@Nadia Great description of the Maidsafe project methodology!
Your simplified “i.e. why did we over/underestimate” description is very similar to the “human resource allocation optimisation” or “care capacity” methodology which I believe is key to achieving the path to the "true decentralised price network/global flat playing field” safe vision and in time underpin the design and use of genetic algorithms on safe.
The two key system/decision points in the benchmark Care Capacity application are
i. roster re-engineering
ii. variance response
which also provides the predictive modelling start pt. This is in a system where the resources being rostered account for 70% of the total cost with demonstrable outcomes improvements & cost reductions of 20%+.
I note the Marketing Update comment re the plan to steer in the direction of focus primarily on DApp developers. We are looking at a safe CCDM dApp Epic, story & tasks design to leverage off this existing opportunity.
The objective is to create a generic CCDM dApp template in context of the safe commons/data marketplace/public utility goal, broken down into chunks i.e. 3 project sections, with each section broken into smaller chunk projects or project workstreams and phases. So hopefully we can reach a point where we can simply compare our Epic Stories to implement.