esearch activities in the field of business analytics (BA) and supply chain management (SCM) are focused on analyzing data collected from a variety of sources and decision making informed by data analysis and supported by optimization techniques, with the aim of enabling enterprises and organizations to improve their service levels and operational efficiency, in particular in the context of supply chain and logistics management.


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The main areas of expertise are therefore analytical methods of uncovering business insights and predicting future situations with use of data (statistical and data mining methods: nonparametric regression models, censored data analysis, discrete choice models, machine learning, natural language processing, pattern recognition, simulation and digital twins…), and also of recommending decisions (operations research methods: mathematical modelling, stochastic programming, combinatorial optimization, exact and heuristic solution approaches, discrete mathematics,…). 

SCM is a major field of application of such analytical methods, and these areas are frequently associated in the so-called “industrial engineering” departments of many foreign universities. 

Research in BA & SCM includes: Design and coordination of supply chains and intermodal transport networks; production, distribution, and transport planning; vehicle routing and loading; pricing and revenue management in transport; reduction of energy consumption and pollutant emissions; health care operations management; portfolio optimization and stock market forecasting; clustering and question-answering systems; methodological developments in the fields of expertise.

At HEC Liège, the Business Engineering curriculum is strongly associated to our research field through core courses, mainly in analytics, and the two fields of specialization “SCM and BA” and “Digital Business”. The Master in Management Science also benefits of the BA & SCM research field through some core courses in quantitative methods and the specialization in “Global Supply Chain Management”. 
We aim at transferring our competencies and internationally recognized research and expertise to our local community and our international partners. The researchers in BA & SCM perform fundamental and applied research. They have numerous collaborations with the public and private sectors. It’s at the same time a need, for data and knowledge, and a goal. In the same spirit, we favor partnerships with companies through chairs and PhD funding; e.g. based on the Digital Lab platform.

Research Team

Research activities in the fields of BA & SCM are mostly conducted by the research team QuantOM (Quantitative methods and Operations Management). QuantOM is the association of several researchers under a common label to stimulate and promote research conducted at HEC Liège (or more broadly, within the ULg) in the fields of quantitative methods and of their applications in SCM and other areas of management and economics.


Business Analytics & Supply Chain Management

Article (Scientific journals)
Fare inspection patrolling under in-station selective inspection policy
Escalona, Pablo; Brotcorne, Luce; Fortz, Bernard et al.
In pressIn Annals of Operations Research
Article (Scientific journals)
Energy-efficient production control of a make-to-stock system with buffer- and time-based policies
Tan, Barış; Karabağ, Oktay; Khayyati, Siamak
In pressIn International Journal of Production Research, p. 1-19
Article (Scientific journals)
Statistical matching using kernel canonical correlation analysis and super-organizing map
Annoye, Hugues; Beretta, Alessandro ; Heuchenne, Cédric
2024In Expert Systems with Applications, 246, p. 123134
Article (Scientific journals)
Solving unconstrained binary polynomial programs with limited reach: Application to low autocorrelation binary sequences
Clausen, Jens Vinther; Crama, Yves ; Lusby, Richard et al.
2024In Computers and Operations Research, 165, p. 106586
Article (Scientific journals)
Min–max optimization of node‐targeted attacks in service networks
Fortz, Bernard ; Mycek, Mariusz; Pióro, Michał et al.
2024In Networks, 83 (2), p. 256-288

Members of the field

updated on 1/19/24

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