Business Talk - Interview of Alexandre Carbonnel
Written by Mattéo Guillemard
In September 19th, TSE hosted a Business Talk featuring Alexandre Carbonnel, a director at AlixPartners, on the topic: “Working as a competition economist at AlixPartners: Cross-collaboration with data scientists, forensic accountants and sectoral experts.” AlixPartners is a global consulting firm in the niche market of performance improvement and company restructuring across various sectors. Due to the growing quantity and diversity of data in the cases handled, AlixPartners increasingly relies on heterogeneous profiles to meet these new requirements. After presenting AlixPartners, Alexandre Carbonnel provided specific examples of how business consultants collaborate with data scientists, sector experts and forensic accountants. For those who missed the event, or would simply like a refresher, here are some insights Alexandre Carbonnel shared with us during the interview.
Could you please outline your academic and professional background, and what motivates you to work in consulting?
I am a competition economist who started his career at the UK’s competition authority (the Office of Fair Trading, now the Competition and Markets Authority) and worked there for around a year and a half. I then joined an economic consultancy in 2013 in Brussels and subsequently relocated to France. I have since been working in economic consulting on a range of competition, litigation and arbitration cases.
Recently, I have joined AlixPartners, which is a consultancy that has been growing rapidly in the areas of competition and litigation in Europe. The firm was willing to expand in France and this was an exciting opportunity at this stage of my career. I was in particular attracted by the collaborative environment and the opportunities that the firm’s presence in other fields such as restructuring and performance improvement could offer.
Economic consulting is a challenging and fast-paced sector, which I enjoy a lot because it is intellectually rewarding, not least because we get to work on a range of cases in different sectors. It is also quickly evolving both because the legal environment is moving and because the tools we use are also changing (for instance, with the development of AI). Therefore, I find it to be an exciting sector, even though one must learn how to cope with the pressure and intensity that is inherent to consulting.
What inspired you to pursue a PhD, and how relevant do you think this experience is to a career in consulting? What additional advantages did you discover from having a PhD once you entered the professional world?
A PhD is not strictly necessary in Europe to go up the ladder in economic consulting, contrary to the US where non-PhD economists are often confronted to a glass ceiling. However, it is certainly a highly valuable asset on a CV. I think the main benefit of a PhD is that teaches us how to think about problems (in our case, competition and litigation), be creative and structure our thoughts. Another valuable is the ability to draft documents, although the key difference between consulting and academia is that in consulting we tend to produce documents for nonspecialist audiences. Therefore, there is still a learning process, but it is typically a shorter one than when someone joins straight out of a Master’s degree.
One benefit that I only noticed after starting my career is that a PhD gives credibility to the economic expert role in front of courts, generally in the context of damages quantification. In this case, having a PhD may help even though, unlike in the US, there are many testifying experts with no PhD in Europe.
Artificial Intelligence and data science are now common terms. When did you realize the importance of using these new tools and skills, and how has this changed the way you work in the industry as an economist? How long did this transition take?
There has been a quick evolution over the last 6 or 7 years in terms of the tools that we use. When I started my career, many consultants used to work entirely on Excel and Stata used to be state-of-the-art. We then progressively switched to R and Python, which allowed us to work much more efficiently when dealing with large datasets. We now have large language models and AI tools that have opened a range of ways to work with information and data. The transition is still taking place, and I expect that there will quickly be new developments, but this will likely change how we work as competition economists.
The key advantage of these new tools is that they allow us to analyze information and data more easily, which has a direct positive impact on the cost of all the background work that we do. This is turn means that we can focus our efforts on the more interesting part of our work, which is thinking about the empirical analyses to run.
This trend also implies that economists increasingly work with data scientists on competition cases, because of the complexity of the new tools. I have personally found this collaboration fruitful because data scientists bring their expertise to cases, and we are highly complementary.
Have these new tools led to increased efficiency or provided truly new insights?
Can you provide a concrete example of a project where AI or data science uncovered significant advance ments about a market or a competitor?
As I highlight above, I believe that data science and AI are truly changing economic consulting for the better, by helping us focus on the conceptual issues in competition and litigation cases, for which our role as economists remains critical. One example of a situation where AI is useful is when we deal with a large volume of documents that are structured differently, and we must extract information for our analyses. For instance, we may be interested in understanding how prices are determined in the context of a supplier-customer relationship, whether there is some indexation, and AI helps us understand this more easily.
What do you think the future holds for consulting in competition economics?
I think there will be greater collaboration with other experts (data scientists, forensic accountants, industry experts on cases, as the complexity and sophistication of our work increases. In particular, as the volume of data we work with increases, the ability to process it efficiently, extract insights and produce high quality economic and statistical analyses will be a key differentiating factor between consultancies. This is the approach that we are following at AlixPartners, where we find that cross collaboration between teams has proven beneficial in large and complex matters.
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