originality of this work is related mainly to the constitution of generic models for bids from the expertise and bidding skills of four industrial partners and the definition of a methodology associated with this capitalization.

Two main issues are addressed:

  • the definition of a generic model to better answer bids, model based on knowledge and experience dedicated to designed systems, reated projects and risks involved in case of success. These works are based, firstly, on the first proposals of an ongoing thesis (Abdourahim Sylla, 2015-2018) on the definition of new indicators, such as confidence and maturity of offers and on secondly on the compendium on best pratice of the industrial pertaners on the OPERA project.
  • the development of a methodology for capitalizing knowledge and experience, constitution of generic models and operations within companies. These works are mainly based on the actions of experience feedback conducted with four industrial partner.

Projects related to the thesis


    Started on : 01/11/2016 Ended on : 30/04/2020


    The current global economy generates heightened competition in all economic activity sectors. This competition associated with web technologies implies that the customer/supplier relationship is less direct and steady, and instead he customers easily hold multiple consultations with different suppliers and choose usually the well-suited one through a competitive bidding process. Consequently the number of tenders increases and generates a need for robust and systematic bidding process. In addition, to better answer to the customers’ requirements, bids must be clearly personalized on their bill-of-material (which are the components), production (how to produce and assemble them), performance, price and delivery time. If an offer is not established through a design or detailed customization work, it comprises most often a significant amount of uncertainty and risk, that have to be mastered.


    Some decades ago, the solution to cope with such uncertainties and risks, was to greatly oversize the estimated cost and delivery time. The offer was primarily based on a human expertise which allowed people to extrapolated past answers by the use of experiences, skills and first knowledge-based systems.

    This actual competition cuts delivery times, reduces costs and drives the performance of products upwards. Therefore, the old strategy of oversizing costs and delivery times is no longer possible to stay competitive. Without reducing uncertainty and risks, costs and deadlines proposed to the customer in a particular offer cannot be systematically held. Failure to comply with cost and deadlines targets causes losses and endangers the existence of firm. To face this situation, the offer definition requires further studies, Human cognitive process intensifies and the use of decision-support systems has become more common and is now a necessity.

    OPERA Proposals

    In order to have more accurate offers, with less uncertainty and risks, the OPERA project aims at developing "Software tools and processes for Bids" . OPERA relies on the first hand, the maturity and confidence in the components of the offer and the second hand, on the risks taken during its delivery process. The goal of the OPERA project is first, to reduce the uncertainty and inaccuracy in the offers and its resulting losses, and second to correlate it with the products maturity and with process risks. This maturity and risks knowledge undoubtedly improves the confidence of the person in charge of the bids and decreases the level of stress in her/his decision.

    A PhD thesis (description of the subject: FR, EN) is opened in connection with this project.

Publications related to the thesis

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