Jamal Ouenniche

Dr Jamal Ouenniche is a Professor and Chair in Business Analytics at the University of Edinburgh Business School (UK), Member of the Senate, Member of the Business School Executive Board, Head of the Management Science and Business Economics group, and Director of the MSc in Business Analytics.

Education He holds a BSc in Mathematics and MSc in Operational Research from the University of Montreal (Canada), and a PhD in Operations Management from Laval University (Quebec, Canada). 

His research portfolio encompasses a broad range of applications and a variety of research methodologies in descriptive, predictive and prescriptive analytics, and tackles important managerial issues in energy, manufacturing, transport, banking, and public sector policy. 

Some of his research is concerned with methodological contributions to the fields of optimization, artificial intelligence, data envelopment analysis, risk modelling and analysis, and forecasting. His teaching experience is international and covers a wide range of areas such as Operations, Logistics, and Supply Chain Management; Operational Research, Management Science and Business Analytics; Business Statistics and Methods of Research; and Business Forecasting.

Dr. Jamal Ouenniche appeared in a citiesabc interview recently, where he said the following: 

Data analytics. “Analytics has always been there, especially as Data itself has no value unless someone analyzes it. That is why so important to invest in analytics. From an education perspective, universities haven’t done enough to add studies related to data and predictive analytics to their offerings. Furthermore, as the demand is growing in the private sector, big and small.” 

Data analytics applied to Financial Industry. “The decision-making process in the financial industry is crucial. That is why using data to make those decisions is so important. The major issue right now for banks is how to deal with this crisis. And we need to look at data, understand it and use it to make the right decisions to avoid closures, bankruptcies, etc.” · 

Rankings and Data Analytics. “Rankings provide valuable information for businesses, people, etc. When you know where you are in the ranking, you know your value and as such, you can improve in the future. Rankings need to be accurate. For example in cities. If you use data analytics to get insights from crime and there is a global ranking for crimes in cities, that can be important for decision-makers and for the population. They are a benchmark from where to improve.”