Faster, bigger, further – all while being more cost-effective: These are the demands of today’s business landscape. As systems grow in complexity, traditional text-based specification approaches are increasingly reaching their limits. In response, model-based approaches emerge as a promising solution, offering a broad spectrum of modelling languages, tools, and methods tailored to various domains. However, in practice, the adoption of model-based approaches often encounters significant hurdles. Despite their potential, fully leveraging the power of modelling and using models to drive profitable outcomes remains a challenge. This raises the question: Why is modelling, though widely regarded as beneficial, so difficult to implement in practice? Is it the complexity of the modelling languages, the tools, the methods, or simply a lack of adequate training?

In this talk, we delve into the challenges and opportunities of model-based approaches, examining the reasons behind their successes and failures. We explore how these approaches can be effectively implemented in practice through structured and adaptive strategies. A critical aspect of this process is selecting the right methods, tailoring them appropriately, and sensibly limiting the degrees of freedom, alongside finding the most suitable tools. Interestingly, these constraints and added restrictions often lead to a more agile approach and broader acceptance than one might expect. Furthermore, clarifying goals and analysing the current status are vital steps in guiding the change process within the organization, ultimately helping to achieve the desired level of modelling maturity