Decision support with ill-known criteria in the collaborative supply chain context

International audienceIn the field of Supply Chain Risk Management, the attitude of managers toward risk affect the tactical decision-making process in collaborative supply chains under an uncertain environment, concerning especially capacity levels, lot-sizing rules, purchasing strategies, production scheduling,…, etc. The issue can be formulated as a sequential decision problem under uncertainty where the customer decisions affect the decisions made by the supplier. In this paper we deal with two kinds of uncertainties. The first one is the uncertainty on the indicators of performance (which are not comparable) used by the decision maker to choose a solution (for example: service quality or inventory cost). Hence, we propose an approach based on subjective probability to evaluate the probability that a decision is optimal for the first actor and the probability that it is optimal for both. From these two evaluations, we propose a ranking function to help the first actor to take into account the second one when selecting a decision. The second kind of uncertainty pertains to the demand. A classical criterion under total uncertainty is Hurwicz criterion where a weight expresses a degree of pessimism. Nevertheless, the degree of pessimism is itself ill-known. Thus, it becomes difficult to take into account the behavior of the actors. Hence, we propose an approach based on possibility theory and the so-called pignistic transform, which computes a subjective probability distribution over the criteria. Then, we apply the method used for uncertain criterion. This approach is illustrated through an example and an industrial case study

Information technology as boundary object for transformational learning

Collaborative work is considered as a way to improve productivity and value generation in construction. However, recent research demonstrates that socio-cognitive factors related to fragmentation of specialized knowledge may hinder team performance. New methods based on theories of practice are emerging in Computer Supported Collaborative Work and organisational learning to break these knowledge boundaries, facilitating knowledge sharing and the generation of new knowledge through transformational learning. According to these theories, objects used in professional practice play a key role in mediating interactions. Rules and methods related to these practices are also embedded in these objects. Therefore changing collaborative patterns demand reconfiguring objects that are at the boundary between specialized practices, namely boundary objects. This research is unique in presenting an IT strategy in which technology is used as a boundary object to facilitate transformational learning in collaborative design work

Towards the realisation of an integratated decision support environment for organisational decision making

Traditional decision support systems are based on the paradigm of a single decision maker working at a stand‐alone computer or terminal who has a specific decision to make with a specific goal in mind. Organizational decision support systems aim to support decision makers at all levels of an organization (from executive, middle management managers to operators), who have a variety of decisions to make, with different priorities, often in a distributed and dynamic environment. Such systems need to be designed and developed with extra functionality to meet the challenges such as collaborative working. This paper proposes an Integrated Decision Support Environment (IDSE) for organizational decision making. The IDSE distinguishes itself from traditional decision support systems in that it can flexibly configure and re‐configure its functions to support various decision applications. IDSE is an open software platform which allows its users to define their own decision processes and choose their own exiting decision tools to be integrated into the platform. The IDSE is designed and developed based on distributed client/server networking, with a multi‐tier integration framework for consistent information exchange and sharing, seamless process co‐ordination and synchronisation, and quick access to packaged and legacy systems. The prototype of the IDSE demonstrates good performance in agile response to fast changing decision situations

Management of the risk of backorders in a MTO-ATO /MTS context under imperfect requirements

International audienceProduction systems are often classified according to the way production is released, e.g. make-to-stock (MTS), make-to-order (MTO), assembly-to-order (ATO) or engineer-to-order (ETO). The choice of a type of production depends on the decoupling point between customer and supplier. In some supply chains, like in the aeronautical sector, a customer may work according to a MTO process (since his product is highly specific) while his supplier works with a MTS process (since he delivers variants of standards components). This situation sets specific problems that are seldom considered in the literature, especially when collaboration between actors is required for an efficient management of the supply chain, which is the case when uncertainties are present. In this paper, we propose a method based on fuzzy modelling allowing a customer to choose a plan taking into account the uncertainty on his requirements when he works in MTO-ATO while his supplier is in MTS

A decision support tool for procurement planning process under uncertainty

This communication presents a method to support the customer in the choice of a procurement plan when the gross requirements are ill-known, in a context of collaboration with the supplier. A general model of imperfect parameter representation is suggested, imperfection gathering uncertainty (through various scenarios) and imprecision (through quantities and dates expressed by possibility distribution). A method to compute the possible quantities required to satisfy the gross requirements under the supplier delivering constraints is proposed. From this value, a set of possible supplied quantities is computed to support the decision making of the customer. The decision maker then evaluates the procurement plan with the possible evolution of the inventory

Modelling of ill-known requirements and integration in production planning

Making decisions on the base of uncertain forecasts is one of the key challenges for efficient Supply Chain Management. This article suggests the use of the theory of possibility for building a procurement plan on the base of ill-known requirements. These requirements, expressed in quantities by date, may come from various sources: forecasts or orders for instance. The possible types of imperfection pervading requirement are analysed and a unified representation model is suggested. A method is then described for calculating a plausible demand by period without loss of information; it is illustrated on an example in the last section

Indian Organised Apparel Retail Sector and DSS (Decision Support Systems)

Indian apparel retail sector poses interesting challenges to a manager as it is evolving and closely linked to fashions. Appealing mainly to youth, the sector has typical information requirements to manage its operations. DSS (Decision Support Systems) provide timely and accurate information & it can be viewed as an integrated entity providing management with the tools and information to assist their decision making. The study exploratory in nature, adopts a case study approach to understand practices of organized retailers in apparel sector regarding applications of various DSS tools. Conceptual overview of DSS is undertaken by reviewing the literature. The study describes practices and usage of DSS in operational decisions in apparel sector and managerial issues in design and implementation of DSS. A multi brand local chain and multi brand national chain of apparel was chosen for the study. Varied tools were found to be used by them. It was also found that for sales forecasting and visual merchandising decisions, prior experience rather than any DSS tool was used. The benefits realized were; “help as diagnostic tool”, “accuracy of records and in billing”, “smooth operations”. The implementation issues highlighted by the store managers were; more initial teething problems rather than resistance on the part of employees of the store, need for investment of time & money in training, due to rapid technological advancements, time to time updation in DSS tools is required . Majority of operational decisions like inventory management, CRM, campaign management were handled by ERP (Enterprise Resource Planning) or POS (Point of Sale). Prioritization as well as quantification of benefits was not attempted. The issues of coordination, integration with other systems in case of ERP usage, training were highlighted. Future outlook of DSS seems bright as apparel retailers are keen to invest in technology.