As a full professor of information systems at KU Leuven, Jan is researching on business intelligence, analytics, business rules, processes & decisions, and information management. He has published more than 200 full papers in reviewed top international journals and high-quality conference proceedings and his Google Scholar page shows an h-index of 59. He is or was (co-)chairholder of five research chairs with industry. He received an IBM Faculty Award in 2011 on smart decisions, and the Belgian Francqui Chair 2009 at FUNDP. He is co-founder and president-elect of the Benelux Association for Information Systems (BENAIS).

Jan has built extensive expertise in the areas of knowledge-based systems, decision modeling and analytics, with applications in healthcare (careflow processes), audit & risk management (rule-based conformance checking), process mining (based on negative events), declarative process modeling & mining, decision modeling & quality (verification and validation). He is a regular speaker at international workshops and conferences (BPM, BBC, CAiSE, RuleML+RR, DecisionCamp, ICPM, CoopIS, BIS, ICEIS).

He is actively involved in the Decision Modeling & Notation standard (DMN) at OMG, integrating and distinguishing business decisions and business processes. He is also member of the IEEE task force on process mining, and co-author of the Business Process Mining Manifesto.

Jan is a member of Leuven.AI – KU Leuven Institute for Artificial Intelligence. He was head of the research group on information systems engineering, chair of the Department of Decision Sciences and Information Management and programme coordinator of the Master of business and information systems engineering.

Why DMN?

Decisions are everywhere. Modelling decisions is important in business processes, information systems, service applications, AI and analytics, and so many other areas. So modelling decisions in the correct way and by the business is imperative. Decision models, with their origin in decision tables, contribute significantly to the description of the requirements and the logic of operational business decisions. The Decision Model and Notation (DMN) standard allows modelling and automating these decisions, combining sound theory, best practices and a simple, standardized notation.

Decision knowledge, especially in knowledge-intensive processes, should not be hidden in process flows or programming logic, because hardcoding (decision) rules in processes and programs leads to complex and inflexible systems. Decision management therefore is as important as data management or process management

Using decision models and tables is a natural expression mechanism for businesses to describe, automate and maintain the business decisions. DMN, however, is not limited to making the decision, but it also acts as a knowledge base to enable reasoning and automatically create intelligent explanation and assistance in real business situations in a reliable, user-friendly way.