Thursday, November 28
09h30 - 10h30
By Eric Grandry, Ministry of Mobility and Public Works, Luxembourg:
Management of digital transformation from the trenches: issues and challenges of a model-based approach in public sector
The government is currently pushing for the digital transformation of its administration. Although some guiding principles were debated in July at the Chamber of Deputies, there is no uniform approach as to how to apply them in practice.
At the Ministry of Mobility and Public Works, we have introduced one year ago an enterprise modelling initiative, and are currently designing enterprise models relying on the Prometa framework managed by the Luxembourg administration.
We intent at going beyond "contemplative models", and exploit the structured information to actually manage the digital transformation of our department of Mobility and Transport.
The way to success is however not only paved by best practices and requires a lot more than the existing standards.
In this session, I will go through our journey, discuss and illustrate these issues ranging from the selection of relevant models and modelling language, to the need of managing coherently multiple views of the enterprise, and including the integration of multiple sources, the lack of usable industry reference models, and the difficulty to acquire modelling expertise on the market. Some issues we faced are solved, while others could represent challenges both for the industry and for the research.
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Eric has been practicing enterprise architecture and engineering for more than two decades, in multiple domains (financial services, healthcare, telco, public services, transport and mobility) and organizations (international group of companies, startups, research and technology organizations and public administrations). He is passionate about modelling as an instrument to structure the intricacies of today’s socio-technical systems. His background in model-based software engineering enables him to design operational enterprise models: capturing and structuring the enterprise information is only the start of the transformation journey! Since late 2018, he is software and enterprise architect in the department of mobility and transport at the Luxembourgish Ministry of Mobility and Public Works. He is in charge of the development of the enterprise engineering initiative, as a mean of steering the digital transformation of the department.
Thursday, November 28
14h00 - 15h00
By Thomas Kallstenius, Chief Executive Officer of The Luxembourg Institute of Science and Technology (LIST):
Enterprise Modelling: mission critical for anti-fragile enterprises?
Enterprises are increasingly confronted with unexpected events; so called black swan events. The increased digitisation of society, including the application of big data, AI, internet of things, digital twins, etc, seems to actually increase the number such black swan events, rather than improve our ability to predict them.
The concept, or rather the challenge, of anti-fragility has been coined by Nassim Nicholas Taleb as a way for "systems" (such as enterprises) can / should deal with a world that is increasingly confronted with black swan events. The promise of the field of enterprise modelling is to provide a model-based approach to gain insight in the current affairs of an enterprise, as well as to reflect about, and articular, its desired affairs. Such insights might prove to be mission critical, potentially making enterprise modelling itself a mission criticial activity which is not only fail-passive and resilient i.e., a system which is able to withstand or recover quickly from difficult conditions, but also antifragile, i.e., a property of a system that increase in capability to thrive as a result of stressors or failures.
The aim of this interactive keynote is to, together with the audience, discuss, and explore, the question if (and possibly how) enterprise modelling can indeed aid enterprises in being / becoming anti-fragile. In doing so, we also need to remain critical about the possible pittfalls. Enterprise modelling can also lead to a "blindness" to possible future events; especially the ones of the yet undiscovered red and blue swan varieties.
| ||Thomas Kallstenius has been Chief Executive Officer at the Luxembourg Institute of Science and Technology since 1 February 2019. Prior to this, he was program director for the Belgian research institute imec’s research & innovation program related to security and privacy. He was also in charge of imec’s strategic orientation of distributed artificial intelligence and high-performance computing. This strategy was preceded by imec’s vertical market strategy, which Thomas was also in charge of. Before joining imec, Thomas was vice president for research and innovation at iMinds, the research institute that merged with imec in 2016. His responsibilities in this role included iMinds’ strategic and applied research programs with academic and industrial partners. Thomas has more than 15 years of experience with industrial research and strategic marketing. He worked as a director at Bell Labs on video communication related topics, and prior to this, he was strategic marketing director at Alcatel-Lucent, responsible for its fixed access portfolio. He has also been a researcher on broadband access within Ericsson Research, and on reliability of semiconductor components within Ericsson Microelectronics. Thomas holds a Masters Degree in Engineering Physics from the Royal Institute of Technology (Stockholm, Sweden), a PhD in semiconductor materials science from Uppsala University (Uppsala, Sweden) and an MBA from Vlerick Management School (Leuven, Belgium). |
Friday, November 29
09h30 - 10h30
Panel session - AI meets Enterprise Modelling
Panellists: Monique Snoeck, KU Leuven, Belgium; Janis Stirna, Stockholm University, Sweden; Hans Weigand, Tilburg University, The Netherlands
Chair: Henderik A. Proper
We are moving towards an Artificial Intelligence (AI) intensive society, in which AI plays an increasingly prominent role in many, if not all, facets of social and economic life.
In our homes, AI enabled thermostats enable us to optimise our energy consumption. When on the road, AI powered apps on our mobile phones help us find the best way to reach our destination. When working in a multi-lingual environment, AI techniques help us translate documents. In healthcare, AI based solutions aid doctors in producing better diagnoses.
As more and more tasks are entrusted to AI based actors, a rich variety of AI techniques is being deployed, ranging from machine learning, data sciences and data analytics, to the more traditional logic and rule-based approaches.
The topic of AI brings about many opportunities and challenges to enterprises in general, and thus, enterprise modelling in particular.
The aim of this panel discussion is to explore the challenges which the an AI intensive society brings to the field of enterprise modelling, as well as opportunities that AI brings to enterprise modelling. Are new modelling concepts needed to cater for AI-based actors? How to capture AI related regulative and / or ethical considerations in enterprise models?
Should enterprise modelling encompass models / concepts for explainable AI? Can AI be used to automate enterprise modelling activities? Can enterprise models be used as inputs to AI based solutions?