Supply chain management and organization

The axis Supply Chain Management and Organization apprehends and manages the complexity, instability and hyper-connectivity of supply chains.

The work carried out in the Supply Chain Management and Organization (or GOL) axis stems from the issues raised by the confrontation of three relatively recent and perfectly inescapable phenomena:

  • The increasingly obvious development of the distributed and collaborative nature of supply chains, otherwise known as logistics chains.
  • The absolute necessity to know how to deal with the disruptions and hazards that now characterize the daily lives of organizations that build these chains.
  • The tremendous opportunity offered by the new information and communication technologies within these chains.

At the crossroads of these phenomena, the question of performance, its nature, level and control, arises. The issue is to find the means to understand and manage the complexity, instability and hyper-connectivity of the networks of organizations involved in supply chains.

Main objective

This axis consists in developing decision support tools capable of properly considering the risks and opportunities (uncertainties) that are now facing supply chain operators. It is based on the use of available data, now considerable, coming from the various information systems present in the supply chains (ERP, APS, connected objects, M2M, TMS, WMS, etc.). In a practical way, the work of the area focuses mainly on the activities of production, distribution, transport and planning.

Scientific obstacles

The current state of knowledge and practice in supply chain management has made it possible, under "normal" operating conditions (i.e. with limited variability and uncertainty), to guarantee the effectiveness and efficiency of the organizations concerned. However, such conditions obviously no longer exist, and current knowledge and practices need to be updated in order to cope better with the uncertainty inherent in today's economic world.

In order to do this, several scientific obstacles need to be overcome:

  1. How to benefit from the wealth offered by the various sources of data available today in supply chains? This scientific issue concerns the collection, structuring and use of heterogeneous data. In particular, it involves the formalization of an appropriate knowledge base.
  2. How to guarantee that the various sources of variability (demand, supply, internal) are taken into account in strategic, tactical or operational decision-making? This scientific challenge focuses on concrete ways to improve the agility, robustness and resilience of supply chains by developing semi-automated behavioral detection and adaptation capacities.
  3. How to evaluate the potential impacts of decisions made on the performance of supply chains? This scientific issue focuses on modeling, simulation and evaluation techniques for logistics activities that enable a quick and relevant choice among the alternative solutions considered.


The work of the axis is based on a vast and international network of academic and industrial partners.

In particular, historical industrial collaborations with the companies PIERRE FABRE and AGILEA Conseil that have contributed significantly to the development of the axis in recent years and that continue to support a significant part of the developments.

Beyond that, many other connections with industrial «end-users» and/or service providers have been established and will serve as a vector for the future work of the axis: SCALIAN, NEXT4, EFS, FAURECIA, ALLIANZ, REPORTONE...

On the academic side, the axis also organised a dense network of partnerships allowing it to establish its legitimacy and extend its competences in the field. Examples include existing collaborations with IRIT or the GSCOP at the national level and with Georgia Tech, Polytechnique Montreal, Beijing Jiaotong University, Michigan State University or Valencia University at the international level.

Moreover, it is important to recall here the consequent investment of the teams of the axis in the learned societies and conferences of reference of the field such as: GDR MACS, GDR RO, ILS, IESM, IISE, POMS, EURO, etc.

This set of interactions makes it possible to ensure a relevant positioning of the work of the axis vis-à-vis the industrial problems addressed on the one hand, and a significant added value of the scientific contributions proposed vis-à-visthe state of knowledge on the subject on the other hand.

Ultimately, this line of applied research is characterized by :

  • An effective and systematic consideration of risks and opportunities in decision-making.
  • An ability to feed decisions appropriately and dynamically with the massive data available today in supply chains (IoT, management software packages, Open Data, etc.).
  • A thorough expertise in business paradigms that break with existing tools and techniques: Demand-Driven Material Requirement Planning or Physical Internet for example.