Recently, I got access to some files from a maintenance company of a very well known and successful European communication company. The maintenance team tried to improve the performance by some knowledge management practices, which were basically, reallocating some maintenance experts and putting them in double positions for sake of knowledge sharing. The knowledge management leader tried to explain why the new process works this well and why the performance increases this dramatically. She used i* modeling notation to show and reason why new knowledge dependencies work and how the maintenance knowledge is now distributed.
I am not going to dig into how i* (or any other modeling approach) worked for them. Things that are very interesting are about how they adopted a modeling notation. The results that now I am reading show that practitioners may ignore the syntax; they kind of model things with any syntax they feel comfortable with. So if the results of the analysis on the model highly depend on correct syntax, the modeling notation may just fail. The other interesting observation I had is that practitioners use the high intuitions of a tool, notation, or technique instead of details. This rings some bells again that syntax and details should be as simple as possible.
So in the i* models I received from industry, syntax of the model are almost wrong, but they have understood the high level intuitions behind the goal-oriented models. An interesting research would compare such results for various modeling notations and from several companies to draw a robust conclusion out of it: How models are adopted in real world?