Hi @jesper, have you seen Max Boisot’s ISpace model - that was an influence on Cynefin and covers some of this domain too? https://warwick.ac.uk/fac/soc/wbs/conf/olkc/archive/oklc4/papers/oklc2003_boisot.pdf
My one comment on your current proposal is that it is arguably too generalised - whilst it holds true as an average overview, actually the time to information in most cases will be highly subjective/dependent on the requester? I think really what you are attempting to calculate here is the information diffusion path traversal time. However the diffusion path is going to be increasingly dependent on the degree of connectivity between information requester and source in the network, the more novel and hidden the information is. For such information within a large organisation, then the time it takes to access it might be minutes or it might be months depending on whether I have an established informal network of trusted contacts I can IM or else whether I need to go via “formal channels”. Similarly pushing decision making to the edge of any network increases adaptability because it reduces the length of the information diffusion paths between sensors/sources and decision makers.
I think there is a generally applicable point that uncodified information entails additional time for decontextualisation and recontextualisation, but apart from that the generalised average for the time to information is only really useful for public/diffused information (where the average value applies to everyone equally). The further you go in the novel/hidden direction, the less you can rely on averages and the more you need to know about the context and specific diffusion path in this instance.