Work is done in processes. So here the actual added value provided by IT is realized. This explains the focus we place in our research on the process aspect. IT, as a fast-changing basic production technology, is impacting business process on a continuous basis. At a strategic level this impact is looked at in the previous research lines. At a more operational design level, this issue is researched here.
Enterprise and process modelling
Enterprise Modelling is oriented towards the systematic analysis and modelling of strategies, business models, processes, business policies and rules, information systems and any other relevant business perspective. Within this domain, process modelling can be situated on the operational layer of the organization, with the aim of analyzing and communicating about internal activities. Enterprise modelling efforts are particularly useful to analyze the current and desired future state of enterprises, which enables them to faster react on external changes and developments.
- Business models for value creation: how can business models be conceptualized to understand what a company needs for creating, delivering, and capturing value in its network of stakeholders.
- Creating value from architecture models: how can architecture models yield more added value to architects and the organizations they work for. An example is Policy Checking in ArchiMate, where we try to support the automatic verification of organization-specific constraints.
- Design patterns for co-evolution of business rules and their system-guided execution: This topic has been exploring business rule-based Semantic Web ontology design patterns for legal concepts and the efficient design of business system user interfaces for them. The current focus of this theme looking ahead is to develop more ontology design patterns that apply beyond law, and that form patterns applying constraints instead of only data models. We also continue exploring techniques for flexibly and efficiently deriving and designing interfaces supporting business data models and constraints on them.
- Models of knowledge management systems in enterprises, extensions of information systems with concepts for decision making.: how to model the vision of enterprises in projects concerning knowledge management systems.
Business Process Management
Business process management (BPM) is the art and science of overseeing how work is performed in an organization to ensure consistent outcomes and to take advantage of improvement opportunities (Dumas et al, 2018). It studies business processes from a holistic point of view involving the people, organizations, applications, documents and other sources of information, to produce business outcomes in support of a business strategy (Gartner, 2020). Various methods, tools and techniques are used to elicit, discover, model, analyze, measure, improve and optimize business processes. The focus in this research theme puts special attention on human aspects of BPM.
- Process model quality: the influence of structure, aesthetics, etc. of a process model on the understandability and comprehension of this model by a model viewer
- The process of process modeling: understanding how do modelers create process models, which mistakes do they make, and how can they best be trained or supported to make better models
- Continuous process improvement: developing and evaluating process analysis and redesign methods to identify bottlenecks and improvement opportunities
- Task/resource allocation in BPM systems: advancing process automation with a focus on human capabilities, experience, and preferences to increase technology fit and adoption
- Application and evaluation of BPM technology, tools and techniques in various (new) domains (e.g. high-tech manufacturing, healthcare).
- Data analytics for BPM. This research theme relates to the application of a broad set of data analytics on business process management in order to create and evaluate new process analysis and improvement methods.
- E.M. Haddouchi
- M.R. Dijkstra
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