I am trying to see how one would use JMP to optimize decision-making. I made some progress but figured that there are entire industries based around this theme (!), so maybe no need to invent the wheel here:
I want to decide which is the best conservation strategy given a set of inputs: a facility's resources, the nature of the environmental problem, and things like that (all on a common scale of 1=bad and 5=great). Depending on these factors, the model will project the optimal conservation solution. I have set this up to where a simple nominal logistic model could be run, in which the conservation approach recommended is the Y. I can then use the profiler and input new data to see which conservation approach is projected. For instance, only extremely wealthy facilities/locales can generally mitigate seawater at large scales; if resources are anything below 5 (the highest), mitigation CANNOT be an option. As another example, if the seawater quality is a 1 (lowest), some conservation strategies make no sense at all (e.g., restoration, in which case everything you placed in the ocean would die). It seems like my preliminary results make sense, but I'm wondering if there are entire platforms dedicated to this kind of exercise, albeit for manufacturing, like the optimization and process capacities.
I want to pitch the notion of "we humans are generally bad at decision-making, some I'm going to let the computer do it for me!" Am I making this into something harder than it actually is? I could see making a really convoluted set of conditional arguments as another alternative.
Anderson B. Mayfield