What role for PhDs in the context of digital transformation?

Par :



Amandine Bugnicourt, PhD, CEO, Adoc Talent Management




Dounia Belghiti, PhD, President, PhDTalent



The digital revolution and big data have been shaking up businesses for almost a decade now. They are sources of both new opportunities and major human challenges for companies. Everyone agrees that attracting and retaining the talent to drive this in-depth transformation is one of these keys issues. Our multifaceted perspective as actors in the doctoral ecosystem leads us to believe that PhDs are assets at different levels for companies in that context.

Through the comments of various experts in the field, which we gathered in the first half of 2019, we look at the characteristics of the digital transformation and the skills required among the employees sought by companies, and in particular the contribution of PhDs, in this new environment. To this end, we draw notably on the testimonials of Etienne de Rocquigny, President of Opération Data, Joseph Pellegrino, ex-Chief Data Scientist at KERNIX and Stéphane Cordier, ex-Director of AMIES.


Digital Transformation: the conditions for success

Over the past 10 years, digital transformation has emerged as the major challenge facing businesses. Whatever their size and sector of activity, they are being led to profoundly rethink their technologies, their organizations and their value propositions. This is called the disruption of business models: data and algorithms allow to re-imagine products/services and the corresponding user experience.

Technological challenges are undoubtedly significant. Nevertheless, particularly "in mature or traditional sectors of our economy (such as agricultural logistics, moving, etc.), it is a whole new shared culture of innovation and digital that needs to be put in place if companies are to achieve digital transformation - or rather data-algorithmic transformation -", comments Etienne de Rocquigny, President of Opération Data, a national partner of Bpifrance and director of the 2015 White Paper "Modèles, Data et Algorithmes : Les nouvelles frontières du numérique". He testifies to an acceleration since 2010: "technology building blocks are already widely available, ranging from massive data acquisition to computing power, and therefore no longer constitute a barrier". For SME managers, modelling processes and phenomena will unlock much more optimal and solid decisions, while triggering development scalability. Among the pillars of successful digital transformation in businesses, Etienne de Rocquigny specifies that "one must first think about value through a hierarchy of 'inconveniences' (internal: money or time lost, risk, customer dissatisfaction and/or external: unmet needs that allow a new service or product to be marketed). This requires a fine knowledge of customers and associated business data, as well as collaboration between data experts, business experts and managers, with an agile and quick organization [...]".

KERNIX is one of those companies with a well-established presence in the digital arena. In order to take the turn towards data, the company has established a data lab back in 2014. Joseph Pellegrino, former Chief Data Scientist at Kernix Lab explained: "Our customers are very diverse, from start-ups to large corporations. They are in the banking and insurance sectors, as well as in industry, media and healthcare. What all our clients have in common is that they want to solve a problem using the data they have collected or that is available in Open Data. For example to improve the performance of existing processes (customer acquisition, inventory management...) or to create new services (recommendation engine, product eligibility prediction...). »

CIGREF, an association of major companies and public sector organizations whose mission is to achieve digital success, has been recruiting doctoral students and PhDs for many years in order to better understand the impact of digital technology on companies' businesses and organisations. Already in 2005, Cigref conducted a study on the place of PhDs in companies (CIGREF, Docteurs en informatique : quelle(s) carrière(s) en entreprise ?, Mai 2011). More recently, CIGREF has published a book that looks at the nine major challenges in implementing the necessary digital transformation of companies (CIGREF, The Enterprise 2020 in the digital age. The stakes and challenges, 2016). These include digital literacy, innovation, collaboration within ecosystems and attracting and retaining the best talent. According to CIGREF, leaders will need to surround themselves with experts to achieve this transformation. Thus, CIGREF's reading of the main challenges for Enterprise 2020 sees an opportunity in the integration into companies of PhDs from the hard sciences as well as the humanities and social sciences.

Digital transformation: first and foremost a human revolution

Obviously, these profound changes are accompanied by changes in the skills that companies need. One thinks immediately of scientific and technical skills in data sciences, machine learning, artificial intelligence. The primary contribution of PhDs in companies is thus on technical issues and algorithmic. This need has led to the emergence of new professions such as data scientists, data analysts, data engineers, etc... Note that data scientist is considered "the sexiest job of the 21st century" by Harvard Business Review (H.Davenport, Data Scientist: The Sexiest Job of the 21st Century, 2012).

It is a vibrant employment sector where demand is growing faster than supply. In its 2016 report "The Future of Jobs - Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution", the World Economic Forum forecasted a net gain of 2 million jobs in computer science, mathematics, architecture and engineering in the countries surveyed between 2015 and 2020.

So there is a talent war going on, and the Data Analytics Post (DAP) is reporting on it in a series of articles on jobs in data. Isabelle Belin looks at different professions and new career paths, with rapid turnover and alternation between salaried and freelance work.

Demand for PhD profiles is very high for these positions. Dounia Kamouni Belghiti, President of PhDTalent, which organizes the annual PhDTalent Career Fair, explains: "The field of data sciences was the most important in terms of stand reservations in 2018. Also, we have noticed within PhDTalent, growing demand for experts for short missions on issues related to the digital field. In order to meet this demand, we have had to set up a pool of PhD experts that can be quickly placed in companies, along with our partner Dataswati. PhD experts have a definite ability to formalize a complex problem and this constitutes 80% of the work of a data scientist". Amandine Bugnicourt, CEO of Adoc Talent Management, adds: "Data scientists and other machine learning experts are the leading types of position in terms of numbers for which we have supported companies in their recruitment in 2018, for sectors ranging from aeronautics to finance, from IoT to consulting, etc.". The discipline of origin of PhDs hired in data science positions is often applied mathematics or computer science, but also astrophysics, fluid mechanics, biomodeling/bioinformatics, econometrics or sociology... because in all these fields, young researchers learn how to manipulate large volumes of data (data collection, cleaning, processing) to make sense of it. »

Joseph Pellegrino explains that at the Kernix Lab: "We are looking for people who have experience in data mining, analysis and modelling and who are able to think critically about the results. For this reason, we have recruited PhDs from the experimental sciences because, thanks to the experience gained during their PhD, they have these qualities and have analyzed real data, quite similar to the data we have in our projects. During their training, they have also acquired the mathematical, statistical and programming skills that are key to working as a data scientist. Moreover, PhD experiences often involve an experimental design approach. They have thus learned to analyze problems and formulate hypotheses. This approach is very similar to the one we adopt to translate business issues into data problems. Finally, the PhDs we have recruited are very curious and they thrive on learning. We are in a sector where everything is changing very quickly and it is this thirst for learning that is a key skill in identifying the best tool or technique to solve a given problem".

France's attractiveness is high for international digital companies looking to invest in research and development for new technology building blocks. Let's mention major players such as Facebook, Huawei, Google or Fujitsu, etc. Among the key reasons given by these companies for choosing France are the quality of the talent pool in mathematics and related disciplines, the richness of the innovation ecosystem and the public policies supporting innovation.

Digital transformation: a necessary hybridization at every stage!

The variety of talents and players is and will increasingly be a guarantee of success: different disciplines and curricula, different professions, large groups, SMEs, start-ups, academics, etc. This requires multiple players to get to know each other and meet each other.

Shared digital literacy and innovation culture are among the levers most widely cited by the players surveyed, both at company and societal level. Organizations such as DAP and AMIES are publicizing these new issues and the various actors stemming from academia and business. DAP, for instance, operates a dedicated a media, while AMIES initiated a study on the socio-economic impact of mathematics in 2015. (Etude de l’impact socio-économique des Mathématiques en France - Les Mathématiques, un atout essentiel pour relever les défis de demain : connaissance, innovation, compétitivité, mai 2015).

Former AMIES director Stéphane Cordier shares examples of initiatives to get various players to collaborate. " In Orléans, I organized a week of business mathematics study (SEME) in 2014, which consists of having PhD students work in teams (generally of 6) on problems proposed by companies (4 in general, of all sizes, SMEs being the priority target). […]. In addition to the often original solutions that are proposed at the weekend, this helps to show, through concrete examples, the interest for companies to work with PhDs [...]. In March 2017, we also set up a project in Orléans called "Institut Convergence Orléans Numérique" (Orléans Digital Convergence Institute), which brings together digital players (students, researchers, companies) in order to get to know them better. [...] We learn to work together through events on the university campus or at the French Tech venue, Lab'O".

Stéphane Cordier also looks at the interdisciplinarity needed to deal with data issues in companies: "We have also set up a GSON graduate school... The goal is to get students from different backgrounds to work together and get them used to working in an interdisciplinary setting from the very beginning of their training. The aim is to train data scientists, but as explained in the article that popularized the term, in 2012, the data scientist is a rare commodity, a person who masters mathematical methods, IT skills, marketing aspects, and legal notions... in short, data scientists is a notion that should rather be understood in the "plural" sense and this is indeed the spirit of the GSON. »

In order to allow this better integration between actors and disciplines, PhDs seem to us to be "bridges" between the academic and entrepreneurial sectors. They are able to communicate the culture of research and innovation that they bring with them. This is why their inclusion in businesses in the face of the digital revolution seems to us to be a catalyst for success.

Dr Amandine Bugnicourt, Adoc Talent Management & Dr Dounia Belghiti, PhD Talent


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