Computational & Data Science Scientific Director, R&D, Air Liquide
Athanasios currently holds the position of “Computational & Data Science R&D Scientific Director”. He is a graduate of National Technical University of Athens and holds a PhD from University of Liège. He joined Air Liquide in 1995. Within the Group, he found several ways to express his passion for simulation and applied math in R&D and Operations. In particular, he is a pioneer in the development of multi-variable predictive control systems and innovative real-time optimization systems. He presented the first roadmap of big data for Air Liquide and set up the first teams of data scientists, in 3 countries, within R&D’s “Computational & Data Science Global Lab”. He introduced artificial intelligence, through proofs of concept and alliances with innovative companies in the field. He recently launched the “data and decision sciences lab” (d2-lab) initiative in Air Liquide, a network of experts and practitioners, to reach scientific excellence in these areas.
We sat down with Athanasios Kontopoulos after he delivered his plenary session lecture at the Industry of Things World congress which took place between the 23-25 th of September.
Athanasios Kontopoulos: As fas as IoT and connectivity are concerned: Machine Learning and cloud computing has made some real progress in the last years. There’s more awareness also around how the data coming from IoT can be activated through analytics and improving decision making.
– Increase in awareness of the potential of analytics with IoT
– cloud computing: many companies like Air Liquide now adopt a ‘cloud first’ strategy with a strong data policy and governance. Previously, all this data was in silos & servers, which meant, even with IoT, it was hard to “activate” the dat. Now, we can.
– Machine Learning algorithms have made a lot of progress, especially with trends like edge computing
So many conditions have now come together to scale up IoT and ensure that our data scientists have access to this data.
Athanasios Kontopoulos: Real interoperability is needed to have a step change. There are initiatives such as the Open Process Automation Forum , to name just one. Now, Industry is not just about grassroot assets to be built but a lot of legacy. And, there, things are more complicated when we talk connectivity. Costs can go high and the business cases need to be clear. Think what you really need to be connected. Value is the key.
Athanasios Kontopoulos: Awareness increases. As well as penetration of digital in everyday life. Some businesses, such as telecoms and banking, have changed in a fast pace. Industry is a bit longer to come, as we mentioned earlier, because of legacy. But, for instance, customer-centric attitude becomes a must. And the digital is key in this direction.
Athanasios Kontopoulos: A lot. Our strategy is based on three axes. Assets: here we find “traditional” topics such as logistics, predictive maintenance, robotics. Then “Customers”. Customer-centricity and customer personalization can really be enabled by AI, cross-sell is just an example to mention. And, finally, “Ecosystems”. E.g. we can using text mining to fastly process information related to internal and external ecosystem.
Athanasios Kontopoulos: You need to get your strategy right. Set the business objectives. Engage people. Have first successes and communicate.
Athanasios Kontopoulos: Difficult to pick just one from all! Customer-centricity enabled by AI is something I strongly support.
Athanasios Kontopoulos: I’d say make sure to get the “why” right first. What is the business case and the benefit you hope to take out of it. Then make sure you engage the stakeholders. That they start the quest being convinced. AI is fine but PEOPLE are in the center.
Athanasios Kontopoulos: Once again: make sure to get the business case correctly. 1) Plan it 2) make it happen and 3) communicate it. The seed will grow.
Athanasios Kontopoulos: I think when they want to “boil the ocean”, make it exceptionally big and completely general. You need to balance ambition with pragmatic and focused approach.
1. Business models and market strategy
2. Human vs machine roles and skills
3. Social corporate responsibility in era where many jobs are being eaten by software/technology
1. Business models need to evolve because there’s significant potential to integrate digital and data-driven services in offerings to customers.
2. Human capital is a core asset of any organization. It is important to upskill our employees constantly to keep pace with Digitalization. For instance, we have a thriving community of 200+ citizen data scientists across Air Liquide, who participate in data competitions, meetings etc.
3. Surely, AI can automate many tasks. In Industry, reality is often the one of “augmented AI” where the combination of human knowledge and AI can give great results.
Athanasios Kontopoulos: I’ve been following the event since the first year and never missed one. It gives great insights and an excellent view to the ecosystem!