(This is a hands-on lab with limited capacity. You should receive an invitation to sign up for your favourite session at latest one week before the conference. Capacity of this session = 28)

A repeating pattern I have discovered during discussions with participants of DDDEU over the last years was always that people are not able to calculate risk and potential value for intangible assets like "organisational flexibility" in the presence of uncertainty for adopting the modern organisational patterns and principles that the DDD community embraces.

Senior managers in larger organisations are seldomly convinced to board such an endeavour just by opinions and subjective assessments.

During these conversations I regularly ask if people have thought about creating a business case that would enable senior management to make a risk vs. value potential decision. And most of the time people do not know how to create such a case, because these "intangibles" seem impossible to measure.

But they are! It is possible by employing statistical methods to derive probabilities for ranges of possible outcomes that are built from various sources of information, i.e. calibrated expert knowledge. Said information can be annotated with an "expected value" when discovered, and other quantitative and qualitative data that doesn't seem obvious in the beginning.

This workshop would teach the basics of bayesian probabilities, how to calibrate people to better estimate ranges of possible outcomes (50% confidence, 70% confidence, 90% confidence), how to weigh results by the expected value of information in uncertain environments, an how to run Monte Carlo simulations on these input parameters, and how to experiment with different probability distributions (Normal, Pareto, Log-normal) to create a "good enough" business case in this uncertainty.

While this workshop would not fit into the classical collaborative model, I believe it can drive adoption of modern system design techniques in more power-oriented structures with these tools and methods (and also is generally very useful knowledge).